Risks, Outcomes, and Costs in Neurosurgery

Home , Coagulation screen

RISKS, OUTCOMES, AND COSTS IN NEUROSURGERY – THE NEW

FRONTIER IN HEALTH SERVICES RESEARCH

ANDREEA SEICEAN MPH

Submitted in partial fulfillment of the requirements

For the degree of Doctor of Philosophy

Dissertation Adviser: Dr. Duncan Neuhauser

Department of Epidemiology and Biostatistics

CASE WESTERN RESERVE UNIVERSITY

May, 2013

CASE WESTERN RESERVE UNIVERSITY

SCHOOL OF GRADUATE STUDIES

We hereby approve the thesis/dissertation of

Andreea Ana-Maria Seicean

candidate for the Doctor of Philosophy degree *.

Duncan Neuhauser PhD

(chair of the committee)

Paul K. Jones PhD

Michael W. Kattan PhD

Robert J. Weil MD MBA

(date) February 12, 2013

*We also certify that written approval has been obtained for any proprietary material contained therein.

Dedication

This work is dedicated to my wonderful uncle, George Manole, and my loving grandfather, Nicolae Seicean, who made my childhood magical. Both passed away from brain tumors.

Table of Contents

List of Tables 5

Acknowledgements 7

Abstract 9

Chapter 1: Introduction 11

Chapter 2: Use and Utility of Preoperative Hemostatic Screening and

Patient History in Adult Neurosurgical Patients 22

Chapter 3: Short Term Outcomes of Craniotomy for Malignant Brain

Tumors in the Elderly 51

Chapter 4: Effect of Smoking on the Perioperative Outcomes of Patients who Undergo Elective Spine Surgery 71

Chapter 5: Pre-operative Anemia and Peri-operative Outcomes in Patients who Undergo Elective Spine Surgery 93

Chapter 6: Conclusion 119

Appendix 123

Bibliography 135

List of Tables:

Chapter 2 Tables:

Table 1: Summary of characteristics, history variables, and outcomes of interest for all 11,804 neurosurgery patients in the 2006–2009

NSQIP database 43

Table 2: Outcomes stratified by INR values, aPTT values, and platelet count in the 11,804 neurosurgery patients screened 45

Table 3: Outcome odds ratios by number of abnormal hemostasis test results in 6,787 neurosurgery patients who underwent all 3 hemostasis tests 46

Table 4: Outcome odds ratios by patient history indicative of potentially abnormal hemostasis in all 11,804 neurosurgery patients 47

Table 5: Abnormal screening test odds ratios by patient history indicative of potentially abnormal hemostasis in neurosurgery patients screened with all 3 hemostatic tests 48

Table 6: Predictive value of patient history indicating potentially abnormal coagulation, abnormal hemostatic test results, both, or neither in 6,787 patients screened with all 3 hemostatic tests 49

Table 7: Cost and rate of preoperative hemostasis screening in 11,804 neurosurgery patients between 2006 and 2009 50

Chapter 3 Tables

Table 1: P Values for covariate balance between age groups, before and after stratification on propensity score 67

Table 2: 30-Day post-operative outcomes, stratified by age groups 69

Table 3: Age group comparisons for adverse outcomes using different

analysis methods 70

Chapter 4 Tables

Table 1: Patient demographics, comorbidities, preoperative lab values,

and intraoperative factors by smoking status 88

Table 2: 30-day post-operative outcomes, stratified by smoking status 89

Table 3: Pre- and intraoperative factors by smoking status after stratification on propensity score and age 90

Table 4: Smoking status comparisons for adverse outcomes using different analysis methods 92

Chapter 5 Tables

Table 1: Patient demographics, comorbidities, preoperative lab values,

and intraoperative factors by anemia status 109

Table 2: 30-day post-operative outcomes, stratified by anemia status 111

Tables 3: Pre- and intraoperative factors by anemia status after

stratification on propensity score 112

Table 4: Anemia status comparisons for adverse outcomes using

different analysis methods 115

Table 5: Cost of excess length of hospitalization attributed to

preoperative anemia in elective spine surgery patients in the USA per

year, assuming our sample is representative of the 644,721 elective

spine surgery cases done in the USA per year and that the average cost

per day in the USA is $3,949 118

Appendix: Supplementary Chapter 4 Tables

Table 1: P Values for pack-years by smoking status at baseline 128

Table 2: Pack-years comparison for adverse outcomes using logistic regression at baseline prior to stratification on propensity scores 129

Table 3A: Pack-years comparison for adverse outcomes after stratification on propensity score and age in current and never smokers 130

Table 3B: Pack-years comparison for adverse outcomes after stratification on propensity score and age in prior and never smokers 131

Appendix: Supplementary Chapter 5 Tables

Table 1: Anemia status comparisons for total length of hospital stay after matching on propensity scores 134

Acknowledgement:

We are very grateful for the funding opportunities that were utilized by each author

during the course of working on this dissertation.

Andreea Seicean: Agency for Healthcare Research and Quality (AHRQ) institutional

training grant T32—HS00059-14 and the U.S. Department of Defense Breast Cancer

Research Program grant W81XWH-062-0033.

Robert Weil: Melvin Burkhardt chair in neurosurgical oncology and the Karen Colina

Wilson research endowment within the Brain Tumor and Neuro-oncology Center at the

Cleveland Clinic Foundation (RJW).

None of the authors have any conflict of interest.

I would like to thank the following people for their mentorship, help, and support over the years:

• My wonderful committee members:

Drs. Duncan Neuahuser PhD, Paul K. Jones PhD, Michael W. Kattan PhD, and

Robert J. Weil MD MBA

• My mother and lifelong mentor, Dr. Sinziana Seicean MD MPH PhD

• Nicholas K. Schiltz

• Nima Alan

• Dr. Benjamin P. Rosenbaum MD

• Dr. Susan Redline MD MPH

• Dr. Kathleen Smyth PhD

• Dr. Alfred Rimm PhD

• Dr. Ralph O'Brien PhD

• Dr. Robert Elston PhD

• Dr. Siran Koroukian PhD

• Epi/Biostats department staff: Cynthia Moore, Joan Langan, Victor Courtney, Alberto

H. Santana

• Allan Chiunda MD MPH PhD

• My family and friends

Risk, Outcomes, and Costs in Neurosurgery – The New Frontier in Health Services

Research

Abstract

ANDREEA SEICEAN

Introduction: Health services research driven from within neurosurgery can be used to

improve access to and quality of care, while helping to control costs.

Aim: To answer clinically relevant questions that make a difference in patient care.

Methods: We chose to use the American College of Surgeons National Safety and

Quality Improvement Project as the database for all components of this dissertation,

which contains prospective, blinded, multi-institutional information about patients

undergoing surgery.

Results: Hemostasis history was as predictive as laboratory testing for all outcomes,

with higher sensitivity. Advanced age does not increase the risk of poor outcomes after

surgical resection of primary or metastatic intracranial tumors, after controlling for other

risk factors. We not find smoking to be associated with early (30-day) peri-operative

morbidity or mortality. All levels of anemia were significantly associated with prolonged

length of hospitalization and poorer operative or 30-day outcomes in patients undergoing

elective spine surgery.

Conclusions: Routine hemostatic laboratory screening appears to have limited utility.

Testing limited to neurosurgical patients with a positive history would save an estimated

$81,942,000 annually. Age should not be used, in isolation, as an a priori factor to

discourage pursuing craniotomy. Smoking cessation can be considered prior to spine surgery for reasons other then early (30-day) peri-operative morbidity or mortality.

Anemia should be regarded as an independent risk factor for peri-operative and postoperative complications that deserves attention prior to elective spine surgery.

Chapter 1: Introduction

Health services research (HSR) examines how people get access to health care,

how much care costs, and what happens to patients as a result of this care. The main

goals of health services research are to identify the most effective ways to organize,

manage, finance, and deliver high quality care; reduce medical errors; and improve patient safety.

- Agency for Healthcare Research and Quality, June 2000

The field of HSR was officially recognized in 1966, through the establishment of

a section of the United States federal government for the review of HSR grants

proposals1. Over the past 60 years, the vast majority of HSR has been focused on

primary care. It is only recently that interest has expanded to pursue HSR in surgical

specialties. Surgical subspecialties provide specialized care at high cost, with limited

evidence-based practice. HSR research driven from within each specialty can be used to

improve access to and quality of care, while helping to control costs.

The application of HSR to neurosurgery is in its infancy. Over 2 million

neurosurgical procedures are done in the United States each year2 by approximately

3,500 practicing neurosurgeons3. Continued trends toward an aging population,

combined with the increased incidence in tumors of all kinds with advancing age, suggest

that the patient volume for neurosurgery may increase. The goal of this dissertation was

to answer clinically relevant questions that make a difference in patient care.

The first step in achieving our goal was to identify an appropriate data source that

could be used to conduct health services research in surgery. The number of national or

11 multicenter databases that contain information of surgical procedures and outcomes is quite limited. Administrative datasets that rely of billing data, such as Medicare and

Medicaid, lack of preoperative and intraoperative factors and plagues by missing data and patient loss to follow-up. The Agency for Healthcare Research and Policy (AHRQ) has invested in a few major data collection initiatives, including: the Nationwide Inpatient

Sample (NIS), the State Ambulatory Surgery Databases (SASD), and the Medical

Expenditure Panel Survey (MEPS) (HCUP Overview)4. The NIS is the largest all-payer inpatient care database in the United States, containing data from approximately 8 million hospital stays each year. Compared to the Medicare and Medicaid datasets, NIS does a better job of capturing preoperative factors but also lacks data on preoperative lab values and intraoperative factors. NIS does not collect any follow-up data after patient discharge from the hospital. The SASD only captures outpatient surgeries, and does not provide preoperative risk factors, complications, or follow-up. The MEPS “collects data on the specific health services that Americans use, how frequently they use them, the cost of these services, and how they are paid for, as well as data on the cost, scope, and breadth of health insurance held by and available to U.S. workers.” (HCUP Databases)5.

MEPS has the same weaknesses of both the NIS and the SASD.

Few surgical specialties have also gathered outcomes data on a national scale.

Thoracic surgeons were the first, starting the Society for Thoracic Surgeons National

Database in 1989 (STS)6. The Surgical Review Corporation (SRC) launched the BOLD bariatric database in 2007 (SRC)7. The Neuropoint Alliance has launched The National

Neurosurgery Quality and Outcomes Database (N²QOD) in 20128. The primary goal of

N²QOD is to “track quality of surgical care for the most common neurosurgical

12 procedures, as well as provide practice groups and hospitals with an immediate infrastructure for analyzing and reporting the quality of their neurosurgical care8.” While information on the contents and details of the database is limited, this dataset holds high promise for future health services research initiatives in neurosurgery.

We chose to use the American College of Surgeons (ACS) National Safety and

Quality Improvement Project (NSQIP) as the database for all components of this dissertation, which contains prospective, blinded, multi-institutional information about patients undergoing surgery9. The ACS launched the NSQIP in 1999 to capture surgical outcomes in the private sector. It was modeled after the VASQIP program, ran by the US

Department of Veterans Affairs, shown to improve surgical outcome since 1986.

Participation in NSQIP is optional, and hospitals can elect to report only general and vascular cases or multispecialty cases. Data is collected and validated for accuracy at each site by a trained surgical clinical nurse coordinator. As of 2011, 315 variables are collected for each patient included in the NIQIP database, consisting of: demographics, preoperative risk factors (including lab variables), intraoperative factors, and 30-day outcomes. Patient sampling is done in a standardized manner at all participating institutions, allowing for a random sample to be selected. Inclusion criteria is: cases performed under general, spinal, epidural anesthesis and carotid endarterectomy, inguinal herniorrhaphy, peretyroidectomy, tyroidectomy, breast lumpectomy, and endovascular abdominal aortic aneurysm regardless of anesthesia type. Exclusion criteria consists of: age <18 year, trauma cases, transplant cases, an American Society of Anaesthesiologists

(ASA) rating of a 6 (brain-dead organ donors), concurrent cases, and >3 inguinal

herniorrhapahies or >3 breast lumpectomies in an 8-day cycle. As of 2011, 315 sites

across the United States participate in the NSQIP.

Benefits and limitations of using the NSQIP database are reviewed in each

individual chapter of this dissertation, but will be briefly mentioned here. The NSQIP

database contains only patients who underwent surgery; therefore we are not able to

capture any patient that did not undergo surgery for any reason. NSQIP provides suboptimal data on pre- and postoperative neurological function. Also, NSQIP only provides the last set of lab results prior to surgery, within 90 days of surgery; therefore we cannot know if prior lab results were different and measures were taken to correct these. We do not have data on the size, exact location, number, or type of primary lesions for patients with brain metastasis; whether WBRT was administered prior to resection; of extent of resection, all of which have been previously identified as affecting survival in patients with brain metastasis10-13. It is the policy of the ACS to maintain

confidentiality for data reporting institutions; thus no data is available related to surgeon

and hospital volume. However, presence or absence of resident participation in the

operating room can be used as a surrogate for academic versus non-academic hospitals,

and tends to correlate with hospital size and volume. Lastly, the surgical population

captured by NSQIP may not be wholly representative of the US neurosurgical population,

as self-selected institutions contribute patient data. However, the gender and

race distributions in the NSQIP database are representative of the US population and data

is collected prospectively from a substantial number of varying types of institutions, thus

providing a large and diverse sample size14. Additional benefits of the NSQIP database are that data was prospectively collected in a standardized manner at each site with strict

variable definitions and annual quality checks14; the database has been validated for

accuracy and reproducibility and achieves >95% 30 day outcome follow-up rate across

consecutive cycles14.

This dissertation is comprised of four papers (Chapters 2-5), in which HSR methodology was applied to address a specific neurosurgical question. Each chapter can stand-alone. A brief introduction to each chapter will follow.

Chapter 2 is entitled “Use and Utility of Preoperative Hemostatic Screening and

Patient History in Adult Neurosurgical Patients15.” The utility of preoperative hemostasis

screening to predict complications is uncertain. We quantified the screening rate in US

neurosurgery patients and evaluated the ability of abnormal test results, compared with

history-based risk factors, to predict hemostasis-related and general outcomes. 11,804

adult neurosurgery patients were identified in the 2006-2009 ACS NSQIP database.

Multivariate logistic regression modeled the ability of hemostatic tests and patient history

to predict outcomes (intra and postoperative RBC transfusion, return to the OR, and 30-

day mortality). Sensitivity analyses were conducted using patient subgroups by

procedure. We found that most patients had all three hemostatic tests (platelet count,

PT/INR, aPTT), but few had any of the outcomes of interest. Screening tests were

significantly associated with intraoperative RBC transfusion, return to the OR, and

mortality; abnormal INR was associated with postoperative RBC transfusion. However,

all tests had low sensitivity (0.09 to 0.2), as was specificity of the platelet count (0.04-

0.05). Association between patient history and each outcome was approximately the

same across tests, with higher sensitivity but lower specificity. Combining abnormal

tests with history accounted for 50% of mortality and 33% of each of the other outcomes.

In summary, this is the first study to assess preoperative hemostasis screening, compared

with patient history, in a large multi-center sample of adult neurosurgery patients to predict hemostasis-related outcomes. History was as predictive as laboratory testing for all outcomes, with higher sensitivity. Routine laboratory screening appears to have limited utility. Testing limited to neurosurgical patients with a positive history would save an estimated $81,942,000 annually.

The title of Chapter 3 is “Short Term Outcomes of Craniotomy for Malignant

Brain Tumors in the Elderly16.” Disparity in resection rates for malignant brain tumors in

elderly patients is partially attributed to a belief that advanced age is associated with

increased risk for postoperative morbidity and mortality. The aim of our study was to

investigate the effect of advanced age (≥75 years) on 30-day outcomes in patients with

primary and metastatic brain tumors who underwent craniotomy for definitive resection

of a malignant brain tumor. We conducted prospective analyses of the 2006-2010 ACS

NSQIP database of 970 patients, ≥40 years of age, who underwent craniotomy for definitive resection of neoplasm. Pre- and intraoperative characteristics and 30-day outcomes were stratified by age. Using propensity scores, 134 patients (≥75 years) were matched to 134 patients 40-74 years of age. Logistic regression was used to predict adverse postoperative outcomes. We found that the median length of hospital stay was 5 days, the rate of minor and major complications were 5.9% and 13.1% respectively, 5.7% of patients returned to the operating room and 4.3% of patients expired within 30 days.

