Investigating Operative and Non-Operative Treatments for Patella Fractures in Elderly, Low-Demand Patients

Investigating operative and non-operative treatments for patella fractures in elderly, low-demand patients

Gurrattan K. Chandhoke

A thesis submitted in conformity with the requirements for the degree of Master’s of Science

Institute of Medical Science University of Toronto

Gurrattan K. Chandhoke

Master’s of Science

Institute of Medical Science University of Toronto 2020

Abstract

Management protocols for displaced patella fractures in older (≥65 years) patients are lacking. While surgery is recommended for displaced fractures and non-operative management is suggested for non/minimally-displaced fractures in young/active patients, it is unclear if this algorithm is applicable to older, low-demand patients. The purpose of this thesis was to evaluate outcomes following operative and non-operative patella fracture management in older patients. Through an orthopaedic surgeon survey, we found that there remains a lack of consensus on the degree of displacement warranting operative management. Through a database study of 6258 patients, we found that re-operation rates are high, and emergency department readmissions are common but generally unrelated to patella fracture diagnosis.

These results suggest that managing fractures in older patients is complex, and complications are prominent. Future studies comparing both interventions are needed. Protocols for a multicenter retrospective study and prospective randomised trial to address these questions are also presented.

ii Acknowledgements

This work would not be possible without the support and guidance of many people to whom I would like to formally acknowledge.

Firstly, I would like to extend my sincerest thanks to my supervisor, Dr. Aaron Nauth. Your mentorship, insightful feedback, and attention to my academic development has guided me through this degree. I have gained a breadth of experiences and knowledge under your supervision and for that, I cannot thank you enough. I would like to acknowledge your commitment to your patients, your students, and to your research, all of which is truly aspirational. I hope our paths will cross again in the future.

Many sincere thanks to my thesis advisory committee members, Dr. David Wasserstein and Dr. Paula Rochon, for investing their time, expertise, and effort into this project and to my learning. Thank you both for your invaluable insight and direction, constant encouragement, and for helping me understand the clinical implications of my research.

This work would not be possible without the support of various colleagues. Many thanks to Drs. Amir Khoshbin, Emil Schemitsch, and Patrick Henry for providing constructive feedback on my projects. I would also like to acknowledge Dr. Gerald Lebovic, for helping me navigate the complex aspects of my statistical coding. Thank you for your patience and time. I felt that our discussions have contributed greatly to my academic development and future research endeavours. I would like to thank the entire ICES team, and in particular, Bo Zhang and Refik Saskin; without whom the project would not be possible. In addition, I extend my deepest thanks to the entire orthopaedic research team – Lynn, Christine, Luana, Lauren, Jennifer, Paril, Ryan, Kayee, and Cecilia – for their encouragement throughout my studies. Specifically, I would like to thank Lynn for her support with all facets of my studies, for always having an open door, and for teaching me about the depths of clinical research. My sincerest thanks to Luana and Lauren, for their feedback and guidance with my ICES project, and to Christine, for helping me navigate my graduate work. Finally, I would like to thank all the research sites and personnel involved in our studies. Without their contribution, this work would not be possible.

To my friends, teammates and mentors, thank you for all your support over many years. In particular, I would like to thank Dr. Sandeep Raha and Dr. Stash Nastos for their continuous inspiration and mentorship throughout my academic career.

Finally, to my family – mum, dad, Gursahiba, Gurmontek and AB – you remain my source of strength. Thank you for your unconditional love and encouragement. Your belief in me allows for all things to be possible.

I gratefully acknowledge the generous support from the Canadian Institute of Health Research Frederick Banting and Charles Best Canada Graduate Scholarship – Master’s, and the Institute of Medical Science.

jo jo hoie soeI suKu mwnY ] (Ang 294)

iii Statement of Contributions

The author of this work solely prepared this thesis. Three of the four studies discussed within this thesis (including the cross-sectional surgeon survey, population-level retrospective cohort study, and retrospective chart review study), were designed, conducted, and analyzed by the author, with guidance from the supervisor and committee members. The fourth study, a randomized trial, was developed by Dr. Aaron Nauth, with the contribution of numerous colleagues and collaborators.

iv Table of Contents

Abstract ...... ii Acknowledgements ...... iii Statement of Contributions ...... iv Table of Contents ...... v List of Abbreviations ...... ix List of Figures ...... x List of Tables ...... xi List of Appendices ...... xii 1.0 Thesis Objectives ...... 1 1.1 Outline ...... 1 1.2 Project Aims ...... 1 2.0 Introduction ...... 2 2.1 Anatomy and Function ...... 2 2.1.1 The Knee ...... 2 2.1.2 Patella Anatomy ...... 2 2.1.3 Patella Function ...... 3 2.2 Fracture Epidemiology ...... 4 2.2.1 Overview ...... 4 2.2.2 Patella Fractures ...... 4 2.3 Aging and Fracture Risks ...... 6 2.3.1 Osteoporotic Fractures ...... 6 2.3.2 Fragility Fractures ...... 6 2.3.3 Frailty ...... 7 2.3.4 Falls ...... 10 2.4 Risk Factors ...... 11 2.4.1 Fracture Risk Factors ...... 11 2.4.2 Post-Treatment Complications Risk Factors ...... 12 2.5 Defining ‘low-demand’ Patients ...... 12 2.6 Diagnosis ...... 13 2.6.1 Mechanisms of Injury ...... 13 2.6.2 Signs and Symptoms ...... 14 2.6.3 Radiographic Evaluation ...... 15 2.6.4 Categorization ...... 15 2.7 Treatment ...... 17 2.7.1 Non-operative Treatment ...... 18 2.7.2 Operative Treatment ...... 18 2.7.3 Summary ...... 20 2.8 Post-Treatment Protocols ...... 20 2.9 Complications ...... 21 2.9.1 Fixation Failure ...... 21 2.9.2 Re-operation ...... 22 2.9.3 Infection ...... 22 2.9.4 Delayed Union or Non-union ...... 23

v 2.9.5 Post-traumatic osteoarthritis ...... 23 2.9.6 Decreased Range of Motion and Knee Stiffness ...... 24 2.9.7 Anterior Knee Pain ...... 24 2.9.8 Osteonecrosis ...... 24 2.9.9 Summary ...... 24 2.10 Outcomes ...... 25 2.10.1 General and knee-related Health ...... 25 2.10.2 Pain ...... 25 2.10.3 Range of Motion ...... 25 2.10.4 Long-term outcomes ...... 26 2.11 Operative versus Non-Operative Treatments of Other Extremity fractures in Older patients in the Orthopaedic Literature ...... 26 2.11.1 Distal Radius Fractures ...... 26 2.11.2 Olecranon Fractures ...... 27 2.11.3 Unstable Ankle Fractures ...... 27 2.11.4 Summary ...... 28 2.12 Operative versus Non-Operative Treatments for Patella Fractures ...... 28 2.13 References ...... 30 3.0 Surgeon management preferences for patella fractures in older, low-demand patients: a cross- sectional survey ...... 38 3.1 Rationale ...... 38 3.2 Study Design ...... 39 3.3 Methods ...... 40 3.3.1 Survey Development ...... 40 3.3.2 Dissemination ...... 41 3.3.3 Inclusion and Exclusion Criteria ...... 42 3.3.4 Sample Size Calculation ...... 42 3.3.5 Statistical Analysis ...... 42 3.4 Results ...... 42 3.4.1 Surgeon characteristics ...... 42 3.4.2 Management preferences ...... 43 3.4.3 Displacement warranting operative management ...... 44 3.4.4 Factors influencing treatment decision ...... 45 3.4.5 Complications ...... 46 3.4.6 Post-Treatment Protocol ...... 46 3.4.7 Defining ‘low-demand’ patients ...... 46 3.4.8 Perceived need for future studies ...... 47 3.5 Discussion ...... 47 3.6 Conclusion ...... 50 3.8 Appendix ...... 55 3.8.1 Letter of Intent ...... 55 3.8.2 Survey ...... 56 4.0 A retrospective cohort evaluating treatment and health services outcomes in older, patella fracture patients ...... 61 4.1 Rationale ...... 61 4.2 Study Design ...... 62 4.3 Methods ...... 63 4.3.1 Cohort Development ...... 63 4.3.2 Project Time Frame ...... 64 4.3.3 Inclusion and Exclusion Criteria ...... 65

vi 4.3.4 Intervention ...... 66 4.3.5 Outcomes ...... 66 4.3.6 Covariates ...... 67 4.3.7 Data Preparation and Accessibility ...... 68 4.3.8 Statistical Analysis ...... 68 4.4 Results ...... 69 4.4.1 Baseline Characteristics ...... 69 4.4.2 Re-operation ...... 73 4.4.3 ED Readmission ...... 76 4.4.4 Length of Stay ...... 79 4.4.5 Discharge Disposition ...... 80 4.4.6 Costs ...... 81 4.5 Discussion ...... 82 4.5.1 Re-operation ...... 82 4.5.2 ED Readmission ...... 83 4.5.3 Length of Stay ...... 84 4.5.4 Discharge Disposition ...... 85 4.5.5 Costs ...... 85 4.5.6 Limitations and Strengths ...... 86 4.6 Conclusion ...... 86 4.7 Acknowledgements ...... 87 4.8 References ...... 88 5.0 Clinical and radiographic outcomes in older, patella fracture patients: a retrospective chart review ...... 92 5.1 Rationale ...... 92 5.2 Study Design ...... 93 5.3 Methods ...... 94 5.3.1 Patient Identification ...... 95 5.3.2 Inclusion and Exclusion Criteria ...... 95 5.3.3 Data Collection ...... 95 5.3.4 Data Management ...... 97 5.3.5 Statistical Analysis ...... 98 5.4 Progress to Date ...... 98 5.5 Conclusion ...... 98 5.6 References ...... 100 6.0 Randomized trial comparing operative versus non-operative patella fracture management in older, low-demand patients ...... 102 6.1 Rationale ...... 102 6.2 Study Design ...... 103 6.3 Methods ...... 104 6.3.1 Patient Identification ...... 104 6.3.2 Inclusion and Exclusion Criteria ...... 106 6.3.3 Intervention ...... 107 6.3.4 Rehabilitative and Physiotherapy Protocol ...... 107 6.3.5 Outcomes ...... 107 6.3.6 Data Management ...... 111 6.3.7 Sample Size ...... 111 6.3.8 Statistical Analysis ...... 111 6.4 Progress to Date ...... 112 6.4.1 St. Michael’s Hospital Screening Log and Recruitment ...... 112

vii 6.4.2 Progress to Date ...... 112 6.5 Conclusion ...... 113 6.6 References ...... 114 7.0 Discussion and Conclusion ...... 118 7.1 References ...... 122

viii List of Abbreviations

CCI Canadian Classification of Health Interventions CCRS Continuing Care Reporting System CI Confidence Interval CIHI Canadian Institute for Health Information CIHI - DAD Canadian Institute for Health Information - Discharge Abstract Database CIHI - SDS Canadian Institute for Health Information - Same Day Surgery COA Canadian Orthopaedic Association CSHA Canadian Study of Health and Aging CSHA-CFS Canadian Study of Health and Aging - Clinical Frailty Scale DASH Disabilities of the Arm, Shoulder, and Hand Questionnaire ED Emergency Department HR Hazard Ratio ICD International Classifcaiton of Disease IQR Interquartile range KOOS Knee Injury and Osteoarthritis Outcome Score K-wires Kirschner wires LHIN Local Health Integration Network LOS Length of Stay LTC Long-term care NACRS National Ambulatory Care Reporting System NRS National Rehabilitation Reporting System mFI Modified Frailty Index ODB Ontario Drug Benefit OHIP Ontario Health Insurance Plan ON-MARG Ontario Marginalization Index OR Odds Ratio ORIF Open reduction internal fixation OTA Orthopaedic Trauma Association RCT Randomized controlled trial RPDB Registered Persons Database ROM Range of motion TBW Tension band wiring WBAT Weight bearing as tolerated WOMAC Western Ontario and McMaster Univerisities Osteoarthritis Index

ix List of Figures

Figure 2.1 AO/OTA patella fracture classification ...... 17 Figure 3.1 Degree of displacement warranting operative management in older, low-demand patients with an intact extensor mechanism ...... 45 Figure 3.2 Factors influencing treatment decision making ...... 45 Figure 4.1 Project Timeline ...... 65 Figure 4.2 Cumulative incidence of re-operation and death within 2 years of treatment by age ...... 75 Figure 6.1 CSHA-CFS Scale ...... 105

x List of Tables

Table 3.1 Characteristics of survey respondents (N=115) ...... 43 Table 3.2 Management preferences for varying displaced fracture patterns in older, low-demand patient with an intact extensor mechanism ...... 44 Table 4.1 Cohort Development ...... 69 Table 4.2 Patient Characteristics at Baseline, stratified by treatment ...... 70 Table 4.3 Treatment Factors for Baseline Operative Cases ...... 72 Table 4.4 Characteristics of Re-operation Patients ...... 73 Table 4.5 Influence of various factors on risk of re-operation, cox proportional hazard model ...... 75 Table 4.6 Frequency of ED readmissions ...... 76 Table 4.7 Frequency of All Diagnosis Codes Associated with Readmission ...... 77 Table 4.8 Frequency of All Diagnosis Codes Associated with Readmission in baseline LTC cases .....78 Table 4.9 Influence of various factors on return to ED within 30 days, logistic regression with multiple predictors ...... 79 Table 4.10 Influence of various factors on treatment LOS, linear regression with multiple predictors ...80 Table 4.11 Discharge Disposition following Inpatient Surgical Intervention, stratified by LTC status at baseline ...... 81 Table 6.1 Study Scheduled Visit ...... 107

xi List of Appendices

3.8.1 Letter of Intent ...... 55 3.8.2 Survey ...... 56

xii

1.0 Thesis Objectives

1.1 Outline

The broad objective of this thesis is to explore and compare operative and non-operative treatment for patella fractures in older patients.

Chapter two begins with a background of patella fractures including epidemiology, aging and its relationship to musculoskeletal health, and fracture risk factors. We discuss general patterns of diagnosis, management, and risks accompanying treatment options. This chapter highlights current knowledge gaps pertaining to the management of patella fractures in older patients.

Chapters three, four, five, and six each comprise separate research projects that were completed as a part of the authors Master’s project. These chapters are organized as individual papers. Chapter three is a study exploring orthopaedic surgeon preferences and considerations when managing patella fractures in older (≥65 years), low-demand patients. The aim of this study was to identify current gaps in research pertaining to treatment decision making and patient selection. The fourth chapter is a retrospective cohort study exploring short- and long-term outcomes following treatment of patella fractures in older patients at a population level. We examine treatment outcomes such as re-operation rates and emergency department bounce-back, as well as health services outcomes including factors contributing to discharge disposition and length of stay. Chapter five explains the methodology of an ongoing multi-centered retrospective chart review investigating clinical and radiographic outcomes in this patient population. The sixth chapter outlines our ongoing randomized controlled trial comparing operative versus non-operative management of patella fractures in older, low-demand patients.

Chapter seven summarizes all projects and provides future directions. The chapter will explain how the findings of this project contribute to the orthopaedic trauma field.

1.2 Project Aims

The aim of this project was to advance our understanding of operative and non-operative treatment for patella fractures in older populations. We aimed to assess this research question at multiple levels, including a healthcare provider perspective, patient outcomes, and finally through a direct comparison via a randomized trial. Our hypothesis was that non-operatively managed older patients would have similar outcomes and fewer complications relative to operatively managed patients.

2.0 Introduction

This chapter provides an overview of the epidemiology of patella fractures and fractures in older patients, and summarizes literature surrounding common patella fracture classifications, treatment approaches, and complications. We discuss current studies comparing operative and non-operative management within the orthopaedic literature, and provide rationale for our studies comparing both treatments approaches for managing patella fractures in older patients.

2.1 Anatomy and Function

2.1.1 The Knee

The knee is a synovial joint, composed of the distal femur, proximal tibia, and patella. Specifically, the tibiofemoral compartment forms a condylar joint, with two round femoral condyles and two tibial condyles; while the patellofemoral compartment forms a gliding joint, limited to only a sliding movement.1,2

To maintain the stability of the knee, ligaments, tendons, muscles, menisci, and the knee joint capsule work collectively to control motion. The joint capsule is further stabilized by the fascia lata, iliotibial band, tendons, and the oblique and arcuate popliteal ligaments. The vastus medialis plays an important role in controlling knee flexion and extension.2

Located in the tibial plateau, the menisci are involved in shock absorption, knee stabilization, and allow for controlled rotatory movements during flexion and extension. The medial and lateral menisci are thought to help maintain even distribution of synovial fluid around the articular cartilage.2 The synovial membrane provides a flexible, well-lubricated lining for the synovial fluid, providing lubrication for the joint surface and nourishment to the cartilage.1 This is the largest synovium in the body.2

The vascular supply is provided by the femoral, profunda femoris, popliteal, and anterior tibial arteries. The femoral, obturator, tibial and common peroneal nerves provide nerve innervation.2

2.1.2 Patella Anatomy

The patella is the largest sesamoid bone in the body, situated in the patellofemoral groove.3-5 The patella is composed of 7 facets,6 ossifying between 3 and 6 years of age to form a single unit.5,7

The anterior portion of the patella forms a convex core.8 Due to its superficial position, the patella protects the anterior distal femur from direct trauma.6 The posterior articular surface is layered with a thick cartilage,4,5,7,9 composed of the medial and lateral facets and separated by the major vertical

ridge.3,5,7 The articular cartilage covering the posterior proximal three-fourths portion of the patella is thick, reaching up to five millimeters.10 The cartilage is known to be flexible relative to articular cartilage found elsewhere, and acts to dissipate forces created during motion.9 This is likely reflective of the increased forces applied to this area.

The patella is kept in position by tendons extending from the quadriceps muscle, composed of the rectus femoris, vastus intermedius, vastus lateralis, vastus medialis muscles.6,7 The quadriceps muscle is attached to the proximal end of the patella via the quadriceps tendon, in which the deep layer inserts at the proximal base, and the superficial layer extends over the patella to insert on the tibia.2,5 The distal end of the patella attaches to the tibial tuberosity via the patellar tendon.6

The medial and lateral patellar retinaculum, extensions of the quadriceps muscle, lengthen from the patella to insert in the medial or lateral condyles, providing added stability.2,7,11 The patellar retinaculum spreads over the anterior patella surface forming an aponeurosis with the fibers of the quadriceps muscle. Patellofemoral ligaments, found deep in the joint capsule, also contribute to the patellar retinaculum; while the quadriceps fibers allow for some active extension.5

The primary patella blood supply is the dorsal arterial ring form the branches of the geniculate anastomotic system.7 The primary interosseous blood supply enters from the mid-anterior and the distal pole of the patella.7 Injuries or fractures around the mid-patella may compromise vascular supply which, in severe cases, can lead to avascular necrosis.11

2.1.3 Patella Function

The patella functions as a lever, maximizing the mechanical advantage of the quadriceps muscle contributing to knee extension.3,4,12,13 In particular, it improves the efficiency of the last 30 degrees of extension.2

The extensor mechanism, composed of the quadriceps muscle, quadriceps tendon, patella, and patellar tendon, allow for knee extension.14 Stability of the extensor mechanism is required for unassisted gait and the maintenance of a standing position.5,7 The patella has many functions. Firstly, it serves as a site for quadriceps tendon insertion, linking the quadriceps tendon with the patellar ligament.15,16 Secondly, it contributes to the knee extensor mechanism as a lever arm during extension.5 With contraction, the quadriceps muscle pulls the patella and the anterior tibia proximally, rotating the knee into extension.17 Finally, the patella decelerates knee flexion, such as when walking down stairs. During this motion, there are high forces on the patella, surpassing up to four times body weight.5

With these important roles, maintaining the function of the patella is critical for daily activities and physical independence. As a result, treatment for patella injuries should be focused on restoring anatomical positioning, limiting complications, and maintaining activity levels.

2.2 Fracture Epidemiology

2.2.1 Overview

With a growing and aging population, overall fracture prevalence is expected to rise. Compared to 1954- 1958, fracture incidence in individuals aged >35 years increased by 50% in 2010/11; with a 5% increase in males and 85% increase in females.18 Notably, the study found a spike in falls-related fractures in all age groups during this time, independent of sex.18 Older patients (≥65 years) showed a significant increase in fracture prevalence in 2010/11 compared to the reference group in 2000 in a recent study.19 Specifically in relation to fractures around the knee (including the distal femur, patella, and proximal tibia), the incidence was reported to increase by 12% from 2010-2017.20 These trends are likely reflective of a growing and aging population with an increased life expectancy. Similar trends are expected for the coming years.

Overall fracture risk for males has remained constant over the past 50 years, apart from a sharp increase at 65 years of age.18 For females, fracture incidence has increased in the past 50 years at multiple points including: an 88% increase in 35-44-year-old fractures, 89% increase in 75-84-year-old fractures, and 61% increase in 85+ year old fractures.18 This is consistent with various studies highlighting the high fracture prevalence seen in older women.19

Women also tend to be older at time of injury relative to males. In one study examining trends of distal femur, proximal tibia, and patella fracture incidence over 20 years, the average age at injury was 62 years (interquartile range [IQR] 46-78 years) for females, and 42 years (IQR 19-59 years) in males.20 Similar trends have been noted in other studies.21 The highest risks for fractures about the knee in women has been observed in patients >50 years ,20 which suggests that age-related factors may play a role. However, it is important to note that these studies may not accurately represent the impact of sex and fracture risk. Women represent a significant number of cases since they have a longer average life expectancy than men.

2.2.2 Patella Fractures

Patella fractures account for approximately 1% of all fractures.3,6 Incidence has shown to follow a bimodal distribution, with peaks prominent in younger and older individuals.22,23 This distribution

indicates higher fracture risk due to trauma in younger individuals, and due to bone fragility in older individuals.22 Similar trends are noted in past retrospective studies, including by Larsen et al. (2016), who found the highest incidence of patella fractures in males was between 10-19 years and in females between 60-80 years within a cohort of 756 patella fractures.24

While men have shown a peak of fracture incidence between 10-19 years, followed by a drop and then steady increase starting at 30-39 years of age, women tend to have a rapid increase in incidence starting at 40 years and surpassing the incidence in men shortly thereafter.24 Unsurprisingly, patients between 65-74 years of age have almost a three-fold increased risk of patella fractures compared to those between 15-44 years of age.23 Similar results have been reported in a retrospective study conducted in the United Kingdom in which 68% of patella fractures in a single year were in patients >50 years of age, of which almost 50% were in patients >65 years of age.25 Age-specific factors, such as lower bone mineral density,26 post-menopausal changes,25 and a heightened falls risk in women,27 may contribute to these trends.

Over the past 50 years, patella fracture incidence has increased.18 Changes in incidence are likely reflective of a prolonged life expectancy and a growing population over the past five decades. However, more recent studies comparing incidence in the 21st century have not shown a significant increase in incidence. A prospective cohort study in Denmark from 1998-2017,20 and in Edinburgh from 2000 to 2010/11,19 both showed relatively stable patella fracture incidence over time.

Consistent with other fractures, women tend to have an older average age at time of injury relative to males. In a retrospective review evaluating 1596 fractures in Korea, women were on average aged 57.3 years, while men with the same injury had an average age of 47.6 years.28 In this cohort, the proportion of females ≥60 years remained consistently high, representing approximately 45% of the fractures across a 14-year study period, whereas the proportion of older males increased from 16% in 2003-2005 to 33% in 2015-2017.28 As a result, the proportion of patella fractures in older patients increased significantly, and steadily over time.

In addition, women represent an increasing number of cases each year. From 2003-2005 to 2015-2017, patella cases in women rose from 22.4% to 50.7% of all cases (p<0.001).28 Similar results have been noted in other patella studies23 and in other fragility fractures.28

It is likely that with an aging population, and increase longevity in females and males that the number of patella fracture cases will continue to rise.23,24 As a result, it is becoming critically important to ensure optimal treatment for these fractures.

2.3 Aging and Fracture Risks

Aging is associated with a range of musculoskeletal changes including increased bone fragility, reduced elasticity of ligaments, loss of cartilage, and decreased muscular strength.27,29,30 In addition to physical changes, older individuals are likely to undergo social and environmental changes around 65 years of age, such as retirement from work and moving homes, all of which can impact overall wellbeing. As a result, lower extremity injuries, such as fractures, that limit their mobility and/or physical independence can be particularly problematic for this population.27

2.3.1 Osteoporotic Fractures

Osteoporosis is marked by inferior bone formation by osteoblasts, while osteoclasts continue bone reabsorption. Multiple factors heighten the risk of osteoporosis including ethnicity and sex. Sex-specific physiological changes, such as menopause, may contribute to these rates, however, the exact interplay of these factors is unclear. Ethnicity plays a role in baseline bone density, which subsequently alters fracture risk later in life. African women have shown to have the highest bone density, followed by Caucasian and then Asian women.27 Women have traditionally had higher rate of osteoporosis and osteoporotic fractures than men.25,27 The lifetime incidence of these fractures range from 40-50% for women and 13-22% in men.31

With increasing bone fragility, individual fracture risk also increases.27 The risk for osteoporotic fractures sharply rises at 60 years of age. Although not as prominent as fractures of the hip, spine, or distal forearm, knee (distal femur, patella, proximal tibia) fractures do represent a considerable number of osteoporotic fractures.32

Patella fractures, at least in older Caucasian women, have recently been reported to be osteoporosis- related in numerous studies,23,25,33 while other studies have indicated otherwise.34 Today, these fractures are not considered to be osteoporotic and are frequently not seen by osteoporosis fracture prevention specialists at clinic visits. However, if osteoporotic, these fractures do require specific management as poor bone quality may lead to treatment complications.28

2.3.2 Fragility Fractures

Fragility fractures are fractures resulting from low-energy mechanisms, such as falls from standing height. Older patients remain at the highest risk of sustaining fragility fractures.31

Many of the risk factors for fragility fractures are common in patella fracture patients. These include: older age, female sex, white race, cognitive impairment, and parental history of fracture. Modifiable risk

factors include: osteoporosis, falls risk, physical inactivity, low body mass index, gait and balance abnormalities, medication, tobacco and alcohol use.31

Injuries from low-energy mechanisms are common and can result in poor outcomes. An increased mortality rate was seen in patients >60 years sustaining low-energy fractures in a variety of locations including the proximal and distal femur, vertebral, pelvic, proximal tibia, ribs, or proximal humerus.35 Increased mortality rates were also noted following hip, femoral diaphysis, and knee (distal femur, patella, proximal tibia) fractures in a recent study.36

With the continuous rise of patella fractures in older patients, particularly in women, and increases the number of injuries sustained from low-energy mechanisms, numerous studies have identified that a large proportion of patella fractures are in fact, fragility fractures.23,24,37 Fragility fractures represent a major health concern. Females present with fractures sustained mostly due to low-energy trauma. Byun et al. (2019) showed that while only 40% of injuries in males were from low-energy mechanisms, 80% of injuries in females were from this mechanism, 68% of which were ground-level falls.28

2.3.3 Frailty

In addition to fractures types, there are various individual factors associated with aging that heighten the initial fracture risk in this patient population. Frailty is often classified as “a state of low physiological reserve and vulnerability due to age-related loss of physical, social, and cognitive functioning”.38 Frailty is complex, and associated with aging and deterioration.39 The number of frail and older patients has been steadily increasing over time.40

The presence of frailty is multifactorial, and is impacted by numerous factors. This can include the presence of sarcopenia, osteoporosis, hormonal changes (menopause or andropause), onset of anabolic resistance, and decrease in active lifestyle. Frailty in particular, has been associated with a decline in function and increased risk of co-morbidities, falls, hospitalization, institutionalization, and death.41 These factors are highly likely to impact treatment outcomes and recovery following injuries, including fractures.

In research, many orthopaedic studies have highlighted the usefulness of frailty measures in evaluating and predicting complications and poor outcomes in older patients.38,42,43 In these studies, frailty was an independent predictor of falls, fractures, post-operative complications, readmission, length of stay, and mortality.42,44,45 Overall, frailty has been identified to be superior to co-morbidity scores or age in predicting post-operative complications following lower-extremity fractures39 The use of frailty measures in surgery is an area of significant recent interest.

Although there are formal frailty assessments, these may not be used in clinical practice as readily. In a qualitative survey of general practitioners, Korenvain et al. (2018) highlighted that instead of a systematic assessment, physicians use a combination of factors to assess baseline frailty including: physical characteristics (age, weight, medical condition, medications), functional characteristics (physical, cognitive, and general functioning), and living conditions (support systems, physical environment).44 It is likely that similar to general practitioners, orthopaedic surgeons use a gestalt impression, with simultaneous assessment of multiple factors. Baseline frailty assessments can help capture pre-injury physical and comorbidity levels to evaluate treatment success and outcomes.

2.3.4.1 Measurement Indexes

There are three main indexes used in acute care settings to assess frailty status including: the frailty phenotype, frailty index, and the Clinical Frailty Scale.

Fried’s Frailty Phenotype

Fried’s frailty phenotype classifies frailty as a “biological syndrome of decreased reserve resulting from cumulative declines”.46 Individual phenotype is assessed on five main items including: fatigue/exhaustion (self-reported), weakness (grip strength measurements), ambulatory status (gait test), weight loss (more than 10 pounds), and physical activity (kilocalorie per week). The items are measured subjectively and scored as a binary variable. A score of 0 indicates robustness, 1-2 indicates pre-frailty, and score >2 indicates frailty.39 The scale requires measurements of gait speed, which may be difficult for patients with lower-extremity injuries.