Advanced age did not increase the odds for poorer short-term outcomes. In conclusion, advanced age does not increase the risk of poor outcomes after surgical resection of primary or metastatic intracranial tumors, after controlling for other risk factors. These

results suggest that age should not be used, in isolation, as an a priori factor to discourage

pursuing craniotomy.

Chapter 4 addressed the “Effect of Smoking on the Perioperative Outcomes of

Patients who Undergo Elective Spine Surgery.” Prior studies have assessed the

association of smoking and long-term outcomes for a number of spine surgery procedures, with conflicting findings. The association between of smoking and 30-day outcomes for spine surgery is unknown. We wished to assess whether preoperative cigarette smoking and smoking duration predicted adverse, early, peri-operative outcomes in patients undergoing elective spine surgery. We identified 14,500 adults, classified as current (N=3,914), prior (N=2,057), and never smokers who underwent elective spine surgery in the 2006-2010 ACS NSQIP database. Using propensity scores, current and prior smokers were matched to never smokers. Logistic regression was used to predict adverse postoperative outcomes. The relationship between pack-years and adverse outcomes was tested. Sensitivity analyses were conducted limiting the study sample to patients who underwent spine fusion (N=4,663), and using patient subgroups by procedure. We found that in unadjusted analyses, prior smokers were significantly more likely to have prolonged hospitalization (1.2, 95% CI: 1.1-1.3) and major complications (1.3, 95% CI: 1.1-1.6) compared with never smokers. No association was found between smoking status and adverse outcomes in adjusted, matched patients models. Current smokers with more then 60 pack-years were more likely to expire within 30 days of surgery (3.0, 95% CI, 1.1-7.8), compared to never smokers. Sensitivity analyses confirmed these findings. In summary, the large NSQIP population was carefully matched for a wide range of baseline comorbidities, including 29 variables

previously suggested to influence peri-operative outcomes. While previous studies conducted in subgroups of spine surgery patients have suggested a deleterious effect for smoking on long-term outcomes in patients undergoing spine surgery, our analysis did not find smoking to be associated with early (30-day) peri-operative morbidity or mortality.

Lastly, Chapter 5 addressed “Pre-operative Anemia and Peri-operative Outcomes in Patients who Undergo Elective Spine Surgery.” Prior studies have assessed the association of anemia on outcomes in various non-cardiac surgical procedures. The association between pre-operative anemia and 30-day outcomes for spine surgery is unknown. We wished to assess whether pre-operative anemia predicted adverse, early, peri-operative outcomes in patients undergoing elective spine surgery. We identified

24,473 adults who underwent elective spine surgery in the 2005-2011 ACS NSQIP databases. The patients were classified as having severe (N=88), moderate (N=314), mild (N = 5,477) and no anemia. Using propensity scores, patients with severe, mild, and moderate anemia were matched to patients with no anemia. Logistic regression was used to predict adverse post-operative outcomes. Sensitivity analyses were conducted limiting the study sample to: patients who did not receive intra- or post-operative transfusion and to patients with and without pre-operative cardiovascular comorbidities. We found that patients with all levels of anemia had significantly higher risk for nearly all adverse outcomes compared with non-anemic patients in unadjusted and propensity-matched models. Patients with moderate and mild anemia were more likely to have prolonged length of hospitalization, experience one or more complications, and expire within 30 days of surgery compared to non-anemic patients. The association between anemia and

adverse outcomes was found independently of intra- and post-operative transfusions, and was not more pronounced in patients with pre-operative cardiovascular comorbidities. In summary, all levels of anemia were significantly associated with prolonged length of hospitalization and poorer operative or 30-day outcomes in patients undergoing elective spine surgery. Our findings, using a large multi-institutional sample of prospectively- collected data, suggests that anemia should be regarded as an independent risk factor for peri-operative and post-operative complications that deserves attention prior to elective spine surgery.

In summary, this dissertation is our first pass at using a large multi-center prospectively collected database to answer simple fundamental questions about the practice of neurosurgery. Each of the four paper that comprise this dissertation has the potential to change the care that surgeons deliver to patients and to educate patients on what to expect from the care that they are being offered and/or provided. Each topic also contains information about resource utilization, indented to allow patients and physicians to make the best decisions while limiting waste in the healthcare system. In addition to the goals put forth in each chapter, I hope that this dissertation as a whole may stimulate interest in researchers and clinicians alike to increase the amount of HSR work being done in neurosurgery and all surgical specialties.

Chapter 1 References

1. Lohr K, Steinwachs D. Health Services Research: An Evolving Definition of the Field Health Serv Res. 2002 February; 37(1): 15–17.

2. Die B. AANS National Neurosurgical Procedural Statistics Survey Offers Insight into Practice Management World of Neurosurgeons. American Association of Neurological Surgeons. Jun 18, 2008.

3. Muraszko K, Benzil D, Todor R. So, You Want to be a Neurosurgeon. Women in Neurosurgery. 2009.

4. HCUP Overview. Healthcare Cost and Utilization Project (HCUP). November 2009. Agency for Healthcare Research and Quality, Rockville, MD. Available at www.hcup-us.ahrq.gov/overview.jsp. Accessed Jan 26, 2013.

5. HCUP Databases. Healthcare Cost and Utilization Project (HCUP). June 2012. Agency for Healthcare Research and Quality, Rockville, MD. Available at www.hcup- us.ahrq.gov/nisoverview.jsp. Accessed Jan 26, 2013.

6. Society for Thoracic Surgeons. STS National Database. Available at http://www.sts.org/national-database. Accessed Jan 26, 2013.

7. Surgical Review Corporation. BOLD Overview. Available at http://www.surgicalreview.org/bold/overview/. Accessed Jan 26, 2013.

8. The Neuropoint Alliance. The National Neurosurgery Quality and Outcomes Database (N²QOD). Available at http://www.neuropoint.org/NPA%20N2QOD.html . Accessed Jan 26, 2013.

9. American College of Surgeons National Surgical Quality Improvement Project. User Guide for the 2011 Participant Use Data File. American College of Surgeons, October 2012.

10. Barnholtz-Sloan JS, Williams VL, et al. Patterns of care and outcomes among elderly individuals with primary malignant astrocytoma. J Neurosurg. 2008;108:642-8.

11. Mohan D, Suh J, Phan J, et al. Outcome in elderly patients undergoing definitive surgery and radiation therapy for supratentorial glioblastoma multiforme at a tertiary care institution. Int J Radiat Oncol Biol Phys 1998;42:981-7.

12. Bindal R, Sawaya R, Leavens M, Lee JJ. Surgical treatment of multiple brain metastases. J Neurosurg. 1993;79:210-6.

13. Patchell R, Tibbs P, Walsh J, et al. A randomized trial of surgery in the treatment of single metastases to the brain. N Engl J Med. 1990;322:494-500.

14. Khuri SF, Henderson WG, Daley J, et al. Principal Site Investigators of the Patient Safety in Surgery Study: The Patient Safety In Surgery Study: Background, Study Design, and Patient Populations. J Am Coll Surg 2007; 204:1089-102.

15. Seicean A, Schiltz NK, Seicean S, Alan N, Neuhauser D, Weil RJ. Use and utility of preoperative hemostatic screening and patient history in adult neurosurgical patients. J Neurosurg. 2012 May;116(5):1097-105.

16. Seicean A, Seicean S, Schiltz NK, Alan N, Jones PK, Neuhauser D, Weil RJ. Short-term outcomes of craniotomy for malignant brain tumors in the elderly. Cancer. 2013 Mar 1;119(5):1058-64.

Chapter 2: Use and Utility of

Preoperative Hemostatic Screening and

Patient History in Adult Neurosurgical

Patients

Andreea Seicean MPH1, Nicholas Schiltz1, Sinziana Seicean MD MPH

PhD2,3, Nima Alan4, Duncan Neuhauser PhD1, Robert J. Weil MD5

1Departament of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, Ohio; 2Departments of Pulmonary, Critical Care and Sleep Medicine, University Hospitals, Cleveland, Ohio; 3Heart and Vascular Institute, Cleveland Clinic Foundation, Cleveland, Ohio; 4 Case Western Reserve University School of Medicine, Cleveland, Ohio; 5The Rose Ella Burkhardt Brain Tumor & Neuro-Oncology Center, and Department of Neurosurgery, the Neurological Institute, Cleveland Clinic, Cleveland, OH.

This work has been published, in full, in the Journal of Neurosurgery. It appears in this dissertation with kind permission from the JNS publishing group.

Seicean A, Schiltz NK, Seicean S, Alan N, Neuhauser D, Weil RJ. Use and utility of preoperative hemostatic screening and patient history in adult neurosurgical patients. J Neurosurg. 2012 May;116(5):1097-105. doi: 10.3171/2012.1.JNS111760. Epub 2012 Feb 17.

This work presented at the American Association of Neurological Surgery National Conference. Socioeconomic Section Session, April 17, 2012, in Miami, FL, USA where it received the best medical student abstract award. It was also presented at the National Research Service Award (NRSA) Trainees Research Conference, June 23, 2012, in Orlando, FL, USA and at the Academy Health national conference, June 25, 2012, in Orlando, FL, USA.

Abstract

Introduction: The utility of preoperative hemostasis screening to predict complications is uncertain. We quantified the screening rate in US neurosurgery patients and evaluated the ability of abnormal test results, compared with history-based risk factors, to predict hemostasis-related and general outcomes.

Methods: 11,804 adult neurosurgery patients were identified in the 2006-2009 American

College of Surgeons NSQIP database. Multivariate logistic regression modeled the ability of hemostatic tests and patient history to predict outcomes (intra and postoperative

RBC transfusion, return to the OR, and 30-day mortality). Sensitivity analyses were conducted using patient subgroups by procedure.

Results: Most patients had all three hemostatic tests (platelet count, PT/INR, aPTT), but few had any of the outcomes of interest. Screening tests were significantly associated with intraoperative RBC transfusion, return to the OR, and mortality; abnormal INR was associated with postoperative RBC transfusion. However, all tests had low sensitivity

(0.09 to 0.2), as was specificity of the platelet count (0.04-0.05). Association between patient history and each outcome was approximately the same across tests, with higher sensitivity but lower specificity. Combining abnormal tests with history accounted for

50% of mortality and 33% of each of the other outcomes.

Conclusions: This is the first study to assess preoperative hemostasis screening, compared with patient history, in a large multi-center sample of adult neurosurgery patients to predict hemostasis-related outcomes. History was as predictive as laboratory testing for all outcomes, with higher sensitivity. Routine laboratory screening appears to

23 have limited utility. Testing limited to neurosurgical patients with a positive history would save an estimated $81,942,000 annually.

Introduction

The utility of and guidelines for preoperative hemostatic screening, consisting of

activated partial thromboplastin time (aPTT), prothrombin time (PT), and platelet count,

remains a controversial topic with clinicians either choosing to screen some or all of their

patients. Several studies have been undertaken to measure the utility of preoperative

hemostatic screening in different surgical populations,8,13,22, 24,29 two of which focused on

neurosurgery patients14,32. One study from Australia assessed the utility of screening in

all neurosurgical patients treated within a single institution, over a one year period32. A second looked at sample of patients undergoing cranial vault remodeling at one institution in Texas during a one year period14. The authors’ recommendations for

screening differ.

In addition to laboratory tests, patient history can also be used to assess risk for

excess bleeding prior to surgery. History-based risk factors previously identified include

family history, previous bleeding history, pharmacological therapies, and current

diseases12,16,18,23. Little is known about the predictive value of history-based risk factors for outcomes in neurosurgery patients.

No previous study has assessed the use and utility of preoperative haemostatic screening and patient history for predicting hemostasis-related complications and general outcomes in a large, prospective series of US neurosurgical patients. While patients requiring intraoperative transfusion have been shown to have impaired outcomes15,

routine preoperative screening is costly, time consuming, and has previously been

reported to lack accuracy and predictive value in various surgical sub-populations12,16,

21,24,31,33. The average cost for the three tests are $30 per PT (INR), $23 per aPTT, and

25 $23 per complete blood count which included platelet count, amounting to $76 per all

three tests9. While this may not seem like a significant sum per individual patient, more than 2 million neurosurgery procedures are done in the US each year10. In addition to cost, the accuracy of results gained from these tests is also under scrutiny with each shown to have a low sensitivity and a high false positive rate: a normal individual undergoing 10 consecutive tests has a 40% chance that at least 1 test will be abnormal12.

The predictive value of test results for bleeding complications is also unclear, with

abnormal results previously being reported as not predictive of amount of blood

transfused in cardiac patients26 not predictive of blood lost during non-cardiac

surgery24,33, further highlighting the need to assess predictive value in neurosurgery patients.

Given these uncertainties, we sought to investigate several, related issues. First, we wished to assess the rate of preoperative haemostatic screening, and the frequency of abnormal results in a large multi-center sample of US adult neurosurgical patients.

Second, we wanted to evaluate the ability of abnormal test results and/or patient history indicative of potentially abnormal hemostasis to predict bleeding complications and general outcomes. Third, we wished to compare hemostatic tests with patient history indicative of potentially abnormal hemostasis for their abilities to predict several relevant peri- and post-operative outcomes.

Methods

Data Source: This study evaluated the medical records of all patients who underwent neurosurgery and were included in the American College of Surgeon (ACS) National

26 Surgical Quality Improvement Program (NSQIP) database between 2006 and 2009.

Detailed description of the ACS-NSQIP database, including design, sampling strategy, and variable definitions can be found elsewhere19,20. All data was collected prospectively using a standardized protocol, and consisting of strictly defined variables. Each participating site had a trained, surgical clinical nurse reviewer responsible for data collection from computerized and paper patient medical records, physician office records, and telephone interviews with the patient. The ACS-NSQIP database has been validated for accuracy and reproducibility20.

Subjects: The study population consists of 11,804 adult patients undergoing neurosurgery between 2006 and 2009. The most frequent types of surgery undergone are: uncomplicated spinal hemi-laminectomy (N=2,121), laminectomy (N = 1028), anterior cervical discectomy (N = 887), exploration of spinal fusion (N = 22830), and supratentorial craniectomy (N = 584) in that order. Sensitivity analyses were conducted separating inpatients and outpatients. Additional sensitivity analyses limited the patient population to uncomplicated spinal hemi-laminectomy and laminectomy cases, as denoted by CPT codes of 63030 and 630477. The role of abnormal coagulation laboratories or a history suggestive of bleeding was assessed in this subpopulation, consisting of 10% of the sample, in which excess bleeding or mortality are unexpected.

Hemostatic screening lab values - (predictor variables): Preoperative hemostatic screening lab values were recorded in the NSQIP database if drawn within 90 days prior to the surgical procedure. Abnormal PT was defined as an international normalized ratio

(INR) of >1.2, and severely abnormal PT as INR >3.03. aPTT was defined as abnormal if

>35 seconds, and as severely abnormal if >60 seconds1. Abnormal low platelet count

27 was defined as <150x10^3/mcL and abnormal high platelet count as >450x10^3/mcL2.

NSQIP records the laboratory value drawn closest temporally to the index surgery.

Sensitivity analyses were conducted by examining test values as continuous variable and using different cutoff values for abnormal results for all three tests.

Patient History Covariates - (predictor variables): We attempted to incorporate all history-based risk factors for abnormal hemostasis previously identified2,3,4. Self- reported patient history of abnormal bleeding, self-reported family history of bleeding disorders, vitamin K deficiency, and a comprehensive list of medications that pose a risk for bleeding abnormalities were all captured through the NSQIP variable bleeding disorders17. Patients requiring regular administration of oral or parenteral corticosteroids in the 30 days prior to surgery for a chronic condition were considered to have chronic steroid use. Chemotherapy and radiotherapy for cancer within 90 days prior to surgery were individually captured. Disseminated cancer was considered positive for patients with spread to one or more sites in addition to the primary site and for patients with acute lymphocytic leukemia (ALL), acute myelogenous leukemia (AML), and stage IV lymphoma. Patients were defined as having renal disease if they had acute or chronic renal failure requiring treatment with peritoneal dialysis, hemodialysis, hemofiltration, hemodiafiltration, or ultrafiltration within 2 weeks prior to surgery. Hepatic disease was considered positive for patients presenting with ascites on physical examination, abdominal ultrasound, or abdominal CT/MRI within 30 days prior to operation, and/or with esophageal varices documented on an EGD or CT scan performed within 6 months prior to surgery.

28 An all-inclusive variable labeled history indicative of potentially abnormal

hemostasis was created by merging the subjects that had a positive response for any one

of the individual risk factor variables defined above. Sensitivity analyses were conducted

using alternate definitions of history indicative of potentially abnormal haemostasis to

include additional variables: smoking, alcohol consumption, hypertensive medications,

weight loss of >10% of body weight in the 6 months preceding surgery.

Outcomes of interest: Intraoperative RBC transfusion was recorded in the NSQIP

database as the number of packed or whole red blood cells (RBC) units given during

surgery, with every 500cc’s of fluid equaling 1 unit. If the amount of RBC’s given was

less than 250 cc, 0 was entered. This variable was dichotomized by whether any RBCs

were given. Postoperative RBC transfusion (yes/no) was defined as having received any

transfusion of packer or whole RBC’s within 72 hours after leaving the operating room

(OR). Return to the OR (yes/no) is defined as any unplanned returns to the OR for a

surgical procedure within 30 days postoperatively. Days of operation till death was used

to dichotomize mortality at 30 days postoperatively.

Statistical Analyses: Frequency distributions were used to describe the entire NSQIP neurosurgery patient population and data and cross-tabulation Tables were used to compare outcomes across the different predictor values. Pearson's chi-square tests were used to compare differences in outcomes across groups according to number of hemostatic tests undergone and individual predictor variables. In cases where some cells had fewer than five observations, Fisher's exact test was used instead. Logistic regression was used to model the ability of hemostatic lab tests and patient history to predict the outcomes of interest, and to test the ability of patient history to predict haemostatic lab

29 results. SAS (Version 9.2, SAS Institute)30, was used for all statistical analyses. A P

value of < 0.05 was considered significant.

Results

Among the 11,804 neurosurgery patients in the ACS-NSQIP database, 7,637

subjects (64.7%) had INR values, 7,026 (59.4%) had aPTT values, and 10,654 (90.2%)

had platelet counts (Table 1). A majority of patients underwent all three tests of hemostasis (57.5%), while only 8.9% underwent no testing. One thousand two hundred and eighty-six (11%) had history indicative of potentially abnormal hemostasis, with one or more risk factors according to patient history. Relatively few patients had any of the

outcomes of interest, the greatest of which was 6.1% patients requiring RBC transfusion.

Assessment of outcomes according to the number of preoperative hemostatic tests

undergone shows a significant positive stepwise association between number of

preoperative screening tests administered and poor outcomes. Patients that had all three

screening tests (N = 6,787) were found to have higher rates of intraoperative RBC

transfusion, postoperative RBC transfusion, return to the OR, and mortality compared to

patients that had undergone 1 or 2 tests (N=3,970), who in turn had higher rates then

patients with no tests (N=1,047).

The distributions of lab values for all patients were found to be approximately

normal, with few outliers. In this study, 4.2% (N = 1,068) of all tests administered were

abnormal, however only 5% of these (N = 55) fit our definition of severely abnormal

(Table 2). Association between abnormal test results and each outcome was assessed

individually for each test, and included all patients who underwent each test. Abnormal

30 lab values for PT (or the international normalized ration, INR), aPTT, and platelet count were found to be significantly associated with intraoperative RBC transfusion, return to the OR, and mortality, with abnormal INR also associated with postoperative RBC transfusion (P = 0.0034) (Table 2). Specificity of INR and aPTT for poor outcomes was high (95-97%), but sensitivity was low (6-24%). Platelet count was found to have both low sensitivity (7-21%) and specificity (5%). Graphical representation of patient lab values showed substantial overlap in values of those having compared to those not having each outcome.

The number of abnormal preoperative hemostatic tests, in patients who had all three tests done (N=6,787), was found to be significantly associated with each poor outcome (Table 3). Patients who had one abnormal test result were more likely to have experienced each of the poor outcomes compared to patients with three normal test results, and patients with two or three abnormal test results had the highest percentage of poor outcomes (Table 3).

Patients with history indicative of potentially abnormal hemostasis (Table 4) were found to have statistically significant higher odds of having each of the poor outcomes, ranging from 2 times the odd for 30 day return to the OR to greater than 8 times the odds for 30 days mortality. While the specificity of history was lower than that of each lab test, the sensitivity was consistently higher for each outcome. In addition, history indicative of potentially abnormal hemostasis was found to significantly increase the odds for each of the lab tests being abnormal anywhere from 2 to 11 times, when compared to patients with no history (Table 5). Overall, patients with an abnormal

31 history had 3.5 times the odds (95% CI 2.9-4.1) of having one or more abnormal hemostatic test compared to patients with no abnormal history (P < 0.0001).

The predictive value of history indicative of potentially abnormal hemostasis compared to hemostatic screening was additionally assessed based on the percentage of each of the poor outcomes that were detected in patients that were screened using all three tests (Table 6). The percentage of patients captured with each of the poor outcomes was approximately the same when using abnormal history compared with 1 or more abnormal screening test results. Combining both abnormal history and abnormal test results was found to detect only a third of patients that underwent intraoperative transfusion, postoperative transfusion and 30 day return to the OR, and about half of patients who expired within 30 days postoperatively. The remainder of patents who had each of the poor outcomes was not captured by either abnormal history or preoperative hemostatic screening.

In sensitivity analyses, outpatients (N = 1,805) were found to have been screened at approximately at the same rate as inpatients, but had a significantly lower rate of abnormal test results, history indicative of potentially abnormal hemostasis, and poor outcomes compared to inpatients. In addition, no statistically significant relationship was identified between abnormal screening test results and any of the outcomes, possibly due to the low prevalence of both. Similar results were observed when the sample was limited to patients who underwent uncomplicated spinal semilaminectomy and laminectomy (N=1,014). The only significant associations observed within this subsample were between a low platelet count and intraoperative RBC transfusion, and

32 between history indicative of potentially abnormal hemostasis and both intraoperative

RBC transfusion and return to the OR.

Discussion

In the NSQIP sample, approximately 58% of US adult neurosurgery patients

underwent all three preoperative hemostasis screening tests. While around 60% of

patients had undergone each of PT and aPTT tests, 90% had reported platelet counts.

Approximately 4% of patients were found to have at least one abnormal test results, with

fewer than 1% fitting the criteria for severely abnormal. Second, nearly all abnormal lab

tests and history indicative of potentially abnormal hemostasis were individually found to

be significantly associated with each outcome, but each with poor sensitivity. A positive

association was identified between the number of abnormal hemostatic test results and

the odds for each outcome, as sensitivity would increase when combining two positive

tests. Third, history indicative of potentially abnormal hemostasis correlated with each

outcome as well as or better than any abnormal hemostasis test. Positive history was

also associated with a 3.5 odds ratio of having at least 1 abnormal hemostatic test

compared to having normal history. However, even when combining the use of abnormal hemostatic values with history indicative of potentially abnormal hemostasis it was not possible to identify approximately two-thirds of neurosurgery patients receiving intraoperative RBC transfer, postoperative RBC transfer, and returning to the OR with 30 days, and half of the 30 day mortality cases.

Interpretations in the Context of the Literature: Our study was consistent with the

Australian neurosurgery study in which preoperative screening with PT and PTT was

33 performed in most patients32. By comparison, a much greater percentage of patients in the NSQIP sample had platelet counts, typically because the platelet count is automatically included in complete blood count orders and/or because clinicians placed greater value of this test compared with PT and aPTT. The latter may be related to the ability to correct low platelet value with transfusion of platelet concentrates and fresh frozen plasma prior to surgery. A previous study done in a sample of non-cardiac surgery patients24 identified higher rates of both procedures in patients with abnormal platelet

counts, but did not find these patients to have higher rates of postoperative bleeding, as

consistent with our findings.

We found a lower rate of abnormal and highly abnormal hemostatic test results in

our sample compared with the study of Schramm et al32, more consistent with findings

from other surgical specialties4,24,25,27,28,33. There exists variety in the literature about

which, if any, hemostatic tests are predictive of intraoperative and postoperative bleeding.

Our results are similar to findings in CABG patients11 and tonsillectomy and

adenoidectomy patients,17 in that abnormal tests were found to be significantly associated

with increased bleeding, and inconsistent from the two previous neurosurgery patient

studies14,32 which identified only an supra-normal PTT as a risk factor. These differences

may be explained by differences in patient populations as well as sample sizes, with our

study consisting of a large multicenter sample of US adult neurosurgery population with

greater power to identify differences not captured in the smaller sample sizes of previous

studies limited to a single center. This is a likely explanation especially since all of the

outcomes are relatively infrequent, with postoperative RBC transfusion being especially

rare at only 0.15% of the NSQIP neurosurgical sample.

34 Previous studies have encouraged the use of patent history to guide or assist in

guiding selective preoperative hemostatic screening14,24,32, but no previous studies have

assessed the utility of aggregate history-based risk factors to predict hemostasis related outcomes. While it is associated with increased risk for abnormal test results, history alone is just as predictive of outcomes as hemostatic test results, but with higher sensitivity.

Clinical Implications: Our findings support previous studies that suggest a limited or absent benefit from routine or standing preoperative hemostatic screen24,29,32. There

appears to be some indication within our sample that clinicians were somewhat selective

as to which patients underwent pre-operative hemostatic testing, with a statistically

significant positive association between number of tests ordered and each outcome.

However, laboratory screening is frequently performed in patients with no risk factors for

abnormal hemostasis. If we were to assume no repeated tests in any patients, the total

cost of hemostasis tests that were conducted in our sample (n=11,804) would be

$635,543, amounting to an average of $53.84 per patient (Table 7). If all three screening

tests were performed only in patients with history indicative of potentially abnormal

hemostasis, the average cost per patient in our sample would be reduced to $14.82, a 71%

reduction in cost. While savings per individual patient may be modest, there are

approximately 2.1 million neurosurgery procedures done in the US annually10. If we

assume that the average rates of testing and the prevalence of patient history indicative of

potentially abnormal hemostasis are similar between our sample and the general US

population, altering clinical approach to utilize all three screening tests only in patients

with a positive history would result in a net healthcare saving of $81,942,000 per year.

35 In additional to cost, our study confirmed hemostatic screening test accuracy to be poor, with a low sensitivity to predict selected, clinically-relevant outcomes of interest12,24.

Using history indicative of potentially abnormal hemostasis as one tool to guide selection of neurosurgery patients for preoperative screening is a medically reasonable and cost- effective strategy. In addition, we recommend limiting laboratory screening in outpatients to those with serious reason of concern for hemostatic abnormality based on history, due to the low incidence of poor outcomes in this population and the very limited ability of laboratory screening tests to predict poor outcomes.

Limitations: We recognize several limitations. The NSQIP database contains only patients who underwent surgery; therefore we are not able to capture any patient that did not undergo surgery due to abnormal hemostasis screening that could not be resolved or those in whom abnormal tests led to identification of an issue with hemostasis that was subsequently resolved. However, previous studies have demonstrated that few patients have surgery cancelled due to abnormal hemostasis results14. A second limitation is that

NSQIP only provides the last set of hemostasis lab results prior to surgery, so if the patient underwent several rounds of testing, only the last set of the tests is available. In addition, there is no way to know how close to time of surgery the tests were administered, beyond the fact that they were administered within 90 days of surgery. A previous study done in all non-cardiac surgery patients found that patients with abnormal hemostasis were more likely to have the anesthesia plan modified and to receive platelet or fresh frozen plasma transfusion prior to surgery compared to patients with normal hemostasis24. We were not able to assess for these differences within our sample because this data was not available in NSQIP. Furthermore, patients requiring emergency

36 neurosurgery due to coagulation issues – for example, patients with hemorrhagic

complications related to warfarin or anti-platelet agents – may also be represented in the

NSQIP sample, which cannot be controlled, but which should also be registered in the patient history features. An additional potential limitation to our study is that none of our outcomes of interest are solely dependent on hemostasis, but rather on a combination of factors. While we are not able to tease out how much of each outcome is based on hemostasis, our study suggests reasonable alternatives to routine laboratory testing. In addition, the surgical population captured by NSQIP may not be considered wholly representative of the US neurosurgical population, with data reported by self-selected institutions, but NSQIP has been shown to be representative of the US population in terms of gender and race5 and is drawn from a large number of varying types of institutions each year across the US, providing a large and diverse sample size20,19.

Further benefits from using the NSQIP database are that data was collected in a

standardized manner at each site with strict variable definitions and annual quality

checks19, the database has been validated for accuracy and reproducibility and has been

found to achieving greater than 95% 30 day outcome follow-up rate across consecutive

cycles15,19. Finally, while cost assessments may be imperfect, it is also recognized that

we may be under-estimating the cost of testing, since additional costs are incurred in

patients in whom abnormal laboratory test results are found and lead to additional

investigations, only to reveal no abnormality of clinical significance; this is not an

uncommon finding with all three of the tests studies here16.In light of these limitations,

together with the potential utility of confirmation of these findings prior to establishing

clinical guidelines, a prospective multi-center study specifically aimed at testing our

37 hypotheses may be useful. Such a trial could benefit from random assignment of

neurosurgery patients at each institution to either having all three hemostasis tests prior to

surgery or to using the proposed history-based selection screening process to only test patients with history indicative of potentially abnormal hemostasis. Cancellation and delay of surgery resulting from abnormal test results, together with any treatment given to correct abnormal findings, should be collected. In addition to all pre, intra, and postoperative variables collected in the NSQIP database, all hemostasis tests should be reported for each patient, together with the date they were administered. The results from such a study could strengthen or weaken the findings here, and in either case make a strong argument for establishing a clinical standard for preoperative hemostasis screening in neurosurgery patients.

Conclusion

To the best of our knowledge, this is the first study to measure the rate of preoperative hemostatic testing in a large population of US adult neurosurgery patients studied prospectively, with verified 30-day outcomes, and the first to use this data to assess the utility of common laboratory screening compared to use of a compound variable capturing history indicative of potentially abnormal hemostasis across several, clinically- relevant outcomes. We found that preoperative hemostasis screening is widespread in this population, with over 90% receiving at least one test regardless of history-based risk factors. Abnormal PT, aPTT, and platelet count were each found to be significantly associated with intraoperative RBC transfusion, 30 day return to the OR, and 30 day mortality, while abnormal PT was additionally associated with postoperative RBC

38 transfusion. There is overlap in the lab values of patients who had vs. did not have each outcome, with low sensitivity common to all three tests, which suggests they are poor screening tool(s) in an average patient population. Patient history indicative of potentially abnormal hemostasis was significantly associated with abnormal test results, and was at least as predictive of each outcome as one or more abnormal test results.

However, even the combination of abnormal hemostatic test results with an abnormal history fails to detect a majority of patients who experienced the following outcomes: intraoperative RBC transfusion, postoperative RBC transfusion, and 30 day return to the

OR. Excess costs associated with unnecessary screening, together with the suboptimal predictive value of each test, suggest that limiting hemostasis screening tests only to neurosurgery patients presenting with history indicative of potentially abnormal hemostasis may be both medically reasonable and cost-effective.

39 Chapter 2 References

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5. American College of Surgeons National Surgical Quality Improvement Project. ACS NSQIP Data User Guide: October 2010. October 2010.

6. American College of Surgeons National Surgical Quality Improvement Project. Program Specifics: ACS NSQIP Data Collection Overview. 2006.

7. American Medical Association. CPT Professional Edition. American Medical Association 2010.

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11. Dorman BH, Spinale FG, Bailey MK, Kratz JM, Roy RC. Identification of patients at risk for excessive blood loss during coronary artery bypass surgery: thromboelastography versus coagulation screen. Anesth Analg 1993;76:694-700.

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40 14. Genecov, DG, Por YC, Barcelo CR, Salyer KE, Mulne AF, Morad AB. Preoperative screening for coagulopathy using prothrombin time and partial thromboplastin time in patients requiring primary cranial vault remodeling. Plastic and Reconstructive Surgery 2005;116:389-94.

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21. Lawrence VA, Gafni A, Gross M. The unproven utility of the preoperative urinalysis: economic evaluation. J Clin Epidemiol 1989;42: 1185-1192

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24. Ng, K. F., Lai, K. W., and Tsang, S. F. Value of preoperative coagulation tests: Reappraisal of major noncardiac surgery. World J. Surg. 26: 515, 2002.