Rockwood & Canadian Study of Health and Aging (CSHA) Frailty Index

In this index, frailty is assessed as an accumulation of deficits: “the more things that are wrong, the more likely that person is frail”.47 The original index included 70-items with an assessment of baseline co- morbidities that impact functional, cognitive, and nutritional status. The index score increases with the number of co-morbidities, indicating increased frailty status.47

The modified frailty index (mFI) is an 11-item questionnaire, developed from the original 70-item questionnaire. It specifically collects history of: diabetes mellitus, chronic obstructive pulmonary disease (COPD), congestive heart failure, myocardial infarction, percutaneous coronary intervention or angina, peripheral vascular disease or rest pain, hypertension requiring medication, impaired sensorium, transient ischemic attach or cerebral vascular accident (CVA), CVA with resulting neurological deficit, and functional status.48

Studies have shown mFI to predict post-operative complications in previous orthopaedic studies including both arthroplasty and trauma patients.42,45,49-52

Frailty Phenotype versus Frailty Index

There are systematic differences in how both tools assess frailty. The Fried’s frailty phenotype assesses frailty as a syndrome, while the Rockwood & CSHA index places greater emphasis on co-morbidities and the accumulation of deficits. The Frailty Index has been shown to be more practical in clinical settings. Previous studies have shown the Frailty Index to be more practical and reliable as a predictor tool for surgical outcomes relative to the Frailty Phenotype.53

Clinical Frailty Scale

The clinical frailty scale is derived from the Frailty Index. Patients are classified on the scale based on their well-being, with scores between 1 (very fit) and 9 (terminally ill) with assessment of functional mobility, co-morbidities, cognition, and energy levels incorporated into the assessment.39,54 The scale is easy to implement in clinical settings and in particular for non-geriatricians, requiring no additional equipment for assessment.

This scale has been used in previous hip fracture studies in older patients to assess discharge disposition, in-hospital complications, and length of stay.54

2.3.4.2 Frailty and Fractures in Older Patients

Frailty has shown to be superior to age in predicting outcomes in older patients.38 Joseph et al. (2015) indicated frail older patients ≥65 years of age to have a 1.8 times greater odds of sustaining a fracture relative to non-frail older patients from ground level falls.38 Although results from patella fractures were not directly reported in this study, frail patients were more likely to sustain femoral and tibial fractures.38 Similar results have been reported in patients >70 years of age, in which frail patients were more likely to sustain odontoid fractures from a traumatic fall than non-frail patients.42 There appears to be an important relationship between frailty and fracture development from falls-related injuries.

Frailty has also been reported in relation to treatment outcomes. In a cohort of 377 operatively managed hip fracture patients >50 years of age, frailty was associated with higher post-operative complication rates, in-hospital mortality rates, and extended length of stay.45 In a separate study of 70 operatively managed odontoid fractures in older patients, frailty was significantly associated with increased likelihood of re-operation, extended length of stay, and higher 30-day and 1-year mortality rates relative

to pre-frail or robust patients.42 Frail patients have also been shown to be less likely to be discharged home.38

Since frailty has been shown to be a clear predictor of both fracture risk and adverse outcomes following fracture treatment in previous studies, further evaluation of its utility in the management of older adults who sustain a fracture is of significant interest, including the management of patella fractures.

2.3.4 Falls

The burden of falls is mostly concentrated to older patients, leading to trauma-related injuries.27,38,55 It is estimated that 1 in 3 individuals ≥65 years of age fall at least once each year,31 with 1 in 2 of those individuals experiencing recurrent falls.56,57 Falls-related injuries are estimated to account for approximately 10% of emergency department visits among older patients.57 For these individuals, a fall can be devastating, and potentially initiate a cascade of deterioration.38

Falls risk increases with age, with risk factors sharply increasing after 70 years of age,57 leaving older patients at a heightened risk.31 Numerous factors have been previously reported to expose individuals to adverse outcomes following ground level falls, leading to fractures, associated injuries, and compromised functional status.38,55,56 Patients with reduced muscle strength, particularly in the lower extremities, impaired mobility, balance abnormalities, visual impairments, and multiple medication users are at a heightened falls risk.27,56,57 Comorbidities, including arthritis, osteoporosis and osteopenia, also heighten baseline falls risk.55,57 Adequately addressing these known risk factors can help prevent falls from occurring. Polypharmacy, the concurrent use of multiple medications, is common in older patients and can be a substantial contributor to falls risk. In one study, tapering psychotropic medications, including sleep agents, antidepressants, and neuroleptic medications over a two-week period was associated with an almost 40% reduction in falls rate.58 There is strong evidence that psychotropic medications use is associated with an increased falls risk.57 Reducing the total number of medications, to four or less, has proven to be an effective strategy in reducing falls risk.57,59

Fractures from slips, trip or falls have been reported as the most common cause of injury leading to patella fractures in numerous studies.23,38,55 In Zhu et al.’s (2019) cohort of 512,187 patients in China, 70% of the patella fractures were due to such falls.23 As a result, falls are problematic in older patients, and steps should be taken to minimize falls risk in older populations.

Falls prevention includes both personal and environmental factors. At an individual level, exercise programs such as resistance training, strength and balance training can reduce falls incidence.56 Physicians can ensure vision correction and frequent medication review to avoid polypharmacy. At an

environmental level, improving living and community conditions with alternatives to steps such as ramps and railings, ensuring adequate lighting, and limiting slippery surfaces can help reduce falls risk.55 Having a fall, especially one that leads to an injury, can result in fear of falling in older patients that significantly results in loss of health over time.55

2.4 Risk Factors

2.4.1 Fracture Risk Factors

Although it is widely accepted that both age and sex play a role in patella fracture risk,23 there are likely numerous contributing factors. We explore these factors below.

Environmental and Social Factors

Socioeconomic status is an important consideration in various areas of medicine. With regards to fractures, one study indicated a significantly higher fracture risk in the most deprived 10% of the population. In this cohort, social deprivation was marked by overcrowding, unemployment in men, household structure and car ownership.60

In a separate study looking at post-menopausal women between 50 and 81 years of age, employment, income, type of housing and marital status all impacted hip fracture risk. Married and employed women living in a one-family house had a lower fracture risk than unemployed women living without a partner in an apartment.61 Both studies highlight the multitude of social and environmental factors intersecting to impact fracture risk. However, both of these studies did not examine the impact of these factors on patella fracture rates.

Medical History and Lifestyle Factors

Frailty has been shown to be a risk factor for adverse outcomes following low-energy injuries, including ground level falls. Frail individuals are more likely to sustain fractures and to be discharged to an institutional facility following a ground level fall relative to non-frail individuals.38 Pre-admission frailty has also been significantly associated with unfavorable discharge disposition, in-hospital complications, and length of stay in older hip fracture patients.54

In addition to frailty and age, past fractures significantly increase the likelihood of sustaining a subsequent fracture.31 Previous studies have shown systolic blood pressure, heart rate and injury severity to be associated with heightened fracture risk after ground level falls.38 These factors must be considered when evaluating baseline risk for fractures in this population.

Lifestyle factors, such as smoking and alcohol consumption have been shown to impact fracture risk. In patients ≥65 years, alcohol use is an independent risk factor for patella fractures.38 Previous reports have indicated that more than eight and six units of alcohol for males and females, respectively, increases risk of fractures.62 With respect to smoking, current smokers have been shown to have an increased risk of fractures relative to non-smokers in a cohort of post-menopausal hip fracture women.63 It is believed that there is a direct impact of nicotine on osteoblasts, with a lower average body weight and lower estrogen levels in post-menopausal smokers, resulting in decreased padding protection during falls.63 Although this study was limited to hip fractures, it is likely that smoking similarly impacts the patella.

2.4.2 Post-Treatment Complications Risk Factors

Medical Factors

Numerous factors have been shown to impact complication rates, including age. Aging has shown to be an independent predictor of failure following operative treatment,64 with multiple studies confirming these results.28,65 It is likely that age is a surrogate marker for factors such as co-morbidities and osteopenic bone which likely impact the fixation. Kadar et al. (2014) found that a history of cerebrovascular accident was significantly correlated with post-operative infection and nonunion; while diabetes was significantly associated with the risk for a second operation.66 There is evidence to suggest that factors such as co- morbidities and age impact recovery and ultimate outcomes in patients following patella fracture.

Management Factors

In patients operatively treated, there are various studies indicating the influence of hardware on complication rates. For example, tension band constructs with K-wires has been indicated as an independent predictor of failure following operative management of patella fractures [Miller2012].65 This is consistent with a report of 447 patients in which patients treated with K-wires had higher re-operation rates relative to patients treated with cannulated screws.67

Additionally, increased follow-up time has been associated with increased rates of re-operation and hardware removal.65 However, generally patients who do have painful hardware or complications with their surgery are more likely to be followed-up for a longer period of time.

2.5 Defining ‘low-demand’ Patients

Although numerous studies have focused on treatments specific to low-demand patients, very few have concretely defined a ‘low-demand’ patient. Many studies have used age in addition to another factor, such as co-morbidities or activity level, for their classification. Hyatt et al. (2010) combined age with

osteoporosis and multiple medical problems in order to define low-demand patients in their cohort of distal radius fractures; while Gross (1985) used age in combination with joint diseases for his classification.68,69 An earlier distal radius fracture study used age in conjunction with activity level to classify high versus low-demand patients, comparing a ‘26-year old athlete’ to a ‘72-year old retired banker’.70

In comparison to trauma studies, arthroplasty studies have often employed slightly different criterion. For hemiarthroplasty patients, Althausen et al. (2014) defined non-ambulators, house-hold ambulators, and limited community ambulators as ‘low-demand’.71 A different study looking at the use of antibiotic loaded acrylic cement for infected total hip arthroplasty classified patients as ‘low’, ‘medium’, or ‘high’ physical demand based on age, weight, pre-admission activity level, and health status as measured by the American Society of Anesthesiologists.72

To our knowledge, there is no standardized definition or assessment criteria for classifying ‘low-demand’ patients in the orthopaedic literature. Age has been a common criterion in most studies, however, age is not a comprehensive assessment. Additionally, there are numerous studies that have not defined ‘low- demand’ patients although treatment and outcomes of these patients were assessed.73,74 There is a clear need for a rigorous and standardized method to classify these patients within the orthopaedic literature.

2.6 Diagnosis

2.6.1 Mechanisms of Injury

Due to the subcutaneous position, the patella is prone to injuries from both direct blows and falls. These can be either high- or low-energy mechanisms leading to direct or indirect force injuries.

High- and Low-Energy Mechanisms

High-energy mechanisms tend to result in significant soft tissue and neurovascular damage, as well as open fractures.21 These injuries are sustained through blunt trauma, such as motor vehicle accidents or falls from a significant height. High-energy injuries are more common in males than in females, and often result in comminuted fracture patterns.75 Byun et al. (2019) found a higher percentage of motor vehicle accidents, associated injuries, and open fractures in males relative to females in their cohort.28

Contrary to high-energy mechanisms, low-energy mechanisms tend to have localized soft tissue damage and often result from a simple fall.75 These injuries are less complex, associated with a good prognosis, and represent the vast majority of patella fractures.76 A higher percentage of these injuries have been noted in older patients.28

The three most common injury mechanisms leading to patella fractures are motor vehicle accidents (dashboard or pedestrian strike), falls, and sports-related injuries.77

Direct and Indirect Force Injuries

Direct force injuries include blows to the knee from a fall or motor vehicle accident. These injuries can be either low- or high-energy mechanisms and in the case of high-energy mechanisms can often result in multiple injuries. Patients are evaluated for additional injuries at baseline including fractures, notably of the femoral neck or shaft, distal femur, and proximal tibia.7 Articular injuries,10,12 soft tissue damage, open injuries,12 and damage to femoral condyles7 can all occur.

Indirect force injuries include falling on the feet, or unexpected rapid flexion of the knee against a contracted quadriceps muscle.10,15,78 In these injuries, the forces on the quadriceps muscle exceeds the intrinsic strength of the patella.4,7,11 In comparison to direct force injuries, indirect force injuries often have more retinacular damage, limited active knee extension,7 less articular damage,15 and greater disruption of the extensor mechanism.78 From these injuries, displaced transverse and avulsion fractures are common.4,7,11,12,78

It is important to note that most patella fractures are due to a combination of forces and rarely can be classified as solely direct or indirect trauma.

2.6.2 Signs and Symptoms

Firstly, a comprehensive patient history and physical examination is initiated for all cases. Patients who have sustained trauma to their knee often present with pain, swelling, and decreased strength of their knee. Indirect trauma injury patients may be unable to preform a straight leg raise. In the case of non- displaced fractures, patients can present with minimal swelling and tenderness.7

During the physical examination, clinicians may palpate the patella to identify regions of tenderness and fragment separation. In addition, all blisters, contusions and abrasions are thoroughly assessed. Due the superficial location of the patella, assessment of the soft tissue status is important.12 The presence of open injuries requires urgent surgical debridement to minimize the risk of infection.7

Straight Leg Raise

The integrity of the extensor mechanism is assessed at this time by evaluating the ability for active knee extension against gravity.7,11 The patient lays in the supine position and is asked to keep the injured

extremity straight and lift it off the hospital bed.78 Inability to perform the lift, as compared to the contralateral limb, indicates disruption of to the extensor mechanism.

It is important to note that significant knee pain can prevent patients from preforming the straight leg raise. As a result, clinicians can either assess the extensor mechanism at a later date, or inject a local anesthetic to eliminate pain hindering test performance.7 Inability to perform the test indicates disruption of extensor mechanism and is a clear surgical indication. It is important to note that the straight leg raise test only assesses for an intact extensor mechanism and does not rule out a fracture diagnosis.

2.6.3 Radiographic Evaluation

Roentgenograms, or x-rays, are ordered at the time of injury of the affected knee, with anteroposterior, lateral, and sunrise views routinely evaluated. Radiographs allow for the baseline assessment of patella position, fracture fragment displacement, and congruity of the articular surface. Physicians may assess for patella baja, or low-riding patella, indicating a rupture of the quadriceps tendon; and patella alta, or high- riding patella, indicating a rupture of the patellar tendon.7

In addition to anteroposterior radiographs, lateral radiographs are useful in visualizing comminution and separation of fracture fragments. Radiographs can be combined with computer tomography (CT) scans to assess open fractures or fracture comminution, while magnetic resonance imaging is useful to evaluate soft tissue damage to ligaments or meniscus.78

A comprehensive clinical and radiographic assessment with all relevant diagnostic testing is important to inform treatment. Lazaro et al. (2013) identified a change in patella fracture classification in two-thirds of all cases when CT scans were used in addition to x-ray imaging. This fracture classification change subsequently led to alterations in surgical approaches.76 As a result, ensuring comprehensive information, with adequate view of fracture pattern, potential comminution, and displacement, in addition to clinical evaluation of the extensor mechanism and open injuries, is important in informing the management strategy.

2.6.4 Categorization

Fractures are classified based on displacement, fracture orientation and position, and degree of comminution.12 Importantly, mechanism of injury impacts injury categorization and is sometimes used to determine treatment course.

Displaced versus Non-Displaced Fractures

Fractures are classified as displaced or non-displaced based on the articular step-off and displacement of fragments evaluated on radiographs. The degree of displacement may be used as a potential indicator for surgery.

There are specific fracture patterns are also more likely to result in either displaced or non-displaced patterns. However, displacement is largely dependent on the mechanism of injury. Non-displaced fractures are commonly transverse in pattern, with majority at the mid-patella or distal pole.7 Longitudinal fractures are commonly displaced, due to the direct impact trauma often leading to injury.7 Comminuted patterns can either result in displaced or non-displaced fractures. These injuries often require investigation of the surrounding tissues.7

Fracture Classification

Once the fracture is classified as either displaced or non-displaced, the fracture can be described based on pattern and location.7 The fracture position is classified as superior pole, mid-patella, or distal pole.

Fracture patterns are dependent on mechanism of injury, bone quality, and the amount of force applied on the patella.5 Patella fractures can be classified morphologically to include:

1. Transverse fractures are the most common fracture pattern occurring horizontally across the patella,4,79-81 and commonly attributed to indirect injuries of the patella.5,11 This pattern is predominantly seen in females.28

2. Vertical fractures occur from the superior to inferior pole.5

3. Marginal, or avulsion, fractures occur predominantly due to direct forces at the superior or inferior pole.5,12

4. Comminuted, or stellate, fractures are common in polytrauma patients, often accompanied by soft tissue damage.5 Comminuted fractures can result from both low- or high-energy injuries, and often vary in degrees of displacement and comminution.7 This fracture pattern is common,4,79-81 and predominantly seen in the male sex.28

5. Osteochondral fractures are associated with patella dislocation, usually due to direct blows upon relocation or subluxation.7,15

Classification System

There is one classification system of based on fracture pattern and injury to the articular surface. The Arbeitsgemeinschaft für Osteosynthesefragen/ Orthopaedic Trauma Association (AO/OTA) classification is the most commonly used system, and shown in Figure 2.1.82

Figure 2.1 AO/OTA patella fracture classification

Reprinted from open access article: Gwinner C, Märdian S, Schwabe P, Schaser KD, Krapohl BD, Jung TM. Current concepts review: fractures of the patella. GMS Interdiscip Plast Reconstr Surg DGPW. 2016 Jan; eCollection.

2.7 Treatment

The treatment of patella fractures is based on the displacement, fracture pattern, clinical presentation, surgical risks, and patient-specific factors (such as age, bone health, and functional demand). The overall

goals of treatment are to preserve the function of the patella, restore continuity of the extensor mechanism, and maintain articular congruency.4,7,12,64

Currently, patients may receive non-operative or operative management.

2.7.1 Non-operative Treatment

Non-operative treatment is generally indicated for fractures that are non- or minimally-displaced with an intact extensor mechanism.7,12 These injuries often have minimal damage to the surrounding tissues. Non- operative treatment has also been suggested for patients who have numerous co-morbidities or are medically complex, non-compliant, or non-ambulatory.10,83 In cases where the surgical risks outweigh potential benefits, non-operative management may be used.7

While non-operative treatment reduces hospital length of stay, and mitigates risks of an invasive procedure and anesthesia,10 it does have potential outcome risks. These include: knee stiffness and/or quadriceps atrophy due to prolonged cast immobilization, non-union leading to loss of full extension, or incongruences at the articular surface leading to post-traumatic arthritis.4,84

There are a few studies that have evaluated the non-operative treatment of patella fracture. In a study of 18 non-operatively treated patients with >10mm of displacement, 9 of the 12 patients had good to satisfactory outcomes at 2 years post-injury. While there were no complications reported, all patients had extensor lag >20 degrees at the end of follow-up.83 In a separate retrospective review of 40 conservatively treated adult patients at a single institution, 10% of patients had restricted flexion beyond 90 degrees, 20% of patients experienced pain, and 8% of patients used a walking aid at the end. Complications included two deep vein thromboses and two cases of re-fracture.84 Although good to excellent results have been reported in studies following non-operative management of non-displaced fractures with early mobilization,6,77 many of these studies are outdated with a relatively small sample size.

2.7.2 Operative Treatment

Operative intervention aims to achieve anatomic reduction, restoration of the articular surface, and repair of the extensor mechanism.7,13 General indications for operative treatment include displaced fractures and disruption of the extensor mechanism.7,78,84 Contraindications include critically ill or non-ambulatory patients, and those with severe infection of the soft tissue or bone.7 Timing of surgery is generally dependent on the presence of open injuries and the integrity of the surrounding skin and soft tissue.11

There are various surgical options for the treatment of patella fractures. In complex cases with severe comminution, a combination of fixation options can be used. This is however, generally limited to high- demand patients and not reflective of the patients currently studied.

2.7.2.1 Modified Anterior Tension Band

The tension band technique converts the anterior tension forces into compression forces.4,7,79 The classic tension band technique involves using two Kirschner wires (K-wires) running through patella, from the superior to inferior pole. A tension band is passed anteriorly, usually in a figure-of-eight pattern.10 This technique however, is associated with various complications including irritation, prominent hardware, implant migration, loss of reduction, and muscle atrophy.4

The modified approach uses the tension band construct in addition to other techniques for added stability.12,15,78,81 Cerclage wiring can be used to provide stability for displaced comminuted fractures,4 while screws hold bone firmly and are commonly used for the management of transverse fractures.10 In cases of anterior surface comminution, plates may be added to provide additional stability .4,10

Modified tension band approaches with cannulated screws have shown good to excellent results in small studies.85 In one study, patients managed with a tension band and cannulated screws had lower rates of re- operation and implant migration, as well as improved reduction in comparison to patients treated with a tension band and K-wires.86 Notably, although improved outcomes have been suggested in cannulated screw groups, proper placement of the screws can be technically challenging.79 This technique is the most widely accepted technique, and is used for the management of displaced transverse and comminuted fractures.7,12

Relative to other approaches, modified tension band approaches are superior to screw fixation, cerclage wiring and partial patellectomy.87 This technique has been effective in achieving fracture union and allowing for early joint movement,81 however, soft tissue irritation is a potential complication.15

2.7.2.2 Patellectomy

For some time, the patella was thought to inhibit the actions of the extensor mechanism. Therefore, patellectomy was a popular treatment until studies showed the biomechanical importance of the patella and the improved function of the extensor mechanism as a result.7 The importance of the patella in the extensor mechanism is now acknowledged for lower extremity functioning.

Partial Patellectomy

Prior to partial patellectomy, all attempts should be made to maintain the patella and articular surface.7 This technique is generally reserved for injuries involving severe comminution at one pole and significantly cartilage loss that is not repairable.7,10,77,78 This approach involves removing de-vascularized fragments and loose bodies and reattaching the quadriceps and patellar tendons.

Total Patellectomy

Total patellectomy is rarely used and is reserved for cases of high comminution, or fractures that are not repairable by internal fixation methods.7 This treatment approach removes the patella, and eliminates the mechanical advantage provided to the extensor mechanism.4

Outcomes following total patellectomy are generally fair to poor.7,15,77 Patient often report decreased motion and knee extensor strength, extensor lag, and overall discomfort.15

2.7.3 Summary

Overall, non-operative treatment is indicated for non- or minimally-displaced fractures with an intact extensor mechanism, while operative management is recommended for displaced fractures with a disrupted extensor mechanism.66,77,83,88 These indications are often universally applied, independent of age. However, the medical and physical needs of younger, active patients and older, low-demand patients are not identical. The degree of displacement warranting operative treatment tends to vary however, general ranges include articular step-off >1-3mm and fragment separation of >2-5mm.4,7,10,13,15,21,76,78,81,89 There are also universal factors, such as anesthesia-related risk, problems with wound breakdown, osteoporotic bone, soft-tissue irritation, and infection that are prominent in older patients that must be considered at the time of management.90 Surgeons must evaluate potential benefits and harms of treatments while considering patient factors, to ensure optimal treatment.

2.8 Post-Treatment Protocols

Both operatively and non-operatively treated patients are placed in a knee immobilizer post-treatment and gradually weaned off the brace over a time period of 4-8 weeks.7 Early studies indicated that the period of immobilization had no impact of rehabilitation.6,21 However, recent studies emphasize the importance of early weight-bearing and preventing prolonged immobilization;66,83 as this may contribute to knee stiffness and loss of extensor strength.11

Early range of motion is recommended to help improve clinical outcomes,7 and articular cartilage healing.15 Generally, active range of motion, resistive and strengthening exercises begin at 2 to 6 weeks post-treatment.3,7,11,15This provides time for the fracture and surrounding soft tissue to heal prior to

exercise initiation. Vigorous activities, including sports, are delayed until rehabilitation is complete.7

While some authors suggest partial weight bearing as tolerated during healing,3,91 others recommend full weight bearing with the addition of crutches or canes.6 Although time of healing is dependent on the individuals’ fracture type, displacement, and overall health, patients will generally achieve maximum functional recovery by one-year post-injury.

These are general guidelines used in previous studies. Post-operative protocols may vary for open or severely comminuted fractures. To our knowledge, there is no standardized protocol for rehabilitative management following both operative and non-operative patella fracture treatment.

2.9 Complications

Previous studies have shown older adults to have a heightened risk for complications and failures following patella fracture management.28,64,65 Evidence also suggests that treatment strategies may also impact the risk of complications and adverse events. In particular, higher failure rates have been reported in patients treated with K-wires.4 Complication risks may also be impacted by fracture characteristics, such as open versus closed injury, fracture pattern, and degree of displacement; as well as surgeon factors, such as experience.

Studies have shown that even after anatomical reduction, extensor mechanism reconstruction and physiotherapy, functional deficits are still prominent.76 This is expected following a traumatic injury.

2.9.1 Fixation Failure

Failure of fracture fixation is a frequent complication following operative management,28,65 observed not uncommonly in fragility fracture patients.92,93 Factors such as technical errors with the implant and/or secondary traumatic events (including subsequent falls) may lead to this failure.79

Symptomatic hardware is the most common complication following patella fractures, with rates as high as 60% in the literature.4 This complication often requires a second operation for removal of the hardware. Rates of symptomatic hardware are thought to be heightened in open fractures3 and patients treated with tension band and K-wires.79

Hardware failure, including implant breakage or migration occurs in 8-22% of cases.4,10 In particular, the use of K-wires has been associated with local and distant wire migration, as well as soft tissue irritation.7,15,79

Loss of reduction occurs in approximately 20% of all cases,5 and may be due to factors such as improper

fixation placement, inadequate tensioning of the implant, or insufficient strength of bone to hold the fixation in place until union.

2.9.2 Re-operation

Re-operation rates range from 0-60% in the literature.3 A meta-analysis of 24 studies, summarizing 737 fractures found a re-operation rate of 33.6%,94 while a single center retrospective review of 188 adults had a 22.3% re-operation rate.66 Of the re-operations performed, 64% of patients had symptomatic hardware, 26% of patients had infection requiring debridement or hardware removal, 7% of patients had hardware failure, and 2% of patients had non-union. The average time to re-operation was 11.6 months.66

Re-operation rates following patella fractures are generally high, and may be influenced by subcutaneous location of the patella. In particular, for older patients, poor bone quality likely impacts the integrity of the fixation long-term. Re-operations are not only costly, but more importantly, they expose patients to additional risks and potential complications.

2.9.3 Infection

The overall infection rate following operative patella fracture fixation is low. Infection rates range from 3- 10% in the literature,4,10,21,79,94-96 however are most prominent following open injuries.7 In a retrospective cohort of 188 patents, 6.8% (13 patients) developed infections, majority of which were superficial and could be managed with debridement or intravenous antibiotics only.66 The authors believed that the older average age (56 years) and presence of co-morbidities in the majority (56%) of patients likely contributed to a high infection rate, however, this relationship was not directly studied.

In general, older patients are more prone to infection due to the presence of co-morbidities, such as diabetes and peripheral vascular disease. Older patients have an increased risk of infection from nosocomial organisms due to institutionalization or hospitalization, with the knee, hip, and shoulder as common infection sites.27 With this increased risk of infection, impacted by a likely weaker immune system, it is critical to limit unnecessary hospitalization in older patients.

General infection management protocol involves irrigation and debridement and a standard course of antibiotics.5 Superficial infections can be managed with antibiotics and wound care, while deep infections may require an incision and drainage.7,15 In extreme cases, postoperative infection can lead to compromised joint function.84

2.9.4 Delayed Union or Non-union

Delayed union or non-union is a result of failure of bone trabeculae to bridge the gap between fracture fragments.7 Fractures are classified as delayed union if there is failure of union within two month of injury with displacements >2mm.7 Non-unions are most prevalent in transverse fractures, but may also be seen in other fracture patterns.7,28,65 In addition to fracture fixation failure, non-union is a common complication in other fragility fractures.92,93

Notably, non-union rates are high following non-operative patella fracture management and can lead to loss of full extension.84 Rates are lower following surgical treatment, in which anatomical reduction is achieved.15 Non-union rate following operatively managed fractures generally ranges from 1.3%94 to 1.6%;66 however, some studies have reported higher rates.4,12

Non-unions are only treated when they are painful or associated with weakness. There are instances when fractures have failed to achieve union radiographically but clinically, the patient may not report any discomfort or significant functional limitation. In these instances, no further treatment is required.15 Re- operation following non-unions may be indicated when fracture separation is >4mm and the patient has significant impairments in function.7

2.9.5 Post-traumatic osteoarthritis

Osteoarthritis, the progressive wear-and-tear disease affecting joints, is marked by deteriorating cartilage. Various factors have been shown to heighten the risk for osteoarthritis, including older age, female sex, obesity, and knee injuries.97 Rates of osteoarthritis are relatively high. In one study of 49 adult patella fracture patients, 36.7% developed moderate to severe osteoarthritis when followed for an average of 8.5 years. Of these patients, 72.2% developed patellofemoral osteoarthritis while the remaining 27.8% developed tibiofemoral osteoarthritis.98

The risks of post-traumatic knee arthritis are increased in patients sustaining traumatic injuries of the articular surface.99 Various factors may influence the development of osteoarthritis post-injury including: fracture comminution, mechanism of injury, and degree of chondral surface injury. Treatment factors such as surgical approach and quality of reduction on articular surface may also play a role.99 This is a known long-term complication following patella fractures, commonly presenting with patellofemoral pain.7 Patellofemoral pain can be managed with activity modification and anti-inflammatory medication, or may require surgical intervention in the form of joint replacement.7

2.9.6 Decreased Range of Motion and Knee Stiffness

Early motion helps avoid scaring and stiffness,3,64 which is thought to improve activities of daily living, symptoms, and overall quality of life. It should be noted however, that patients will generally regain the majority of their knee range of motion (ROM), however a few degree of loss if expected.15 There are numerous factors that can effect overall ROM and stiffness. Internal fixation allows for early ROM, although it has not been proven to limit stiffness.3 Knee stiffness is a concern following non-operative management and cases of infection, in which there is often a prolonged immobilization period and inadequate rehabilitative treatments.5,10,12,84

2.9.7 Anterior Knee Pain

Anterior knee pain is a common concern following trauma to the knee. Factors contributing to patellar maltracking and subsequent anterior knee pain include limited muscle activity, muscle atrophy, and reduced quadriceps performance.76 Knee pain can be further exacerbated by scarring and tightness around the knee joint, as well as post-traumatic arthritis.10,76

Rates of anterior knee pain are high, with Lazaro et al. (2013) reporting 80% of adults in their cohort indicated knee pain.76 Rates of pain following non-operative treatment are limited to a retrospective review of 40 cases, in which 20% of patients experienced post-treatment pain.84 It is important to note that generalizability of both study results is limited given their retrospective design.

2.9.8 Osteonecrosis

In cases of severe high-level trauma, osteonecrosis is of concern. This develops after revascularization of fracture fragments.76 However, given our focus on low-energy trauma, risk for osteonecrosis are minimal.