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42 Chapter 2 Tables

Table 1: Summary of characteristics, history variables, and outcomes of interest for all

11,804 neurosurgery patients in the 2006–2009 NSQIP database*

Parameter No. (%) mean age in yrs† 55.2 ± 0.27 male sex 6165 (52.2) white 8998 (76.2%) transfer status, outpatient 1805 (15.3) preop hemostatic screening tests‡ INR 7637 (64.7) aPTT 7026 (59.5) platelet count 10,645 (90.2) history variables indicative of potential bleeding tendency bleeding disorder 337 (2.9) chronic steroid use 687 (5.8) chemotherapy 87 (0.74) radiation therapy 90 (0.75) disseminated cancer 358 (3.0) renal disease 40 (0.34) hepatic disease 13 (0.11) history indicative of potentially abnormal hemostasis§ 1286 (10.9) outcomes of interest intraop RBC transfusion 720 (6.1) postop RBC transfusion 18 (0.15) return to OR 607 (5.1) mortality 190 (1.6)

* OR = operating room.

† Analyses conducted using survey analyses.

43 ‡ Number of patients who underwent each of the preoperative hemostatic tests within 90 days prior to surgery.

§ Patient had one or more of the following risk factors for abnormal hemostasis: history of abnormal bleeding, self-reported family history of bleeding disorder, vitamin K deficiency, currently taking medications that pose a risk for bleeding abnormalities and/or failing to discontinue use of such medications with adequate time for normal hemostasis to be restored, chronic steroid use, chemotherapy and/or radiotherapy for cancer within

90 days prior to surgery, disseminated cancer, renal disease, and/or hepatic disease.

44 Table 2: Outcomes stratified by INR values, aPTT values, and platelet count in the 11,804 neurosurgery patients screened

No. (%) Test & No. of Intraop RBC Postop Return to Mortality Result Patients Transfusion RBC OR Transfusio n INR 7637

normal 7339 494 (6.7) 12 (0.16) 410 (5.6) 125 (1.7) mildly 277 46 (16.6) 0 (0) 28 (10.1) 35 (12.6) abnormal severely 21 5 (23.8) 2 (9.5) 0 (0) 5 (23.8) abnormal all 298 51 (17.1) 2 (0.67) 28 (9.4) 40 (13.4) abnormal p value* <0.001 <0.001 0.003 <0.001 sensitivity 0.094 0.14 0.064 0.24 specificity 0.97 0.96 0.96 0.97 aPTT 7026 normal 6643 486 (7.3) 11 (0.17) 391 (5.9) 140 (2.1) mildly 359 46 (12.8) 2 (0.56) 38 (10.6) 19 (5.3) abnormal severely 24 1 (4.2) 0 (0) 1 (4.2) 2 (8.3) abnormal all 383 47 (12.3) 2 (0.52) 39 (10.2) 21 (5.5) abnormal p value* <0.001 0.24 0.0013 <0.001 sensitivity 0.088 0.15 0.091 0.13 specificity 0.95 0.95 0.95 0.95 platelet 10,645

count normal 9958 588 (5.9) 14 (0.14) 498 (5.0) 135 (1.4) abnormal 512 57 (11.1) 2 (0.39) 40 (7.8) 37 (7.2) low abnormal 175 20 (11.4) 0 (0%) 18 (10.3) 9 (5.1) high p value† <0.001 0.32 <0.001 <0.001 sensitivity 0.088 0.13 0.074 0.21 ‡ specificity 0.046 0.048 0.047 0.045

* All abnormal compared with normal. † Abnormal low platelet count compared with normal platelet count. ‡ Sensitivity and specificity are for abnormal low platelet count only.

45 Table 3: Outcome odds ratios by number of abnormal hemostasis test results in 6,787 neurosurgery patients who underwent all 3 hemostasis tests

No. of No. w/ Patients All 3 No. w/ 1 No. w/ 2 Global Tests OR OR Outcome Abnorm or 3 p w/in (95% (95% Variable al Test Abnormal Value Normal CI)* CI)* (%) Tests (%) † Range (%) no. of 5855 792 140 patients intraop 521 1.9 3.45 396 97 <0.000 RBC (1.5– 28 (20.0) (2.3– (6.8) (12.3) 1 transfusion 2.4) 5.3) postop 12 8.47 10 RBC 0 NA 2 (1.4) (1.9– 0.023 (0.17) transfusion 39.0) 407 1.7 2.41 return to 318 <0.000 72 (9.1) (1.3– 17 (12.1) (1.4– OR (5.4) 1 2.3) 4.1) 154 4.7 13.1 <0.000 mortality 82 (1.4) 50 (6.3) (3.3– 22 (15.7) (7.9– 1 6.8) 21.7) * Odds ratios are relative to all 3 test results within normal range.

† Pearson chi-square test used to compare differences in outcomes across all groups.

46 Table 4: Outcome odds ratios by patient history indicative of potentially abnormal hemostasis in all 11,804 neurosurgery patients No. (%) w/ w/o OR Outcome No. of p Specifi History* History* (95% Sensitivity Variable Patients Value city CI) no. of 1286 10,518 patients intraop 2.4 156 564 RBC 720 (2.0– <0.001 0.22 0.10 (12.1) (5.4) transfusion 2.9) postop 3.2 RBC 18 5 (0.4) 13 (0.1) (1.1– 0.03 0.28 0.11 transfusion 8.9) 2.0 return to 116 491 607 (1.6– <0.001 0.19 0.10 OR (9.0) (4.7) 2.5) 8.2 mortality 190 92 (7.2) 98 (0.9) (6.1– <0.001 0.48 0.10 11.0)

* History = history indicative of potentially abnormal hemostasis.

47 Table 5: Abnormal screening test odds ratios by patient history indicative of potentially

abnormal hemostasis in neurosurgery patients screened with all 3 hemostatic tests

No. of w/ w/o Test OR Patients History* History* p Value Findings (95% CI) no. of 1286 10,518 patients mildly 277 3.2 (2.7– abnormal 108 169 <0.001 3.9) INR severely 21 11.0 (4.6– abnormal 13 8 <0.001 26.7) INR all abnormal 298 5.1 (4.0– 121 177 <0.001 INR 6.5) mildly 359 2.3 (1.8– abnormal 89 270 <0.001 3.0) aPTT severely 24 3.4 (1.4– abnormal 8 16 0.005 7.9) aPTT all abnormal 383 2.4 (1.9– 97 286 <0.001 aPTT 3.1) abnormal 512 3.6 (2.9– low platelet 151 361 <0.001 4.4) count abnormal 175 2.8 (2.0– high platelet 45 130 <0.001 3.9) count

*History = history indicative of potentially abnormal hemostasis.

48 Table 6: Predictive value of patient history indicating potentially abnormal coagulation,

abnormal hemostatic test results, both, or neither in 6,787 patients screened with all 3

hemostatic tests

w/ History* w/o History* & ≥1 &/or ≥1 No Abnormal Outcome No. of w/ History* Abnormal Abnormal Coagulation Variable Patients Test Test Tests

no. of 890 932 1551 5225 patients intraop RBC 521 23.8% 24.0% 37.4% 62.6% transfusion postop RBC 12 25.0% 16.7% 33.3% 66.7% transfusion return to OR 407 21.6% 21.9% 35.9% 64.1%

mortality 154 50.6% 46.8% 65.6% 34.4%

* History = history indicative of potentially abnormal hemostasis.

49 Table 7: Cost and rate of preoperative hemostasis screening in 11,804 neurosurgery

patients between 2006 and 2009

Cost per No. of Tests Cost of Tests No. of Tests Cost Attributed Test ($)* Done Done ($) Done in to Unnecessary Test Patients w/o Tests ($)‡ History† PT 30 7637 229,110 6647 199,410 aPTT 23 7026 161,598 6109 140,507 platelet 23 10,645 244,835 9437 217,051 count§ * Costs as reported in the 2011 Healthcare Blue Book.9

† History = history indicative of potentially abnormal hemostasis.

‡ Unnecessary tests are defined as those done in patients with no history indicative of

potentially abnormal hemostasis.

§ Cost of a complete blood count was used to report cost of platelet coun

Chapter 3: Short Term Outcomes of

Craniotomy for Malignant Brain Tumors in

the Elderly

Andreea Seicean MPH1, Sinziana Seicean MD MPH PhD2,3, Nicholas K. Schiltz1,

Nima Alan4, Paul K. Jones PhD1, Duncan Neuhauser PhD1, Robert J. Weil MD5

1Departament of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, Ohio; 2Departments of Pulmonary, Critical Care and Sleep Medicine, University Hospitals, Cleveland, Ohio; 3Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio; 4Case Western Reserve University School of Medicine, Cleveland, Ohio; 5The Rose Ella Burkhardt Brain Tumor & Neuro-Oncology Center, and Department of Neurosurgery, the Neurological Institute, Cleveland Clinic, Cleveland, OH.

This work has been published, in full, in the Cancer. It appears in this

dissertation with the kind permission from American Cancer Society &

Wiley Publishers.

Seicean A, Seicean S, Schiltz NK, Alan N, Jones PK, Neuhauser D, Weil RJ. Short-term outcomes of craniotomy for malignant brain tumors in the elderly. Cancer. 2012 Oct 12. doi: 10.1002/cncr.27851. [Epub ahead of print]

This work presented at the American Association of Neurological Surgery National Conference. Socioeconomic Section Session, April 14-18, 2012, in Miami, FL, USA; at the National Research Service Award (NRSA) Trainees Research Conference, June 23, 2012, in Orlando, FL, USA; and at the Academy Health national conference, June 23, 2012, in Orlando, FL, USA. This work was featured in HemOnc Today January 7, 2013.

51 Abstract

Background: Disparity in resection rates for malignant brain tumors in elderly patients

is partially attributed to a belief that advanced age is associated with increased risk for

postoperative morbidity and mortality. The aim of this study was to investigate the effect

of advanced age (≥75 years) on 30-day outcomes in patients with primary and metastatic

brain tumors who underwent craniotomy for definitive resection of a malignant brain

tumor.

Methods: Prospective analyses of the 2006-2010 American College of Surgeons

National Surgical Quality Improvement Project (NSQIP) database of 970 patients, ≥40 years of age, who underwent craniotomy for definitive resection of neoplasm. Pre- and intraoperative characteristics and 30-day outcomes were stratified by age. Using propensity scores, 134 patients (≥75 years) were matched to 134 patients 40-74 years of age. Logistic regression was used to predict adverse postoperative outcomes.

Results: Median length of hospital stay was 5 days, the rate of minor and major complications were 5.9% and 13.1% respectively, 5.7% of patients returned to the operating room and 4.3% of patients expired within 30 days. Advanced age did not increase the odds for poorer short-term outcomes.

Conclusions: Advanced age does not increase the risk of poor outcomes after surgical resection of primary or metastatic intracranial tumors, after controlling for other risk factors. These results suggest that age should not be used, in isolation, as an a priori factor to discourage pursuing craniotomy.

52 Background

Each year in the United States, over 20,000 patients are diagnosed with a primary malignant glial neoplasm and between 100,000 and 200,000 patients are diagnosed with a new brain metastasis (BM)1. Continued trends toward an aging population, combined with the increased incidence in tumors of all kinds with advancing age, lends greater importance to identifying the effect of advanced age on a patient’s ability to withstand aggressive cancer treatments, including craniotomy for tumor.

Several studies have shown that surgical tumor resection, with and without additional treatment, prolongs survival in patients with both primary2,3 and metastatic brain tumors4,5. However, a recent study conducted in a nationally representative sample of US adults6 confirmed a persistent disparity in surgical resection rates in the elderly.

This inequity has been partially attributed to a belief that elderly patients are a more fragile population, unable to tolerate long surgeries, and have a higher risk of morbidity and mortality following craniotomy for malignant tumor resection6-9.

The object of this study was to investigate the effect of advanced age (≥75 years), alone and in combination with several pre- and intraoperative factors, on 30-day outcomes in patients with primary and metastatic brain tumors who underwent craniotomy for definitive resection of neoplasm.

Methods

Data Source: The medical records of all patients who underwent craniotomy for definitive resection of an intracranial primary or metastatic brain tumor that were included in the American College of Surgeon (ACS) National Surgical Quality

53 Improvement Program (NSQIP) database between 2006 and 2010 were evaluated.

Detailed description of the ACS-NSQIP database, including design, sampling strategy,

and variable definitions can be found elsewhere10. This study was approved by the

Cleveland Clinic Institutional Review Board.

Subjects: The study population consists of 970 adult patients, 40 years of age and older,

who underwent craniotomy between 2006 and 2010. We used the Current Procedure

Terminology Codes (CPT) to identify craniotomy patients who underwent definitive

resection of tumor and matched cases with those who had been assigned an International

Classification of Disease (ICD-9) code that corresponded with malignant neoplasm. Of these 970 patients, 563 (58%) had a malignant glioma, 380 (39%) had a metastatic brain tumor, and 27 (3%) had a malignant tumor of a cranial nerve, cranial meninges, or not

otherwise specified.

Age: Age at surgery was categorized as: 40 to 74, and ≥75 years. Sensitivity analyses

were conducted using age as categorized by decade, and altering the definition of elderly

to ≥60 years and ≥65 years.

Patient History Covariates: All available pre-and intraoperative factors, previously

identified as having an effect on postoperative outcomes11, were assessed. Transfer status

was dichotomized as being admitted from home vs. being transferred from another

facility (any of: an acute care hospital, chronic care facility, and outside emergency

department). Alcohol intake was recorded as having consumed ≥ 2 drinks per day in the

2 weeks prior to admission. Functional status captures the ability to perform activities of

daily living within 30 days prior to surgery and was dichotomized as independent vs.

partially or totally dependent. American Society of Anesthesiologists (ASA) physical

54 status classification values were dichotomized as 1 and 2 indicative of normal healthy patient or patient with mild disease, and 3 and 4 as having severe systemic disease that is

/ is not life threatening. Patients that required ventilator-assisted respiration during the 48 hours prior to surgery, had been diagnosed with chronic obstructive pulmonary disease

(COPD), and/or had evidence of pneumonia at the time of surgery were considered to have pulmonary comorbidities. Cardiovascular comorbidities were considered positive for patients with: diagnosis of congestive heart failure (CHF) within 30 days prior to surgery, myocardial infarction (MI) in the 6 months prior to surgery, percutaneous coronary intervention (PCI), previous cardiac surgery, self-reported angina in the month prior to surgery, angioplasty or revascularization procedure for atherosclerotic peripheral vascular disease (PVD), and/or was experiencing rest pain or gangrene. Dyspnea was self-reported as difficult, painful, or labored breathing with moderate exertion. Patients with acute or chronic renal failure requiring treatment with peritoneal dialysis, hemodialysis, hemofiltration, hemodiafiltration, or ultrafiltration within 2 weeks prior to surgery were considered to have renal comorbidities. Central nervous system (CNS) comorbidities were reported positive for patients having had coma for ≥ 24 hours, hemiplegia, transient ischemic attacks (TIA), cerebrovascular accident, paraplegia, or quadriplegia. Chemotherapy and radiotherapy for cancer within 90 days prior to surgery were individually captured. Self-reported patient history of abnormal bleeding, self- reported family history of bleeding disorders, vitamin K deficiency, and a comprehensive list of medications that pose a risk for bleeding abnormalities were captured through the

NSQIP variable bleeding disorders. Preoperative hemostatic screening lab values were recorded in the NSQIP database if drawn within 90 days prior to the surgical procedure.

55 Intra and postoperative transfusions were aggregated, using RBC amount given of ≥ 250 cc as indicative of transfusion.

Outcomes of interest: Time between hospital admission and surgery, operation and discharge, and total length of stay (LOS) were individually assessed. Prolonged LOS was defined as LOS >75% of the patients in the sample, which was 9 days. Postoperative complications were defined as occurring within 30 days of surgery. Minor complications were one or more of: superficial surgical site infection, urinary tract infection, deep venous thrombosis (DVT) or thrombophlebitis. Major complications were one or more of: deep incision surgical site infection, organ or space surgical site infection, wound disruption, pneumonia, unplanned intubation, pulmonary embolism, >48 hour postoperative ventilator-assisted respiration, progressive renal insufficiency, acute renal failure, cardiovascular accident with neurological deficit, coma of >24 hours, peripheral nerve injury, cardiac arrest requiring CPR, myocardial infarction, graft, prosthesis or flap failure, sepsis, septic shock, and/or 30-day return to the operating room (OR). The total number of postoperative complications per patient was also reported. Return to the OR

(yes/no) was defined as any unplanned return to the OR for a surgical procedure within

30 days postoperatively. Days of operation until death was used to dichotomize mortality at 30 days postoperatively.

Statistical Analyses: Pre- and intraoperative and 30-day outcomes were compared across age groups using Pearson's chi-square tests for categorical variables; ANOVA was used for continuous variables. Propensity scores, including all variables in Table 1, were generated to obtain an approximately unbiased measure of the effect of age on adverse outcomes in the 40-74 years vs. ≥75 years age groups. A 1:1 greedy matching

56 technique12 was used to match all elderly patients (≥75 years of age) with a unique

patient 40-74 years of age. Covariates were compared between age groups in the

matched sample. Logistic regression analysis was used to test whether age was

independently associated with adverse outcomes. Covariates that remained unbalanced

after matching on propensity scores were included in the final models. In addition, all

analyses were repeated for primary glioma and metastatic brain tumor patients separately.

A p-value of <0.05 was significant. SAS (Version 9.2, SAS Institute), was used.

Results

Of the 970 patients who underwent craniotomy for definitive resection of a malignant, intracranial brain tumor, 134 (13.8%) were ≥75 years of age. Compared to patients 40-74 years of age, elderly patients (≥75 years) were slightly more likely to be male; and less likely to be: admitted directly from home, current smokers, have independent functional status or an ASA classification of 1 or 2 (Table 1). Patients ≥75 years of age had slightly lower mean baseline BMIs compared with patients 40-74 years of age (26.8 kg/m² vs. 28.2 kg/m²). The elderly had higher rates of pulmonary, cardiovascular and CNS comorbidities, hypertension requiring medication, and diabetes mellitus. They also were less likely to have received preoperative chemotherapy or radiation (1.5% of elderly compared with 10.1% in the 40-74 year age group). The frequency of emergency cases was similar between age groups. Elderly patients had a higher prevalence of abnormal preoperative lab values, including sodium, creatinine, and albumin levels (Table 1). There were no significant differences in preoperative alkaline phosphatase, bilirubin, hematocrit, white blood cell count, and platelet count across age

57 groups; nor between the frequency of emergency procedures, level of residency

supervision during the surgery, or wound classification. Prevalence of intraoperative

factors consisting of level or residency supervision, wound class, and transfusions

undergone were similar between age groups.

The 30-day outcomes for the entire group were: 5.9% (n=57) of all patients

experienced one or more minor complication, 13.1% (n=127) one or more major

complication, 5.7% (n=55) returned to the OR within 30 days, and an overall 4.3%

(n=42) 30 day mortality (Table 2). Though total length of hospitalization was not

significantly different between age group, elderly patients more likely to have prolonged

LOS (41.0%) (Table 2). No association was found between age and minor, major, or

total number of complications. No difference was found in the percentage of elderly

returning to the OR or dying within 30 days postoperatively.

All covariates shown in Table 1 were used to generate the propensity score, and elderly patients (≥75 years of age) were matched 1:1 with patients 40-74 years of age.

After matching, BMI remained the only covariate to have significantly different values

between age groups. The relationship between age and each adverse outcome of interest

was determined using logistic regression at baseline, after matching by propensity scores,

and further including BMI (Table 3). While in the unmatched analyses elderly patients

have 2.3 (95% CI, 1.5-3.2) the odds for prolonged LOS compared to patients 40-74 years

of age, this difference becomes non-significant after propensity matching. There is no

relationship between age and any of the adverse outcomes in the propensity matched

sample with and without BMI included (Table 3).

58 Sensitivity analyses limiting the sample to malignant glioma (n=563) and those with BM (n=380) individually produced consistent results. As did using age as categorized by decade, and altering the definition of elderly to ≥60 years and ≥65 years.

Using different modeling techniques, including multivariate logistic regression analyses and backwards selection model building produced the same findings. Extensive analyses for potential interactions between age and other pre- and intraoperative variables revealed no significant effects.

Discussion

Advanced age (≥75 years) was not found to be associated with poorer operative or

30-day outcomes in patients undergoing craniotomy for definitive resection of a malignant intracranial tumor. Patients ≥75 years of age fared equally as well as patients

40-74 years of age, the typical age range for most adults with a malignant brain tumor who undergo aggressive therapy, and the population that is usually included in most, if not all, clinical trials.

Interpretations in the Context of the Literature: Elderly patient are frequently excluded from clinical trials13-15, such as the 2005 Stupp et al trial16 looking at addition of temozolomide to radiotherapy in glioblastoma patients. While a few trials since have included older patients17,18 the focus of these has been on application of adjuvant therapy after non-definitive, attempted or completed gross total resection of tumor; gross total resection has been shown to have a survival advantage compared to partial resection and certainly biopsy alone2,3.

59 Few studies have explored the association between age and short term

postoperative outcomes, and with conflicting findings19-22. Using samples that contained patients undergoing resection of both primary and metastatic tumors, two studies found age to be associated with increased risk of major complications7,9. Two other studies,

only sampling patients with BM, found age to be associated with increased morbidity and

mortality19,22. In contrast, two studies of patients with malignant glioma concluded that

advanced age was not associated with increased morbidity and found no association

between age and postsurgical neurological function20,21. Major limitations of previous study designs include limited assessment of pre- and intraoperative factors , single institution patient samples7,9,21,22, small sample sizes with few events7,21,22, and reliance

on univariate analyses to arrive at their conclusions7,13,21,22.

We identified elderly patients as having a higher prevalence for prolonged LOS across our entire sample; however, there was no significant difference between age groups when looking at total length of hospital stay as a continuous variable (Table 2).

No association between age and prolonged LOS remained after matching by propensity scores. While elderly patients do have somewhat longer lengths of hospitalization with a mean of 2 days longer for patients ≥75 years of age compared to those 40-74 years of

age, this difference is non-significant and disappears completely after adjusting for other

pre and intraoperative variables.

Clinical Implications: Although a number of studies have shown enhanced survival in

patients with both primary2,3 and metastatic brain tumors4,5, there remains controversy about the risk for surgical complications in the elderly causing inequities in surgery rates.

Our study suggests that the perception that elderly patients have a higher risk for

60 morbidity and mortality following craniotomy6-9 is unsupported. To our knowledge, only

one previous study has shown an association between age (>60 years) and increased odds

for major regional complications9 in craniotomy patients. This finding was published

almost a decade and a half ago and came from a single institution, with a limited sample

size, a small event rate, and a limited number of pre- and intraoperative variables analyzed. Our study revisits this topic, and finds no effect of age on 30-day morbidity and mortality in patients undergoing craniotomy for resection of primary or metastatic tumor, after controlling for other risk factors, and cautions against the use of age as an a priori factor to discourage pursuing craniotomy.

Limitations: The NSQIP database contains only patients who underwent surgery; therefore we are not able to capture any patient that did not undergo surgery due to preexisting risk factors, including advanced age, as has been reported in other surgical specialties23. One cannot account for issues of surgeon and hospital volume, known to

influence postoperative morbidity and mortality after craniotomy for brain tumor24, since

it is ACS policy to maintain confidentiality for data reporting institutions10. However, we

did model for presence or absence of resident participation in the OR, which is a

surrogate for academic versus non-academic hospitals, and tends to correlate with hospital size and volume, and which was not found to be different between age groups

(Table 1) nor related to any of our outcomes of interest (data not shown). In addition, the low levels of postoperative complications identified in our sample are similar to those at high-volume facilities24. Third, NSQIP only provides the last set of lab results prior to surgery, within 90 days of surgery; nor does it include certain features (such as the presence of a neurological deficit, rather than overall functional status) that may

61 influence outcome, disposition, and survival. Fourth, we do not have data on the size, exact location, number, or type of primary lesions for patients with metastasis (n=380); whether WBRT was administered prior to resection; of extent of resection, all of which have been previously identified as affecting survival2-5. However, postoperative complications and short term mortality have been previously found to be similar between patients undergoing craniotomy for single vs. multiple tumor resections4, and although type of primary lesion has been found to affect overall survival25, no study has yet shown a difference in postoperative short term outcomes. Fifth, since there is suboptimal data on pre- and postoperative neurological function, one cannot compare these results against studies that only assessed neurological function as a postoperative complication20,21.

Finally, the surgical population captured by NSQIP may not be wholly representative of the US neurosurgical population, as self-selected institutions contribute patient data.

However, the gender and race distributions in the NSQIP database are representative of the US population and data is collected prospectively from a substantial number of varying types of institutions, thus providing a large and diverse sample size10. Additional benefits of the NSQIP database are that data was collected in a standardized manner at each site with strict variable definitions and annual quality checks10; the database has been validated for accuracy and reproducibility and achieves >95% 30 day outcome follow-up rate across consecutive cycles10,26.

Conclusion

This is the first prospective, multi-institutional study to assess the relationship between age, other pre- and perioperative risk factors, and short-term outcomes after

62 craniotomy for definitive tumor resection in the elderly (≥75 years of age) compared with

younger adults. Advanced age (≥75 years) did not with poorer short-term outcomes.

While a few studies have assessed the role of age on short term outcome of patients with a primary or metastatic tumor, these possess numerous limitations7,9,19-22. Since patients

75 years of age (and, in some cases 65 or 70 years of age or older) are usually or

frequently excluded from most clinical trials13-15, there is a paucity of data regarding the risk of definitive surgical resection and its correlation with short-term, perioperative outcomes in these patients. Contrary to common assumptions, our analysis of a large, prospective, multi-institutional database suggests that advanced age does not predispose individuals undergoing aggressive surgical therapy for primary or metastatic intracranial tumor to increased risk for operative or short-term postoperative morbidity or mortality.

63 Chapter 3 References

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6. Iwamoto F, Reiner A, Nayak L, Panageas KS, Elkin EB, Abrey LE, et al: Prognosis and patterns of care in elderly patients with glioma. Cancer. 2009;115:5534-40.

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11. American College of Surgeons National Surgical Quality Improvement Project. ACS NSQIP Data User Guide: October 2010. American College of Surgeons, 2010.

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64 13. Hutchins LF, Unger JM, Crowley JJ, Coltman CA Jr, Albain KS. Underrepresentation of patients 65 years of age or older in cancer-treatment trials. N Engl J Med 1999;341:2061-7.

14. Townsley CA, Selby R, Siu LL: Systematic review of barriers to the recruitment of older patients with cancer onto clinical trials. J Clin Oncol. 2005;23:3112-24.

15. Lewis JH, Kilgore ML, Goldman DP, Trimble EL, Kaplan R, Montello MJ, et al. Participation of patients 65 years of age or older in cancer clinical trials. J Clin Oncol. 2003;21:1383-1389.

16. Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, et al: Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med. 2005;352:987-96.

17. Keime-Guibert F, Chinot O, Taillandier L, Cartalat-Carel S, Frenay M, Kantor G, et al: Radiotherapy for glioblastoma in the elderly. N Engl J Med. 2007;356:1527-35.

18. Wick W, Platten M, Meisner C, Felsberg J, Tabatabai G, Simon M, et al: Temozolomide chemotherapy alone versus radiotherapy alone for malignant astrocytoma in the elderly: the NOA-08 randomized, phase 3 trial. Lancet Oncol. 2012;13:707-715.

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20. Chang SM, Parney IF, McDermott M, Barker FG 2nd, Schmidt MH, Huang W, et al: Perioperative complications and neurological outcomes of first and second craniotomies among patients enrolled in the Glioma Outcome Project. J Neurosurg. 2003;98:1175-81.

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22. Stark A, Tscheslog H, Buhl R, et al: Surgical treatment for brain metastases: prognostic factors and survival in 177 patients. Neurosurg Rev. 2005;28:115-9.

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65 25. Sperduto P, Kased N, Roberge D, Xu Z, Shanley R, Luo X, et al: Summary report on the graded prognostic assessment: an accurate and facile diagnosis-specific tool to estimate survival for patients with brain metastases. J Clin Oncol. 2012;30:419-25.

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66 Chapter 3 Tables

Table 1: P Values for covariate balance between age groups, before and after stratification on propensity score

40-74 yr ≥ 75 yr Unstratifie Stratified (N = 836) (N = 134) d P† P Value‡ 86.2% 13.8% Female gender 46.9% 44.8% 0.04 0.55 African American 6.6% 6.0% 0.79 1.0 Admitted from home 90.2% 85.1% 0.07 0.62 Smoking status <0.001 0.76 Current 27.5% 9.7% Previous 26.9% 39.6% Never 45.6% 50.8% >2 drinks per day 5.3% 4.5% 0.86 0.78 Independent functional <0.001 0.32 80.7% 67.9% status ASA classification <0.001 1.0 1 + 2 19.6% 3.7% 3 + 4 79.7% 96.3% Body Mass Index (kg/m2) 28.2 (±6.3) 26.8 (±5.6) 0.02 <0.001 ; mean (±SD) Pulmonary comorbidities 8.5% 19.4% <0.001 0.64 Cardiovascular 7.5% 23.9% <0.001 0.56 comorbidities Hypertension requiring 42.2% 76.1% <0.001 0.57 meds Dyspnea 9.1% 12.7% 0.19 0.84 CNS comorbidities 30.3% 38.8% 0.04 0.45 Diabetes mellitus 11.4% 23.1% <0.001 1.0 Disseminated cancer 33.1% 31.3% 0.68 0.90 Weight loss >10% in 6 3.7% 7.5% 0.04 0.82 months prior to surgery Steroid use for chronic 26.3% 20.2% 0.13 0.65 condition Preoperative chemo 10.1% 1.5% 0.001 1.0 and/or radiotherapy Preoperative sepsis 8.3% 11.9% 0.16 0.22 Bleeding disorder 2.8% 4.5% 0.27 0.76 Prior operation within 30 2.4% 1.5% 0.80 0.90 days Abnormal albumin 11.2% 24.6% <0.001 0.75 Abnormal alkaline 5.3% 4.5% 0.91 0.88

67 phosphatase Abnormal creatinine 3.7% 14.9% <0.001 0.73 Abnormal hematocrit 47.0% 56.7% 0.11 0.82 Abnormal platelet count 11.2% 7.5% 0.35 0.81 Abnormal sodium 11.5% 23.1% 0.001 0.78 Abnormal total bilirubin 3.2% 3.7% 0.67 0.57 Abnormal white blood 39.1% 43.3% 0.55 0.76 cell count Level of residency supervision in the OR 0.23 0.86 Attending alone 48.7% 55.2% Attending and resident 50.7% 43.3% Emergency case 5.9% 3.0% 0.17 0.70 Wound class 0.48 1.0 Clean 96.5% 98.5% Clean-contaminated 1.7% 0.8% Contaminated of infected 1.8% 0.8% Transfusion δ 4.4% 5.2% 0.68 0.78 *DNR status, presence of ascites, presence of esophageal varices, renal comorbidities, and transfusion of >4 units of RBC’s in 72 hours prior to surgery were each present in less than 1% of the entire cohort.

†Unstratified P value obtained from comparison of ≥ 75 years of age group against all others (40-74 years of age) at baseline.

‡Stratified P value obtained after using a propensity score 1:1 matching strategy.

δ Intra or postoperative.

68 Table 2: 30-Day post-operative outcomes, stratified by age groups (N = 970)

40-74 yr ≥ 75 yr (N = 836) (N = 134) P† 86.2% 13.8% Time between hospital admission and operation (days); 0 (0-3) 2 (0-4) 0.76 median (IQR) Time between operation and discharge 3 (2-6) 5 (3-7) 0.28 (days); median (IQR) Total Length of Hospital Stay (days); median 5 (3-8) 7 (4-12) 0.41 (IQR) Prolonged length of hospital Stay (>9 days) 24.2% 41.0% <0.001 Minor complications 5.9% 6.0% 0.96 Major complications 12.7% 15.7% 0.34 Total number of complications 0.09 0 83.5% 81.3% 1 10.2% 7.5% ≥2 6.3% 11.2% Return to the OR 5.3% 8.2% 0.17 30 day mortality 4.0% 6.7% 0.14 *IQR = Interquartile Range

†Unstratified P value obtained from comparison of ≥ 75 years of age group against all others (40-74 years of age) at baseline.

69 Table 3: Age group comparisons (≥75 yrs vs. 40-75 yrs of age) for adverse outcomes

(Odds Ratios) using different analysis methods

Analyses Adverse Propensity- Logistic Propensity-Matched Outcomes Matched Sample Regression† Sample plus BMI Prolonged LOS 2.2 (1.5-3.2) 1.3 (0.8-2.2) 1.1 (0.7-1.9) (>9 days) Minor 1.0 (0.5-2.2) 0.5 (0.2-1.3) 0.5 (0.2-1.4) complications Major 1.3 (0.8-2.1) 1.0 (0.5-1.8) 0.9 (0.5-1.8) complications Total number of 1.2 (0.8-1.9) 0.8 (0.5-1.5) 0.8 (0.4-1.5) complications 30 day return to 1.6 (0.8-3.2) 1.2 (0.5-3.1) 1.2 (0.4-3.0) the OR 30 day mortality 1.8 (0.8-3.7) 1.3 (0.5-3.6) 1.0 (0.4-2.9) †At baseline prior to stratification on propensity scores

70 Chapter 4: Effect of Smoking on the

Perioperative Outcomes of Patients who

Undergo Elective Spine Surgery

Andreea Seicean MPH1, Sinziana Seicean MD MPH PhD2,3, Nima Alan4, Nicholas K.