2.9.9 Summary

Overall, complication rates following patella fractures remains relatively high, with re-operation and fixation failure rates being prominent. High complication rates can impact overall clinical, functional and patient satisfaction outcomes. In one study, 28% of patients reported being unsatisfied with knee function following operative patella fracture management.95 High complication rates likely influence the overall satisfaction experienced by patients.

There are several limitations of the previously conducted studies. Firstly, the majority of the studies evaluating complication rates have studied younger and older patients jointly. The rates therefore, may not accurately represent the true risk level in older patients. Secondly, the majority of studies were

conducted at a single academic center. These patients tend to be more complex trauma cases relative to community practices. Therefore, the reported complication rates may not be representative of the entire population. As a result, large scale, population-based studies are needed to more accurately evaluate the rates of complications.

2.10 Outcomes

High-quality outcome studies following patella fractures are lacking. Most of the studies are limited to investigating outcomes following operative management only.

2.10.1 General and knee-related Health

In a review of 40 patients, LeBrun et al. (2011) found the long-term patient outcomes to be poor following operative patella management.13 General and knee-related health measures, as measured by Short-Form 36 and the Knee Injury and Osteoarthritis Outcome Score (KOOS), respectively, were different from population norms; and over 50% of patients required a re-operation within the mean follow-up time of 6.5 years. Despite the insight provided, this study is limited by a small sample size at a single institution, therefore lacking generalizability. In addition, patients were retrospectively identified and prospectively followed, introducing potential volunteer bias.

2.10.2 Pain

Pain is often reported as a long-term outcome, and this is likely to do with joint incongruity and subsequent degenerative changes, that are common in these patients.13 Similar results of increased pain and worse function were noted in a retrospective cohort of patella fracture cases compared to population averages on the Western Ontario and McMaster Universities Osteoarthritis indexes. In particular, individuals reported increased pain during sporting activities.98

2.10.3 Range of Motion

Extensor lag tends to be commonly reported outcome, with approximately 1 in 5 patients reporting greater than five degrees of lag post-surgery.13

Clinically, patients may have loss of extensor strength and experience quadriceps weakening, but may not report any symptoms related to this deficit. In a prospective study, older adults tended to be asymptomatic despite having a 30 degrees loss of knee flexion or 10 pounds of quadriceps weakness relative to their contralateral limb.77 This suggests that the thresholds for evaluating treatment efficacy and patient satisfaction may differ between younger and older patients.

2.10.4 Long-term outcomes

Patella fractures patients do not have an increased mortality rate at one-year post-injury.100 Previous patella fracture patients have shown an elevated risk for total knee arthroplasty, although the overall incidence is low. The greatest effects are seen in the first five years following fracture diagnosis. It is likely that a combination of factors, including pain, decline in function, and osteoarthritis contribute to the need for knee arthroplasty.99

2.11 Operative versus Non-Operative Treatments of Other Extremity fractures in Older patients in the Orthopaedic Literature

There have been numerous recent studies within the orthopaedic trauma literature that have challenged traditional surgical indications for displaced extremity fractures in older patients.

2.11.1 Distal Radius Fractures

Arora et al. (2009) published a retrospective analysis comparing non-operative versus volar locking plating for the management of unstable Colles type distal radius fractures in patients ≥70 years. From 2000 to 2005, they included 114 patients with an average age of 79 years (range 70-97 years), with a majority (68.4%) of patients being of the female sex. At end of follow-up, there was no difference in mean active range of motion (ROM), grip strength, final Disabilities of the Arm, Shoulder and Hand (DASH; upper extremity disability questionnaire), patient-reported wrist evaluation, and Green and O’Brien (pain, functional status, ROM, grip strength evaluation) outcomes between operatively and non- operatively treated patients. There was however, significantly higher pain reported in the operative group relative to the non-operative group. Seven (13%) operatively treated cases developed complications, with 6 requiring a second operation; whereas 5 (8%) non-operatively treated cases developed complex regional pain syndrome type 1, all of which was managed with physiotherapy and oral analgesia. Despite a high (89%) radiographic mal-union rate in the non-operative group, clinical outcomes did not differ between groups.101

This study led the authors to conduct a randomized trial comparing volar locking plate fixation and non- operative management for displaced and unstable distal radius fractures in patients ≥65 years. The trial included 73 patients, 37 of which received non-operative management. At one year post-injury, ROM, pain, and wrist function (as measured by the Patient-Rated Wrist Evaluation score and DASH) were equal between treatment arms. Complications were also significantly higher in the operative group relative to the non-operative group (p<0.05). This study showed that despite achieving anatomical reduction in the

operative group, there were no significant improvements in daily activities, pain, or motion relative to patients conservatively managed.102

2.11.2 Olecranon Fractures

In a different study, Duckworth et al. (2014) retrospectively reviewed and prospectively followed 43 patients who were non-operatively managed for displaced (>2mm) olecranon fractures. The average age of included patients was 78 years (range 40-98 years), with 67% being women. Eighty-eight percent of patients had at least one comorbidity at baseline. At a mean of four months post-injury, 72% of patients had good to excellent short-term outcomes as measured by the Broberg and Morrey score (motion, stability, strength, and pain of elbow) at mean of 4 months post-injury.90

This study lead the authors to conduct a prospective randomized trial comparing non-operative versus operative treatment in the management of displaced (>2mm) olecranon fractures in patients ≥75 years. The trial was stopped prematurely at 19 patients, due to the high post-operative complication rate. Eighty- two percent of operative cases reported complications including: 1 infection, 6 loss of reduction (all treated with TBW) and 3 implant removals (2 plates, 1 TBW). With the data collected of 19 patients, the primary DASH outcome did not differ between groups at any point during follow-up. Similar trends were seen with the secondary outcomes of ROM, Broberg and Morrey, Mayo Elbow Score, and pain between groups during the first year of injury, with no difference between both groups.103

Although the study did not go to completion, the high post-operative complication rate and equivalence in clinical outcomes at one year with the data collected, support the use of non-operative management in older, low demand patients with displaced olecranon fracture patients.

2.11.3 Unstable Ankle Fractures

Willett et al. (2016) reported results from their randomized controlled trial comparing the equivalence of closed casting versus surgery for unstable ankle fractures in patients ≥60 years of age. The study included 24 hospitals in United Kingdom with 620 patients, with mean age 71 years and 74% women. There was no difference in the primary outcome of Olerud-Molander Ankle Score at 6 months between both groups. There was no difference in secondary outcomes of quality of life, ankle pain, and patient satisfaction at 6 weeks and 6 months. There was a 6% complication rate in the operative group, compared 1% complication rate in the casting group, with a higher percentage of the operative group requiring a re- operation. Notably, 19% of non-operatively treated patients receive surgery to manage early loss of fracture reduction. There was a lower mal-union rate but higher infection/ wound breakdown rate in the operative group relative to the non-operative group.104

This study provided high-level evidence for the use of non-operative management for unstable ankle fractures compared to surgery at the end of 6 months further indicating that non-operative treatment can be used in the management of displaced fractures in older adults.

2.11.4 Summary

These studies provide strong evidence of similar, if not better, clinical outcomes and lower complication rates following non-operative treatment compared to operative treatment in the management of displaced extremity fractures in older low-demand patients. These results question the rationale of applying the same surgical indications used in younger/active patients to older/low-demand patients, emphasizing the need for more conservative approaches in older patients. However, it is important to note that all of these studies have used age as an indicator of low functional demand, which may not be comprehensive in classifying these patients. Active patients, independent of age, would likely benefit from surgical fixation of many of these fractures.

2.12 Operative versus Non-Operative Treatments for Patella Fractures

There are currently very few studies that have compared outcomes between operatively and non- operatively managed patella fractures. An early study in 1975 included 104 adult patella fractures managed both operatively and non-operatively. Motor vehicle accidents (51%) and falls (42%) accounted for the majority of injuries. The majority of conservatively treated patients had nondisplaced fractures, and reported good to excellent outcomes. Of those non-operatively managed and reporting unsatisfactory outcomes, 71% had a displaced fracture. In the operatively treated group, 75% were satisfied with their results; however recurrent pain and knee stiffness were common problems.77

In a more recent study by Shabat et al. (2003), 68 older (≥65 years) patients were treated either operatively or non-operatively for their falls-related injury.88 Eight-two percent of patients reported injuries from simple falls, 88% had an intact extensor mechanism, and most patients had at least one baseline disease (such as ischemic cardiac disease, hypertension, and diabetes). In this cohort, 58 (85.3%) patients were treated surgically and 10 (14.7%) conservatively. Immediate post-operative complications included infected wounds, and late complications included implant migration and breakage of wires in two operatively treated patients. Patients who had a disrupted extensor mechanism but non-operatively treated had an extensor lag of 10-30 degrees; while five (9%) patients managed operatively had an extensor lag of 10-30 degrees. Other minor complications in the operative group included: two superficial wound infections, two wire breakages, and one late migration of wires.88 Although this study is one of the few studies investigating outcomes following both operative and non-operative treatment, it is limited by

its retrospective design that has inherent limitations. In addition, fractures with disrupted extensor mechanisms were treated non-operatively, resulting in extensor lag. However, extensor mechanism disruption is generally regarded as an indication for surgery. The study did not indicate the degree of displacement in both groups, or provide a rationale for treatment decision making.

Although the studies conducted by Sanderson et al. (1975) and Shabat et al. (2003) provide important information on outcomes following both operative and non-operative patella fracture management, there are inherent limitations within the design that limit the interpretation of study results. A recent Cochrane review also highlighted the need for future studies to directly compare operative and non-operative treatments of patella fractures.105 As the older population grows with increased life expectancy, the need for high-level evaluation is of growing importance, particularly with regard to limiting unnecessary surgical interventions. We aim to focus on a particular subset of older adults who can be classified as ‘low-demand’ and evaluate the roles of operative and non-operative treatment.

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60. Court-Brown CM, Aitken SA, Duckworth AD, Clement ND, McQueen MM. The relationship between social deprivation and the incidence of adult fractures. J Bone Joint Surg Am. 2013;95(6):e321-e327. 61. Farahmand BY, Persson PG, Michaëlsson K, et al. Socioeconomic status, marital status and hip fracture risk: a population-based case-control study. Osteoporos Int. 2000;11(9):803-808. 62. Scholes S, Panesar S, Shelton NJ, et al. Epidemiology of lifetime fracture prevalence in England: a population study of adults aged 55 years and over. Age Ageing. 2014;43(2):234-240. 63. Baron JA, Farahmand BY, Weiderpass E, et al. Cigarette smoking, alcohol consumption, and risk of hip fracture in women. Arch Intern Med. 2001;161(7):983-988. 64. Matthews B, Hazratwala K, Barroso-Rosa S. Comminuted Patella Fracture in Elderly Patients: A Systematic Review and Case Report. Geriatr Orthop Surg Rehabil. 2017;8(3):135-144. 65. Miller MA, Liu W, Zurakowski D, Smith RM, Harris MB, Vrahas MS. Factors predicting failure of patella fixation. J Trauma Acute Care. 2012;72(4):1051-5. 66. Kadar A, Sherman H, Glazer Y, Katz E, Steinberg EL. Predictors for nonunion, reoperation and infection after surgical fixation of patellar fracture. J Orthop Sci. 2015;20(1):168-73. 67. Catalano JB, Iannacone WM, Marczyk S, et al. Open fractures of the patella: long-term functional outcome. J Trauma. 1995;39(3):439-444. 68. Gross AE. Surgery for the arthritic knee. Can Fam Physician. 1985;31:563-569. 69. Hyatt BT, Hanel DP, Saucedo JM. Bridge Plating for Distal Radius Fractures in Low-Demand Patients With Assist Devices. J Hand Surg Am. 2019;44(6):507-513. 70. Hotchkiss RN. Displaced Fractures of the Radial Head: Internal Fixation or Excision?. J Am Acad Orthop Surg. 1997;5(1):1-10. 71. Althausen PL, Lu M, Thomas KC, Shannon SF, Biagi BN, Boyden EM. Implant standardization for hemiarthroplasty: implementation of a pricing matrix system at a level II community based trauma system. J Arthroplasty. 2014;29(4):781-785. 72. Beaupre LA, Stampe K, Masson E, et al. Health-related quality of life with long-term retention of the PROSthesis of Antibiotic Loaded Acrylic Cement system following infection resolution in low demand patients. J Orthop Surg (Hong Kong). 2017;25(2):2309499017716257. 73. Young BT, Rayan GM. Outcome following nonoperative treatment of displaced distal radius fractures in low-demand patients older than 60 years. J Hand Surg Am. 2000;25(1):19-28. 74. Jain R, Koo M, Kreder HJ, Schemitsch EH, Davey JR, Mahomed NN. Comparison of early and delayed fixation of subcapital hip fractures in patients sixty years of age or less. J Bone Joint Surg Am. 2002;84(9):1605-1612.

75. Luo TD, Marino DV, Pilson H. Patella Fractures. [Updated 2020 Mar 13]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2020. 76. Lazaro LE, Wellman DS, Sauro G, et al. Outcomes after operative fixation of complete articular patellar fractures: assessment of functional impairment. J Bone Joint Surg Am. 2013;95(14):e96-8. 77. Sanderson MC. The fractured patella: a long-term follow-up study. Aust N Z J Surg. 1975;45(1):49- 54. 78. Della Rocca GJ. Displaced patella fractures. J Knee Surg. 2013;26(5):293-299. 79. Hoshino CM, Tran W, Tiberi JV, Black MH, Li BH, Gold SM, Navarro RA. Complications following tension-band fixation of patellar fractures with cannulated screws compared with Kirschner wires. J Bone Joint Surg Am. 2013;95(7):653-9. 80. Nummi J. Fracture of the patella. A clinical study of 707 patellar fractures. Ann Chir Gynaecol Fenn Suppl. 1971;179:1-85. 81. Lee SY, Choi JY, Lee HI, Lee JM, Cho JH. The Comparison of Postoperative Outcomes Open and Closed Reduction for Patellar Fractures. J Knee Surg. 2020;33(1):73-77. 82. Colton C, Gebhard F, Kregor P, Oliver C. AO Classification of Patella Fractures. AO Foundation; 2008. Available at: https://www2.aofoundation. org/wps/portal/surgery?showPage¼diagnosis& bone¼Knee&segment¼Patella (accessed December 2019). 83. Pritchett JW. Nonoperative treatment of widely displaced patella fractures. Am J Knee Surg. 1997;10(3):145-148. 84. Braun W, Wiedemann M, Rüter A, Kundel K, Kolbinger S. Indications and results of nonoperative treatment of patellar fractures. Clin Orthop Relat Res. 1993;(289):197-201. 85. Berg KO, Wood-Dauphinee SL, Williams JI, Maki B. Measuring balance in the elderly: validation of an instrument. Can J Public Health. 1992;83 Suppl 2:S7-S11. 86. Tian Y, Zhou F, Ji H, Zhang Z, Guo Y. Cannulated screw and cable are superior to modified tension band in the treatment of transverse patella fractures. Clin Orthop Relat Res. 2011;469(12):3429- 3435. 87. Böstman O, Kiviluoto O, Santavirta S, Nirhamo J, Wilppula E. Fractures of the patella treated by operation. Arch Orthop Trauma Surg. 1983;102(2):78-81. 88. Shabat S, Mann G, Kish B, Stern A, Sagiv P, Nyska M. Functional results after patellar fractures in elderly patients. Arch Gerontol Geriatr. 2003;37(1):93-98. 89. Harris RM, Fractures of the patella and injuries to the extensor mechanism. In: Bucholz, RW, Heckman, JD, Court-Brown CM, eds. Fractures in Adults. Ed 6. Philadelphia, PA: Lippincott Williams and Wilkins; 2006:1969–1998.

90. Duckworth AD, Bugler KE, Clement ND, Court-Brown CM, McQueen MM. Nonoperative management of displaced olecranon fractures in low-demand elderly patients. J Bone Joint Surg Am. 2014;96(1):67-72. 91. De Palma A, McCoy S, Finnerson B, Osburn W, Connolly J. De Palma's The Management Of Fractures And Dislocations. Philadelphia: Saunders; 1981. 92. Chao EY, Inoue N, Koo TK, Kim YH. Biomechanical considerations of fracture treatment and bone quality maintenance in elderly patients and patients with osteoporosis. Clin Orthop Relat Res. 2004;(425):12-25. 93. Pidgeon TS, Johnson JP, Deren ME, Evans AR, Hayda RA. Analysis of mortality and fixation failure in geriatric fractures using quantitative computed tomography. Injury. 2018;49(2):249-255. 94. Dy CJ, Little MT, Berkes MB, Ma Y, Roberts TR, Helfet DL, et al. Meta-analysis of re-operation, nonunion, and infection after open reduction and internal fixation of patella fractures. J Trauma Acute Care. 2012;73(4):928-32. 95. Hung LK, Chan KM, Chow YN, Leung PC. Fractured patella: operative treatment using the tension band principle. Injury. 1985;16(5):343-347. 96. Smith ST, Cramer KE, Karges DE, Watson JT, Moed BR. Early complications in the operative treatment of patella fractures. J Orthop Trauma. 1997;11(3):183-187. 97. Blagojevic M, Jinks C, Jeffery A, Jordan KP. Risk factors for onset of osteoarthritis of the knee in older adults: a systematic review and meta-analysis. Osteoarthritis Cartilage. 2010;18(1):24-33. 98. Larsen P, Vedel JO, Vistrup S, Elsoe R. Long-Lasting Hyperalgesia Is Common in Patients Following Patella Fractures. Pain Med. 2018;19(3):429-437. 99. Larsen P, Rathleff MS, Østgaard SE, Johansen MB, Elsøe R. Patellar fractures are associated with an increased risk of total knee arthroplasty: A Matched Cohort Study of 6096 Patellar Fractures with a mean follow-up of 14.3 Years. Bone Joint J. 2018;100-B(11):1477-1481. 100. Larsen P, Elsoe R. Patella fractures are not associated with an increased risk of mortality in elderly patients. Injury. 2018;49(10):1901-1904. 101. Arora R, Gabl M, Gschwentner M, Deml C, Krappinger D, Lutz M. A comparative study of clinical and radiologic outcomes of unstable colles type distal radius fractures in patients older than 70 years: nonoperative treatment versus volar locking plating. J Orthop Trauma. 2009;23(4):237-242. 102. Arora R, Lutz M, Deml C, Krappinger D, Haug L, Gabl M. A prospective randomized trial comparing nonoperative treatment with volar locking plate fixation for displaced and unstable distal radial fractures in patients sixty-five years of age and older. J Bone Joint Surg Am. 2011;93(23):2146-2153.

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3.0 Surgeon management preferences for patella fractures in older, low-demand patients: a cross- sectional survey

This chapter presents the objectives of our cross-sectional survey study, describing the study design, and providing an overview of our methods. We present the baseline characteristics of surgeons included and the results, and discuss the study implications.

3.1 Rationale

Older patients increasingly represent a larger proportion of patella fracture cases each year.1-3 It is well established that numerous factors contribute to an increased fracture risk and post-operative complication rate in older patients. Despite these rising rates and complex needs, there remains paucity in management protocols and uncertainty regarding the applicability of traditional treatment algorithms for displaced fractures in older patients. This is especially of interest given recent shifts in the management of displaced extremity fractures in older populations, where evidence has recommended an expanded role for non- operative management.4-6

Currently, operative treatment is indicated for displaced fractures with >2-5mm separation and fractures presenting with a disrupted extensor mechanism.7-18 However, smaller scale studies have indicated good to fair outcomes in patients managed conservatively with significantly displaced fractures.19 Outcome studies following patella fractures in older patients also remains limited, with younger and older patients often combined together in study populations. Previous studies do suggest potential differences in functional and clinical outcome thresholds between younger and older patients following patella fracture management. In one study, older patients tended to be asymptomatic despite loss of knee flexion and quadriceps weakening.20

In addition, patient-specific factors also impact baseline fracture risk and outcomes following management. Factors such as older age, increased falls risk and frailty, which are often present in older patients, have shown to increase baseline fracture risk.21-25 The presence of co-morbidities has also been linked to greater complication rates following operative patella fracture management.26 As a result, these factors likely impact both surgeon management preferences and treatment outcomes, but this has not been quantified in the literature.

Given these considerations and the growing prevalence of patella fractures in older patients, our study aimed to explore current management preferences and surgical considerations when treating older (≥65 years), low-demand, patella fracture patients. In this study, low-demand patients are defined as individuals ≥65 years of age, who are ambulatory, and may or may not have some degree of dependence

for activities of daily living, but are not routinely active beyond walking. In addition, we aimed to investigate the influence of surgeon characteristics on preferred management of patella fractures in this population. The goal of this study was to provide insight into surgeon decision making and their perceptions of patient outcomes, and to ultimately facilitate future research.

3.2 Study Design

This study aimed to investigate orthopaedic surgeon perspectives, preferences and decision making when managing patella fractures in older patients. Results gathered can be used to identify gaps in knowledge and current trends in fracture management, both of which may be used to develop clinical research questions and support the need for more rigorous studies.27 Given the demographic and injury under investigation, surgeons provide invaluable insight on current practices and opinions, and therefore were the population of interest in our study.28

Unlike other study methods, surveys allow for information to be collected in a relatively short period of time.29 We opted for an electronic survey compared to administration via mail, phone or in-person. Electronic surveys provided a cost-effective method to study a large population, with ease in data collection and compilation.28,29 Given the geographic distribution of surgeons contacted, we aimed for a user-friendly medium allowing for completion at convenience. Despite these strengths, electronic surveys do not allow questions to be clarified or answers to be further discussed, unlike phone or in-person surveys, which both provide dialogue between interviewer and interviewee.28,29 In addition, phone and in- person methods have a higher completion rate due to personal interactions between both members.28 However, given our population of interest, we determined that electronic surveys would be most effective and appropriate.

Independent of the administration method, sources of bias in a cross-sectional survey study remain constant. Non-response bias, in which the survey results of respondents differ from non-respondents, is one source of potential bias in our design.28 Stemming from a low response rate, non-response bias can be due to multiple factors including poor questionnaire design or implementation strategy.27,28 We aimed to limit response bias in many ways. Firstly, we ensured clarity of instructions both in our letter of intent and within the question stem. We also highlighted that responses were anonymously collected within our letter of intent. Finally, reminder emails were sent to surgeons regarding survey completion. In addition to non-response bias, measurement bias, occurring when questions are either poorly written or do not accurately reflect the study objectives, was mitigated in our study design.30 This was done by pilot testing our questionnaire with a group of orthopaedic surgeons to ensure all concepts were properly captured and there was clarity in our questionnaire. Selection bias, occurring when the group sampled is not

representative of the entire population, was limited by ensuring that members of the contacted organizations had equal opportunity to participate in the survey. Social desirability bias, the tendency to respond in a manner deemed favourably by others, was reduced by implementing an anonymous online survey without collecting any identifiable information.28 However, this simultaneously limited our ability to ask for clarification and probe for further information.

Despite these potential risks for bias, we determined that an electronic cross-sectional survey design to be the most optimal study design to explore our research question. With consultation of orthopaedic surgeons on survey content and using best practices from previous surveys in our group, we administered our survey to address our study objectives.

3.3 Methods

3.3.1 Survey Development

Item Generation and Pilot Testing

Survey items were initially generated from the literature, aimed at assessing a specific study objective. Questions were made to be closed-ended, clear and unambiguous, in order to avoid confusion. We avoided neutral responses and open-ended questions (included only when necessary) to limit potential bias in interpretation and make responses easier to analyze. Similar topics were grouped, and questions appeared in a manner of addressing our primary and secondary objectives first, prior to moving to exploratory topics. In order to determine how surgeon characteristics influence management preferences, we inquired about surgeon demographics, practice patterns and experience. The survey was made to be as short as possible while obtaining all required information.

During the survey development phase, we pilot tested our questionnaire with four orthopaedic surgeons within this research area. This was done to evaluate face validity (identifying if our survey addresses the question of current practice patterns in treating patella fractures in the older adults), and content validity (measuring all facets of the construct) of the proposed survey. Feedback was collected and incorporated into the survey to ensure proper wording, clarity of questions and options, as well as limit redundancy or confusion.28 Surgeons were contacted in succession for feedback.

Our final electronic survey contained 37 items inquiring about surgeon preferences for managing different fracture patterns, operative and non-operative indications, and complication rates.

Survey Layout

Instructions for each question were made clear, visible, and inline with the question stem. We ensured consistent format, with consecutive numbering of questions from start to end. We avoided organizing options horizontally on the page, and ensured adequate spacing between answer options and between questions. A progress bar was included at the bottom of the survey to indicate progress to completion. The survey layout was consistent with recommendation and guidelines provided by Dillman et al. (2009).27

3.3.2 Dissemination

Letter of Intent

A formal cover letter was included at the start of the survey to introduce surgeons to the study, survey and consent process. After reading the letter of intent, participating surgeons were aware of their role in the study, and were able to contact study personnel should they have any study-related questions prior to survey initiation. An implied consent process was used. As such, a completed questionnaire assumed that the participant has read the cover letter and understood his/her participation in the study.

Survey Administration

The electronic questionnaire was administered through SurveyMonkey Inc. (SurveyMonkey adheres to the US-EU Safe Harbor Privacy Principles of notice, choice, onward transfer, security, data integrity, access and enforcement). The survey was sent to all members of the Canadian Orthopaedic Association (COA) and the Orthopaedic Trauma Association (OTA) via email, inviting them to participate in the study. In addition to receiving email reminders, the survey was posted on both association websites, targeted at active members. No monetary incentives or pre-notification telephone calls were used. Responses were kept confidential and survey completion was voluntary. Date of survey completion and survey responses were tracked. Responses were limited to one per computer. A reminder email was sent prior to the study completion date.

The survey was available online for two months (posted June 6th) on the COA website, and three months (posted May 9th) on the OTA website, with a closing date of July 31st 2019. The discrepancy in survey availability was due to administrative differences in posting the survey online. However, since there is considerable overlap between surgeons who are members of both associations, the impact of this discrepancy was likely minimal.

Response Rate

We took many steps to ensure an adequate response rate. In preparing our survey prior to dissemination, we ensured relevance and interest in topic by surveying members of the orthopaedic community who would likely manage these fractures in their independent practice. We introduced the study objectives, participation, instructions, and approximate survey length (10 minutes) in our letter of intent. Additionally, a reminder email was sent to participating surgeons regarding completion, prior to the closing date.

3.3.3 Inclusion and Exclusion Criteria

The survey was limited to orthopaedic surgeons who were members of either the COA or OTA, at the time of survey dissemination, and agreed to participate. Surgeons must be able to read English in order to complete the survey.

3.3.4 Sample Size Calculation

Our sample size calculation was based on the following parameters: an alpha of 0.05, maximum variability in probability of 50%, margin of error of 0.05. This yielded a required number of 278 participants. Given a conservative response rate of 60%, as seen in previous orthopaedic surgeon surveys,31 we calculated that the survey would need to be administered to 695 surgeons.

3.3.5 Statistical Analysis

All data was descriptively summarized as counts and proportions, subsequently stratified for analysis. χ² and Fisher’s exact tests were used to compare differences across surgeon strata for each outcome. Fisher’s exact test was used when one or more cells had an expected frequency equal or less than five. Analysis was performed on R Statistics programme (R Foundation for Statistical Computing, Vienna, Austria).32

The research ethics board at St. Michael’s Hospital has approved this study.

3.4 Results

3.4.1 Surgeon characteristics

Of the 123 surgeons who opened the survey, 115 (93.5%) responded to at least one question and were included in the analysis. Approximately half (56.5%) of the respondents were ≤50 years of age, and the majority were male (87.8%). The majority of survey respondents practiced in Canada (81.6%), and predominantly in academic hospitals affiliated with a university (61%), followed by community public hospitals (33.3%), and community private hospitals (5.7%). Trauma and lower extremity fellowships were most common, completed by 38.5% and 21.7% of respondents, respectively. ‘Other’ responses for

fellowship training included: upper extremity (6 surgeons), spine (5 surgeons), arthroplasty (4 surgeons), and foot and ankle (3 surgeons). Demographic data is summarized in Table 3.1.

Table 3.1 Characteristics of survey respondents (N=115) N % Age ≤ 40 years 35 31.0 > 40 years 78 69.0 Sex Male 100 87.7 Female 13 11.4 Prefer not to say 1 0.9 Practice Location Canada 93 81.6 USA 20 17.5 International 1 0.9 Practice Type‡ Academic Hospital affiliated with a University 75 61.0 Community Public Hospital 41 33.3 Community Private Hospital 7 5.7 Years of Independent Practice Current fellow 2 1.8 ≤ 5 years 32 28.1 6 - 15 years 30 26.3 16 - 25 years 22 19.3 > 25 years 28 24.6 Fellowship Training‡ Lower extremity 35 21.7 Trauma 62 38.5 Sports medicine 23 14.3 No training 11 6.8 Other 30 18.6 ‡Respondents could have more than one answer

3.4.2 Management preferences

There was general consensus that non-/minimally-displaced patella fractures should be conservatively managed (80%), while displaced fractures should be treated with surgery (85%). Preferred operative fixation methods included open reduction internal fixation [ORIF] with Kirschner wires [K-wires] and tension band wiring [TBW] (46.9%), and screws and TBW (26%). Surgeon demographics did not influence the management of non-/minimally-displaced fractures, while surgeons with lower extremity and trauma fellowships were more conservative in their approach of displaced fractures (p=0.02). There was a trend for surgeons ≤40 years of age to be less likely to treat displaced fractures operatively compared to older surgeons (p=0.06).

In the management of displaced fractures in older, low-demand patients with an intact extensor mechanism, operative management was generally preferred: 81.8% for transverse fractures, 74.7% for superior/inferior pole fractures, 70.4% for comminuted fractures, and 53.1% for vertical fractures (Table 3.2). Practice location, fellowship training, and years of experience did not significantly impact treatment approach; however, surgeons ≤40 years of age were less likely to treat displaced transverse (p=0.004), comminuted (p=0.009), and superior/inferior pole (p=0.01) fractures operatively, in comparison to surgeons over 40 years of age. A trend towards significance was seen in lower extremity fellowship trained surgeons being less likely to treat displaced transverse fractures operatively relative to surgeons without this training (p=0.06). A similar pattern was seen in the management of displaced vertical fractures, with Canadian surgeons opting for more conservative approaches (p=0.05) compared to surgeons practicing internationally.

Table 3.2 Management preferences for varying displaced fracture patterns in older, low-demand patient with an intact extensor mechanism Operative (n,%) Other Non- ORIF with Plate and Fracture pattern Screw Screws and fixation (ex: operative K-wires and screw fixation TBW suture (n,%) TBW fixation fixation) Transverse 42 (42.4) 1 (1.0) 4 (4.0) 31 (31.3) 3 (3.0) 18 (18.2) Vertical 6 (6.1) 27 (27.6) 3 (3.1) 12 (12.2) 4 (4.1) 46 (46.9) Comminuted 35 (35.7) 2 (2.0) 9 (9.2) 13 (13.3) 10 (10.2) 29 (29.6) Superior/ 17 (17.2) 2 (2.0) 2 (2.0) 6 (6.1) 47 (47.5) 25 (25.3) Inferior Pole ORIF= open reduction internal fixation; K-wires= Kirschner wires; TBW= tension band wiring

3.4.3 Displacement warranting operative management

There was no consensus on the degree of displacement warranting operative management: 25% of surgeons indicated <5mm, 37% indicated 5-10mm, 17% indicated 10-20mm, 10% indicated >20mm, and 10% indicated ‘other’ (Figure 3.1). Open-ended responses for ‘other’ factors influencing degree of displacement included: evaluating the knee in extension, assessing for an intact extensor mechanism, patient factors such as function and co-morbidities, and measuring articulate step. Surgeon demographics did not influence the degree of displacement warranting surgery.

Figure 3.1 Degree of displacement warranting operative management in older, low-demand patients with an intact extensor mechanism

3.4.4 Factors influencing treatment decision

An intact extensor mechanism most strongly influenced the treatment decision, indicated by 88% of surgeons. Additional strongly influencing factors included: compromised soft tissue (66%), functional demand (65%), open wounds (65%), and fracture displacement (64%). Open-ended responses for ‘other’ factors included considering patient residence (such as small northern communities). All factors and their associated influence are summarized in Figure 3.2.

Figure 3.2 Factors influencing treatment decision making

Open wounds 5.00% 30.00% 65.00%

Compromised soft tissue 1.00% 33.00% 66.00%

Intact extensor mechanism 12.00% 88.00%

Patient compliance 9.00% 63.00% 28.00%

Number and size of fragments 10.10% 51.52% 38.38%

Fracture pattern 4.00% 48.00% 48.00%

Comorbidities 3.03% 58.59% 38.38%

Bone quality 7.00% 59.00% 34.00%

Displacement 36.00% 64.00%

Functional demand 1.00% 34.00% 65.00%

Age 8.33% 60.42% 31.25%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Not at all Somewhat Strongly

3.4.5 Complications

Sixty-eight percent of the respondents believed that post-treatment complications occur in less than 20% of older patella fracture patients. Estimates of re-operation rates were similarly low, with 49.5% of respondents indicating <10% of patients would require a second operation. The most common post- operative complications identified by surgeons was symptomatic hardware (54.8%), failure of fracture fixation (43.8%), and knee stiffness (27.3%). The least common post-operative complication was infection, indicated by the overwhelming majority of respondents (87.5%). The most prevalent complications following conservative treatment were thought to be knee stiffness (46.4%), extensor lag (37.2%), and mal-union (37.0%).

3.4.6 Post-Treatment Protocol

We inquired about post-treatment rehabilitation protocol for patella fracture cases in older, low-demand patients. Surgeon preferences for rehabilitation protocol did not differ between operatively and non- operatively treated patients. Weight-bearing as tolerated (WBAT) was recommended by 86% of surgeons for all patients. Delayed range of motion for flexion and extension was indicated for both operatively and non-operatively treated fractures by the majority of surgeons. There was limited consensus on the number of weeks that range of motion exercises should be delayed following operative management, but the majority (51.2%) of surgeons suggested starting at 4 to 6 weeks post treatment. Additional factors impacting this recommendation included: fracture pattern, fixation method, and wound healing. Similarly, for non-operatively treated fractures, delaying range of motion exercises for 4 to 6 weeks was prominent, indicated by 69.1% and 63.8% of respondents, respectively. Immobilization using a splint or brace was recommended by 97% of surgeons, independent of the management approach.

3.4.7 Defining ‘low-demand’ patients

When asked how to identify ‘low-demand’ patients, 91% considered individual activities of daily living and living arrangements, such as residing in long-term care facility or independent living. Seventy-six percent of surgeons simultaneously acknowledged co-morbidities, and 59.3% considered age. Common open-ended responses included: assessing the patient overall during the examination and evaluating the patient’s activity history.

3.4.8 Perceived need for future studies

Most surgeons identified a need for future trials comparing operative and non-operative management in older, low-demand patients (69.6%). The majority (89.1%) of surgeons would be willing to change their treatment practices following a randomized trial comparing treatments for this patient demographic.

3.5 Discussion

This is the first study to examine surgeon preferences and considerations for the management of patellar fractures in older (≥65 years), low-demand patients. Our primary finding was the lack of agreement amongst surgeons with regard to the amount of fracture displacement warranting operative treatment. Seventy-five percent of survey respondents indicated that a displacement >5mm represents an indication for surgery, which is contrary to general measurements indicated in the literature.8,15,17,33,34 This suggests that not only are reported indications not reflective of clinical practice in older patients; but, there remains a lack of consensus within the orthopaedic community regarding what degree of displacement warrants surgical intervention. We suspect that patient factors, including co-morbidities and functional demand, are more strongly considered at the time of treatment decision making compared to fracture displacement, which may explain our results. Although we had a subset of surgeons indicating displacements >10mm indicating surgery, research in this area is sparse and limited to a few studies.19 Further investigations is required as the degree of displacement warranting surgical intervention in this patient population remains unclear.

There was general consensus that non-/minimally-displaced fractures in older, low-demand patients with an intact extensor mechanism should be conservatively managed, while displaced fractures require operative intervention. These results are consistent with previously reported treatment algorithms.7,33,35 However, the degree of displacement remains unclear. We also found that surgeon demographics do influence treatment decision making. In particular, younger surgeons were less likely to operate on displaced patellar fractures. This may be reflective of recent high-level studies challenging fracture management practices in older patients.4-6 Similar clinical shifts have been noted in orthopaedic practice following randomized trials for the treatment of displaced mid-shaft clavicle fractures36,37 and acute Achilles tendon ruptures.38,39 Additionally, management practices may also be influenced by differences in standard of care by geography and/or payment matrixes (i.e. universal healthcare payment in Canada versus fee-for-service in the United States) which may not be accurately captured in the literature. This may explain why we found Canadian surgeons to be more conservative in their approach of displaced vertical fractures in comparison to international surgeons, although the relationship was not significant.

Our results suggest that surgeon demographics influence treatment preferences, particularly in the management of displaced fractures.

Technical surgical preferences in older, low-demand patients were consistent with previous studies. TBW is the most widely employed technique for the management of patella fractures,33,35,40 and our results in displaced transverse and comminuted fractures confirmed these practices. The addition of K-wires, screws, and cerclage wiring has also been noted in our survey results and in previous reports.35,41-43 Suture fixation has been consistently preferred for pole fractures.44

Vertical fracture pattern was the only fracture pattern that indicated a predominance of conservative management in our results. This is consistent with Boström’s (1974) study showing good to excellent results in almost all conservatively managed pole fractures at the end of the 9-year period.45

Furthermore, our study confirmed the importance of assessing the the extensor mechanism on treatment decision making.26,33,35,43 This was followed by the evaluation of open wounds and soft tissues, which exposes patients to potential complications if not addressed immediately.46 The majority (58.6%) of survey respondents only somewhat considered patient co-morbidities, contrary to the reported importance indicated in previous studies. Kadar et al. (2014) indicated that co-morbidities, in particular cerebrovascular accidents or diabetes, significantly heightens the risk for complications following operative patella fracture fixation.26 Other studies have recommended patients with multiple co- morbidities should be treated conservatively, independent of fracture displacement.7

For post-treatment rehabilitation, WBAT was recommended for all patients to allow for early mobility, especially important for older patients. Delay in the initiation of range of motion exercises for 4 to 6 weeks was the most common response for both operatively and non-operatively treated patients. This was consistent with past reports,18,26,35 although no standardized rehabilitation protocol exists to our knowledge.

In addition to surgeon management preferences, we explored surgeons’ estimates of complication rates following operative and non-operative management in older, low-demand patients. Our results suggest that surgeons perceive the overall rates to be low. Symptomatic hardware, usually due to irritation of the implant with peripatellar tissues,7 is believed to be one of the most frequent complications following operative treatment,33,35 consistent with our survey results. Fixation failure is another common post- operative complication, shared by other fragility fractures.22 Miller et al. (2012) found older age to be a significant predictor of fixation failure,42 which may be due to the bone lacking strength to support operative fixation to the point of union.43 Knee stiffness was noted as a complication in both treatment

approaches, the risk of which may be heightened in older patients due to the progressive decline in range of motion and increased joint stiffness with age.47 Although the reported estimates of complications quoted by surgeons in our survey were low, patients ≥60 years have shown to have a significantly higher post-operative complication rate relative to younger patients.22,33 However, we did not inquire about differences in complication rates between patient age groups.

The estimation of re-operation rates of <10% from our results were lower than those reported in the literature, including 22% in a cohort study,26 23% in a retrospective review,42 and 33.6% in a meta- analysis of 24 studies,48 all of which included a large age range of patients. We would expect re-operation rates to be potentially increased in older patients, since symptomatic hardware and fixation failure are common complications, and a higher complication rate has been reported in older relative to younger patients.22,42 Our results however, may reflect a more conservative approach already employed in managing these fractures, or perhaps a more conservative approach in managing complications. This warrants further investigation.

In inquiring how surgeons define a ‘low-demand’ patient, most considered a combination of daily activities and living arrangements, with over half of surgeons considering patient co-morbidities. In past orthopaedic studies, ‘low-demand’ patients have been defined using a combination of age,49-51 osteoporotic bone health,49 medical history,49,52 and activity level/lifestyle.49,50-52 Notably, age was only considered by approximately 60% of our respondents, while it has been a prominent indicator in past studies. This may suggest a shift in how ‘low-demand’ patients are defined in recent years. Living arrangements was a new theme in our results, assessing levels of independence. Identifying the factors used to determine functional demand at baseline provides insight into physician conceptualization, that can be compared to the tools currently available. Although there is some consistency, evaluation criteria are not uniform across surgeons. To our knowledge, there is no formal definition of ‘low-demand’ patients in the orthopaedic trauma literature.

The majority of survey respondents indicated a need for future high level studies evaluating treatment options in this patient group. Similar gaps in knowledge have been highlighted by a recent Cochrane review.53

Furthermore, our final sample of surgeons was smaller than the calculated size. By not reaching the required sample size, we may have missed potential relationships between certain variables and our outcomes. Both the OTA and COA circulated the survey to approximately 1800 members of which approximately 4% of OTA members, and 1.7% (first email) and 2.2% (second email) of COA members clicked on the survey link.

Additionally, our final sample had 90% males and therefore limited our abilities to determine the influence of sex on management practices. This proportion however, is representative of orthopaedic surgeons practicing in Canada. According to the Canadian Medical Association in 2018, 12% of orthopaedic surgeons in Canada were females.54 The number of female orthopaedic surgeons is growing and many are early in their careers. Therefore, management practices of female surgeons may not be accurately captured within our survey.

Our study provides new insight regarding preferences for the management of patella fractures in older adults, a demographic that will continue to grow and contribute to an increased prevalence of patella fractures.21 There are however, several limitations to our study. Firstly, survey data has inherent limitations since estimates are not based on observational or experimental results. Consequently, responses may not accurately represent current practices. Additionally, since only two orthopaedic associations were contacted for survey dissemination, this may introduce selection bias. Membership to the COA and OTA is largely based in North America, and therefore our results are not generalizable to all surgeons globally. Our sample had an over-representation of surgeons practicing in Canada and at academic centers, and thus the results are not representative of non-Canadian or community-based surgeons. Survey questions inquired about preferences and past practices, in which misclassification due to recall or response bias is possible. Since we asked about complication and re-operation rates, this could potentially introduce social desirability. Responses were also limited to categorical variables, which may not be accurate in representing surgeon preferences. Despite these shortcomings, we are the first survey to evaluate treatment patterns in this population. The results have helped us identify trends to support the need for future studies.

3.6 Conclusion

Current studies evaluating indications and outcomes following patella fracture management in older populations are limited. There is lack of consensus on operative indications for the management of patella fractures in older, low-demand patients, particularly with regard to amount of displacement. Fracture management was shown to be influenced by surgeon age, fellowship training, and practice location. There also appears to be no consistency in the criteria used for identifying ‘low-demand’ patients within the orthopaedic practice. With the complexity in managing older, low-demand patients, and the increasing importance of optimizing musculoskeletal care in an aging population, future high level studies in this patient demographic is warranted.

3.7 References 1. Court-Brown CM, Duckworth AD, Clement ND, McQueen MM. Fractures in older adults. A view of the future? Injury. 2018;49(12):2161-2166. 2. Larsen P, Court-Brown CM, Vedel JO, Vistrup S, Elsoe R. Incidence and Epidemiology of Patellar Fractures. Orthopedics. 2016;39(6):e1154-e1158. 3. Court-Brown CM, Aitken SA, Duckworth AD, Clement ND, McQueen MM. The relationship between social deprivation and the incidence of adult fractures. J Bone Joint Surg Am. 2013;95(6):e321-e327. 4. Arora R, Lutz M, Deml C, Krappinger D, Haug L, Gabl M. A prospective randomized trial comparing nonoperative treatment with volar locking plate fixation for displaced and unstable distal radial fractures in patients sixty-five years of age and older. J Bone Joint Surg Am. 2011;93(23):2146-2153. 5. Willett K, Keene DJ, Mistry D, et al. Close Contact Casting vs Surgery for Initial Treatment of Unstable Ankle Fractures in Older Adults: A Randomized Clinical Trial. JAMA. 2016;316(14):1455- 1463. 6. Duckworth AD, Clement ND, McEachan JE, White TO, Court-Brown CM, McQueen MM. Prospective randomised trial of non-operative versus operative management of olecranon fractures in the elderly. Bone Joint J. 2017;99-B(7):964-972. 7. Della Rocca GJ. Displaced patella fractures. J Knee Surg. 2013;26(5):293-299. 8. Rockwood C, Green D, Heckman J, Bucholz R. Rockwood And Green's Fractures In Adults. Philadelphia: Lippincott Williams & Wilkins; 2001:1779, 1788-9. 9. Harris RM, Fractures of the patella and injuries to the extensor mechanism. In: Bucholz, RW, Heckman, JD, Court-Brown CM, eds. Fractures in Adults. Ed 6. Philadelphia, PA: Lippincott Williams and Wilkins; 2006:1969–1998. 10. Lee SY, Choi JY, Lee HI, Lee JM, Cho JH. The Comparison of Postoperative Outcomes Open and Closed Reduction for Patellar Fractures. J Knee Surg. 2020;33(1):73-77. 11. Böstman O, Kiviluoto O, Nirhamo J. Comminuted displaced fractures of the patella. Injury. 1981;13(3):196-202. 12. Steinmetz S, Brügger A, Chauveau J, Chevalley F, Borens O, Thein E. Practical guidelines for the treatment of patellar fractures in adults. Swiss Med Wkly. 2020;150:w20165. 13. Schuett DJ, Hake ME, Mauffrey C, Hammerberg EM, Stahel PF, Hak DJ. Current Treatment Strategies for Patella Fractures. Orthopedics. 2015;38(6):377-384. 14. Lazaro LE, Wellman DS, Sauro G, et al. Outcomes after operative fixation of complete articular patellar fractures: assessment of functional impairment. J Bone Joint Surg Am. 2013;95(14):e96-8.

15. LeBrun CT, Langford JR, Sagi HC. Functional outcomes after operatively treated patella fractures. J Orthop Trauma. 2012;26(7):422-426. 16. Carpenter JE, Kasman R, Matthews LS. Fractures of the patella. Instr Course Lect. 1994;43:97-108. 17. Boström A. Fracture of the patella. A study of 422 patellar fractures. Acta Orthop Scand Suppl. 1972;143:1-80. 18. Lorich DG, Warner SJ, Schottel PC, Shaffer AD, Lazaro LE, Helfet DL. Multiplanar Fixation for Patella Fractures Using a Low-Profile Mesh Plate. J Orthop Trauma. 2015;29(12):e504-e510. 19. Pritchett JW. Nonoperative treatment of widely displaced patella fractures. Am J Knee Surg. 1997;10(3):145-148. 20. Sanderson MC. The fractured patella: a long-term follow-up study. Aust N Z J Surg. 1975;45(1):49- 54. 21. Zhu Y, Liu S, Chen W, Wang L, Zhang X, Zhang Y. Socioeconomic factors and individual lifestyles influencing the incidence of patella fractures: a national population-based survey in China. Int Orthop. 2019;43(3):687-695. 22. Byun SE, Sim JA, Joo YB, Kim JW, Choi W, Na YG, Shon OJ. Changes in patellar fracture characteristics: A multicenter retrospective analysis of 1596 patellar fracture cases between 2003 and 2017. Injury. 2019;50(12):2287-2291. 23. Gheno R, Cepparo JM, Rosca CE, Cotten A. Musculoskeletal disorders in the elderly. J Clin Imaging Sci. 2012;2:39. 24. Friedman SM, Mendelson DA. Epidemiology of fragility fractures. Clin Geriatr Med. 2014;30(2):175-181. 25. Joseph B, Pandit V, Khalil M, et al. Managing older adults with ground-level falls admitted to a trauma service: the effect of frailty. J Am Geriatr Soc. 2015;63(4):745-749. 26. Kadar A, Sherman H, Glazer Y, Katz E, Steinberg EL. Predictors for nonunion, reoperation and infection after surgical fixation of patellar fracture. J Orthop Sci. 2014;20(1):168-73. 27. Dillman D, Phelps G, Tortora R et al. Response rate and measurement differences in mixed-mode surveys using mail, telephone, interactive voice response (IVR) and the Internet. Soc Sci Res. 2009;38(1):1-18. 28. Safdar N, Abbo LM, Knobloch MJ, Seo SK. Research Methods in Healthcare Epidemiology: Survey and Qualitative Research. Infect Control Hosp Epidemiol. 2016;37(11):1272-7. 29. Jones D, Story D, Clavisi O, Jones R, Peyton P. An introductory guide to survey research in anaesthesia. Anaesth Intensive Care. 2006;34(2):245-53. 30. Ponto J. Understanding and Evaluating Survey Research. J Adv Pract Oncol. 2015;6(2):168-171.

31. Busse JW, Morton E, Lacchetti C, Guyatt GH, Bhandari M. Current management of tibial shaft fractures: a survey of 450 Canadian orthopedic trauma surgeons. Acta Orthop. 2008;79(5):689-94. 32. R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/. 33. Schuett DJ, Hake ME, Mauffrey C, Hammerberg EM, Stahel PF, Hak DJ. Current Treatment Strategies for Patella Fractures. Orthopedics. 2015;38(6):377-84. 34. Kakazu R, Archdeacon MT. Surgical Management of Patellar Fractures. Orthop Clin North Am. 2016;47(1):77-83. 35. Melvin JS, Mehta S. Patellar fractures in adults. J Am Acad Orthop Surg. 2011;19(4):198-207. 36. Schneider P, Bransford R, Harvey E, Agel J. Operative treatment of displaced midshaft clavicle fractures: has randomised control trial evidence changed practice patterns?. BMJ Open. 2019;9(9):e031118. 37. Canadian Orthopaedic Trauma Society. Nonoperative treatment compared with plate fixation of displaced midshaft clavicular fractures. A multicenter, randomized clinical trial. J Bone Joint Surg Am. 2007;89(1):1-10. 38. Sheth U, Wasserstein D, Jenkinson R, Moineddin R, Kreder H, Jaglal SB. The epidemiology and trends in management of acute Achilles tendon ruptures in Ontario, Canada: a population-based study of 27 607 patients. Bone Joint J. 2017;99-B(1):78-86. 39. Willits K, Amendola A, Bryant D, et al. Operative versus nonoperative treatment of acute Achilles tendon ruptures: a multicenter randomized trial using accelerated functional rehabilitation. J Bone Joint Surg Am. 2010;92(17):2767-75. 40. Smith ST, Cramer KE, Karges DE, Watson JT, Moed BR. Early complications in the operative treatment of patella fractures. J Orthop Trauma. 1997;11(3):183-187. 41. Gwinner C, Märdian S, Schwabe P, Schaser KD, Krapohl BD, Jung TM. Current concepts review: Fractures of the patella. GMS Interdiscip Plast Reconstr Surg DGPW. 2016;5:Doc01. 42. Miller MA, Liu W, Zurakowski D, Smith RM, Harris MB, Vrahas MS. Factors predicting failure of patella fixation. J Trauma Acute Care. 2012;72(4):1051-5. 43. Mathew SA, Gane E, Heesch KC, McPhail SM. Risk factors for hospital re-presentation among older adults following fragility fractures: a systematic review and meta-analysis. BMC Med. 2016;14(1):136. 44. Egol K, Howard D, Monroy A, Crespo A, Tejwani N, Davidovitch R. Patella fracture fixation with suture and wire: you reap what you sew. Iowa Orthop J. 2014;34:63-67. 45. Boström A. Longitudinal fractures of the patella. Reconstr Surg Traumatol. 1974;14(0):136-146.

46. Tull F, Borrelli J Jr. Soft-tissue injury associated with closed fractures: evaluation and management. J Am Acad Orthop Surg. 2003;11(6):431-438. 47. Misner JE, Massey BH, Bemben MG, Going S, Patrick J. Long-term effects of exercise on the range of motion of aging women. J Orthop Sports Phys Ther. 1992;16(1):37-42. 48. Dy CJ, Little MT, Berkes MB, Ma Y, Roberts TR, Helfet DL, et al. Meta-analysis of re-operation, nonunion, and infection after open reduction and internal fixation of patella fractures. J Trauma Acute Care. 2012;73(4):928-32. 49. Hyatt BT, Hanel DP, Saucedo JM. Bridge Plating for Distal Radius Fractures in Low-Demand Patients With Assist Devices. J Hand Surg Am. 2019;44(6):507-513. 50. Gross AE. Surgery for the arthritic knee. Can Fam Physician. 1985;31:563-569. 51. Hotchkiss RN. Displaced Fractures of the Radial Head: Internal Fixation or Excision?. J Am Acad Orthop Surg. 1997;5(1):1-10. 52. Young BT, Rayan GM. Outcome following nonoperative treatment of displaced distal radius fractures in low-demand patients older than 60 years. J Hand Surg Am. 2000;25(1):19-28. 53. Sayum Filho J, Lenza M, Teixeira de Carvalho R, Pires OG, Cohen M, Belloti JC. Interventions for treating fractures of the patella in adults. Cochrane Database Syst Rev. 2015;(2):CD009651. 54. Canadian Medical Association. Orthopedic Surgery Profile. https://www.cma.ca/sites/default/files/2019-01/orthopedic-surgery-e.pdf. Updated August 2018. Accessed August 30, 2020.

3.8 Appendix

3.8.1 Letter of Intent

Dear potential participant, You are being asked to consider taking part in a study investigating orthopaedic surgeons’ approaches to managing patella fractures.

Description of the Research: The purpose of this study is to compare surgeons' preferences in the management of patella fractures in elderly, low-demand patients. Specifically, we will inquire about preferred method of treatment for different types of fractures, operative/non-operative indications, and complication rates.

By taking 10 minutes to complete the survey, you will assist in providing the above information.

We would appreciate your responses to all questions however, no individual question is mandatory. A participant ID number will be assigned to track completion of the surveys. No identifiable information will be captured and survey responses will be limited to one per computer.

This survey will be available until July 31st, 2019.

Participation and Withdrawal: Your consent to participate in this study is implied by the completion and submission of the survey. The decision to participate or not, and the survey responses, will have no professional impact. You may withdraw from the study at any time without giving reason and without penalty by contacting the study PI or research staff at [email protected]. Completed surveys will be reviewed by the study investigators for data entry and analysis. The results of this study may be presented at conferences, seminars or other public forums, and published in journals. No information used in these presentations would disclose your identity as a study participant. No information from this study will be released or printed that would disclose your personal identity without your permission.

By completing this survey you are agreeing to the following: As Survey Monkey’s servers are located in the United States, they are subject to the conditions of the PATRIOT ACT. As such, we cannot guarantee that these files will not be accessed by others. However, no information that personally identifies you will be collected in this survey. Please do not hesitate to contact us if you have any questions at (416) 864-6060 ext 2608 during business hours. If you have any questions regarding your rights as a research participant, you may contact the Unity Health Toronto Research Ethics Board at (416) 864-6060 ext 2557 during business hours.

Please keep a copy of this document for your records.

Sincerely,

Aaron Nauth MD MSc FRCS(C) Orthopaedic Surgery St. Michael's Hospital, Toronto, ON Canada [email protected] (416) 864-6060 ext 2608

3.8.2 Survey

Part A: Demographic Information 1. What is your age? a. < 30 years b. 30 - 40 years c. 41 - 50 years d. 51 - 60 years e. ≥ 61 years 2. Are you: a. Male b. Female c. Prefer not to say 3. Where is your location of practice? a. Canada b. USA c. International 4. Type of practice: (check all that apply) a. Academic Hospital affiliated with a University b. Community Public Hospital c. Community Private Hospital 5. How many years have you practiced independently? a. ≤ 5 years b. 6 - 15 years c. 16 - 25 years d. > 25 years e. I am currently a fellow 6. What fellowship training have you completed? (check all that apply) a. Lower extremity b. Trauma c. Sports medicine d. No training e. Other (please specify): ______

Part B: Institutional Patella Fracture History 1. Approximately how many patella fractures present at your institution per year? a. ≤ 5 b. 6 - 15 c. 16 - 25 d. 26 - 35 e. > 35 2. Approximately what percentage of patella fractures are treated operatively at your institution? a. < 20% b. 20 - 40% c. 40 - 60% d. 60 - 80% e. 80 - 100% 3. At your institution, what percentage of patella fracture patients are elderly (≥ 65 years)?

a. < 20% b. 20 - 40% c. 40 - 60% d. 60 - 80% e. 80 - 100%

Part C: Treatment Options 1. Given an elderly (≥65 years), low-demand patient with an intact extensor mechanism, what degree of displacement warrants operative treatment in your opinion? a. 1 - 2 mm b. 2 - 5 mm c. 5 - 10 mm d. 10 - 20 mm e. > 20 mm f. Other (please specify): ______2. Please indicate your preferred treatment for patella fracture with the displacement indicated below for elderly (≥65 years), low-demand patients with an intact extensor mechanism. ORIF with ORIF with Screws Other Non- Kirschner wires Plate Patella Kirschner and fixation operative/ and tension band Screw and Fracture wires and tension (ex: conservati wiring with non- fixation screw displacement tension band suture ve absorbable fixation band wiring wiring fixation) treatment sutures

Non- /minimally- displaced

Displaced

3. Please indicate your preferred treatment for each of the displaced patella fracture patterns in elderly (≥65 years), low-demand patients with an intact extensor mechanism. ORIF with ORIF with Screws Other Non- Kirschner wires Plate Patella Kirschner and fixation operative/ and tension band Screw and Fracture wires and tension (ex: conservati wiring with non- fixation screw classification tension band suture ve absorbable fixation band wiring wiring fixation) treatment sutures

Displaced transverse

Displaced vertical

Displaced comminuted/ stellate

Displaced Superior or inferior pole

4. How strongly do the following factors influence your treatment decision when deciding between operative and non-operative management? Factors Not at all Somewhat Strongly

Age

Functional demand

Displacement

Bone quality

Comorbidities

Fracture pattern

Number and size of fragments

Patient compliance

Intact extensor mechanism

Compromised soft tissue

Open wounds

Other (please specify):

Part D: Operative Management 1. What is your preferred post-operative protocol for: weight bearing a. Weight bearing as tolerated b. Restrictive weight bearing 2. What is your preferred post-operative protocol for range of motion: flexion a. Immediate i. Immediate Flexion: To what angle (in degrees)? ______ii. Immediate Flexion: For how many weeks? ______b. Delayed i. Delayed Flexion: For how many weeks? ______3. What is your preferred post-operative protocol for range of motion: active extension a. Immediate b. Delayed i. Delayed Active Extension: For how many weeks? ______4. What is your preferred post-operative protocol for: immobilization a. Use of splint or other brace b. No immobilization 5. Based on your experience, what are the three most common complications following operative management in elderly (≥65 years) patients? Rank top three choices from most to least common. a. Failure of fixation (breakage/migration of implant, loss of reduction)

b. Symptomatic hardware c. Infection d. Non-union e. Mal-union f. Post-traumatic arthritis g. Knee stiffness h. Extensor lag i. Wound breakdown j. Other (please specify): ______6. Based on your experience, estimate what percentage of elderly (≥65 years), operatively treated patients develop post-operative complications? a. < 10% b. 10 - 20% c. 20 - 40% d. ≥ 40% 7. Based on your experience, estimate what percentage of elderly (≥65 years), operatively treated patients require re-operation? a. < 10% b. 10 - 20% c. 20 - 40% d. ≥ 40%

Part E: Non-operative Management 1. What is your preferred non-operative protocol for: weight bearing a. Weight bearing as tolerated b. Restrictive weight bearing 2. What is your preferred post-operative protocol for range of motion: flexion a. Immediate i. Immediate Flexion: To what angle (in degrees)? ______ii. Immediate Flexion: For how many weeks? ______b. Delayed i. Delayed Flexion: For how many weeks? ______3. What is your preferred post-operative protocol for range of motion: active extension a. Immediate b. Delayed i. Delayed Active Extension: For how many weeks do you delay? ______4. What is your preferred non-operative protocol for: immobilization a. Use of splint or other brace b. No immobilization 5. Based on your experience, what are the three most common complications following non- operative management in elderly (≥65 years) patients? Rank top three choices from most to least common. a. Non-union b. Mal-union c. Post-traumatic arthritis d. Knee stiffness e. Extensor lag f. Other (please specify): ______6. Based on your experience, estimate what percentage of elderly (≥65 years), non-operatively managed patients develop complications? a. < 10%

b. 10 - 20% c. 20 - 40% d. ≥ 40%

Part F: Defining low-demand 1. How do you determine if a patient is “low-demand”? (check all that apply) a. Age b. Activities of daily living c. Presence of comorbidities d. Living status (nursing home, assisted living, or independent) e. Frailty Index/Score (ex: Canadian Study of Healthy Aging- Clinical Frailty Scale (CSHA-CFS)) f. Activity scoring system (ex: Physical Activity Scale of the Elderly, Lahey Clinic Demand Score g. Other (please specify): ______

Part G: Future Research 1. Do you feel there is a need for further trials to evaluate outcomes following operative versus non- operative management of patella fractures in elderly (≥65 years), low-demand patients? a. Yes b. No

2. Would you change your practice if a large randomized controlled trial showed a clear benefit to operative or non-operative management of patella fractures in elderly (≥65 years), low-demand patients? a. Yes b. No

Thank you for taking the time to complete this survey.