Schiltz1, Benjamin P. Rosenbaum MD6, Paul K. Jones PhD1, Duncan Neuhauser

PhD1, Michael W. Kattan PhD5, Robert J. Weil MD6

1Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, Ohio; 2Departments of Pulmonary, Critical Care and Sleep Medicine, University Hospitals, Cleveland, Ohio; 3Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio; 4Case Western Reserve University School of Medicine, Cleveland, Ohio; 5Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH; 6The Rose Ella Burkhardt Brain Tumor & Neuro-Oncology Center, and Department of Neurosurgery, the Neurological Institute, Cleveland Clinic, Cleveland, OH.

This work has been accepted for publication, in full, in the Spine. It appears

in this dissertation with the kind permission from Lippincott Williams &

Wilkins publishing.

71 Abstract

Study Design: Retrospective analysis of the prospectively-collected American College of

Surgeons National Surgical Quality Improvement (NSQIP) database.

Objective: We wished to assess whether preoperative cigarette smoking and smoking

duration predicted adverse, early, peri-operative outcomes in patients undergoing elective

spine surgery.

Summary of Background Data: Prior studies have assessed the association of smoking and long-term outcomes for a number of spine surgery procedures, with conflicting findings. The association between of smoking and 30-day outcomes for spine surgery is

unknown.

Methods: 14,500 adults, classified as current (N=3,914), prior (N=2,057), and never

smokers. Using propensity scores, current and prior smokers were matched to never

smokers. Logistic regression was used to predict adverse postoperative outcomes. The

relationship between pack-years and adverse outcomes was tested. Sensitivity analyses

were conducted limiting the study sample to patients who underwent spine fusion

(N=4,663), and using patient subgroups by procedure.

Results: In unadjusted analyses, prior smokers were significantly more likely to have

prolonged hospitalization (1.2, 95% CI: 1.1-1.3) and major complications (1.3, 95% CI:

1.1-1.6) compared with never smokers. No association was found between smoking status and adverse outcomes in adjusted, matched patients models. Current smokers with more then 60 pack-years were more likely to expire within 30 days of surgery (3.0, 95%

CI, 1.1-7.8), compared to never smokers. Sensitivity analyses confirmed these findings.

72 Conclusions: The large NSQIP population was carefully matched for a wide range of

baseline comorbidities, including 29 variables previously suggested to influence peri- operative outcomes. While previous studies conducted in subgroups of spine surgery patients have suggested a deleterious effect for smoking on long-term outcomes in patients undergoing spine surgery, our analysis did not find smoking to be associated with early (30-day) peri-operative morbidity or mortality.

73 Introduction

Smoking is responsible for significant morbidity as well as 1 in 5 deaths in the United

States, yet 19.3% of US adults are current cigarette smokers1. With >3 million elective

spine surgery procedures done in the US between 2006 and 20102 (see Appendix Chapter

3: Supplemental Digital Content (SDC)), it is important to assess the effect of current

smoking status and prior cigarette consumption on postoperative complications and 30-

day mortality.

Prior studies have assessed the association between smoking and pain, quality of

life, disability, and patient satisfaction for a number of spine surgery procedures, with

conflicting findings3-22. The effect of smoking on short-term outcomes for spine surgery is uncertain.

We investigated the association between preoperative cigarette smoking and smoking duration as determined by number of pack-years, alone and in combination with several pre- and intraoperative factors, and 30-day outcomes in patients undergoing elective spine surgery.

Materials and Methods

Data Source: The medical records of all patients who underwent elective spine surgery that were included, prospectively, in the American College of Surgeon (ACS) National

Surgical Quality Improvement Program (NSQIP) database between 2006 and 2010 were evaluated. Detailed description of the ACS-NSQIP database, including design, sampling strategy, and variable definitions can be found elsewhere23. This study was approved by the Cleveland Clinic Institutional Review Board.

74 Subjects: We used the Current Procedure Terminology Codes (CPT) to identify 14,980 adult patients who underwent spine surgery between 2006 and 2010. We excluded 402 patients that had an emergency procedure because these patients were presumably treated, on an emergency basis, regardless of their smoking status. All remaining patients had a recorded smoking status. We excluded an additional 78 patients because they were coded as current smokers but had 0 pack-years recorded, an inconsistency making their smoking status uncertain. Our final study sample consisted of 14,500 elective spine surgery patients with known smoking status. Of these 14,500 patients, about a third

(N=4,663) had spine fusion as either the primary procedure or an additional procedure.

The most common primary procedure was single level lumbar laminotomy (N = 3,326;

CPT code 63030), followed by single level lumbar laminectomy (N = 1,777; CPT code

63047), and single level anterior cervical discectomy (N = 1,571; CPT code 63075).

Smoking: Smoking was categorized as: current, prior, or never smoker24. Please see the

SDC for a detailed description of this variable.

Patient History Covariates: All available pre-and intraoperative factors, previously identified as having an effect on postoperative outcomes25, were analyzed. Please see the

SDC for a detailed description of each covariate.

Outcomes of interest: Total length of hospital stay (LOS), minor and major complications, 30 day return to the operating room (OR) and 30 day postoperative mortality were assessed for each smoking group (current, prior, and never). Please see the SDC for a detailed description of each outcome.

Statistical Analyses: Pre- and intraoperative and 30-day outcomes were compared across smoking groups (never, prior, current) using Pearson's chi-square tests for categorical

75 variables; ANOVA was used for continuous variables. Propensity scores26, including all

variables that were statistically significant in Table 1, were generated to obtain an

approximately unbiased measure of the association between smoking status and adverse

outcomes in the never vs. prior vs. current smoker groups. A 1:1 greedy matching

technique27 was used first to match all prior smokers with a unique never smoker on both

propensity score and age, and then to match all current smokers with a unique never

smoker. Restrictions were set on the matching criteria to within 0.2*(standard deviation) of the propensity score, to allow for increased accuracy in matching. Covariates were compared between smoker groups in the matched sample. Logistic regression analysis was used to test whether smoker status was independently associated with adverse outcomes. Covariates that remained unbalanced after matching on propensity scores were included in the final models. The relationship between pack-years and adverse outcomes was also tested in the entire sample, and after matching on propensity score separately comparing current with never smokers and prior with never smokers.

All analyses were repeated comparing prior and current smokers to each other, and using pack-years as a continuous and categorical predictor variable for each outcome.

Sensitivity analyses included using all variables in Table 1 to generate the propensity score, including CPT code into the propensity score, and matching without criteria restrictions.

In addition, analyses were repeated separately for spine fusion patients, and limiting study sample to patients within each CPT code. A p-value of <0.05 was significant. SAS (Version 9.2, SAS Institute) was used.

76 Results

Of the 14,500 patients who underwent elective spine surgery, 3,914 (27.0%) were current smokers and 2,057 (14.2%) were prior smokers. Patient demographics, comorbidities, and lab values are summarized in Table 1. Compared to never smokers, both current and prior smokers were less likely to be female and to be operated on by an attending surgeon alone, without a resident physician assisting. Current smokers were the youngest group, had the lowest mean BMI, and were more likely to be: African

American, consume alcohol prior to surgery, have pulmonary comorbidities, and have abnormal sodium and white blood cell count. Compared to both prior and never smokers, current smokers had fewer: comorbidities, abnormal lab values, and intra/postoperative transfusions. Prior smokers were older than current and never smokers, had more comorbidities and abnormal lab values, and were less likely to be operated on by the attending alone. The mean pack-years of smoking for current smokers was 28 years (SD

= 23) and for prior smokers, 27 years (SD = 25).

The 30-day outcomes for the entire group were: 3.2% (n=462) of all patients experienced one or more minor complication, 5.6% (n=813) one or more major complication, 3.3% (n=473) returned to the OR within 30 days, and an overall 0.4%

(n=59) 30 day mortality. Though mean length of hospital stay was 2 days for all 3 groups, current smokers has a shorter inter-quartile range of 1-3 days compared to 1-4 days for both prior and never smokers (Table 2). Prior smokers were most likely to have prolonged LOS (30.2%), with current smokers being the least likely (22.2%). Prior smokers were also found to have significantly more major complications where compared to never smokers, with 7% and 5.4% respectively. No association was found

77 between smoking status and minor complications, return to the OR, or dying within 30

days postoperatively.

All covariates that were significant in Table 1 were used to generate the

propensity score. Current smokers were matched 1:1 with never smokers on both

propensity score and age, restricting matching to values within 0.2*(standard deviation)

of the propensity score. The same approach matched prior with never smokers. We

successfully matched 3,760 (96.1%) of the current smokers with controls, and 2,045

(99.4%) of the prior smokers (Table 3). After matching, BMI and level of residency

supervision in the OR remained significantly different for both current and prior smokers.

Current smokers remained significantly more likely to be female, have slightly higher

ASA classification, consumer alcohol prior to surgery, have pulmonary comorbidities,

and have abnormal sodium compared to never smokers (Table 3).

The relationship between smoking status and each outcome of interest was

determined using logistic regression at baseline, after matching by propensity scores, and

further including all unbalanced covariates (Table 4). In the unmatched analyses, compared to never smokers, current smokers have 0.8 (95% CI, 0.7-0.8) the odds for

prolonged LOS and prior smokers have higher odds for both prolonged LOS (1.2; 95%

CI, 1.1-1.3) and major complications (1.3; 95% CI, 1.1-1.6). There is no relationship

between smoking status and any of the adverse outcomes in the propensity matched

sample with, or without the unbalanced covariates included (Table 4).

The distribution of pack-years is shown in SDC Table 1. There are 15% more

current than prior smokers in the less than 20 pack-years category. At baseline, subjects

with 20 pack-years or less were significantly less likely to have prolonged LOS (0.8; 95%

78 CI, 0.7-0.9) and less likely to expire within 30 days of surgery (0.3; 95% CI, 0.1-0.9)

compared to never smokers, while those with more than 60 pack-years had higher

likelihood to expire within 30 days (3.9; 95% CI, 1.6-9.3) compared with never smokers

(SDC Table 2). After stratification on propensity scores, current smokers with 20 pack-

years or less, continue to be less likely to have prolonged LOS (0.7; 95% CI, 0.6-0.9)

then never smokers, while those with more then 60 pack-years had higher likelihood for

both prolonged LOS (1.5; 95% CI, 1.1-2.1) and to expire within 30 days of surgery (3.0,

95% CI, 1.1-7.8) compared with never smokers (SDC Table 3A). There appear to be no

meaningful relationship between pack-years and adverse outcomes when comparing prior

with never smokers in the final model (SDC Table 3B).

Sensitivity analyses, including all variables in Table 1, were used to generate the

propensity score; matching without criteria restrictions produced consistent results, as did

limiting the study sample to patients that had spine fusion (N=4,663), or limiting the

study sample to patients within each CPT code (data not shown).

Discussion

Smoking itself was not found to be associated with poorer operative or 30-day

outcomes in patients undergoing elective spine surgery, in nearly all patients. Current

and prior smokers fared equally well as never smokers. While there was no association

between pack-years and adverse outcomes overall, current smokers with more then 60 pack-years were more likely to expire within 30 days of surgery, compared to never smokers.

79 Interpretations in the Context of the Literature: Although the body of literature

examining the effects of smoking on surgical outcomes in different surgical

subpopulations and specialties is copious, this is the first, large, analysis of the

prospectively collected and validated data of the role of smoking on short term

postoperative outcomes in patients undergoing elective spine surgery. Prior studies of the

association between smoking and spine surgery outcomes were nearly all limited to

specific procedures, focused on determining postoperative pain, function, patient

satisfaction, quality of life, or fusion rates; and, nearly all report conflicting findings3-22.

One multicenter study showed that spine patients who smoked had lower Short Form

Health Survey (SF-36) scores postoperatively compared to nonsmokers, indicative of

poorer health3. Nearly all other studies focused exclusively on the effect of smoking on

spine fusion4-12, spinal stenosis13-19, and disc herniation20-22.

We found no relationship between smoking and 30 day adverse outcomes in

unadjusted and adjusted analyses when limiting our sample to patients who underwent

lumbar fusion. All nine prior studies that assessed the relationship between smoking and

long-term outcomes consistently report detrimental effects relation to smoking4-12. Six

studies reported an increased incidence of nonunion in current smokers4-10, one of which also assessed the impact of pack-years on fusion rates, and found no association10.

Another three studies assessed combinations of pain, function, and patient satisfaction

relative to cigarette smoking at the time of spine fusion6,11,12. Carpenter et al6 reported a

negative association between outcome score and pack- years and Peolsson11 found that

current smokers had higher levels of pain postoperatively. Interestingly, Luca et al12

80 found that smoking and pain were related in patients that had translaminar screw fixation,

but not in those that had transforaminal interbody fusion.

Prior studies of the effect of smoking on spinal stenosis13-19 and on disk

herniation20-22 conflict. Two13,19 found that smoking was associated with higher long

term levels of pain and inferior results from spinal stenosis, while the other five14-18 reported no relationship between smoking and pain, disability, functional status or patient satisfaction. Similarly, one study21 found that smoking was a predictor of poorer quality

of life one year after surgery for herniated lumbar disk, while another two20,22 identified

no relationship between smoking and pain or disability.

Limitations of previous study designs, with respect to early peri- and post-

operative outcomes (≤30 days from surgery), both individually and collectively

considered include: restricted assessment of pre- and intraoperative factors, single institution patient samples5,6,8,10-17,20,22, small sample sizes with few events5-7,11,13,15-17,20,

and reliance on univariate analyses5-8,10,13,15,22. In addition, some authors do not adjust for baseline differences in demographics and health characteristics between current and

never smokers3-10,13,16,17. None of the studies took prior smoking history into account,

limiting their analyses to smokers at the time of or after surgery, and failing to explain

whether prior smokers were included in their sampling of non-smokers. Please see the

SDC for additional interpretations.

Clinical Implications: While our data show that smoking is not associated with 30-day

peri-operative morbidity or mortality, this finding is not intended to discourage smoking

cessation. Smoking has been associated with considerable adverse health effects29, and

81 several studies suggest that spine fusion patients who smoke are at an increased risk for

poorer long-term outcomes compared to nonsmokers4-12.

Limitations: The NSQIP database captures smoking status within a year prior to surgery,

allowing for possible misclassification of prior smokers as current smokers due to

preoperative smoking cessation. Though we could not assess the effect of smoking

cessation in our sample, our findings show that neither prior nor current smokers were at

increased risk for adverse short-term outcomes. While it is was not possible to account for issues of surgeon and hospital volume due to ACS policy to maintain confidentiality for data reporting institutions23, we did model for presence or absence of resident

participation in the OR, which is a surrogate for academic versus non-academic hospitals,

and which correlates with hospital size and volume. While we found significant

differences between smoking groups (Table 1) with prior smokers most likely to be operated on by an attending and a resident and never smokers were most likely to be operated on by an attending alone (Table 1), level of supervision in the OR was not found to be related to any of the outcomes of interest (data not shown). Nevertheless, level of supervision in the OR was included into the propensity score (Table 3), and the final model containing all unbalanced covariates (Table 4).

The NSQIP database is limited in that it provides only the last set of lab results prior to surgery, within 90 days of surgery, and no data on certain patient characteristics at baseline such as pain score, neurological deficit, and depression, which prior studies suggest influence long term outcomes3-22. The surgical population captured by NSQIP

may not be wholly representative of the US population of patients who undergo spine

surgery, as institutional data reporting is voluntary. However, the gender and

82 race distributions in the NSQIP database are representative of the US population and data is collected prospectively from a number and variety of institutions, which provides a large and diverse sample size23. Finally, all NSQIP data are collected in a standardized manner, with annual quality checks23, and data reporting achieves >95% 30 day outcome follow-up rate across consecutive cycle, with high accuracy and reproducibility23,30.

In summary, this is the first, large, multi-institutional analysis of prospectively- collected data to assess the relationship between preoperative cigarette smoking and smoking duration as determined by number of pack-years, alone, and in combination with multiple pre- and intraoperative factors, on 30-day outcomes in patients undergoing elective spine surgery. While current smokers with more then 60 pack-years were more likely to expire within 30 days of surgery compared to never smokers, our analysis of a large, prospective, multi-institutional database suggests that a current or prior history of smoking does not predispose individuals undergoing elective spine surgery to increased risk for operative or short-term postoperative morbidity or mortality. Additional studies in this patient population, both of cessation strategies as well as other long-term outcomes, are warranted.

83 Chapter 4 References

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3. Vogt MT, Hanscom B, Lauerman WC, et al. Influence of smoking on the health status of spinal patients: the National Spine Network database. Spine 2002;27:313-9.

4. Brown CW, Orme TJ, Richardson HD. The rate of pseudarthrosis (surgical nonunion) in patients who are smokers and patients who are nonsmokers: a comparison study. Spine 1985;11:942-3.

5. Thalgott J, LaRocca H, Gardner V, et al. Reconstruction of failed lumbar surgery with narrow AO DCP plates for spinal arthrodesis. Spine 1991;16:S170-5.

6. Carpenter CT, Dietz JW, Leung KY, et al. Repair of a pseudarthrosis of the lumbar spine. A functional outcome study. J Bone Joint Surg Am 1996;78:712-20.

7. Thalgott JS, Sasso RC, Cotler HB, et al. Adult spondylolisthesis treated with posterolateral lumbar fusion and pedicular instrumentation with AO DC plates. J Spinal Disord 1997;10:204-8.

8. Glassman SD, Rose SM, Dimar JR, et al. The effect of postoperative nonsteroidal anti- inflammatory drug administration on spinal fusion. Spine 1998;23:834–8.

9. Mooney V, McDermott KL, Song J. Effects of smoking and maturation on long-term maintenance of lumbar spinal fusion success. J Spinal Disord 1999;12:380-5.

10. Glassman SD, Anagnost SC, Parker A, et al. The effect of cigarette smoking and smoking cessation on spinal fusion. Spine 2000;25:2608-15.

11. Peolsson A, Vavruch L, Oberg B. Predictive factors for arm pain, neck pain, neck specific disability and health after anterior cervical decompression and fusion. Acta Neurochir (Wien) 2006;148:167-73; discussion 173.

12. Luca A, Mannion AF, Grob D. Should smoking habit dictate the fusion technique? Eur Spine J 2011;20(4):629-34.

13. Lehto M, Honkanen P. Factors influencing the outcome of operative treatment for lumbar spinal stenosis. Acta Neurochirurgica 1995;137:25-28.

84 14. Amundsen T, Weber H, Nordal HJ, et al. Lumbar spinal stenosis: conservative or surgical management?: A prospective 10-year study. Spine 2000;25:1424-35.

15. McGregor AH, Hughes SP. The evaluation of the surgical management of nerve root compression in patients with low back pain: Part 2: patient expectations and satisfaction. Spine 2002;27:1471-6; discussion 1476-7.

16. Spratt KF, Keller TS, Szpalski M, et al. A predictive model for outcome after conservative decompression surgery for lumbar spinal stenosis. Eur Spine J 2004;13:14- 21.

17. Sinikallio S, Aalto T, Airaksinen O, et al. Lumbar spinal stenosis patients are satisfied with short-term results of surgery - younger age, symptom severity, disability and depression decrease satisfaction. Disabil Rehabil 2007;29:537-44.

18. Jansson KA, Németh G, Granath F, et al. Health-related quality of life (EQ-5D) before and one year after surgery for lumbar spinal stenosis. J Bone Joint Surg Br 2009;91:210-6.

19. Sandén B, Försth P, Michaëlsson K. Smokers show less improvement than nonsmokers two years after surgery for lumbar spinal stenosis: a study of 4555 patients from the Swedish spine register. Spine 2011;36:1059-64.

20. Schade V, Semmer N, Main CJ, et al. The impact of clinical, morphological, psychosocial and work-related factors on the outcome of lumbar discectomy. Pain 1999;80:239-49.

21. Jansson KA, Németh G, Granath F, et al. Health-related quality of life in patients before and after surgery for a herniated lumbar disc. J Bone Joint Surg Br 2005;87:959- 64.

22. Dewing CB, Provencher MT, Riffenburgh RH, et al. The outcomes of lumbar microdiscectomy in a young, active population: correlation by herniation type and level. Spine 2008;33:33-8.

23. Khuri S, Henderson W, Daley J, et al. Principal Site Investigators of the Patient Safety in Surgery Study: The Patient Safety In Surgery Study: Background, Study Design, and Patient Populations. J Am Coll Surg 2007;204:1089-102.

24. Hawn MT, Houston TK, Campagna EJ, et al. The attribuTable risk of smoking on surgical complications. Ann Surg 2011;254:914-20.

25. American College of Surgeons National Surgical Quality Improvement Project. ACS NSQIP Data User Guide: October 2010. American College of Surgeons, 2010.

26. Rosenbaum PR, Rubin D. The central role of the propensity score in observational

85 studies for causal effects. Biometrika 1983; 70:41–55.

27. Bergstralh E, Kosanke J. Computerized matching of cases to controls. Technical Report Serial No. 56. Minnesota: Mayo Clinic Section of Biostatistics, 1995.

28. Turan A, Mascha EJ, Roberman D, et al. Smoking and perioperative outcomes. Anesthesiology 2011;114:837–846.

29. U.S. Department of Health and Human Services. The Health Consequences of Smoking: A Report of the Surgeon General. Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2004. Available at: http://www.ncbi.nlm.nih.gov/books/NBK44695/. Accessed Nov 5, 2012.

30. Glance L, Dick A, Mukamel D, et al. Association between intraoperative blood transfusion and mortality and morbidity in patients undergoing noncardiac surgery. Anesthesiology 2011;114:283-92.

86 Chapter 4 Tables

Table 1: Patient demographics, comorbidities, preoperative lab values, and intraoperative factors by smoking status (N = 14,500)

Current Prior Never P (N = 3,914) (N = 2,057) (N = 8,529) P‡ Value 27.0% 14.2% 58.8% δ Age, y, mean ± SD 49 ± 12 62 ± 13 57 ± 15 <0.001 <0.001 Female gender 45.2% 39.9% 49.5% <0.001 <0.001 African American 9.2% 6.0% 7.6% <0.01 0.01 Admitted from home 98.2% 98.4% 97.9% 0.26 0.18 >2 drinks per day 6.7% 4.9% 2.3% <0.001 <0.001 Partially or fully dependent functional 5.2% 7.3% 6.5% <0.01 0.17 status ASA classification 0.57 <0.001 1 + 2 60.4% 48.3% 59.3% 3 + 4 39.6% 51.5% 40.6% BMI, kg/m2, mean ± 28.8 ± 6.5 30.0 ± 6.1 30.0 ± 6.6 <0.001 0.52 SD Pulmonary 7.2% 7.1% 1.7% <0.001 <0.001 comorbidities Cardiovascular 7.6% 14.9% 8.7% 0.04 <0.001 comorbidities Hypertension requiring 37.9% 58.6% 50.2% <0.001 <0.001 meds Dyspnea 8.1% 8.8% 5.1% <0.001 <0.001 CNS comorbidities 10.4% 12.5% 11.6% 0.04 0.26 Diabetes mellitus 10.7% 17.8% 15.1% <0.01 <0.01 Disseminated cancer 0.7% 1.8% 1.0% 0.05 <0.01 Weight loss >10% in 6 0.8% 0.5% 0.6% 0.19 0.59 months prior to surgery Steroid use for chronic 3.2% 4.5% 3.8% 0.12 0.13 condition Preoperative chemo- 0.4% 0.7% 0.4% 0.60 0.07 and/or radiotherapy Bleeding disorder 1.3% 2.3% 1.6% 0.16 0.03 Prior operation within 1.4% 1.4% 1.5% 0.80 0.79 30 days Abnormal albumin 4.4% 5.1% 5.0% 0.39 <0.01 Abnormal alkaline 1.4% 1.9% 1.4% 0.87 0.13 phosphatase Abnormal BUN 15.9% 23.8% 20.5% <0.001 <0.001

87 Abnormal creatinine 4.4% 9.8% 7.6% <0.001 <0.001 Abnormal hematocrit 43.1% 43.1% 42.6% 0.89 0.34 Abnormal platelet 4.1% 6.4% 4.8% 0.29 <0.01 count Abnormal SGOT 5.8% 5.7% 5.4% 0.29 0.01 Abnormal sodium 6.6% 6.3% 6.3% <0.01 0.90 Abnormal total 1.3% 1.2% 1.6% 0.45 0.03 bilirubin Abnormal white blood 15.8% 13.4% 12.7% <0.001 0.62 cell count Level of residency supervision in the OR <0.01 <0.001 Attending alone 68.8% 57.1% 70.2% Attending and resident 30.9% 42.4% 29.2% Wound class 0.58 <0.001 Clean 97.6% 96.6% 97.8% Clean-contaminated 1.0% 2.0% 1.0% Contaminated of 1.4% 1.4% 1.2% infected Intra/Postoperative <0.001 <0.001 3.8% 7.8% 5.8% Transfusions ¶ ASA = American Association of Anesthesiologists; BMI = body mass index; BUN = blood urea nitrogen; INR = international normalized ratio; SGOT = serum glutamic oxaloacetic transaminase

* DNR status, presence of ascites, presence of esophageal varices, and renal comorbidities were each present in less than 1% of the entire cohort.

† P values that are significant (<0.05) are bolded

‡ P comparing current smokers to never smokers

δ P comparing previous smokers to never smokers

¶ Intra or postoperative

88 Table 2: 30-day post-operative outcomes, stratified by smoking status (N = 14,500)

Current Prior Never (N = 3,914) (N = 2,057) (N = 8,529) P† P‡ 27.0% 14.2% 58.8% Total length of hospital stay (days); 2 (1-3) 2 (1-4) 2 (1-4) <0.001 <0.001 median (IQR) Prolonged length of hospital stay (>4 22.2% 30.2% 26.9% <0.001 <0.01 days) Minor 2.8% 3.7% 3.3% 0.17 0.31 complications Major 5.4% 7.0% 5.4% 0.85 <0.01 complications Return to the OR 3.5% 3.6% 3.1% 0.30 0.24 30 day mortality 0.4% 0.3% 0.4% 0.68 0.55 IQR = Interquartile Range (25-75%); OR = operating room

* P values that are significant (<0.05) are bolded

† Unstratified P value obtained from comparison of current smokers against never smokers at baseline.

‡ Unstratified P value obtained from comparison of prior smokers against never smokers at baseline.

89 Table 3: Pre- and intraoperative factors by smoking status after stratification on propensity score* and age

Current Never Prior Never (N = (N = P‡ (N = (N = P δ 3,760) 3,760) 2,045) 2,045) Age, y, mean ± SD 49 ± 12 49 ± 13 0.29 62 ± 13 61 ± 13 0.63 Female gender 45.9% 42.3% <0.01 40.0% 41.9% 0.46 African American 9.2% 8.0% 0.06 6.0% 7.5% 0.05 Admitted from 98.4% 98.4% 0.93 97.8% 98.4% 0.11 home >2 drinks per day 5.7% 4.0% <0.001 4.8% 5.3% 0.47 Partially or fully dependent 4.9% 4.8% 0.83 7.2% 7.4% 0.81 functional status ASA classification 1 + 2 62.0% 64.8% 48.6% 48.0% 0.03 0.83 3 + 4 40.0% 35.1% 51.3% 52.0% BMI, kg/m2, mean 28.9 ± 29.9 ± 30.0 ± 29.5 ± <0.001 <0.01 ± SD 6.5 6.8 6.0 6.3 Pulmonary 4.2% 3.2% 0.02 6.6% 6.0% 0.48 comorbidities Cardiovascular 7.0% 7.6% 0.33 14.8% 15.3% 0.69 comorbidities Hypertension 37.3% 37.6% 0.76 58.5% 56.1% 0.13 requiring meds Dyspnea 6.7% 5.8% 0.11 8.7% 9.0% 0.70 CNS comorbidities 10.3% 9.5% 0.28 12.5% 12.9% 0.71 Diabetes mellitus 10.7% 11.4% 0.36 17.7% 15.8% 0.11 Disseminated 0.6% 1.0% 0.07 1.8% 1.3% 0.20 cancer Weight loss >10% in 6 months prior to 0.7% 0.6% 0.47 0.5% 0.6% 0.53 surgery Steroid use for 3.0% 3.6% 0.14 4.5% 4.1% 0.59 chronic condition Preoperative chemo- and/or 0.3% 0.4% 0.69 0.7% 0.6% 0.56 radiotherapy Bleeding disorder 1.2% 1.5% 0.27 2.3% 2.1% 0.59 Prior operation 1.4% 1.4% 1.0 1.4% 1.5% 0.90 within 30 days Abnormal albumin 4.4% 4.4% 0.97 5.1% 5.0% 0.98 Abnormal alkaline 1.5% 0.9% 0.08 1.9% 1.4% 0.28

90 phosphatase Abnormal BUN 15.9% 15.9% <0.01 23.8% 23.3% 0.42 Abnormal 4.3% 5.1% 0.27 9.8% 8.9% 0.59 creatinine Abnormal 42.5% 41.5% 0.09 43.1% 45.4% 0.34 hematocrit Abnormal platelet 3.9% 4.5% 0.11 6.3% 5.3% 0.19 count Abnormal SGOT 5.7% 5.6% 0.99 5.7% 5.8% 0.97 Abnormal sodium 6.4% 4.7% <0.01 6.3% 7.0% 0.49 Abnormal total 1.3% 1.2% 0.87 1.2% 1.2% 0.99 bilirubin Abnormal white 15.5% 14.6% 0.16 13.3% 14.7% 0.29 blood cell count Level of residency supervision in the OR Attending alone 69.4% 63.6% <0.001 57.3% 62.2% 0.01 Attending and 30.3% 36.1% 42.3% 37.6% resident Wound class Clean 97.7% 97.4% 0.41 96.6% 97.3% 0.43 Clean-contaminated 1.0% 1.3% 2.1% 1.6% Contaminated of 1.4% 1.3% 1.4% 1.2% infected Intra/Postopertative 0.22 0.34 3.8% 4.3% 7.9% 7.1% Transfusions δ ASA = American Association of Anesthesiologists; BMI = body mass index; BUN = blood urea nitrogen; INR = international normalized ratio; SGOT = serum glutamic oxaloacetic transaminase

* Propensity score consists of all factors significant (p<0.05) in Table 1

† P values that are significant (<0.05) are bolded

‡ P comparing current smokers to never smokers after stratification on propensity score and age

δ P comparing previous smokers to never smokers after stratification on propensity score and age

91 Table 4: Smoking status comparisons for adverse outcomes using different analysis methods

Current vs. Never Smoker Analyses Prior vs. Never Smoker Analyses Odds Ratios (95% CI) Odds Ratios (95% CI) Propensity Propensity- -Matched Matched Adverse Propensity Propensity Sample Logistic Sample Logistic Outcomes -Matched -Matched plus Regressi plus Regressi Sample Sample unbalance on† unbalanced on† plus Age‡ plus Age‡ d covariates covariates δ ¶ Prolonged 0.8 1.0 0.9 1.2 1.0 0.9 LOS (0.7-0.8) (0.9-1.1) (0.8-1.0) (1.1-1.3) (0.9-1.1) (0.8-1.1) (>4 days) Minor 0.9 1.0 1.0 1.2 0.8 0.8 complicati (0.7-1.1) (0.8-1.3) (0.7-1.3) (0.9-1.5) (0.6-1.2) (0.6-1.1) ons Major 1.0 1.0 0.9 1.3 1.0 1.0 complicati (0.9-1.2) (0.8-1.2) (0.8-1.1) (1.1-1.6) (0.8-1.3) (0.8-1.3) ons 30 day 1.1 1.0 0.9 1.2 1.0 0.9 return to (0.9-1.4) (0.8-1.2) (0.7-1.2) (0.9-1.5) (0.7-1.3) (0.7-1.3) the OR 30 day 0.9 1.4 1.2 0.8 0.6 0.6 mortality (0.5-1.6) (0.6-3.2) (0.5-2.9) (0.3-1.8) (0.2-1.5) (0.2-1.5) CI = Confidence Interval; OR = operating room

* Odds ratios that are significant are bolded

† At baseline prior to stratification on propensity scores

‡ Propensity score consists of all factors significant in Table 1

δ Unbalanced covariates after matching on propensity score from Table 3, including: gender, ASA classification, alcohol consumption, BMI, pulmonary comorbidities, abnormal BUN, abnormal sodium, and level of residency supervision in the OR

¶ Unbalanced covariates after matching on propensity score from Table 3, including: race, BMI, and level of residency supervision in the OR

92 Chapter 5: Pre-operative Anemia and

Peri-operative Outcomes in Patients who

Undergo Elective Spine Surgery

Andreea Seicean MPH1, Sinziana Seicean MD MPH PhD2,3, Nima Alan4, Nicholas K.