4.0 A retrospective cohort evaluating treatment and health services outcomes in older, patella fracture patients

This chapter presents the primary and secondary objectives of our retrospective population-level cohort study. We provide an overview of the data sources used, study population, data analysis methods, and identify main outcomes and covariates of interest. Outcomes from the study are presented and discussed. We summarize limitations and provide directions for future research.

4.1 Rationale

There remains a substantial lack of understanding regarding treatment and health services outcomes following patella fracture management in older patients. Most studies are limited due to the large age range of patients included, short follow-up duration, small sample size, and/or inclusion of only operatively managed patients. As a result, large scale studies evaluating outcomes in older patients following both operative and non-operative management are limited.

Rates of re-operation, following initial patella fracture management in older adults has not been well- described in the literature. Current studies report re-operation occurring in up to 60% of cases,1-3 however, there remains a lack of consensus on the true rate. Older patients may have a higher re-operation rate than other age groups, given their heightened complication rate following operative management, and predisposition to various factors that impact treatment recovery.4

In addition to treatment outcomes, many health services outcomes have not been previously reported in this patient population. Older adults have been reported to use emergency department (ED) services more than any other age group.5 Reasons for ED readmission are often related to medical conditions such as cardiac, respiratory and cerebrovascular-related health, or falls-related injuries.5,6 Readmissions may also be due to complications following treatment.7 Evaluating the frequency and cause of ED readmission provides an assessment of healthcare performance following both operative and non-operative management, and the opportunity to improve the quality of care in older patients.

Additionally, length of stay (LOS) at time of surgery provides information on resource utilization.8 Identifying factors that are associated with increased LOS may assist in improving patient flow and hospital expenditure, which is increasingly relevant as the global population ages. Prolonged LOS may be impacted by the inability to discharge patients home or to support facilities, and may be associated with an increased risk of hospital-acquired infections.9 Patient comorbidity status has been commonly associated with prolonged LOS in previous hip fracture studies,8,10,11 however, no studies have evaluated risk factors in patella fracture patients.

To our knowledge, there has been no population cohort study evaluating treatment and health services outcomes in older patella fracture patients treated operatively and non-operatively. Health services outcomes, including discharge disposition and health services costs, in addition to LOS and readmissions, have not been adequately studied in this patient population. Therefore, we have designed a population- based retrospective cohort study to evaluate these outcomes in older (≥66 years), patella fracture patients managed both operatively and non-operatively.

4.2 Study Design

To evaluate our objectives, a population-level cohort study has been designed using a health administrative database. Administrative data provides access to a large sample size, long-term follow-up outcomes, and a population-level assessment that adds generalizability of study results. Nevertheless, a retrospective cohort design does have numerous limitations. Firstly, although there are data abstraction atlases and chart studies showing data quality to be good, there is possibility that data coding has changed overtime which may result in missing or inaccurate data. Secondly, administrative datasets are dependent on the accuracy and completeness of medical records and diagnosis/procedural codes. This information may not be completely representative of what occurred with the patient during the healthcare visit. Additionally, since clinical details from the healthcare interaction are not accessible, important factors may be missing. This can include fracture characteristics such as displacement and pattern, baseline functional status, and outcomes such as osteoarthritis, malunion, or nonunion. Other considerations include potential problems in linking data across datasets and data reliability across sites, providers or overtime.

Additionally, there are sources of potential bias within our study. Steps were taken to minimize the impact of bias on our study results. Attrition bias, resulting from loss of patient follow-up, is limited in our study since we are only including Ontario residents who can be tracked, as well as using a population-based study design allows for comprehensive follow-up overtime. Moreover, selection bias is likely by nature of the study design. Since data is encounter based, the results and data do not represent patients who do not interact with the healthcare system. Finally, information bias, including differences in collection or recording of study data,12 was limited by only using data from one administrative database within Ontario and only using one version of diagnosis and procedural codes. This limited potentially differences in disease and procedure classification across different versions.

4.3 Methods

4.3.1 Cohort Development

This retrospective cohort study was developed in collaboration with scientists at ICES (www.ices.on.ca), using administrative healthcare data in Ontario, Canada. A unique, anonymous identifier, in the form of an ICES Key Number (IKN), codes each individual. This identifier allows data to be linked across datasets.

Relevant datasets include:

(1) Canadian Institute of Health Information (CIHI), including Discharge Abstract Database (DAD) and Same Day Surgery Database (SDS): CIHI details clinical and demographic information about hospital admissions across the province. In particular, information regarding diagnosis, procedures, physicians involved in circle of care, length of stay, and disposition at discharge are coded. Both DAD and SDS are updated annually (DAD since 04/1988 and SDS since 04/1991).

(2) Ontario Health Insurance Plan Claims Database (OHIP) inventories all claims made by physicians and healthcare providers for insured services across the Province. The data accessible through OHIP includes: diagnostic information, physician and healthcare team involved in circle of care, date of treatment, and associated fee paid to the healthcare provider are indicated. OHIP is updated bi-monthly (since 07/1991).

(3) Registered Persons Database (RPDB) is a population-based registry containing population and demographic factors held by the Ministry of Health and Long-Term Care. RPDB is updated every two months (since 04/1991).

(4) National Ambulatory Care Reporting System (NACRS) captures patient visits to hospital and community-based ambulatory care centers including day surgery, outpatient clinic visits, emergency department visits, and living arrangements at time of admission. NACRS emergency department database is updated annually (since 07/2000).

(5) Ontario Drug Benefits Claims (ODB) contains information regarding drug claims for all patients’ ≥65 years of age, and has been shown to have an error rate of <1%.13 ODB also has a flag indicating long-term care (LTC) residence status. ODB is updated monthly (since 04/1990, last update 10/2018).

(6) Continuing Care Reporting System (CCRS) contains information on which individuals are LTC residents. CCRS is updated annually (since 07/1996).

(7) National Rehabilitation Reporting System (NRS) includes information on inpatient rehabilitation admission. NRS is updated annually (since 04/2000).

In addition to the datasets, Ontario Marginalization Index (ON-MARG) and Charlson Comorbidity Index tools will be used for this study.

The ON-MARG is an area-level marginalization index, developed from previous frameworks studying deprivation and marginalization. The index has shown to be robust overtime and across geographic locations. A total of four dimensions are coded over the 18 indicators. The four main dimensions include: residential instability (areas of high rate of family or housing instability), material deprivation (indicating inability to attain basic material needs), dependency (representing the concentration of people without employment income), and ethnic concentration (indicating areas of recent immigration and/or areas with large visible minority population). The ON-MARG is summarized into a score for each dimension and quintiles for analysis.14 ON-MARG is updated every few years, with the census data (last update 03/2019).

The second tool used in our cohort is the Charlson-Deyo Comorbidity Index, assessing 1-year mortality risk and burden of disease. This validated index combines comorbidities into a single numeric score allowing patients to be stratified into subgroups based on disease severity. Based on interaction with the healthcare system, the original index contains 19 comorbidities weighted from 1 to 6 for mortality risk and disease severity.15,16 Deyo adapted the score to contain 17 comorbidities to be used with the International Classification of Diseases (ICD) codes.17 A look back window of 3 years will be used and is based on previous orthopaedic cohort studies using administrative data.18 Alternatives of the Charlson- Deyo Comorbidity Index includes the American Society of Anesthesiologists (ASA) scoring system and John’s Hopkins Adjusted Clinical Groups (ACGs).

The research ethics board at St. Michael’s Hospital approved this study.

4.3.2 Project Time Frame

The accrual start and end dates are 01-April-2004 and 31-March-2016. The maximum follow-up date is 31-March-2018 for 2 year follow-up outcomes. Look back windows will include: (1) 5 years prior to index date for the exclusion criteria and baseline dementia diagnosis; (2) 3 years prior to index date for

the Charlson-Deyo Comorbidity Index; and (3) 1 year prior to index date for the diagnosis of osteoporosis via ODB billing. See Figure 4.1.

Figure 4.1 Project Timeline

4.3.3 Inclusion and Exclusion Criteria

Inclusion Criteria

Patients eligible for the study must be diagnosed with a patella fracture via International Classification of Disease 10th version (ICD-10) codes between 01-April-2004 and 31-March-2016. Patients must be ≥66 years of age at the time of injury.

Exclusion Criteria

Patients meeting at least one of the following criteria will be excluded from the study:

• residing outside of Ontario without a valid IKN (due to limitations in long-term follow-up);

• previous patella fracture, knee arthroplasty, operative quadriceps or patellar tendon repair within 5 years preceding diagnosis index via Canadian Classification of Health Intervention (CCI) codes;

• metastatic bone cancer within 5 years preceding diagnosis via CIHI entry;

• previous diagnosis of Paget’s disease, hypercalcemia of malignancy, or breast cancer within 5 years preceding diagnosis via CIHI entry (anti-absorptive therapy, although mostly prescribed for osteoporosis, can be prescribed for the diagnosis’ above);19,20

• patients with bilateral patellar fracture, as indicated by two identical fee codes on the same day via NACRS;

• patients with missing or incorrect data (such as: missing IKN, age, sex, index date is after death – coding error).

4.3.4 Intervention

CIHI-SDS and DAD was used to determine which patients were operatively managed. All patients without surgical codes within the first 4 weeks of their diagnosis were assumed to be non-operatively treated.

Patients with multiple billings for the same injury (submitted due to second opinions, on-call versus outpatient surgeon, etc.) will be counted as one patient using the last billing physician.

4.3.5 Outcomes

Primary Outcome

Our primary outcome was the rate of re-operation (primary or revision open reduction internal fixation [ORIF], hardware removal) in both group at two years post-injury. Re-operation was defined as a new or additional fixation procedure or hardware removal intervention within two years of initial treatment.

Secondary Outcomes

In addition, several health services outcomes were evaluated. Firstly, the frequency and cause of early (within 30 days of treatment discharge) readmission to the ED for all cases via NACRS. All diagnoses were summarized and categorized as patella-related, falls-related and/or medical-related readmissions, adapted from previous studies.5,21 Factors predicting early ED readmission were determined via a logistic regression model.

Furthermore, the cost differential per patient, calculated as one year post-treatment costs minus one year pre-treatment costs, was determined. This was based on a methodology developed at ICES using the “getCost macro”.22 Briefly, patients are classified based on the Comprehensive Ambulatory Classification System (CACS) at time of NACRS admission. CACS groups individuals based on the main diagnosis as

well as the intervention received, age, and gender. CACS groupings are combined to Resource intensity weight (RIW), account for the intensity of healthcare resources used, to form CACS RIW for each case. This reflects the average resource utilization for the CACS group. The case costs for each patient is estimated by multiplying CACS RIW weight by the provincial cost per CACS weighted case (CPCACSC) [Equation 1]. CPCACSC is based on the total reported Management Information System (MIS) costs and the total reported NACRS CACS weights based on databases [Equation 2].

Equation 1: Case Cost (year) = CACS RIW (individual, year) * CPCACSC (institution, year)

Equation 2: CPCACSC (year) = Total Care Costs (year) / Total Weighted Cases (year)

Following operative management, patient discharge information was collected and summarized into four main categories: death in hospital, transferred home, transferred to facility, or LTC home discharge. Discharge disposition will be determined via DAD, and rehabilitative admissions will be determined via NRS. From this data, we will evaluate what proportion of patients return to home versus LTC after injury, and what proportion of patients are transferred to rehabilitative facilities after their injuries. In Ontario, LTC facilities are those providing 24-hour nursing care or supervision within a secure setting, not including retirement homes or rehabilitation units.5

Our final outcome determined factors predicting LOS in hospital at time of operative intervention. LOS was defined as the number of calendar days from the admission to discharge obtained from DAD. LOS was treated as a continuous variable for analysis. Same day discharge was defined as LOS =0.

4.3.6 Covariates

Patient Factors

We determined patient age, sex, geographic LHIN, and income quintiles using RPDP. The ON-MARG dimensions of residential instability, material deprivation, dependency, and ethnic concentration will be analyzed as quintiles.14 The Charlson-Deyo Comorbidity Index using CIHI-DAD data was a marker of medical status at baseline.17 Additional fractures sustained at the time of injury (i.e. distal radius, humerus, proximal femur, etc.) were captured using ICD-10 codes from the index admission. At baseline, a diagnosis of patellar tendon and quadriceps tendon injuries will be noted. Physician-diagnosed dementia in the 5 years preceding the fracture will be determined via ICD-10 codes, as conducted in previous studies.5,23 Since residents are eligible for public prescription benefits starting at 65 years of age, we will use the ODB database to track prescriptions of osteoporosis from the previous year. The diagnosis of osteoporosis will be inferred from diagnosis codes and/or prescriptions for oral anti-absorptive therapies

including bisphosphonates (alendronate, risedronate, etidronate, zoledronic acid) and denosumab. Patients will be considered to have osteoporosis if they filled one prescription for bisphosphonate in the previous year. LTC residence at baseline will be determined using CCRS and/or ODB flag.

Injury and Treatment Factors

Diagnosis of a patella fracture was inferred from ICD-10 codes. CCI procedural codes were used to determine the baseline intervention received (operative or non-operative). Discharge disposition and length of stay at time of intervention will be determined using CIHI-DAD and CIHI-SDS.

Health Services Factors

The delay in treatment delivery for operative patients was inferred by subtracting date of surgery from date of diagnosis. Institution type, categorized as either academic or non-academic/community, was based on membership within the Council of Academic Hospitals of Ontario (CAHO; www.caho-hospitals.com). Index surgeon volume was inferred from the number of times the surgeon was billed the previous two years from the index date for operative patella fracture management. The “feesuff” A category within OHIP was used to determine volume, with “A” referring to procedures performed by the physician.

4.3.7 Data Preparation and Accessibility

Data was prepared in collaboration with an analyst and scientist at ICES. Steps were taken to ensure feasibility of study prior to initiation. We worked closely with the ICES team to ensure all variables were accurately accounted for. When the final data was prepared, a legend was prepared to record all variables with their appropriate description.

Data was accessible via the ICES Data and Analytic Virtual Environment (IDAVE). This is an online system on the ICES server that provides access to study data without being able to transfer or copy data to a personal device. The statistical software was available on IDAVE for use.

4.3.8 Statistical Analysis

All outcomes were summarized using descriptive statistics. There were a total of three variables that had >50% missing data, including: Charlson Comorbidity Index, physician volume, and intervention location. These variables were removed from the analysis.

Our primary outcome, evaluating the rate of re-operation, was evaluated using a cox proportional hazard model followed by a cumulative incidence analysis with competing risk model censoring for death and end of the observation period.

For the secondary outcomes, a multivariate logistic regression model was used to identify covariates affecting ED readmission for both operative and non-operative cases. The causes for ED readmission for each intervention group, as well as for LTC patients, was summarized separately. A multivariate linear regression model was used to determine factors influencing treatment LOS at time of surgery. Additionally, proportions will be used to summarize discharge dispositions and costs for both groups, with a sensitivity analysis for LTC patients.

All analyses were performed using the R Statistics programme (version 3.3.0).24 The following packages were used within R: haven, dplyr, MASS, survival, survminer, car, ggplot2, rms, tidyverse, and boot.25-35 A collaborating ICES scientist and statistician helped with the development of the cohort data and the associated analyses.

4.4 Results

4.4.1 Baseline Characteristics

We identified 23,570 patients with a patella fracture between 2004 and 2016, 6,258 of which met our initial inclusion criteria: 4503 treated conservatively and 1755 treated operatively. A table summarizing the inclusion process is presented in Table 4.1. Women represented 75% of all cases. Approximately 30% of patients had osteoporosis at baseline, and less than 5% of patients had dementia or resided in a LTC home prior to their injury, and approximately 10% of cases sustained an additional fracture at baseline. The average time to death was 1697.32 days (standard deviation [SD] ± 1224.7 days) in the non-operative group, and 2014.82 days (SD ± 1261.2 days) in the operative group. The difference between groups was statistically significant (p<0.001). Complete baseline demographic information is shown in Table 4.2.

Table 4.1 Cohort Development Variable No. of Patients Cohort Size (pre-exclusion) 23,570 Exclusion Criteria Death before index date 16 Non-Ontario residents 11 Age <66 years 14,902 Inegligible for OHIP on index date 8 Patella fracture, knee arthroplasty, operative quadriceps or patellar 272 tendon repair within 5 years prior to injury Metastatic bone cancer within 5 years prior to injury 19 Diagnosis of Paget’s disease, hypercalcemia of malignancy, or 92 breast cancer within 5 years prior to injury Bilateral fracture at baseline 134 Missing CIHI entry within 3 years after 1,834 Small cell count for privacy checking† 24

Cohort Size (post-exclusion) 6,258 †Based on a combination of index year, sex, age group, and LHIN; small cell sizes (<5 cases) were removed to minimize the risk of re-identifying individuals and/or disclosing information of a potentially known person

Table 4.2 Patient Characteristics at Baseline, stratified by treatment Operative Non-operative Total p-value No. of Cases, n(%) 1755 (28.0) 4503 (72.0) 6258 --- Diagnosis, n(%) 0.130‡ S82.000 – closed 1738 (27.8) 4477 (71.5) 6215 (99.3) S82.001 – open 17 (0.3) 26 (0.4) 43 (0.7) Demographics Age, n(%) <0.001‡ 66-69 383 (6.1) 652 (10.4) 1035 (16.5) 70-74 424 (6.8) 849 (13.6) 1273 (20.3) 75-79 415 (6.6) 979 (15.6) 1394 (22.3) 80-84 305 (4.9) 978 (15.6) 1283 (20.5) 85-89 228 (3.6) 1045 (16.7) 1273 (20.3) Sex, n(%) <0.001‡ Male 375 (6.0) 1232 (19.7) 1607 (25.7) Female 1380 (22.1) 3271 (52.3) 4651 (74.3) Residence, n(%) 0.500∏ Missing 1 (0.0) 1 (0.0) 2 (0.0) Rural 206 (3.3) 553 (8.8) 759 (12.1) Urban 1548 (24.7) 3949 (63.1) 5497 (87.8) Year of Injury, n(%) --- 2004 (starting April) 94 (1.5) 245 (3.9) 339 (5.4) 2005 135 (2.2) 338 (5.4) 473 (7.6) 2006 130 (2.1) 369 (5.9) 449 (7.2) 2007 135 (2.2) 361 (5.8) 496 (7.9) 2008 135 (2.2) 319 (5.1) 454 (7.3) 2009 145 (2.3) 363 (5.8) 508 (8.1) 2010 138 (2.2) 365 (5.8) 503 (8.1) 2011 132 (2.1) 350 (5.6) 482 (7.7) 2012 155 (2.5) 394 (6.3) 549 (8.8) 2013 169 (2.7) 405 (6.5) 574 (9.2) 2014 180 (2.9) 448 (7.2) 628 (10.0) 2015 154 (2.5) 432 (6.9) 586 (9.4) 2016 (until March) 53 (0.8) 114 (1.8) 167 (2.7) Fiscal Year, n(%) 0.232† 2004 132 (2.1) 325 (5.2) 457 (7.3) 2005 135 (2.2) 346 (5.5) 481 (7.7) 2006 132 (2.1) 366 (5.8) 498 (8.0) 2007 128 (2.0) 355 (5.7) 483 (7.7) 2008 144 (2.3) 316 (5.0) 460 (7.4) 2009 136 (2.2) 382 (6.1) 518 (8.3) 2010 145 (2.3) 339 (5.4) 484 (7.7) 2011 130 (2.1) 362 (5.8) 492 (7.9) 2012 160 (2.6) 413 (6.6) 573 (9.2) 2013 196 (3.1) 412 (6.6) 608 (9.7)

2014 160 (2.6) 420 (6.7) 580 (9.3) 2015 157 (2.5) 467 (7.5) 624 (10.0) LHIN, n(%) 0.013† Missing 234 (3.7) 628 (10.0) 862 (13.8) 1 56 (0.9) 131 (2.1) 187 (3.0) 2 127 (2.0) 377 (6.0) 504 (8.1) 3 52 (0.8) 158 (2.5) 210 (3.4) 4 204 (3.3) 548 (8.8) 752 (12.0) 5 51 (0.8) 90 (1.4) 141 (2.3) 6 83 (1.3) 246 (3.9) 329 (5.3) 7 160 (2.6) 490 (7.8) 650 (10.4) 8 260 (4.2) 528 (8.4) 788 (12.6) 9 220 (3.5) 514 (8.2) 734 (11.7) 10 64 (1.0) 134 (2.1) 198 (3.2) 11 130 (2.0) 345 (5.5) 475 (7.6) 12 32 (0.5) 101 (1.6) 133 (2.1) 13 66 (1.1) 179 (2.8) 245 (3.9) 14 16(0.3) 34(0.5) 50(0.8) Dementia at baseline, n(%) 50 (0.8) 217 (3.5) 267 (4.3) <0.001‡ LTC resident at baseline, n(%) 33 (0.5) 203 (3.2) 236 (3.8) <0.001‡ Osteoporosis at baseline, n(%) 596 (9.5) 1433 (22.9) 2029 (32.4) 0.111‡ Repeat Cases, n(%) 3 (0.0) 24 (0.4) 27 (0.4) 0.080‡ Additional Fractures at baseline, 144 (2.3) 540 (8.6) 684 (10.9) <0.001‡ n(%) Quadriceps or Patellar tendon 10 (0.2) 28 (0.4) 38 (0.6) 0.955‡ injury at baseline, n(%) Socioeconomic Indicators Income Quintile, n(%) 0.176† Missing 8 (0.1) 24 (0.4) 32 (0.05) Q1 (lowest) 397 (6.3) 1008 (16.1) 1405 (22.5) Q2 383 (6.1) 914 (14.6) 1297 (20.7) Q3 294 (4.7) 884 (14.1) 1178 (18.8) Q4 333 (5.3) 834 (13.3) 1167 (18.6) Q5 (highest) 340 (5.4) 839 (13.4) 1179 (18.8) ON-MARG dependency quintile, n(%) 0.031† Missing 14 (0.2) 50 (0.8) 64 (1.0) Q1 (lowest) 194 (3.1) 496 (7.9) 690 (11.0) Q2 256 (4.1) 609 (9.7) 865 (13.8) Q3 284 (4.5) 714 (11.4) 998 (15.9) Q4 401 (6.4) 906 (14.5) 1307 (20.9) Q5 (highest) 606 (9.7) 1728 (27.6) 2334 (37.3) ON-MARG material deprivation quintile, n(%) 0.900† Missing 14 (0.2) 50 (0.8) 64 (1.0) Q1 (lowest) 285 (4.6) 761 (12.2) 1046 (16.7) Q2 354 (5.7) 878 (14.0) 1232 (19.7) Q3 344 (5.5) 852 (13.6) 1196 (19.1) Q4 360 (5.8) 918 (14.7) 1278 (20.4) Q5 (highest) 398 (6.6) 1044 (16.7) 1442 (23.0) ON-MARG ethnic concentration quintile, n(%) 0.022† Missing 14 (0.2) 50 (0.8) 64 (1.0)

Q1 (lowest) 350 (5.6) 983 (15.7) 1333 (21.3) Q2 333 (5.3) 925 (14.8) 1258 (20.1) Q3 326 (5.2) 837 (13.4) 1163 (18.6) Q4 351 (5.6) 885 (14.1) 1236 (19.8) Q5 (highest) 381 (6.1) 823 (13.2) 1204 (19.2) ON-MARG residential instability quintile, n(%) 0.005† Missing 14 (0.2) 50 (0.8) 64 (1.0) Q1 (lowest) 224 (3.6) 464 (7.4) 688 (11.0) Q2 291 (4.7) 682 (10.9) 973 (15.5) Q3 337 (5.4) 834 (13.3) 1171 (18.7) Q4 355 (5.7) 929 (14.8) 1284 (20.5) Q5 (highest) 534 (8.5) 1544 (24.7) 2078 (33.2) Follow-up Follow-up (days) <0.001◊ N 1755 4503 6258 Mean ± SD 701.2± 119.0 647.2 ± 160.8 681.8 ± 150.7 Median (IQR) 730 (0) 730 (0) 730 (0) Range 726 729 729 No. of patients with complete --- 1621 (92.4) 3856 (85.6) 5477 (87.5) follow-up ‡ Pearson’s χ² test with Yates’ continuity correction; †Pearson’s χ² test; ∏Fisher’s Exact Test with Yates’ Continuity Correction; ◊Wilcoxon rank sum test with continuity correction

Of the patients treated operatively, the mean time to surgery was 7.3 days (SD ± 5.5 days). Ninety percent of cases were inpatient cases, with an average length of stay of 6.7 days (SD ± 6.1 days) at time of surgery. The majority of the procedures were conducted at community hospitals, and patients were predominately discharged either home (with or without supports) or to a long-term care or continuing care facilities following their surgery. Table 4.3 summarizes treatment information for all operatively-treated patients.

Table 4.3 Treatment Factors for Baseline Operative Cases Variable No. of Patients Time from Injury to Surgery (days) N 1755 Mean ± SD 7.3 ± 5.5 Median (IQR) 6 (7) Range 28 Treatment Source, n(%) Inpatient 1567 (89.3) Same Day Surgery 188 (10.7) Discharge Disposition following Inpatient Surgery, n(%) Transferred to another facility providing inpatient hospital care or 122 (7.8) acute care inpatient institution Transferred to a long term or continuing care facility 415 (26.5) Transferred to other ambulatory care, palliative care/hospice, addiction treatment centre, jails, infants and children 12 (0.8) discharged/detained by social services

Discharged to a home setting with support services 396 (25.3) Discharged to home (no support service from an external agency 614 (39.2) required) Signed out (against medical advice) 1 (0.1) Died 7 (0.4) Hospital Type, n(%) Community 1347 (76.8) Teaching 407 (23.2) Other 1 (0.1) Length of Stay following surgery (days) N 1567 Mean ± SD 6.7 ± 6.1 Median (IQR) 5 (6) Range 1, 125

4.4.2 Re-operation

Of the 1755 patients who received baseline operative treatment, 373 patients (21.3%) underwent re- operation within 2 years (Table 4.4). A total of 400 procedures were preformed, 78.3% for hardware removed, 14.5% for revision ORIF, and 7.2% for hardware removal surgery followed by revision ORIF within seven days. Re-operation was predominately (70%) treated as outpatient cases conducted primarily at community hospitals. The average time to hardware removal was 258.7 days (SD ± 172.7 days).

Table 4.4 Characteristics of Re-operation Patients Variable No. of Patients Re-operation No. of Patients, n(%) 373 (21.3) No. of Cases, n(%) 400 (22.8) Re-operation Type, n(%) Revision ORIF 54 (14.5) Hardware Removal 292 (78.3) Both 27 (7.2) Source, n(%) Inpatient 112 (30.0) Same Day Surgery 261 (70.0) Discharge Disposition following Inpatient Care, n(%) Transferred to another facility providing inpatient hospital care or 6 (5.4) acute care inpatient institution Transferred to a long term or continuing care facility 26 (23.2) Transferred to other ambulatory care, palliative care/hospice, addiction treatment centre, jails, infants and children 1 (0.9) discharged/detained by social services) Discharged to a home setting with support services 27 (24.1) Discharged to home (no support service from an external agency 52 (6.4) required) Discharge Disposition following Inpatient Surgery, n(%) Transfer to Facility 7 (6.3)

Transfer to LTC home 26 (23.2) Home 79 (70.5) Hospital Type, n(%) Community 286 (76.7) Teaching 81 (21.7) Small 1 (0.3) Other 5 (1.3) Length of Stay at Time of Surgery (days) N 112 Mean ± SD 6.9 ± 9.8 Median (IQR) 4 (6) Range 1, 72 Revision ORIF Time to Re-operation (days) N 81 Mean ± SD 71.6 ± 112.5 Median (IQR) 35 (51) Range 1, 663 Treatment Code, n(%) 1.VP.74.LA-KD 46 (56.8) Fixation of patella – using open approach and wire, tension band (encirclage) 1.VP.74.LA-KDN 17 (21.0) Fixation of patella – using open approach and synthetic tissue with wire, tension band 1.VP.74.LA-NW 17 (21.0) Fixation of patella – using open approach and and screw/plate 1.VP.74.LA-XXN 1 (1.2) Fixation of patella – using open approach and synthetic tissue [e.g. bone cement or paste] Hardware Removal Time to Hardware Removal (days) N 319 Mean ± SD 258.7 ± 172.7 Median (IQR) 225 (231) Range 7, 724 Treatment Code, n(%) 1.VP.55.LA-KD 282 (88.4) Removal of device, patella – of wire/tension band (encirclage) using open approach 1.VP.55.LA-NW 37 (11.6) Removal of device, patella – of screw/plate using open approach

Within the two-year period, 373 operatively-treated patients had a re-operation, 101 were deceased, and 1281 patients neither experienced re-operation or death following their operative intervention. From the model, age was identified as a time-varying covariate and added into the final model as an interaction term. Overtime, the hazard of re-operation was similar between patients between 66-74 years and 75-89

years (hazard ratio [HR] = 0.999; 95% confidence interval [CI] = 0.997 – 1.000, p=0.059). No other predictors were significant. The model and the estimates are summarized in Table 4.5. Figure 4.2 shows the cumulative incidence curve for re-operation stratified by age, with the competing risk of death. Table 4.5 Influence of various factors on risk of re-operation, cox proportional hazard model Re-operation Events included, N 368 Factor HR (95% CI) p-value Age <0.001 66-74 Reference 75-89 1.058 (0.701 – 1.597) Time 0.445 (0.405 – 0.489) <0.001 Treatment LOS 0.987 (0.961 – 1.015) 0.262 Sex, male 0.833 (0.600 – 1.156) 0.270 Dementia at baseline 0.862 (0.360 – 2.065) 0.498 LTC resident at baseline 0.597 (0.174 – 2.046) 0.915 Osteoporosis at baseline 0.950 (0.699 – 1.292) 0.701 Dependency, 4-5 0.906 (0.686 – 1.195) 0.549 Age*Time 0.060 66-74*Time Reference 75-89*Time 0.999 (0.997 – 1.000) HR = hazard ratio; CI = confidence interval Figure 4.2 Cumulative incidence of re-operation and death within 2 years of treatment by age

4.4.3 ED Readmission

Within 30 days of treatment, 951 patients (15.2%) returned to the ED, representing 1213 visits. Most (79%) patients only returned once during the 30 day period. While non-operative patients represented 74.6% of the patients visited, the proportion of patients returning to the ED following treatment were not significantly different between groups (15.7% for non-operative cases compared to 13.8% for operative cases, p=0.052). The mean days to ED readmission was 11.65 days ± 9.12 days. Table 4.6 summarizes all characteristics of readmission. Table 4.6 Frequency of ED readmissions Variable Operative Non-operative Total p-value No. of total readmissions,∏ n(%) 298 (24.6) 915 (75.4) 1213 No. of patients returned, % 13.79 15.7 15.2 0.052 Days to ER readmission 0.054◊ Mean ± SD 10.9 ± 9.1 11. 9 ± 9.1 11.7 ± 9.1 Median (IQR) 9 (16) 10 (16) 10 (16) Range 1, 30 1, 30 1, 30 Index Year, n(%) --- 2004 (starting April) 19 (1.6) 66 (5.4) 85 (7.0) 2005 26 (2.1) 66 (5.4) 92 (7.6) 2006 25 (2.1) 82 (6.8) 107 (8.8) 2007 21 (1.7) 69 (5.7) 90 (7.4) 2008 22 (1.8) 66 (5.4) 88 (7.3) 2009 16 (1.3) 78 (6.4) 94 (7.7) 2010 20 (1.6) 73 (6.0) 93 (7.7) 2011 18 (1.5) 78 (6.4) 96 (7.9) 2012 25 (2.1) 67 (5.5) 92 (7.6) 2013 28 (2.3) 80 (6.6) 108 (8.9) 2014 35 (2.9) 84 (6.9) 119 (9.8) 2015 31 (2.6) 81 (6.7) 112 (9.2) 2016 (until March) 12 (1.0) 25 (2.1) 37 (3.1) Fiscal Year, n(%) --- 2004 24 (2.0) 78 (6.4) 102 (8.4) 2005 27 (2.2) 76 (6.3) 103 (8.5) 2006 27 (2.2) 76 (6.3) 103 (8.5) 2007 18 (1.5) 77 (6.3) 95 (7.8) 2008 20 (1.6) 59 (4.9) 79 (6.5) 2009 16 (1.3) 84 (6.9) 100 (8.2) 2010 22 (1.8) 66 (5.4) 88 (7.3) 2011 18 (1.5) 76 (6.3) 94 (7.7) 2012 27 (2.2) 66 (5.4) 93 (7.7) 2013 36 (3.0) 88 (7.3) 124 (10.2) 2014 29 (2.4) 73 (6.0) 102 (8.4) 2015 34 (2.8) 96 (7.9) 130 (10.7) Visit Disposition, n(%) --- Home 148 (12.2) 562 (46.3) 710 (58.5) Place of residence (institution) 14 (1.2) 79 (6.5) 93 (7.7)

Transfer to another facility (acute care, non-acute care, 15 (1.2) 22 (1.8) 37 (3.1) intra-facility transfer day surgery or clinic) Admitted to reporting facility as 121 (10.0) 248 (20.4) 369 (30.4) inpatient Deceased 0 (0.0) 2 (0.2) 2 (0.2) Signed Out 0 (0.0) 2 (0.2) 2 (0.2) ◊Wilcoxon rank sum test with continuity correction; ∏patients may have more than one readmission

The frequency of diagnosis codes from all readmissions are summarized in Table 4.7. The most common code was an unspecified place of occurrence code; generally used in combination with a falls, exposure, or other external cause codes (such as exposure to flames). Unfortunately, this diagnosis code does not indicate the exact exposure resulting in readmission. Falls codes (including ICD-10: W00-W19) represented 11.1% of all readmissions. Approximately 70% of falls-related readmissions were in the non- operative treatment group. Patella fracture represented 9.1% of all readmissions, however this code provides little information on the specific reason for the readmission. All other diagnosis codes represent a small proportion of readmissions. The majority of ED readmissions were related to reasons other than a patella fracture or orthopaedic follow-up care.

Table 4.7 Frequency of All Diagnosis Codes Associated with Readmission Variable Operative Non-operative Total No. of total readmissions, n(%) 298 (24.6) 915 (75.4) 1213 No. of total patients, n(%) 242 (13.8) 709 (15.7) 951 (15.2) All Cause Readmissions, n(%) U98.9 – Unspecified place of occurrence 75 (2.6) 198 (6.8) 278 (9.4) S82.00 – Patella fracture 104 (3.6) 161 (5.5) 265 (9.1) W19 – unspecified fall 23 (0.8) 87 (3.0) 110 (3.8) W01 – Fall on same level of slipping, 31 (1.1) 68 (2.3) 99 (3.4) tripling and stumbling Z47.8 – Other specified orthopaedic 12 (0.4) 83 (2.9) 95 (3.3) follow-up care U98.0 – Place of occurrence, home 25 (0.9) 58 (2.0) 83 (2.9) W18 – Other fall on same level 15 (0.5) 31 (1.1) 46 (1.6) E119 – Type 2 diabetes mellitus 10 (0.3) 31 (1.1) 41 (1.4) without (mention of) complications U999 – During unspecified activity 15 (0.5) 24 (0.8) 39 (1.3) E14.9 – Unspecified diabetes mellitus 7 (0.2) 30 (1.0) 37 (1.3) without (mention of) complication I10.0 – Benign hypertension 4(0.1) 30 (1.0) 34 (1.2) X59.0 – Exposure to unspecific factor 9 (0.3) 24 (0.8) 33 (1.1) causing fracture N39.0 – Urinary tract infection, site not 9 (0.3) 23 (0.8) 32 (1.1) specified

Z09.4 – Follow-up examination after 6 (0.2) 25 (0.9) 31 (1.1) treatment of fracture W10 – Fall on and from stairs and steps 15 (0.5) 15 (0.5) 30 (1.0) U98.1 – Place of occurrence, residential 3 (0.1) 26 (0.9) 29 (1.0) institution All remaining codes represent less than 1% of readmissions

A total of 45 (4.5%) baseline LTC patients returned to the ED within 30 days of their treatment, representing 53 visits (Table 4.8). The frequency of codes were similar to those indicated in the main cohort. Place of occurrence codes (ICD-10: U98), falls-related codes (ICD-10: W00-W19), and patella fracture codes represented 13.2%, 11.0%, and 6.6% of all codes, respectively. The majority of codes were related to other medical reasons for readmission, including pneumonia, dementia, urinary tract infection, and congestive heart failure.

Table 4.8 Frequency of All Diagnosis Codes Associated with Readmission in baseline LTC cases Variable Operative Non-operative Total No. of total readmissions, n(%) 5 (9.4) 48 (90.6) 53 No. of total patients, n(%) 5 (0.5) 40 (4.2) 45 (4.7) All Cause Readmissions, n(%) U98.1 – Place of occurrence, residential 1 (0.7) 10 (7.4) 11 (8.1) institution S82.00 – Patella fracture 1 (0.7) 8 (5.9) 9 (6.6) J18.9 – Pneumonia, unspecified 0 (0.0) 8 (5.9) 8 (5.9) W19 – Fall, unspecified 1 (0.7) 5 (3.7) 6 (4.4) F03 – Dementia, unspecified 0 (0.0) 5 (3.7) 5 (3.7) N39.0 – Urinary tract infection, site not 0 (0.0) 5 (3.7) 5 (3.7) specified 150.0 – Congestive heart failure 0 (0.0) 4 (2.9) 4 (2.9) U98.9 – Place of occurrence, unspecified 0 (0.0) 4 (2.9) 4 (2.9) W18 – Fall, on same level 0 (0.0) 4 (2.9) 4 (2.9) I64 – Stroke, not specified as hemorrhage or 0 (0.0) 3 (2.2) 3 (2.2) infarction W05.00 – Fall, involving wheelchair 0 (0.0) 3 (2.2) 3 (2.2) Z47.8 – Other specified orthopaedic follow- 0 (0.0) 3 (2.2) 3 (2.2) up care E11.9 – Type 2 diabetes mellitus without 1 (0.7) 1 (0.7) 2 (1.5) (mention of) complications E14.52 – Unspecified diabetes mellitus with 0 (0.0) 2 (1.5) 2 (1.5) certain circulatory complications E14.78 – Unspecified diabetes mellitus with 1 (0.7) 1 (0.7) 2 (1.5) multiple other complications I10.0 – Benign hypertension 0 (0.0) 2 (1.5) 2 (1.5) K92.0 – Haematemesis 1 (0.7) 1 (0.7) 2 (1.5) R07.4 – Chest pain, unspecified 0 (0.0) 2 (1.5) 2 (1.5) R55 – Syncope and collapse 0 (0.0) 2 (1.5) 2 (1.5) S72.420 – Supracondylar fracture of femur 0 (0.0) 2 (1.5) 2 (1.5)

X59.0 – Exposure to unspecified factor 0 (0.0) 2 (1.5) 2 (1.5) causing fracture All remaining codes represent less than 1% of readmissions

A logistic regression model was included to determine predictors significant for return to ED within 30 days. Significant predictors included sex, place of residence, and baseline dementia diagnosis (Table 4.9). Males had a 20% higher odds returning to the ED compared to females (odds ratio [OR] = 1.207, 95% CI = 1.030-1.408, p = 0.020); patients with baseline dementia had 48% higher odds of returning to the ED (OR = 1.484, 95% CI = 1.075-2.046, p = 0.016); and the odds for a patient living in a rural area returning to the ED within 30 days was 101% greater than a patient not living in a rural area (OR = 2.017, 95%CI = 1.656-2.451, p <0.001). Overall, the R2 value, indicating the amount of variance in the dependent variable explained by the independent variables, was low at 2.1%.

Table 4.9 Influence of various factors on return to ED within 30 days, logistic regression with multiple predictors Return to ED within 30 days Events included, N 935 Factor OR (95% CI) p-value Age 0.281 66-74 Reference 75-89 0.921 (0.792 – 1.070) Sex, male 1.204 (1.030 – 1.408) 0.020 Residence, rural 2.015 (1.656 – 2.451) <0.001 Dementia at baseline 1.484 (1.076 – 2.046) 0.016 LTC resident at baseline 1.128 (0.783 – 1.625) 0.518 Treatment 0.171 Operative 0.893 (0.760 – 1.050) Non-operative Reference Ethnic Concentration, 4-5 0.960 (0.818 – 1.127) 0.813 Dependency, 4-5 0.982 (0.845 – 1.142) 0.616 OR = odds ratio; CI = confidence interval

4.4.4 Length of Stay

The LOS at time of surgery was collected for all inpatient cases, with a mean time of 6.72 days ± 6.05 days. After removing two outliers, with LOS of 48 days and 125 days respectively, the mean LOS was 6.62 days ± 5.16 days.

To determine predictors impacting treatment LOS, a linear regression model was built. The original model was not normally distributed, violating the model assumption of normality. Applied transformations were unsuccessful normally-distributing the right skewed dataset. The original model

with bootstrap confidence intervals (2000 iterations) was preformed. From this analysis, four predictors significantly influenced treatment LOS (Table 4.10). The average treatment LOS increased by 0.776 days (95% CI = 0.722 – 0.823) for every one day delay in treatment. The average treatment LOS decreased by 0.955 days (95% CI = -1.552 - -0.456) for patients living in rural areas relative to urban areas; increased 1.780 days (95% CI = 1.239 – 2.362) in patients with other fractures at baseline; and increased 0.419 days (95% CI = 0.171 – 0.696) in patients between 75-89 years of age relative to those patients between 66-74 years of age.

Table 4.10 Influence of various factors on treatment LOS, linear regression with multiple predictors Treatment LOS Events included, N 1538 Factor Estimates (Bootstrap 95% CI) p-value < alpha (0.05) Age * 66-74 Reference 75-89 0.419 (0.171 – 0.696) Residence, rural -0.955 (-1.552 – -0.456) * Dementia at baseline -0.179 (-1.514 – 0.599) Other fractures at baseline 1.780 (1.239 – 2.362) * Days till treatment 0.776 (0.722 – 0.823) * Deprivation, 4-5 0.091 (-0.164 – 0.402) Ethnic Concentration, 4-5 0.186 (-0.059 – 0.445) Instability, 4-5 -0.037 (-0.322 – 0.242) Osteoporosis at baseline 0.241 (-0.024 – 0.524) Hospital Type Teaching 0.102 (-0.269 – 0.454) Community Reference CI = confidence interval

4.4.5 Discharge Disposition

Discharge disposition information was available for all inpatient operatively treated cases. All non- operative cases were managed as outpatients, and roughly 10% of operative cases were managed as same day cases.

The majority of patients were discharged home (64.5%) with or without support services. Roughly a quarter of patients (26.5%) were transferred to a LTC or continuing care facility. The remaining patients were discharged either to an acute care facility, signed out against medical advice, or were deceased prior to discharge.

With regards to baseline LTC patients who received inpatient surgery, 77.4% returned back to a LTC home or continuing care facility post-intervention. Roughly 10% of patients were discharged home (with

or without support services), and another 10% to an acute care facility. The full breakdown of discharge disposition is presented in Table 4.11.

Table 4.11 Discharge Disposition following Inpatient Surgical Intervention, stratified by LTC status at baseline Variable LTC Non-LTC Total p-value No. of total patients, n(%) 31 (2.0) 1536 (98.0) 1567 -- Discharge Disposition, n(%) <0.001 Transfer to Acute Care Facility 3 (0.2) 131 (8.4) 134 (8.6) Transfer to LTC home 24 (1.5) 391 (25.0) 415 (26.5) Home 3 (0.2) 1007 (64.3) 1010 (64.5) Deceased 1 (0.1) 6 (0.4) 7 (0.4) Signed Out 0 (0.0) 1 (0.1) 1 (0.1)

There was a subset of patients who had rehabilitative facility admission following their baseline intervention. Four hundred and twenty-five patients (6.8%) had rehabilitative facility admission within 7 days of their intervention date. A total of 120 (2.7%) non-operative cases were admitted, however, it is unclear if the readmission was related to their patella fracture, as we have no information regarding their discharge disposition and/or reason for admission. A total of 305 (17.3%) operative patients were admitted to a rehabilitative facility within 7 days of their surgery, 36 (11.8%) of which had an acute care facility discharge following surgery. The mean time to admission for all operative cases was 0.259 days ± 1.133 days. The mean time to rehabilitative admission was significantly different between operative and non-operative groups (p<0.001).

4.4.6 Costs

Total costs were determined based on the algorithm developed at ICES one year prior and after the index date. All costs including, but not limited to: rehabilitation, ED admissions, medications via ODB, LTC home residence, outpatient clinic costs and surgery, were included in the total costs.

At baseline, the mean costs of operative and non-operative patients differed (p<0.001). The mean costs one year prior to injury in the operative group was $7,029.53 ± $13642.34, while the mean costs one year prior to injury in the non-operative was $12,580.61 ± $23,897.66. Contrary, at one-year post-injury, the mean costs were higher in the operative group compared to the non-operative group (p<0.001). Mean costs one-year post-intervention were $33,155.72 ± $31,426.52 and $29,180.23 ± $35,831.17 for operative and non-operative groups, respectively. The net cost differential, the difference in costs one year after injury versus one year prior to injury, was significantly different between groups based on

intervention methods (p<0.001). The net cost for the operative group was $26,126.19 ± $29,744.36 and $16,599.63 ± $34,177.22 for the non-operative group.

In a subgroup analysis, we evaluated healthcare spending of LTC residents. At baseline, one year prior to any injury, there was no difference in the costs between treatment groups (p=0.95). However, at one-year post-injury, costs were significantly different between groups (p=0.041), and higher in the operative group. The mean costs at one year post-injury were $59,747.94 ± $23,823.97 in the operative group and $56,721.79 ± $33,416.38 in the non-operative group. The net cost differential between operative and non- operative cases was not significantly different (p=0.062). The mean net cost for an operatively and non- operatively treated LTC patient was $6,568.64 ± $40,601.79 and $4,547.64 ± $30,892.23, respectively.

4.5 Discussion

This study presents the results from a large, population-based retrospective cohort of older (≥66 years) patella fracture patients across Ontario using administrative data. We identified rates and predictors of various treatment and health services outcomes, which will aid both clinicians and researchers. Given the current lack of data surrounding both treatment and health services outcomes following operative and non-operative management of patella fractures in older patients, our results will be a valuable addition to current literature.

4.5.1 Re-operation

There have been no previous studies evaluating rates of re-operation following operative patella fracture management in older adults. In our cohort, the re-operation rate for revision ORIF and hardware removal was high at 21.3% of patients undergoing a re-operation within two years of initial treatment. The most common reason for re-operation was hardware removal (78.2%). The results also revealed re-operation to be a resource intensive process, with 90% of patients being readmitted at time of re-operation.

Our results are similar to previous single-centered reviews in patients of a wider age group (range 13-94 years),3 but lower than a large meta-analyses which reported a rate of 33.6%.2 There has been no consensus in the literature regarding the true re-operation rate following operative intervention. Melvin and Mehta (2011) indicated literature rates ranging from 0-60%, with inconsistencies in reporting and with regard to surgical technique.1 While our results are not applicable to the high variability reported in existing studies of wider age ranges, they do identify that in patients ≥65 years, re-operation is high.

Furthermore, our investigation revealed that none of the variables we examined were predictive of re- operation. Previous studies have also reported age and sex to not be influential,2 while diabetes was

shown to significantly increase the risk of re-operation.3 Unfortunately, given that diabetes or comorbidity status was not included in our model due to incomplete data, we cannot comment on this finding in our study. Additionally, while some studies have suggested that operative technique does not significantly influence the rate of re-operation,2 others have shown a higher re-operation rate in patients treated with Kirchner wires,36,37 and found partial patellectomy to be protective against re-operation.3 Since we did not have specific details of surgical technique, we were unable to analyze this. Future studies are needed to clarify the relationship between surgical technique and re-operation. We would assume that surgical factors, such as technique, and fracture characteristics, such as displacement and pattern, may influence re-operation to a certain degree. However, there remains a lack of research evaluating the influence of these factors on re-operation.

4.5.2 ED Readmission

ED readmission within 30-days of treatment discharge poses an important problem to our healthcare system. Return to ED is not only costly, but can be burdensome to patients. Our study revealed a 30-day readmission rate of 15.2%; which, compared to previous fracture studies, is elevated. Most reported rates are approximately 10%.7,38-40 Elevated rates in our cohort may be attributed to the inclusion of the non- operative group. However, the difference in readmission rates between treatment groups was not statistically significant (p=0.052). Our results indicate that treatment method does not significantly influence ED readmission.

Reasons for ED readmission varied between patients. Falls codes represented 11% of readmissions, with the majority of presenting cases in the non-operative group. Our results are similar to previous studies indicating that approximately 10% of ED visits in older adults are due to falls-related injuries.41 Falls and low-energy trauma are the most common mechanism of injury in older fracture patients,4 with risk increasing with age.42 As such, incorporating a comprehensive falls assessment at time of fracture management, especially for non-operative cases, may help prevent these injuries from occurring. The falls-related literature is extensive and there are various known risk factors for falls that increase with age. This includes balance abnormalities, visual impairments, and polypharmacy, amongst others.41,43-45 A Cochrane review highlighted interventions such as muscle strengthening and balance retraining programs, home hazard assessment and modification, and multidisciplinary health and environmental fracture screening and interventions are likely effective in reducing falls risk.46

In addition to falls-related readmissions, orthopaedic follow-up care codes, pertaining to general follow- up care, casting, traction device and external fixators, represent potential areas of improvement at the provider level. However, these codes represented only a small subset of readmissions. The majority

readmissions were pertaining to other medical comorbidities. This may suggest that pre-existing medical history have a high influence on readmissions, which is consistent with previous reports.5 Our analysis did not include co-morbidity due to incomplete data. This is however an important factor that should be addressed in future studies.

To determine how to decrease early ED readmission following patella fracture management, understanding which factors predict readmission is important. We found that male sex, rural residence and baseline dementia diagnosis to be predictors of early ED readmission. Similar to our results, a systematic review of 35 studies in patients ≥65years following fragility fractures also found male sex and dementia to be predictive of hospital re-presentation, amongst other variables including medical comorbidities and treatment LOS.47 Our study unfortunately did not include a comorbidity index, which would likely influence ED readmission since the majority of the readmissions in our cohort were for medical reasons unrelated to the patients’ patella fracture. Our model did have low R2 value indicating that important predictors of ED readmission within 30 days were missing. As such, future research should expand on our results by exploring additional predictors of early readmission accounting for both clinical and treatment variables.

4.5.3 Length of Stay

Inpatient length of stay following surgery was significant at an average of 6.62 days. We identified days to surgery, additional fractures at baseline, older age, and rural residence as independent factors predicting treatment LOS. Numerous studies within the orthopaedic trauma literature have highlighted patient comorbidity as an important predictor of LOS.8,10,11,48 However, apart from comorbidity status, there is no consensus on the influence of other factors on patient LOS.

Since comorbidity status was not included in our model, older age and osteoporosis diagnosis (a predictor trending towards statistical significance) may serve as a surrogate for more complex patients with comorbidities. In a national study of patients >50 years of age in Germany, 95% of adults with osteoporosis had at least one other comorbidity, and 66% of adults with osteoporosis had three or more comorbidities.49 Additional fractures at baseline may indicate more complex injuries or fracture patterns, and/or impaired mobility, both of which may delay recovery and hospital discharge. Delays in treatment may be impacted by resource availability (i.e. operating room, surgeon, etc.), however, in general, patients had a length of stay of seven days. Further investigation is warranted to clarify reasons for treatment delay, and the relationship between important predictors of co-morbidity status and frailty on treatment LOS.

Additionally, our evaluation of LOS did not include patients who were non-operatively managed. These patients may have had a readmission, however, our results did not capture this. Future studies may evaluate the LOS of patients following non-operative management.

4.5.4 Discharge Disposition

Discharge placements following operative patella fracture management have not been previously reported. Most of the patients (64.5%) in our cohort were discharged home with support services, or to a care setting (such as acute care or LTC facility), indicating that majority of patients require some level of post-injury care to regain independence and mobility.

As a descriptive analysis, our results provided insight into discharge displacements of patients following operative intervention. Discharge location is an important marker for functional independence.50 Therefore, identifying factors that may influence discharge location may be effective to minimize or prevent unneeded transfers. Although determining factors was not within scope of this study, previous studies have indicated male sex, increased age, pre-injury dependence and hospital-sustained injuries as factors predicting discharge to a location other than residence in a cohort of hip fracture cases.50 With the knowledge of some predictive factors, future analysis may consider these factors to determine how to optimize transfer to acute, rehabilitative, and LTC settings following patella fracture injuries.

4.5.5 Costs

At baseline, the non-operatively treated group had higher costs one-year prior to injury in comparison to the operative group. This may suggest that the non-operative group is more medically complex at baseline, considering the higher healthcare spending. Previous studies have suggested that patients with numerous comorbidities should be non-operatively managed,51,52 which would explain our results. However, without a baseline comorbidity index, it is difficult to draw a distinct conclusion.

The net cost one-year post injury was higher in the operative group in both the general cohort and in the sensitivity analysis of only LTC patients, as expected. It is well-reported that operative management is costlier in comparison to non-operative management.53,54 At a global level, it is difficult to directly compare operative and non-operative groups since the operative group likely represents more complex injuries (such as larger fracture displacement) while the non-operative arm is generally predominated by non- or minimally-displaced fractures. Without important clinical factors, such as fracture displacement, pattern, and mechanism of injury, it is difficult to compare both groups directly. However, one major contributor to healthcare costs in hospital stay at time of surgery, which is not applicable to non- operatively managed cases. This may be an area of potential improvement, should surgery be feasible as

an outpatient procedure. As such, a clinical study comparing similar fracture characteristics receiving both operative and non-operative treatment is needed for a cost-effectiveness analysis.

4.5.6 Limitations and Strengths

Limitations of our study is the use of a retrospective, administrative database. Although various relevant variables are collected, potentially important clinical variables such as fracture type, fracture displacement, and patient functional ability are missing. Specific to our analysis, there were multiple variables that had >60% missing data, and therefore were excluded from our analysis. This included the Charlson-Deyo comorbidity index, which determines baseline comorbidity status based on hospital admissions three years prior to the patients injury. Future analyses may include the Johns Hopkins Comorbidity Index, which unlike the Charlson score, is based on all healthcare interactions including, but not limited to, hospital admissions. Additionally, intervention/surgical codes (via CCI) to differentiate fixation methods is difficult because it is often times not coded or coded incorrectly. As a result, our analysis did not consider the influence of surgical technique on the outcomes assessed.

Strengths of our study include the large sample size with long-term follow-up. The vast majority of previous studies have included single institutions with small sample sizes, none of which have studied patients ≥65 years of age only. With a population-level study, there is generalizability of results, which we believe to be an important strength. Additionally, we included the evaluation of both operative and non-operative groups. Although both groups likely represent different injury severities, it is important to examine all treatments and outcomes. Non-operative management is the most common treatment approach for older adults, however the literature remains sparse. By including various patient and clinical factors that may influence treatment received and subsequent outcomes, there is robustness in our analysis and results.

4.6 Conclusion

In conclusion, this is the first study to our knowledge to evaluate treatment and health services outcomes following operative and non-operative patella fracture management in a large cohort of older patients. Our study revealed that the overall rate of re-operation due to revision ORIF and hardware removal is high (20%) following operative management, and mostly related to hardware removal. Based on the factors analyzed, we were unable to determine any factors predictive of re-operation. Additionally, early ED readmission within 30 days of treatment was significant (15.2%), but generally related to medical concerns unrelated to the patella. ED readmission was not influenced by treatment received, however, male sex, rural residence, and baseline dementia diagnosis were significant predictors of early ED

readmission. Furthermore, delay in treatment and LOS following operative intervention were both significant and averaged around seven days. Delay in surgery, additional fractures at baseline, osteoporosis diagnosis, and rural residence were also independent factors influencing treatment LOS. Finally, net costs were higher following operative intervention, although the non-operative group had an average higher baseline costs prior to injury. Significant factors such as surgery, re-operation, and hospital LOS at time of surgery likely influence the higher costs seen in the operative group. Future studies are required to further evaluate clinical and patient factors predicting important outcomes and clarify the relationship between comorbidity status and relevant outcomes.

4.7 Acknowledgements

The dataset from this study is held securely in coded form at ICES. While data sharing agreements prohibit ICES from making the dataset publicly available, access may be granted to those who meet pre- specified criteria for confidential access, available at www.ices.on.ca/DAS. The full dataset creation plan and underlying analytic code are available from the authors upon request, understanding that the computer programs may rely upon coding templates or macros that are unique to ICES and are therefore either inaccessible or may require modification.

This study contracted ICES Data & Analytic Services (DAS) and used de-identified data from the ICES Data Repository, which is managed by ICES with support from its funders and partners: Canada’s Strategy for Patient-Oriented Research (SPOR), the Ontario SPOR Support Unit, the Canadian Institutes of Health Research and the Government of Ontario. The opinions, results and conclusions reported are those of the authors. No endorsement by ICES or any of its funders or partners is intended or should be inferred.

Parts of this material are based on data and information compiled and provided by CIHI. However, the analyses, conclusions, opinions and statements expressed herein are those of the author, and not necessarily those of CIHI.

4.8 References

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15. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83. 16. Roffman CE, Buchanan J, Allison GT. Charlson Comorbidities Index. J Physiother. 2016;62(3):171. 17. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613-9. 18. Ravi B, Jenkinson R, Austin PC, Croxford R, Wasserstein D, Escott B, et al. Relation between surgeon volume and risk of complications after total hip arthroplasty: propensity score matched cohort study. BMJ. 2014;348:g3284 19. Leslie WD, Lix LM, Yogendran MS. Validation of a case definition for osteoporosis disease surveillance. Osteoporos Int. 2011;22(1):37-46. 20. Park-Wyllie LY, Mamdani MM, Juurlink DN, Hawker GA, Gunraj N, Austin PC, et al. Bisphosphonate use and the risk of subtrochanteric or femoral shaft fractures in older women. JAMA. 2011;305(8):783-9. 21. Bronskill SE, Corbett L, Gruneir A, Stevenson, JE. Introduction. In: Bronskill SE, Camacho X, Gruneir A,Ho MM, editors. Health System Use by Frail Ontario Seniors: An In-Depth Examination of Four Vulnerable Cohorts 22. Wodchis W, Austin P, Henry D. A 3-year study of high cost users in healthcare. CMAJ. 2016. 23. Seitz DP, Gill SS, Austin PC, Bell CM, Anderson GM, Gruneir A, et al. Rehabilitation of Older Adults with Dementia After Hip Fracture. J Am Geriatr Soc. 2016;64(1):47-54. 24. R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. 25. Wickham H, Miller E. haven: Import SPSS, Stata and SAS Files. R package version 0.2.0. 2015. https:// CRAN.R-project.org/package=haven 26. Wickham H, Francois R. dplyr: A grammar of data manipulation. R package version 0.4.3. 2015. https:// CRAN.R-project.org/package=dplyr 27. Venables WN, Ripley BD. Modern applied statistics with S. Fourth Edition. Springer, New York. 2002. ISBN 0-387-95457-0. 28. Therneau T. A package for survival Analysis in S. R version 2.38. 2015. https:// CRAN.R- project.org/package=survival 29. Kassambara A, Kosinski M. survminer: Drawing Survival Curves using ‘ggplot2’. R version 0.2.2. 2016. https:// CRAN.R-project.org/package=survminer 30. Fox J, Weisberg S. An R Companion to Applied Regression, Second Edition. Thousand Oaks CA: Sage. 2011. 31. Wickham H. ggplot2: Elegant graphics for data analysis. Springer-Verlag, New York. 2009.

32. Harrell FE. rms: Regression modelling strategies. R package version 4.5-0. 2016. https:// CRAN.R- project.org/package=rms 33. Wickham H. t 2idyverse: Easily install and load ‘Tidyverse’ packages. R package version 1.0.0. 2016. https:// CRAN.R-project.org/package=tidyverse 34. Canty A, Ripley B. boot: Bootstrap R (S-Plus) functions. R package 1.3-18. 2016. https:// CRAN.R- project.org/package=boot 35. Davison AC, Hinkley DV. Bootstrap methods and their application. Cambridge University Press, Cambridge. 1997. 36. Miller MA, Liu W, Zurakowski D, Smith RM, Harris MB, Vrahas MS. Factors predicting failure of patella fixation. J Trauma Acute Care. 2012;72(4):1051-5. 37. Hoshino CM, Tran W, Tiberi JV, Black MH, Li BH, Gold SM, Navarro RA. Complications following tension-band fixation of patellar fractures with cannulated screws compared with Kirschner wires. J Bone Joint Surg Am. 2013;95(7):653-9. 38. Martin CT, Gao Y, Pugely AJ. Incidence And Risk Factors For 30-Day Readmissions After Hip Fracture Surgery. Iowa Orthop J. 2016;36:155-60. 39. Pollock FH, Bethea A, Samanta D, Modak A, Maurer JP, Chumbe JT. Readmission within 30 days of discharge after hip fracture care. Orthopedics. 2015 Jan;38(1):e7-13. 40. Basques BA, Bohl DD, Golinvaux NS, Leslie MP, Baumgaertner MR, Grauer JN. Postoperative length of stay and 30-day readmission after geriatric hip fracture: an analysis of 8434 patients. J Orthop Trauma. 2015;29(3):e115- e120. 41. Tinetti ME. Clinical practice. Preventing falls in elderly persons. N Engl J Med. 2003;348(1):42-9. 42. Singal BM, Hedges JR, Rousseau EW, Sanders AB, Berstein E, McNamara RM, Hogan TM. Geriatric patient emergency visits. Part I: Comparison of visits by geriatric and younger patients. Ann Emerg Med. 1992 Jul;21(7):802-7. 43. Pijnappels M, van der Burg PJ, Reeves ND, van Dieën JH. Identification of elderly fallers by muscle strength measures. Eur J Appl Physiol. 2008;102(5):585-92. 44. Gheno R, Cepparo JM, Rosca CE, Cotten A. Musculoskeletal disorders in the elderly. J Clin Imaging Sci. 2012;2:39. 45. Campbell VA, Crews JE, Moriarty DG, Zack MM, Blackman DK. Surveillance for sensory impairment, activity limitation, and health-related quality of life among older adults--United States, 1993-1997. MMWR CDC Surveill Summ. 1999;48(8):131-56. 46. Gillespie LD, Robertson MC, Gillespie WJ, Sherrington C, Gates S, Clemson LM, Lamb SE. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2012;(9):CD007146.

47. Mathew SA, Gane E, Heesch KC, McPhail SM. Risk factors for hospital re-presentation among older adults following fragility fractures: a systematic review and meta-analysis. BMC Med. 2016;14(1):136. 48. Court-Brown CM, Biant L, Bugler KE, McQueen MM. Changing epidemiology of adult fractures in Scotland. Scot Med J. 2014;59(1):30-4. 49. Puth MT, Klaschik M, Schmid M, Weckbecker K, Münster E. Prevalence and comorbidity of osteoporosis- a cross-sectional analysis on 10,660 adults aged 50 years and older in Germany. BMC Musculoskelet Disord. 2018 May 14;19(1):144. 50. Deakin DE, Wenn RT, Moran CG. Factors influencing discharge location following hip fracture. Injury. 2008;39(2):213-8. 51. Pritchett JW. Nonoperative treatment of widely displaced patella fractures. Am J Knee Surg. 1997;10(3):145-8. 52. Steinmetz S, Brügger A, Chauveau J, Chevalley F, Borens O, Thein E. Practical guidelines for the treatment of patellar fractures in adults. Swiss Med Wkly. 2020;150:w20165. 53. Corbacho B, Duarte A, Keding A, Handoll H, Chuang LH, Torgerson D, Brealey S, Jefferson L, Hewitt C, Rangan A. Cost effectiveness of surgical versus non-surgical treatment of adults with displaced fractures of the proximal humerus: economic evaluation alongside the PROFHER trial. Bone Joint J. 2016;98-B(2):152-9. 54. Barlow DR, Higgins BT, Ozanne EM, Tosteson AN, Pearson AM. Cost Effectiveness of Operative Versus Non-Operative Treatment of Geriatric Type-II Odontoid Fracture. Spine (Phila Pa 1976). 2016;41(7):610-7.

5.0 Clinical and radiographic outcomes in older, patella fracture patients: a retrospective chart review

This chapter summarizes the objectives and study design of our third study, an ongoing retrospective review. We detail our study and analysis methods, and provide an update on the study progress. The candidate was involved in designing the study, collecting data, and coordinating study completion at all sites.

5.1 Rationale

Numerous studies have reported on the high prevalence of patella fractures in older females due to low- energy trauma,1 classifying these injuries as fragility fractures.2,3 Previous studies have also indicated the heightened complication rate following operative treatment in older patients.1,4 It is likely that the high prevalence of comorbidities and poor bone quality affect treatment recovery.1,4 As a result, non-operative treatment may be an important treatment option for managing fractures in this population. However, treatment outcomes following conservative management relative to operative management remains elusive. Furthermore, there is a lack of clinical evidence on outcomes in general for older patients following patella fracture management. In order to understand past trends and inform future studies, we aim to explore clinical and radiographic outcomes following both operative and non-operative patella fracture treatment in older patients.

The majority of previous retrospective studies have focused on evaluating outcomes following operative management. These studies have either evaluated treatment outcomes (such as fixation failure, re- operation, non-union, or mal-union), clinical outcomes (such as quadriceps strength, flexion and extension), pain, and/or knee-related outcome scores.4-9 To our knowledge, the only retrospective analysis studying outcomes following non-operatively treatment is a study by Braun et al. in 1993, which evaluated pain, range of motion, and post-treatment complications in 40 adult patients.10 This study, in addition to having a small sample size, may not be representative of advances in orthopaedic care today.

Furthermore, there are two previous retrospective studies evaluating outcomes following both operative and non-operative treatment. Shabat et al. in 2003 conducted a single-centre review of 68 patients ≥65 years of age and reported on mechanisms of injury, fracture patterns, and post-operative complications including non-union and osteoarthritis.11 This study however, has limited generalizability due to the uneven sample sizes (10 non-operative cases, 58 operative cases) and data collection limited to a single centre. Additionally, there were a few patients with a disrupted extensor mechanism who were treated non-operatively, although this is generally considered an indication for surgery. This may explain the

higher rate of extensor lag in the conservative group (30%) relative to the operative group (9%). In addition, a separate retrospective review included 570 patients ≥60 years of age between 2003-2017 at five academic hospitals in Korea. The study was limited to evaluating fracture and injury trends overtime, such as a reporting the increasing rate of low-energy injuries between 2003 and 2017.1 The study did not report on injury characteristics, such as average fracture displacement, radiographic evaluation; or clinical outcomes, such as range of motion.

Overall, previous retrospective analyses are limited to either reporting on epidemiology trends or operative outcomes across populations. There has been only one study evaluating outcomes in older patella fracture cases, which was limited by a small sample size.11 Retrospective analyses allow researchers to gather important information regarding extensor mechanism attachment and fracture displacement at injury, as well as clinical outcomes such as pain and function at follow-up. These factors are important in influencing treatment decision making, and recovery following intervention. Reduced range of motion, pain, and knee osteoarthritis are well established outcomes following patella fracture management which directly impact patient quality of life. As a result, these factors require critical evaluation.

Our proposed study seeks to address this gap. We will be conducting a multi-centered, retrospective study evaluating short- and long-term outcomes in older (≥65 years) patella fracture patients treated either operatively or non-operatively. The primary aim of the study is to explore complication rates and radiographic outcomes following management, as well as to evaluate potential predictors of complications. This study design will also allow us to report on common mechanisms of injury, fracture patterns, and radiographic displacement. With the current lack of studies, a retrospective design will allow for outcomes and recovery to be tracked in order to inform future prospective studies. As the prevalence of patella fractures continues to increase with an aging population, it is critical to understand complication rates and predictors of outcome in order to ensure optimal treatment.

5.2 Study Design

A retrospective chart review allows for access to rich, readily accessible data. This information can be used to identify healthcare trends and intervention protocols.12 Unlike a retrospective cohort study at a population level, access to hospital charts allows for retrieval of important variables influencing treatment decision making including: injury and fracture characteristics, such as fracture displacement, fracture pattern, extensor mechanism function, and mechanism of injury; fracture healing status; clinical outcomes, such as return to work and pre-injury functional levels; and long-term outcomes, such non-union, pain, and osteoarthritis.

A retrospective design has numerous benefits, including access to data that can be de-identified and obtained without patient consent. Unlike prospective data, retrospective patient data is both cost-effective and time-efficient.12 With this information, we can identify potential risk factors of interest, and generate hypotheses for further exploration. However, this design is not without limitations. Since it is retrospective, we cannot evaluate temporal relationships or determine causation. The data is limited by the quality of the documentation available in the medical records. There is an assumption that the clinical chart data is accurate in representing what transpired with each patient. Missing data, incomplete records, and difficulty interpreting recorded data are common limitations with this design.12 This is particularly of concern since the data was collected for clinical rather than research purposes. Although there is effort to account for all confounders, unknown or unmeasured confounders can interfere with data interpretation and study conclusions. These factors cannot be accurately accounted for in this design.12

Similar to other study designs, there are sources of bias within a retrospective study. Steps were taken to reduce the impact of bias in the study design. The first type of bias, misclassification bias, occurs when there is error in coding during data collection.13 We minimized misclassification bias by including data abstractors who have clinical experience within orthopaedics, along with providing a standardized abstraction guide with definition for all clinical and radiographic variables. Both tools were pilot tested to ensure accuracy prior to dissemination to study personnel across sites. Additionally, since there was no systematic approach in assigning patients to either treatment group, selection bias may be prominent in our study. It is likely that baseline groups of patients treated either operatively or non-operatively are not directly comparable.14 Therefore, our a priori analysis will include comparing patients with displaced fractures treated operatively versus patients with displaced fractures treated non-operatively. Furthermore, since we are using healthcare data, reporting bias, including unclear or underreporting of complications, may impact our rates and estimates of outcomes. This is an inherent bias of retrospective designs that cannot be mitigated. Ascertainment bias, which includes differences in how individuals were chosen to participate in the study, will be reduced by having a standardized inclusion and exclusion criteria, along with using the same diagnostic codes to identify cases across all sites.15

In summary, despite the limitations of a retrospective design, we determined it to be most appropriate for our study purposes. We have taken measures to reduce bias and account for all known confounders within both the study design and analysis.

5.3 Methods

This is a multi-centered retrospective chart review conducted at six academic hospitals across Canada. The lead site is St. Michael’s Hospital, with participating sites including: Sunnybrook Health Sciences,

Ottawa Hospital, Hamilton Health Sciences, London Health Sciences, and Calgary Foothills Medical Centre.

For this minimal risk study, only de-identified information will be collected. Ethics approval from each institutions board will be received prior to study initiation. Contracts between each site and the lead site will be in place prior to study initiation.

The research ethics board at St. Michael’s Hospital has approved this study.

5.3.1 Patient Identification

We will include all patients who have sustained a patella fracture between October 2007 and October 2017. We expect approximately 150-250 cases from each centre over this 10-year period. Patients will be identified using diagnostic codes through existing database maintained at each hospital. All inclusion and exclusion criteria will be applied at this time, with a standardized strategy applied at each site.

A convenience sample will be used for this study. This sampling approach allows for the inclusion of all cases during the study period. A convenience sample is most often employed for uncommon injuries, such as patella fractures, however, does limit the generalizability of study results. Unlike other methods, this allows for all patients meeting the inclusion criteria to equally participate in the study.16

5.3.2 Inclusion and Exclusion Criteria

We will include all patients ≥65 years of age at time of injury with a patella fracture diagnosis, as identified by diagnostic codes. Patients must have sustained a patella fracture between the study dates to be included. We will exclude patients with a prior ipsilateral patella fracture or knee injury, metastatic bone cancer or pathological bone fracture.

5.3.3 Data Collection

Baseline Variables

At baseline, we will collect demographic information including: age at injury, sex, smoking status (options: never smoked, previous smoker, current smoker, not available), medical history, and ambulatory status (options: walker, cane, other, no assistance, not available). Injury characteristics, including date of injury, mechanism of injury (options: fall, car accident via dashboard mechanism, car accident via pedestrian struck, motorcycle accident, cycling accident or fall, sports, other, not available) and an intact extensor mechanism, will be collected from the clinical chart.

Treatment Variables

We will collect treatment-specific information for each patient. For operatively treated cases, information regarding their surgery date (used to determine time to treatment from date of injury), procedure and technique (options: open reduction internal fixation [ORIF] with Kirschner-wires [K-wires] and tension band wiring, ORIF with K-wires and tension band wiring with non-absorbable sutures, screw fixation, plate and screw, other), intra-operative complications, post-operative immobilization, and physiotherapy protocol (including weight-bearing status and range of motion) will be collected. For non-operatively treated patients, information regarding the application of a knee immobilizer, and physiotherapy protocol (including weight-bearing status and range of motion), will be noted.

Clinical Outcomes

Follow-up visits start at two weeks and include up to one-year post-injury. Clinical information collected includes ambulatory status (options: walker, cane, crutch, non-ambulatory, other, no assistance, not available), functional status (including weight-bearing status), return to work and other activities (options: yes, no, not available), and complications (including: infection, mal-union, non-union, knee stiffness, symptomatic hardware).

Long-term follow-up outcomes will be collected up to two-years post-injury. This will include duration of follow-up related to fracture (date of last appointment related to patella fracture), and date and purpose of re-operation.

All clinical data will be collected from the patient charts by either a research assistant, orthopaedic surgery resident, or clinical fellow.

Radiographic Outcomes

At baseline, we will collect information on the fracture pattern (options: transverse- proximal pole, transverse- mid patella, transverse- distal pole, vertical, comminuted/stellate), and displacement (largest distance between fracture fragments on any view measured in millimetres).

For operatively treated cases, we will evaluate the first available post-operative x-ray and classify the surgical reduction as anatomical, fair or poor. Follow-up x-rays will correspond to clinical data collected from the charts, starting at two weeks and including up to one-year post-injury. Fractures will be assessed for healing status (options: no healing, partial union, union), displacement (largest distance between fracture fragments on any view measured in millimeters), surgical reduction (options: reduction maintained or loss of reduction), and maintenance of surgical reduction, for operatively treated cases. Our

definitions for assessing healing and surgical reduction were based on previous orthopaedic trauma studies evaluating radiographic healing in older patients.17

All radiographic data will be collected from local image archiving systems by either an orthopaedic surgery resident or clinical fellow at each site.

5.3.4 Data Management

Administration

De-identified patient data will be collected electronically via Microsoft Excel spreadsheets. This method allows data abstractors to access the collection forms at convenience, and reduces costs. Since our study is a large, multi-centered study, these forms allows for centralized data storage, while reducing time required for data input and transcription error.16 All data will be sent and received through hospital email accounts with password protected files.

Data Quality

All data abstractors have significant clinical experience collecting patient data and/or analyzing x-ray images of fracture patterns. This limits potential errors in interpreting radiographic data or collecting clinical data due to inability to locate and/or interpret information within patient charts.12

Variability in data collection, including intra-rater reliability (ability for same person to reproduce results) and inter-rater reliability (ability to reprocedure same results between different people), is of concern.16 As a result, we implemented a procedural manual to ensure accuracy and consistent in data collection across sites for both clinical and radiographic data.

For clinical data, each variable and option was explained in a legend accompanying the data collection forms to ensure consistency in interpretation. Prior to dissemination to sites, feedback was gathered from research personnel on our team to ensure clarity of all variables and options. For radiographic measurements, a legend defining each variable and option was included in the radiographic form. Images of sample radiographs were included to aid in the interpretation. Our tool was pilot tested by a resident at the lead site with seven cases (both operative and non-operative) to ensure that all constructs were accounted for prior to dissemination. These tools were created with the aim of minimizing error, providing clarity to data abstractors, and ensuring consistency in reporting across sites.

Data Management

Data will be managed at St. Michael’s Hospital, the lead site. Clinical outcomes will be collected from the patient chart available on the electronic health records at each institution. Radiographic outcomes will be collected and measured using available x-ray imaging. Each row of indicates a unique study identification number and each column indicates a data point. Each site will also have a site-specific master linking log to track all patient study identification number and related medical record number. This log will not be sent to the lead site and remain on the participating site only.

Each participating site is responsible for collecting de-identified information on Microsoft Excel spreadsheets using drop-down options for each patient at their site. Once all data has been collected, the password protected spreadsheet will be sent to the lead site.

5.3.5 Statistical Analysis

Baseline demographic characteristics will be summarized using descriptive statistics (e.g. means and standard deviations for numeric data or frequencies and percentages for categorical data). Data will be stratified by treatment received at baseline (operative or non-operative) for analysis. For each complication outcome of interest (infection, mal-union, non-union, knee stiffness, symptomatic hardware) univariate analysis will be performed to compare several variables between patients who have the complication during the follow-up period versus those who are complication-free. A multivariate stepwise logistic regression will be applied to control for confounding and identify the independent predictors for each complication. A prior subgroup analysis will include comparing patients with displaced fractures receiving non-operative treatment with patients receiving operative treatment. We will also assess time to radiographic healing and return to work. A p-value of <0.05 will be considered statistically significant. Analysis will be performed on R Statistics programme (R Foundation for Statistical Computing, Vienna, Austria).18

5.4 Progress to Date

All six sites participating in the study are active, with institutional ethics approval received, and all necessary contracts in place. Clinical and radiographic data collection is ongoing at all sites.

We expect that data will be finished collection by November 2020, with analysis beginning shortly after.

5.5 Conclusion

This study will the first, and largest, retrospective review to evaluate both clinical and radiographic outcomes following patella fracture management in older patients. In particular, we will be able to directly compare patients operatively and non-operatively treated with significant fracture displacement, a

comparison that has not previously been reported. This multi-centered review will help address a substantial gap in knowledge, while identifying current treatment practices. This information will used to inform future studies in this area. As the population continues to age, this study will provide important insight into how to optimize fracture management.

5.6 References 1. Byun SE, Sim JA, Joo YB, Kim JW, Choi W, Na YG, Shon OJ. Changes in patellar fracture characteristics: A multicenter retrospective analysis of 1596 patellar fracture cases between 2003 and 2017. Injury. 2019;50(12):2287-2291. 2. Bengnér U, Johnell O, Redlund-Johnell I. Increasing incidence of tibia condyle and patella fractures. Acta Orthop Scand. 1986;57(4):334-336. 3. Larsen P, Court-Brown CM, Vedel JO, Vistrup S, Elsoe R. Incidence and Epidemiology of Patellar Fractures. Orthopedics. 2016;39(6):e1154-e1158. 4. Miller MA, Liu W, Zurakowski D, Smith RM, Harris MB, Vrahas MS. Factors predicting failure of patella fixation. J Trauma Acute Care. 2012;72(4):1051-5. 5. Lee SY, Choi JY, Lee HI, Lee JM, Cho JH. The Comparison of Postoperative Outcomes Open and Closed Reduction for Patellar Fractures. J Knee Surg. 2020;33(1):73-77. 6. Böstman O, Kiviluoto O, Nirhamo J. Comminuted displaced fractures of the patella. Injury. 1981;13(3):196-202. 7. Hoshino CM, Tran W, Tiberi JV, et al. Complications following tension-band fixation of patellar fractures with cannulated screws compared with Kirschner wires. J Bone Joint Surg Am. 2013;95(7):653-659. 8. Kadar A, Sherman H, Glazer Y, Katz E, Steinberg EL. Predictors for nonunion, reoperation and infection after surgical fixation of patellar fracture. J Orthop Sci. 2014;20(1):168-73. 9. Levack B, Flannagan JP, Hobbs S. Results of surgical treatment of patellar fractures. J Bone Joint Surg Br. 1985;67(3):416-419. 10. Braun W, Wiedemann M, Rüter A, Kundel K, Kolbinger S. Indications and results of nonoperative treatment of patellar fractures. Clin Orthop Relat Res. 1993;(289):197-201. 11. Shabat S, Mann G, Kish B, Stern A, Sagiv P, Nyska M. Functional results after patellar fractures in elderly patients. Arch Gerontol Geriatr. 2003;37(1):93-98. 12. Connelly LM. Retrospective chart reviews. Medsurg Nurs. 2008;17(5):322-323. 13. Catalogue of Bias Collaboration, Spencer EA, Mahtani KR, Brassey J, Heneghan C. Misclassification bias. In Catalogue Of Bias 2018. https://catalogofbias.org/biases/misclassification- bias/ 14. Sauerland S, Lefering R, Neugebauer EA. Retrospective clinical studies in surgery: potentials and pitfalls. J Hand Surg Br. 2002;27(2):117-121. 15. Catalogue of Biases Collaboration, Spencer EA, Brassey J. Ascertainment bias. In: Catalogue Of Bias 2017. https://catalogofbias.org/biases/ascertainment-bias/

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16. Vassar M, Holzmann M. The retrospective chart review: important methodological considerations. J Educ Eval Health Prof. 2013;10:12. 17. Duckworth AD, Bugler KE, Clement ND, Court-Brown CM, McQueen MM. Nonoperative management of displaced olecranon fractures in low-demand elderly patients. J Bone Joint Surg Am. 2014;96(1):67-72. 18. R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

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6.0 Randomized trial comparing operative versus non-operative patella fracture management in older, low-demand patients

This chapter presents our methods for an ongoing randomized trial and our progress to date. We present our study hypotheses, identify the study population and define the outcome measures. Within the study, the student was involved in grant writing and establishing the online REDCap system.

6.1 Rationale

There remains a lack of clear surgical indications regarding the management of displaced patella fractures in older patients. Older age and baseline comorbidities are also significant risk factors for both patella fracture and post-operative complications.1-3 Moreover, the re-operation rate following operative treatment is high,4 with poor functional outcomes often reported. Since loss of mobility and/or physical independence can be particularly devastating for this population,5 it remains crucial to determine how patient outcomes can be optimized following injury.

As previously introduced, there have been several recent studies within the orthopaedic literature that have challenged surgical indications in older patients with extremity fractures. Studies of unstable distal radius fractures in patients ≥70 years,6 displaced olecranon fractures in patients ≥75 years,7 and unstable ankle fractures in patients ≥60 years,8 have shown operatively and non-operatively treated patients to have equivalent outcomes at final follow-up. It is our hypothesis that older patients sustaining displaced patella fractures will have similar outcomes following operative and non-operative treatment. However, there have been no high-level evidence studies comparing these treatment approaches to date.

Past randomized trials on patella fractures have focused on comparing various operative techniques, including biodegradable versus metallic implants, patellectomy with advancement of vastus medialis obliquus versus simple patellectomy, and percutaneous patellar osteosynthesis versus open surgery. All studies were small single-center studies, with patient ages ranging from 14 to 76 years.9 To our knowledge, there has been no randomized study comparing operative versus non-operative management for patella fractures at any age.

Our proposed study seeks to address this gap in evidence. We propose a randomized controlled trial (RCT) comparing operative versus non-operative management of displaced patella fractures in older (≥65 years), low-demand patients. The primary objective is to determine if non-operative treatment leads to equivalent functional outcomes relative to open reduction and internal fixation (ORIF) for the treatment of displaced patella fractures. We hypothesize that non-operative treatment will lead to non-inferior outcomes at one-year post injury, with a lower rate of complications.

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For this study, we will be using a Canadian Study of Health and Aging – Clinical Frailty Scale (CSHA- CFS) to select low-demand patients for study inclusion. Frailty has previously shown to be an independent risk factor for in-hospital complications10,11 and fracture risk.10 We are one of the first orthopaedic studies to include a frailty index to select patients for study inclusion. In addition, we will prospectively collect clinical information regarding general health status, pain, and joint mobility, all of which are key contributors to patient health long-term. With the addition of both clinical and radiographic outcomes, we will have a comprehensive understanding of outcomes following both treatment options for older patients with displaced patella fractures.

6.2 Study Design

A well designed RCT is the gold standard for evaluating the effectiveness of an intervention.12 Although it can be costly and resource intensive, this design allows for the balance of both known and unknown prognostic variables between groups, prevents selection bias, and allows for the evaluation of causal relationships.13 As a result, this study design can be the most rigorous method of hypothesis testing available.14 With the various underpowered retrospective reviews and reports investigating outcomes following patella fracture management completed to date, there is a need for high-quality evidence comparing both treatment modalities in older patients.

Prior to initiating an RCT design, we considered other study designs. Retrospective studies allow for the evaluation of readily accessible data at a low-cost, however, the prominence of missing data and difficulty interpreting information found in the healthcare records are limitations. There are also various confounders that would need to be accounted for, many of which may not be clearly indicated in patient charts. In addition, there is a lack of standardization of management and rehabilitation protocols that would make it difficult to establish a cause and effect relationship.15-18 An additional study design considered was a prospective design. Prospective studies are less costly and allow for long-term follow- up, similar to an RCT. However, this design exposes our study to selection bias and potential imbalance of confounders. With this design, both operative and non-operative groups are likely to differ in ways other than the main intervention under investigation.19 As a result, we determined that an RCT was the most appropriate study design to evaluate our hypothesis.

Despite the strengths of an RCT design, biases may not be completely eliminated, and steps were taken to minimize the impact of bias within our study. Selection bias occurs when baseline characteristics are not balanced between groups.20,21 This bias will be limited by having online randomization via a web-based system (www.randomize.net), allowing for equal distribution of prognostic factors, and random allocation to treatment group.13,22-24 Additionally, volunteer bias occurs when there are systematic difference

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between those who participate in the research study in comparison to those who do not.25 Within our study, volunteer bias is likely low, as patients will be receiving standard of care treatment independent of the treatment arm. We have also taken steps to include numerous sites across both North America and Europe to ensure generalizability of our results. Performance bias is a systematic difference in how care is provided between groups.26 Since we are comparing two treatment approaches without blinding, it is difficult to safeguard against differences in attention received from healthcare workers.20,24 There is also opportunity for potential placebo or behavioral responses as a result of the intervention received.20,26 However, given our study constraints and ethical issues surrounding sham surgery, blinding is a not feasible option. To help prevent performance bias, we have included both objective (ex: “Time Up and Go” Test, radiographic assessment) and subjective measurements (ex: Knee Injury and Osteoarthritis Outcome Score, Visual Analogue Scale for pain) during follow-up. In addition, study outcomes will be assessed by non-investigators. Furthermore, attrition bias, occurs when there are different rates or types of patients who are loss to follow-up.20,24,27 This can impact both study conclusions and generalizability of results, as well as contribute to incomplete data.20,27 As a result, the patients remaining until end of follow-up may not be representative of the entire population. Since our study does include older patients, loss to follow-up is a concern. It may be difficult to assess if patients are getting worse due to age, intervention adverse events, a combination of factors, or an unrelated reason.24,27 We aim to limit the risks of attrition bias by employing an intention-to-treat analysis, and providing a monetary incentive to study sites to ensure completion of patient follow-ups.27

6.3 Methods

We will be conducting a multi-centered RCT comparing operative versus non-operative treatment for displaced patella fractures in older (≥65 years) low-demand patients. Patients will be followed for two- years post-injury. The lead site is St. Michael’s Hospital, and participating sites include: Halifax, Laval University, London Health Sciences Centre, Mount Sinai Hospital, Ottawa Hospital, Mútua Terrassa University Hospital, Vall d’Hebron University Hospital, and University Hospital of Valladolid.

The research ethics board at St. Michael’s Hospital has approved this study. All institutional ethics approval and study contracts will be in place prior to trial initiation.

6.3.1 Patient Identification

For our study, all low-demand patients ≥65 years of age at the time of injury with a displaced patella fracture will be approached for study participation. A consecutive sampling method will be employed, in

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which all patients who meet the study criteria will be approached for recruitment. Patients must meet all study criteria to participate in the study. Patients are equally eligible for both interventions.28

We chose to assess patient demand/functional status using CSHA-CFS.29 As previously indicated, the scale was derived from the Frailty Index and includes an assessment of overall well-being. Patients are scored between 1 (very fit) to 9 (terminally ill). Patients ranging from and including 3 (managing well) up to and including 6 (moderately frail), are eligible for the study, indicating an ambulatory and functionally independent individual who is relatively healthy. This criteria excludes both highly active individuals who may benefit from surgical intervention and individuals who are very frail and have limited mobility who would likely not benefit from surgery. The scale allows for selection of a specific subset of older patients who are “low-demand” but are potential candidates for operative treatment. We chose to use the CSHA- CFS since it is easy to implement in a clinical setting, especially for non-geriatricians, and requires no additional equipment or extensive medical history. We are one of the first orthopaedic trauma studies to use this scale to select low-demand patients for study inclusion. With the CSHA-CFS (Figure 6.1), we can confidently select and study a specific subset of the population to whom the results will be applicable.

Figure 6.1 CSHA-CFS Scale

Reprinted with permission from: Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, Mitnitski A. A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005 Aug 30;173(5):489-95.

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6.3.2 Inclusion and Exclusion Criteria

Inclusion Criteria For patients to be eligible for this study, they must meet all of the following criteria:

• Aged 65 years of age or over at the time of injury;

• Ambulatory prior to injury (with or without walking aids);

• Score between 3 and 6 on the CSHA-CFS, indicating a low-demand patient;

• Sustain a closed patella fracture;

• Fracture displacement of at least 5mm on any x-ray view with knee in full extension;

• Patient is able to perform a straight leg raise with less than 30 degrees of extensor lag, within 14 days of injury;

• Patient is willing and able to sign consent (in-person or via substitute decision maker), follow the study protocol and attend follow-up visits;

• Patient is able to read and understand English (or is there a qualified interpreter available).

Exclusion Criteria For a patient to be eligible for this study, they must not meet any of the criteria below:

• Associated extremity injuries or polytrauma injuries that would otherwise require surgery or interfere substantially with rehabilitation or outcome in the opinion of the investigator;

• Any neurovascular injuries at the level of the knee requiring surgery;

• Pathological fracture;

• Periprosthetic fracture, or if the patient has had other previous knee surgery which would contra- indicate inclusion in the study;

• Contra-indications to surgery;

• Likely problems, in the judgment of the investigators, with maintaining patient follow-up.

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6.3.3 Intervention

At baseline, patient demographics (including age, sex, medical history) and mechanism of injury will be recorded. Once patients have met study criteria and signed the study consent form, they will be randomized to a treatment arm.

Operative treatment will include ORIF using screw(s), wire(s), pin(s), plate(s) or suture fixation at the discretion of the treating surgeon. The trial is designed in a pragmatic fashion, allowing participating surgeons to perform fixation as per the standard of care at their institution. Patients will be placed in a knee immobilizer post-operatively. Non-operative treatment will include immediate placement in a knee immobilizer post-randomization.

6.3.4 Rehabilitative and Physiotherapy Protocol

Independent of the treatment approach, both groups will receive the identical rehabilitative protocol. Following treatment, all patients will be weight bearing as tolerated in a removable knee immobilizer, with progressive range of motion exercises starting at 2 weeks post-treatment. Apart from being removed for bathing and physiotherapy, the knee immobilizer will remain on at all times for 6 weeks. At 6 weeks, patients will begin active extension and progressive strengthening exercises.

6.3.5 Outcomes

Follow-up visits will occur at 2 weeks, 3 months, 6 months, 12 months and 24 months post-injury. Each participant will complete study measurements and questionnaires at standardized intervals, as shown in Table 6.1. Standard of care procedures such as clinical and radiographic evaluation will be maintained.

Table 6.1 Study Scheduled Visits Follow-up Screening/ Treat- 2w 6w 3m 6m 12m 24m Baseline Enrollment ment (+/- (+/- (+/- (+/- (+/- (+/- 3d) 2w) 2w) 1m) 1m) 1m) Eligibility x Consent x Randomization x Radiographs x x x x x x x CSHA-CFS x x x x x x x Pain via VAS x x x x x x x QoL via ED- x x x x x x x 5D-5L KOOS x x x x x TUG Test x x x x x ROM x x x x x

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MRC Grading x x x x x Adverse Events x x x x x x x d = days; w = weeks; m = months; CRFs = Case Report Forms; QoL = quality of life

6.3.5.1 Primary Outcome

Knee Injury and Osteoarthritis Outcome Score Our primary outcome is the Knee Injury and Osteoarthritis Outcome Score (KOOS) at one-year post- injury.30 KOOS is a validated, patient-reported questionnaire with five constructs evaluating: knee- related pain severity and frequency, symptoms, knee-related quality of life, difficulties experienced during sports and recreation, and difficulties experienced during activities of daily living.30,31 The KOOS is used to assess post-traumatic osteoarthritis, and injuries leading to post-traumatic osteoarthritis.31 The 42-item questionnaire examines the five constructs on a five-point Likert scale, measuring symptoms and functions from the previous week.30

The KOOS questionnaire was developed based on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), a literature review, expert panel, pilot study, and feedback from patients with knee conditions. This tool has had extensive psychometric testing prior to establishment. Although the five dimensions are scored separately, the score can be aggregated for the purposes of an RCT. Lower scores are associated with worse outcomes, with population based normative values available for comparison. As a freely available tool with minimal scoring burden, the KOOS was ideal for our research purposes. The KOOS is available in English, French, and Spanish; and therefore applicable to all study sites independent of geographic location. The KOOS has adequate face, content, and construct validity; and is responsive to change overtime.31

Prior to adopting the KOOS for our primary outcome measure, we did consider other functional tools and include the following: (1) The Lysholm Knee Scoring System assesses 8 items including limp, support, locking, instability, pain, swelling, stair climbing, and squatting.31-33 The scale has been previously used in various patella fracture studies,34-36 and can be used to compare surgical and non-surgical interventions. The Lysholm scale however, does require in-person clinical administration and is generally used for assessment of short-term outcomes.31 (2) Another common scale is the WOMAC, used to assess disease severity and response to treatment in patients with either hip or knee osteoarthritis. This 24-item questionnaire is responsive to changes following both operative and non-operative treatment and is composed of three subscales including: pain severity during activity, severity of joint stiffness, and difficulty preforming daily activities.37 The WOMAC, unlike the KOOS, focuses on fewer constructs and requires permission and a licensing fee payment. The WOMAC is also focused on long-term treatment implications, while the KOOS can be used for both short- and long-term assessment. The KOOS was

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developed as an extension to WOMAC and therefore, the WOMAC score can be retrieved from the KOOS.30 (3) One subscale developed from the KOOS is the Physical Function Short Form (KOOS-PS), focused on activities of daily living and sports/recreation subscales.38 This scale was not ideal since it did not consider all constructs important to older patients. (4) The Activities of Daily Living Scale (KOOS- ADL) was also developed from the KOOS, and is useful for symptoms and functional limitations for patients with various knee pathologies, including osteoarthritis, ligament/meniscal injury, and patellofemoral pain. The scale focuses on symptoms and functional limitations, with a separate scale for sporting activities. The KOOS-ADL has no normative values and has not been validated after translation into French or Spanish, which is required for our multi-centered study.31 (5) Furthermore, the Oxford Knee Score is for patients undergoing total knee replacement, and therefore not applicable to our population.39 (6) The final scale is the International Knee Documentation Committee Subjective Knee Evaluation Form, focused on ligament injuries, meniscal injuries, articular cartilage lesions, and patellofemoral pain.40 Similar to previously introduced tools, this scale is not applicable to our patient population.

6.3.5.2 Secondary Outcomes

In addition to our primary KOOS outcome, a variety of secondary outcomes will be collected to evaluate clinical and functional improvements following treatment. Outcomes will include pain, health-related quality of life, clinical and adverse outcomes.

Pain Pain is a common concern in patients follow injury. As a result, pain-intensity will be assessed using the Visual Analogue Scale (VAS). The VAS is a well-established pain measurement tool used in diverse population groups.41 It is self-administered, easy to understand, and available free of cost. Participants indicate their level of pain on a continuous scale, with options ranging from 0 (no pain) to 100 (worst imaginable pain).42 The VAS measurement tool have been used in previous patella fracture studies.43,44

Health-related Quality of Life Health-related quality of life will be evaluated using the patient-reported 5-level EuroQol-5D (EQ-5D-5L) score. The EQ-5D-5L is a generic health quality index including 5 main dimensions including: mobility, self care, usual activities, pain/discomfort, and anxiety/depression. Participants are asked to check the level that most accurately represents their health that day with options including: no problems, slight problems, moderate problems, severe problems, unable to/extreme problems. This is a self-administered questionnaire widely used across populations in both clinical and research settings.45 In addition, EQ-5D-

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5L is a generic preference-based measure allowing to generate quality adjusted life years used in health economic models.46

Clinical Outcomes Clinical outcomes, such as range of motion, extensor lag, and extensor strength will be assessed at each follow-up visit. Flexion and extension knee range of motion (ROM) is needed for daily functional activities.47 Assessment of ROM following injury allows for assessment of joint mobility, providing insight on the status of joint stiffness, swelling, and pain. Loss of ROM can have detrimental effects, such as altered gait pattern, impacting both the ankle and hip joint.47 ROM is assessed during follow-up visits, using a goniometer, and anatomical land markings, such as the greater trochanter, lateral epicondyle, and lateral malleolus. Patients will be assessed for flexion by being asked to flex the knee as far as possible while laying supine on the examining table. Full knee flexion is 135 degrees, or whatever the normal is for the patient on the unaffected leg, with 0 degrees being a straight knee. Extension of the knee will also be measured, with hyperextended measurements reported as negative values.48 ROM measurements can include both active and passive motion. Active movements involve testing for joint range, muscle power, muscle control, and a patient’s willingness to preform the movement. Movements of the injured limb are compared to the contralateral side. Passive movements allow for the determination of the actual amount of ROM persisting at the joint, often requiring assistance of the examiner.48

The second measurement will include assessing extensor lag, occurring when there is a lack of full knee extension when the quadriceps muscle is fully contracted. This lag is common following traumatic injuries, and often due to weakness of the quadriceps muscle. Physical therapy aims to mitigate the impact of extensor lag through strengthening exercises.49 To assess extensor lag clinically, patients sit on the edge of the examining table with their legs dangling. The patient slowly and actively extends the knee as far as possible. The examiner may passively try to extend the patients knee, measuring and recording extensor lag.

The final measurement is extensor strength testing, evaluating muscle weakness, an important assessment for determining neurological deficits. Muscle testing is preformed as a part of the physical examination, allowing for differentiation between weakness from balance of improper endurance.50 The most common grading system is the Medical Research Council of Great Britain Muscle Strength Grading System.51,52 Patients are tested against the examiners resistance and graded on a scale of 0 (no muscle activation) to 5 (muscle activation against examiner’s full resistance, full range of motion).51 This test is easily implemented in a clinical setting, requiring no additional equipment for assessment.50

Radiographs

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Radiographs will be retrieved and and evaluated at each clinical follow-up as per standard of care. Images will be used to monitor radiographical healing and measure fracture displacement. Patients will be also evaluated for non-union, mal-union, loss of surgical reduction, and hardware failure (including hardware migration and hardware breakage).

Adverse Outcomes and Complications All adverse outcomes and complications will be noted at time of follow-up as per standard of care. This will include infection, symptomatic hardware, knee stiffness, osteonecrosis and pain.

6.3.5.3 Additional Outcomes

In addition to our primary and secondary outcomes, we will assess patient mobility via the “Timed Up and Go” (TUG) Test.

Clinical change in mobility will be assessed using the TUG test up to 24 months post injury. This locomotor performance test for older patients is useful in predicting falls risk, and identifying gait and balance abnormalities based on time required to complete the test.53-55

6.3.6 Data Management

All patient data will be collected on Case Report Forms at each study site with data transferred onto an online system. REDCap is a safe and well-established tool for clinical data collection and management. With REDCap, data will be de-identified and directly accessible by the lead site.

6.3.7 Sample Size

This is a non-inferiority trial design evaluating whether the primary outcome (KOOS) scores in the non- operative group are non-inferior to KOOS scores in the operative group at 1 year post-injury. The minimally clinically important difference, the smallest change needed in the score to be clinically meaningful, is estimated to be between 8 and 10 points.30 Assuming a non-inferiority margin of 9, a standard deviation of 15, an alpha of 0.05 and 80% power, we estimate that we will require a total sample size of 70. Based on similar RCTs, we expect a 20% loss to follow-up. Therefore, the required sample size will be 88 patients total.

6.3.8 Statistical Analysis

All baseline demographic variables, as well as primary and secondary outcomes will be analyzed descriptively. Continuous variables will be described with measures of central tendency (mean, median) and variability (standard deviation, interquartile range). Categorical variables will be described using

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counts and proportions. Our primary outcome, KOOS measured at 1 year post-injury, will be analyzed with a linear regression model. Point estimates and 90% confidence intervals of the difference between treatment groups will be used to draw conclusions regarding the non-inferiority of the treatment to control arm. Continuous secondary and additional outcomes, such as pain and the TUG test, will be analyzed at 2 years using ANCOVA while controlling for baseline score. Binary secondary outcomes, such as such as non-/mal-union, will be analyzed with a logistic regression model. Parameter estimates and confidence intervals will be reported.

6.4 Progress to Date

6.4.1 St. Michael’s Hospital Screening Log and Recruitment

Screening and recruitment started in September 2018 at St Michael’s Hospital. Since initiation to the end of February 2020, our single site has screen 62 patients total. Of these patients, three patients have met the study criteria, however, all patients declined study participation and opted for conservative management.

Of all the patients screened at our site, 33 (53.2%) have been females and 29 (46.8%) have been males. Of the 59 patients not meeting the inclusion criteria, 38 patients did not meet the age criteria (<65 years of age at time of injury), 1 patient was not ambulatory at baseline, 2 patients were not ‘low-demand’ (not scoring between 3 and 6 on CSHA-CFS), 1 patient did not have a closed, isolated fracture, 13 patients had a non-displaced fracture (<5mm displacement), 3 patients were not able to preform the straight leg raise, and 1 patient was unable to read and understand the study consent form.

6.4.2 Progress to Date

In addition to our lead site, St. Michael’s Hospital, we have 8 sites involved across North America and Europe. Of these sites, four are currently screening and recruiting patients. These sites include Halifax, Ottawa Hospital, Mount Sinai Hospital, and University Hospital of Valladolid. A total of four sites are in the process of institutional ethics or contracts and have not started recruitment. These sites include: Laval University, London Health Sciences Centre, Mútua Terrassa University Hospital, and Vall d’Hebron University Hospital.

Unfortunately, due to COVID-19, all sites have currently suspended recruitment for the study. It is unclear when study recruitment will resume.

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6.5 Conclusion

Our proposed study will be the first RCT to compare the outcomes of operative and non-operative treatment of patella fractures in older, low-demand patients. We are also one of the first studies in the orthopaedic trauma literature to use a frailty scale to identify low-demand patients and determine study eligibility, as most studies in the past have used age as surrogate for functional status. As a well-designed, multi-centered study, the results from this trial have the potential to clear up areas of uncertainty and inform fracture management in older patients. With our targeted objectives, this study will improve our understanding of older, low-demand patients, drivers of outcomes, and clinical decision-making.

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6.6 References

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14. Last JM. A dictionary of epidemiology. New York: Oxford University Press, 2001. 15. Dworkin RJ. Hidden bias in the use of archival data. Eval. Health Prof. 1987;10(2):173–185. 16. Hess DR. Retrospective studies and chart reviews. Respir Care. 2004;49(10):1171–1174. 17. Pan L, Fergusson D, Schweitzer I, Hebert PC. Ensuring high accuracy of data abstracted from patient charts: The use of a standardized medical record as a training tool. J Clin Epidemiol. 2005;58(9):918–923. 18. VonKoss Krowchuk H, Moore ML, Richardson L. Using health records as sources of data for research. J Nurs Meas. 1995;3(1):3–12. 19. Mann CJ. Observational research methods. Research design II: cohort, cross sectional, and case- control studies. Emerg Med J. 2003;20:54–60. 20. 8.4 Introduction to sources of bias in clinical trials. (2018). Retrieved from https://handbook-5- 1.cochrane.org/chapter_8/8_4_introduction_to_sources_of_bias_in_clinical_trials.htm 21. Lotte Gluud L. Bias in Clinical Intervention Research. Epidemiol Rev. 2006;163(6):493–501. 22. Catalogue of Bias Collaboration, Nunan D, Bankhead C, Aronson JK, Selection bias. Catalogue Of Bias 2017. http://catalogofbias.org/biases/selection-bias/ 23. Jadad AR, Enkin. Bias in Randomized Controlled Trials. In Randomized Controlled Trials (eds A. R. Jadad and M. W. Enkin). 2008. 24. Jüni P, Altman DG, Egger M. Assessing the quality of controlled clinical trials. BMJ. 2001:323(7303):42–6. 25. Jordan S, Watkins A, Storey M, Allen SJ, et al. Volunteer Bias in Recruitment, Retention, and Blood Sample Donation in a Randomised Controlled Trial Involving Mothers and Their Children at Six Months and Two Years: A Longitudinal Analysis. PLoS One. 2013;8(7): e67912. 26. Mansournia MA, Higgins JP, Sterne JA, Hernán MA. Biases in Randomized Trials: A Conversation Between Trialists and Epidemiologists [published correction appears in Epidemiology. 2018 Sep;29(5):e49]. Epidemiology. 2017;28(1):54-59. 27. Catalogue of Bias Collaboration, Bankhead C, Aronson JK, Nunan D. Attrition bias. In: Catalogue Of Bias 2017. https://catalogofbias.org/biases/attrition-bias/ 28. Kendall J. Designing a research project: randomised controlled trials and their principles. Emerg Med J. 2003; 20(2):164–8. 29. Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005;173(5):489-95. 30. Roos EM, Lohmander LS. The Knee injury and Osteoarthritis Outcome Score (KOOS): from joint injury to osteoarthritis. Health Qual Life Outcomes. 2003;1(1):64.

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31. Collins NJ, Roos EM. Patient-reported outcomes for total hip and knee arthroplasty: commonly used instruments and attributes of a "good" measure. Clin Geriatr Med. 2012;28:367-94. 32. Lysholm J, Gillquist J. Evaluation of knee ligament surgery results with special emphasis on use of a scoring scale. Am J Sports Med. 1982;10(3):150-154. 33. Briggs KK, Lysholm J, Tegner Y, Rodkey WG, Kocher MS, Steadman JR. The reliability, validity, and responsiveness of the Lysholm score and Tegner activity scale for anterior cruciate ligament injuries of the knee: 25 years later. Am J Sports Med. 2009;37(5):890-897. 34. Greenberg A, Kadar A, Drexler M, et al. Functional outcomes after removal of hardware in patellar fracture: are we helping our patients?. Arch Orthop Trauma Surg. 2018;138(3):325-330. 35. Levack B, Flannagan JP, Hobbs S. Results of surgical treatment of patellar fractures. J Bone Joint Surg Br. 1985;67(3):416-419. 36. Suh KT, Suh JD, Cho HJ. Open reduction and internal fixation of comminuted patellar fractures with headless compression screws and wiring technique. J Orthop Sci. 2018;23(1):97-104. 37. Bellamy JL, Runner RP, Vu CCL, Schenker ML, Bradbury TL, Roberson JR. Modified Frailty Index Is an Effective Risk Assessment Tool in Primary Total Hip Arthroplasty. J Arthroplasty. 2017;32(10):2963-2968. 38. Perruccio AV, Stefan Lohmander L, Canizares M, et al. The development of a short measure of physical function for knee OA KOOS-Physical Function Shortform (KOOS-PS) - an OARSI/OMERACT initiative. Osteoarthritis Cartilage. 2008;16(5):542-550. 39. Jenny JY, Diesinger Y. The Oxford Knee Score: compared performance before and after knee replacement. Orthop Traumatol Surg Res. 2012;98(4):409-412. 40. Anderson AF, Irrgang JJ, Kocher MS, Mann BJ, Harrast JJ; International Knee Documentation Committee. The International Knee Documentation Committee Subjective Knee Evaluation Form: normative data. Am J Sports Med. 2006;34(1):128-135. 41. Carlsson AM. Assessment of chronic pain.Aspects of the reliability and validity of the visual analogue scale. Pain. 1983;16(1):87-101. 42. Hawker GA, Mian S, Kendzerska T, French M. Measures of adult pain: Visual Analog Scale for Pain (VAS Pain), Numeric Rating Scale for Pain (NRS Pain), McGill Pain Questionnaire (MPQ), Short- Form McGill Pain Questionnaire (SF-MPQ), Chronic Pain Grade Scale (CPGS), Short Form-36 Bodily Pain Scale (SF-36 BPS), and Measure of Intermittent and Constant Osteoarthritis Pain (ICOAP). Arthritis Care Res (Hoboken). 2011;63 Suppl 11:S240-S252. 43. Anand S, Hahnel JC, Giannoudis PV. Open patellar fractures: high energy injuries with a poor outcome?. Injury. 2008;39(4):480-484.

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44. Larsen P, Vedel JO, Vistrup S, Elsoe R. Long-Lasting Hyperalgesia Is Common in Patients Following Patella Fractures. Pain Med. 2018;19(3):429-437. 45. Herdman M, Gudex C, Lloyd A, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727-36. 46. Brazier J, Ara R, Rowen D, Chevrou-Severac H. A Review of Generic Preference-Based Measures for Use in Cost-Effectiveness Models. Pharmacoeconomics. 2017;35(Suppl 1):21-31. 47. Shah N. Increasing knee range of motion using a unique sustained method. N Am J Sports Phys Ther. 2008;3(2):110-113. 48. Magee D, Sueki D. Orthopedic Physical Assessment Atlas And Video. 1st ed. St. Louis, Missouri: Elsevier; 2011:2,342. 49. Sprague RB. Factors related to extension lag at the knee joint. J Orthop Sports Phys Ther. 1982;3(4):178-182. 50. Naqvi U, Sherman Al. Muscle Strength Grading. [Updated 2019 Jul 1]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2020 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK436008/?report=classic 51. Council MR. Aids to the examination of the peripheral nervous system: His Majesty’s Stationary Office, Editor. 1981. 72 p. 52. James MA. Use of the Medical Research Council muscle strength grading system in the upper extremity. J Hand Surg Am. 2007;32(2):154-156. 53. Podsiadlo D, Richardson S. The timed "up & go": A test of basic functional mobility for frail elderly persons. J Am Geriatr Soc.1991;39(2):6. 54. Freter SH, Fruchter N. Relationship between timed 'up and go' and gait time in an elderly orthopaedic rehabilitation population. Clin Rehabil. 2000;14(1):96-101. 55. Okumiya K, Matsubayashi K, Nakamura T, et al. The timed ‘Up & Go’ test is a useful predictor of falls in community-dwelling older people. J Am Geriatr Soc. 1998;46:928-9.

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7.0 Discussion and Conclusion

The primary purpose of this thesis was to investigate and compare operative and non-operative treatments for patella fractures in older patients. With the current uncertainty regarding surgical indications in older adults, in addition to the poor outcomes and high re-operation rates reported in the literature, further investigation is required to determine optimal management. The project aimed to explore this question at multiple levels including: healthcare provider perspectives via a surgeon survey, retrospective analysis using both population-level and hospital databases, and prospective analysis via a randomized trial to directly compare treatment approaches.

We found that although orthopaedic surgeons generally agreed that displaced fractures require operative management and non-/minimally-displaced fractures can be treated non-operatively. However, the degree of displacement warranting operative management lacked consensus. Displacement however, is only one indicator for surgery, and often considered in combination with various other factors, such as assessing the integrity of the extensor mechanism. We found that roughly half of the surgeons believed that re- operations occur in less than 10% of patients, while our retrospective cohort study found the rate to be greater than 20%, which was consistent with the high rates reported in the literature. Although our study did not identify any patient factors predictive of re-operation due to revision ORIF and hardware removal, future studies are needed to evaluate clinical factors (such as operative technique, fracture pattern, fracture displacement), and its influence on re-operation. By identifying these factors, clinicians may use this information to determine patients at risk for a second operation, and help manage patients’ expectations.

Additionally, ED readmissions were common following patella fracture, and were independent of treatment received. In analyzing the causes of readmission, most patients returned for medical-related factors, however falls-related readmissions were significant, especially amongst non-operatively treated patients. At baseline, these patients were found to have a higher average healthcare costs relative to the operative group, which may indicate a greater number of co-morbidities. However, without direct evaluation of co-morbidity status, it is difficult to confirm this. Injuries due to falls in older individuals may indicate the need for falls-assessments at the time of injury in order to reduce subsequent injuries and ED readmissions. In addition, on average, patients had an average seven day LOS at time of surgery. Delays in surgery date and hospital discharge also directly influence healthcare costs. Finally, our cohort study found operatively treated patients to have higher net healthcare costs relative to non-operatively treated patients, while the baseline costs pre-injury were higher in the non-operative group. This may indicate that non-operatively treated patients are more medically complex at baseline; however, without

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any assessment of co-morbidity or frailty status, it is difficult to draw a conclusion. Future studies should focus on the influence of co-morbidity status and clinical variables (such as fracture characteristics) on the outcomes described.

Through the completion of these two studies, significant advancements have been made in the field. Our studies are one of the first to report on rates of re-operation in older adults, as well as describe ED readmission, LOS and surgeon management practices following patella fractures. In addition, our studies also serve as an important educational opportunity for surgeons regarding the incidence of complications and health service outcomes. For example, our survey indicated that surgeons estimate a <10% re- operation rate, while our cohort study indicated the rate to be 21% in older adults. The discrepancy highlights the potential underestimation of complications and overestimation of outcomes, and therefore provides important insight for healthcare providers.

While our studies have addressed gaps in knowledge pertaining to treatment and health services outcomes, as well as surgeon perspectives, there remains limited literature regarding best practices for managing patella fractures, as well as patient experiences following intervention, particularly in elderly patients. Our ongoing multicentre retrospective study and prospective randomised trial seek to address these gaps, and their protocols were described in this thesis.

The completion of our retrospective chart review will allow for the comparison of both clinical and radiographic outcomes following operative and non-operative management for displaced fractures. From this study, we will be able to gather information on important clinical factors, such as average fracture displacement, fracture pattern, return to work/activities, rehabilitation protocols, and complications such as infection, mal/non-union, pain and osteoarthritis; as well as radiographic outcomes, such as fracture displacement and fracture healing. These outcomes have not been previously assessed in other studies. We have established an apriori analysis of comparing radiographic healing, complication rates, and return to work/activities in a subset of patients with displaced fractures treated either operatively or non- operatively. This would be the first study to compared outcomes for displaced fractures between treatments in this patient population, and will be the largest study to date evaluating clinical and radiographic outcomes in older patients.

While our retrospective analysis allows for the comparison of outcomes following patella fracture management, there are limitations of this study design. Without standardized reporting and measuring, as well as potentially missing important covariates, it is difficult to draw distinct conclusions from this study design regarding optimal treatments for this patient group. As a result, we have developed a randomised trial comparing operative and non-operative management for displaced patella fractures in older, low-

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demand patients. The primary outcome in this study is the Knee Injury and Osteoarthritis Outcome Score at one-year post-injury, which accounts for patient-reported pain, symptoms, knee-related quality of life, sports and recreation function, and activities of daily living. Unlike our previous studies, this design allows for the direct comparison between treatment groups with the balance of known and unknown prognostic factors. Additionally, the application of a standardized criteria and outcome measurement across sites allows for outcomes to be directly compared between groups across sites. Furthermore, this would be the first study in the orthopaedic trauma literature to use a validated Frailty Index to select low- demand patients for study inclusion. Frailty has shown to be an important risk factor for in-hospital complications and fracture risk in older patients. The completion of this study would be the highest level of evidence available comparing treatment options for managing displaced patella fractures in older patients, and will likely influence treatment practices.

Through the completion of the ongoing retrospective and randomised studies, significant advancements will be made in understanding the clinical and radiographic outcomes in patients previously treated for patella fractures, and patient reported outcomes following a standardized trial. These studies will provide important evidence that increases our understanding of managing fractures in older adults, while prompting the need for further studies. Firstly, future studies may expand this evaluation to different aspects of geriatric care including the assessment of frailty, and its relationship to patient outcomes following treatment. Frailty has shown to be an important factor in predicting outcomes and complications in the orthopaedic trauma literature however, there remains a lack of studies exploring the influence on patella fracture outcomes. Often times, age has been used as a surrogate marker for frailty, which may not be an accurate evaluation. Future studies using tools such as the CSHA-CFS to assess baseline frailty are warranted. Secondly, our findings highlighted falls to be the most common mechanism of injury, and a common reason for ED readmission in older fracture patients. This finding speaks to the importance of a comprehensive geriatric assessment at time of injury to help limit, and potentially prevent, falls-related injuries. A geriatric assessment provides an evaluation of the individual’s functional level, physical, cognitive and mental health, as well as their socio-environmental circumstances.1 The results from this assessment help inform long-term care needs of the patient and is used to coordinate care within a multidisciplinary team.1 Future studies may also evaluate the influence of falls-prevention strategies, such as exercise and strengthening programs for improving gait and balance in this patient group. Strategies may focus on addressing medical (polypharmacy, visual impairments) and/or environmental factors (ensuring adequate lighting, limiting stairs, having hand rails accessible) that influence falls risk and long-term outcomes. Since older patients represent a large and growing population, optimizing these aspects of care are critical to improve their health and reduce the number of

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injuries. Additionally, future studies may focus on utilizing patient reported outcome measurements to evaluate patient experience following both operative and non-operative interventions. Many of the studies within the orthopaedic trauma literature have focused on epidemiology trends, clinical and radiographic outcomes, or surgical techniques. Although important, these studies fail to capture patient outcomes and perspectives pertaining to recovery and satisfaction. Our aim with our randomised study is to address some of these concerns, by incorporating a patient reported outcome measure (KOOS) as our primary outcome; however, there is a need for future studies within orthopaedics using similar tools. Moreover, future studies may evaluate the role of co-morbidities in relationship to the health services outcomes. In our cohort, missing data hindered our ability to directly evaluate the influence of co-morbidity status on patient outcomes and the effectiveness of co-morbidities as a predictor for our outcomes. Baseline comorbidity status is likely an influential variable given our population of interest. As a result, incorporating indices such as the Johns Hopkins Comorbidity Index or using a disease specific algorithm available at ICES are important next steps. Finally, there remains a substantial lack of evidence evaluating the effectiveness of rehabilitative protocols on outcomes following operative and non-operative management in older patella fracture patients. Rehabilitation is an important aspect of patient recovery impacting post- injury mobility and strength. There remains a lack of studies summarizing current rehabilitative protocols (including time to weight-bearing, range of motion, etc.), and directly comparing different rehabilitative practices.

With an increased life expectancy and aging population, patella fracture incidence in older patients, particularly older women, is likely to rise. Given that these patients often have complex needs, optimizing musculoskeletal care is of importance. With no clear consensus on treatment approaches, continuing the evaluation of treatment options in a rigorous scientific manner is needed. The completion of the RCT in progress will address some of these gaps.

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7.1 References

1. Elsawy B, Higgins KE. The geriatric assessment. Am Fam Physician. 2011;83(1):48-56.

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