Schiltz1, Benjamin P. Rosenbaum MD5, Paul K. Jones PhD1, Michael W. Kattan

PhD6, Duncan Neuhauser PhD1, Robert J. Weil MD5

1Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, Ohio; 2Departments of Pulmonary, Critical Care and Sleep Medicine, University Hospitals, Cleveland, Ohio; 3Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio; 4Case Western Reserve University School of Medicine, Cleveland, Ohio; 5The Rose Ella Burkhardt Brain Tumor & Neuro-Oncology Center, and Department of Neurosurgery, the Neurological Institute, Cleveland Clinic, Cleveland, OH; 6Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH.

This work has been accepted for publication, in full, in the Spine. It appears

in this dissertation with the kind permission from Lippincott Williams &

Wilkins publishing.

93 Abstract

Study Design: Analysis of the prospectively-collected American College of Surgeons

National Surgical Quality Improvement (NSQIP) database.

Objective: We wished to assess whether pre-operative anemia predicted adverse, early, peri-operative outcomes in patients undergoing elective spine surgery.

Summary of Background Data: Prior studies have assessed the association of anemia on outcomes in various non-cardiac surgical procedures. The association between preoperative anemia and 30-day outcomes for spine surgery is unknown.

Methods: 24,473 adults, classified as having severe (N=88), moderate (N=314), mild (N

= 5,477) and no anemia. Using propensity scores, patients with severe, mild, and moderate anemia were matched to patients with no anemia. Logistic regression was used to predict adverse post-operative outcomes. Sensitivity analyses were conducted limiting the study sample to: patients who did not receive intra- or post-operative transfusion and to patients with and without pre-operative cardiovascular comorbidities.

Results: Patients with all levels of anemia had significantly higher risk for nearly all adverse outcomes compared with non-anemic patients in unadjusted and propensity- matched models. Patients with moderate and mild anemia were more likely to have prolonged length of hospitalization, experience one or more complications, and expire within 30 days of surgery compared to non-anemic patients. The association between anemia and adverse outcomes was found independently of intra- and post-operative transfusions, and was not more pronounced in patients with pre-operative cardiovascular comorbidities.

94 Conclusions: All levels of anemia were significantly associated with prolonged length of hospitalization and poorer operative or 30-day outcomes in patients undergoing elective spine surgery. Our findings, using a large multi-institutional sample of prospectively- collected data, suggests that anemia should be regarded as an independent risk factor for peri-operative and post-operative complications that deserves attention prior to elective spine surgery.

95 Introduction

Anemia is associated with increased need for blood transfusion and has been

suggested as an independent risk factor for post-operative complications in patients undergoing various non-cardiac surgical procedures1-6. Spine surgery is not infrequently

associated with blood loss, which may range from 100 to 4,700 ml, depending on the

procedure7. A single institution study that assessed factors associated with spine fusion

failure found anemia to be a risk8. The effect of anemia on global short-term outcomes of

spine surgery, including mortality, has not been defined. With >3 million elective spine

surgery procedures performed in the United States between 2006 and 20109 (see

Supplemental Digital Content (SDC)), it is important to assess the effect of anemia on

postoperative complications and 30-day mortality.

We investigated the association between pre-operative anemia, alone and in

combination with several pre- and intra-operative factors, on 30-day outcomes in patients

undergoing elective spine surgery.

Materials and Methods

Data Source: We evaluated patients who underwent elective spine surgery included,

prospectively, in the American College of Surgeon (ACS) National Surgical Quality

Improvement Program (NSQIP) database between 2006 and 2011. Detailed description of the ACS-NSQIP database, including design, sampling strategy, and variable definitions can be found elsewhere10,11. The study was approved by the Cleveland Clinic

Institutional Review Board.

96 Subjects: We used the Current Procedure Terminology (CPT) codes to identify 27,719

adult patients, 18 years of age and older, who underwent spine surgery between 2006 and

2011. We excluded 2,407 patients who had missing pre-operative hematocrit values, and

88 patients who underwent pre-operative transfusion. We excluded 810 patients that had

an emergency procedure, as defined in the NSQIP database, because these patients were

presumably treated irrespective of their anemia status. Our final study sample consisted

of 24,473 patients with a defined pre-operative hematocrit, who underwent elective spine

surgery. Of these 24,473 patients, about 40% (N=9,762) had a fusion as either the

primary procedure or an additional procedure.

Anemia: Using pre-operative hematocrit levels, anemia was categorized according to levels established in other several other studies1,12 as: severe (hematocrit <25%),

moderate (26% to 29%), mild (30% to 37%), and no anemia (> 38%).

Patient History Covariates: All available pre- and intra-operative factors, previously

identified as having an effect on post-operative outcomes1-6, were analyzed (Table 1).

Please see the SDC for a detailed description of each covariate.

Outcomes of interest: Post-operative complications, defined as occurring within 30 days

of surgery, were assessed for each anemia group (severe, moderate, mild, and none).

Prolonged length of hospital stay (LOS) was defined as LOS >75% of the patients in the

sample, which was 9 days. Minor complications consisted of one or more of: superficial

surgical site infection, urinary tract infection, deep venous thrombosis or

thrombophlebitis. Major complications were one or more of: deep incision surgical site

infection, organ or space surgical site infection, wound disruption, pneumonia, unplanned

intubation, pulmonary embolism, >48 hour postoperative ventilator-assisted respiration,

97 progressive renal insufficiency, acute renal failure, cardiovascular accident with

neurological deficit, coma of >24 hours, peripheral nerve injury, cardiac arrest requiring

CPR, myocardial infarction, graft, prosthesis or flap failure, sepsis, septic shock, and/or

30-day return to the OR. Any complication was defined as having > 1 minor or major

complications. Return to the OR, defined as any unplanned return to the OR for a

surgical procedure, and mortality were also assessed.

Statistical Analyses: Pre- and intra-operative and 30-day outcomes were compared

between each category of anemia (severe, moderate, mild) and no anemia using Pearson's

chi-square tests for categorical variables; ANOVA was used for continuous variables.

Propensity scores, including all variables from Table 1, were generated to obtain an

approximately unbiased measure of the association between anemia categories and

adverse outcomes13. A 1:1 greedy matching technique14 was used first to separately

match the patients in each anemia group (severe, moderate, and mild) with a unique

patient with no anemia on propensity score. Restrictions were set on the matching

criteria to allow for increased accuracy in matching. Covariates were compared between

anemia groups in the matched sample. Logistic regression analysis was used to test

whether different levels of anemia were independently associated with adverse outcomes.

Covariates that remained unbalanced after matching on propensity scores were included

in the final models. Sensitivity analyses excluding patients that underwent intra- or postoperative transfusion, and repeating all analyses separately for patients with and without preoperative cardiovascular comorbidities. In addition, all analyses were also repeated using pre-operative hematocrit levels as the predictor variables. A p-value of

<0.05 was significant. SAS (Version 9.2, SAS Institute) was used.

98 Results

Of the 24,473 adult patients who underwent elective spine surgery, 88 (0.4%) had severe anemia, 314 (1.3%) had moderate anemia, and 5,477 (22.4%) had mild anemia.

Patient demographics, comorbidities, and lab values are summarized in Table 1. Patients with all levels of anemia were generally more likely to be older, female, racial minority, have partially or fully functional dependent status, higher ASA classification, suffer from comorbidities, and have abnormal lab values.

The 30-day outcomes for the entire group were: 7.5% (n=1,845) of all patients experienced one or more complications, 3.1% (n=749) returned to the OR within 30 days, and an overall 0.4% (n=101) 30-day mortality. The mean length of hospital stay was 3

days overall, patients without anemia having the shortest length of hospital stay (Table

2). While length of hospitalization increased with anemia level, patients with severe

anemia actually had slightly shorter hospitalizations than patients with moderate anemia.

While patients with any degree of anemia were more likely then patients without anemia

to have each of the adverse outcomes of interest, patients with moderate anemia had the

higher frequency of adverse events, followed by those with severe anemia, and lastly by

those with mild anemia.

We successfully matched 99% of patients in each anemia class with control

patients with no anemia (Table 3). After matching, gender, admission status, prior

operation within 30 days, and abnormal albumin remained significantly different for both

moderate and mild anemia patients. A number of additional covariates remained

significant for patients with moderate and mild anemia.

99 The relationship between anemia level and each outcome of interest was

determined using logistic regression at baseline, after matching by propensity scores, and

further including all unbalanced covariates (Table 4). In the unmatched analyses, patients with any level of anemia had significantly higher odds for each of the outcomes of

interest compared with patients with normal hematocrit levels. Patients with moderate

anemia had the highest odds for adverse outcomes.

After stratification on propensity scores, patients with anemia continued to have

longer lengths of hospitalization than their non-anemic counterparts (SDC Table 1).

Patients with mild and moderate anemia also were more likely to experience

complications and 30-day mortality compared with patients without anemia (Table 4).

Patients with moderate anemia were also approximately twice as likely to experience both minor complications and major complications compared with patients without anemia. After adding the unbalanced covariate to the propensity-matched models, patients with mild and moderate anemia remained significantly more likely to have prolonged LOS and the latter also continued to have higher likelihood for any complications. Removing patients having intra- or postoperative transfusion from the analyses had little effect on the odds for each adverse event for patients with mild anemia, but interesting effects for the moderate anemia group. In the propensity-matched models, removing patients with transfusion caused the odds ratios to increase for moderate anemia patients having prolonged LOS, any complication, and 30-day mortality and also made 30-day return to the OR significant. In sensitivity analyses, the effect of anemia was no worse in patients with or without preoperative cardiovascular comorbidities (data not shown).

100 Discussion

All levels of anemia were associated with prolonged LOS and poorer

postoperative or 30-day outcomes in patients undergoing elective spine surgery. Patients

with moderate anemia had the greatest risk for adverse outcomes. These findings

persisted after removal of patients that underwent intra and/or postoperative transfusions,

suggesting that anemia is an independent risk factor for adverse outcomes in our patient

sample.

Interpretations of Results: While our study demonstrates that patients with anemia have

higher odds for adverse events compared with patients without anemia, it is interesting

that patients with moderate anemia consistently have the highest odds ratio for each

adverse outcome. In the unadjusted models, patients with severe anemia have lower odds

for each adverse event compared with patients with moderate anemia, but higher odds

compared with patients with mild anemia. However, after propensity matching, patients

with severe anemia do not reach significance for any of the outcomes of interest. We

suspect that our findings are related to three separate reasons: sample size, physiological

adjustment, and surgeon technique. The sample size for patients with severe anemia is

small (N=88) and with relatively few events, making the effect of severe anemia more

difficult to detect in the propensity-matched sample. However, this does not account for the unadjusted values that show that patients with severe anemia have lower odds for each adverse event then patients with moderate anemia. It has been proposed that patients

living with a chronic low level of oxygenation are more accustomed to being at that

level15. Thus while our patients with severe anemia may be accustomed to functioning

with low oxygen levels, patients that had mild or moderate preoperative anemia and lost

101 blood during the surgery causing their hematocrit to drop to the levels of patients with

severe anemia at baseline had a much more difficult time adjusting to the change in

oxygen. It is also possible that surgeons operating on patients with severe anemia were

especially attentive to minimizing blood loss during the surgery.

Interpretations in the Context of the Literature: Although the body of literature

examining the effects of anemia on surgical outcomes in different surgical

subpopulations and specialties is abundant, this is the first, large analysis of

prospectively-collected and validated data of the role of preoperative anemia on short

term post-operative outcomes in patients undergoing elective spine surgery. Prior studies

of the association between pre-operative anemia and surgical outcomes in non-cardiac surgical patients used samples that contained no1-3 or very few spine surgery patients4-6,

defined as <10% of the sample. Although a few studies have assessed the effectiveness

of different transfusion techniques in patients undergoing different spine surgical

procedures16-20, we are only aware of one study8 that identified anemia as a risk factor for

adverse outcomes in spine surgery. This single institution study, conducted by Snider et

al8, identified anemia as a risk factor for fusion failure.

While it is difficult to compare findings head-to-head with other studies, due to

differences in the way that anemia was assessed and the outcomes collected, our results

are consistent with prior studies in other non-cardiac surgery patients1-6 in finding a

relationship between pre-operative anemia and adverse outcomes. Three prior studies1,3,5

each reported that anemia is associated with increased LOS in different groups of non-

cardiac surgical patients. Of these, the two studies distinguishing between levels of

anemia1,5 each found an inverse association between hematocrit and LOS. We found that

102 patients with severe anemia had slightly shorter LOS than patients with moderate anemia,

and that patients with moderate anemia had the greatest risk for prolonged LOS. Our

finding that moderate patients have the higher risk for complications is supported by two

studies that measure complications at different levels of anemia1,5. In fact, our propensity

matched odd ratios for each anemia category are nearly identical to the 2011 Leichtle et

al.1 study of colon and rectal surgery patients; in both our study and the Leichtle study1

patients with moderate anemia had the highest odd ratios for adverse events. Our

adjusted mortality odds ratio, according to each level of anemia, is about two to three

times higher than that presented in the sole study assessing mortality risk according to

hematocrit levels, the 2007 Wu et al paper4 on older patients undergoing any sort of non-

cardiac surgical procedure. Our finding is consistent with the high potential for blood

loss that spine surgery holds compared to other surgical procedures7.

Several studies have identified pre-operative anemia as a strong predictor for subsequent transfusions5,21. Transfusion has been associated with increased morbidity

and mortality in and of itself in various patient populations5,22. Our removal of patients that underwent intra- or postoperative transfusion allowed us to isolate the effect of

anemia, from those mediated by transfusion. Two studies in mixed surgical cohorts4,6 found increased risk for adverse events in patients with preoperative cardiovascular comorbidities. Our finding that anemia is not more predictive of adverse outcomes in patients who have pre-operative cardiovascular comorbidities, compared to patients without, is consistent with Leichtle et al.1 study of patients who underwent colorectal

surgery.

103 Clinical Implications: Our data show that pre-operative anemia is independently associated with prolonged length of hospitalization, and significantly higher likelihood for 30-day peri-operative morbidity and mortality in patients undergoing elective spine surgery. Anemia was no more predictive of adverse events for patients with preoperative cardiovascular risk factors, suggesting that anemia is an independent risk factor for postoperative complications that may require attention and correction prior to elective spine surgery. Our recommendation is consistent with the Network for Advancement of

Transfusion Alternatives guidelines made for elective orthopedic patients23. While it is

difficult to assess the financial and other costs associated with increased risk for

complications and mortality, length of hospital stay alone justifies delaying elective spine

surgery in anemic patients, when it is possible, until the anemia has been corrected. If

our study sample were representative of the approximately 600,000 patients undergoing

elective spine surgery every year in the United States9, then more than $700,000,000 is spent yearly for excess hospitalization (Table 5). While outpatient treatment to correct anemia may not be possible for all patients prior to surgery, improving hematocrit levels even in some patients can have an impact on both outcomes and cost of care.

Limitations: Our study has limitations. Because this is an observational study, we cannot establish causation nor rule out the possibility of residual confounding from unobserved variables. However, we did capture and control for all covariates used in the six prior studies that assessed the effect of anemia is various surgical populations1-6.

While no data is available in NSQIP concerning the amount of blood loss per se during surgery, we were able to match patients according to weather or not they underwent spine fusion and according to the total operation times, both of which are known to correspond

104 to amount of blood loss7. It was also not possible to separate intra- and postoperative transfusions from each other; while these variables were collected separately in the 2006 through 2009 datasets, starting in 2010 the ACS merged intra- and postoperative transfusions into once variable10. The NSQIP database contains only patients who

underwent surgery; therefore we would not capture any patient that did not undergo

surgery due to preexisting risk factors, including anemia. The surgical population

captured by NSQIP may not be wholly representative of the US population of patients

who undergo spine surgery, as institutional data reporting is voluntary. However, the

gender and race distributions in the NSQIP database are representative of the US

population and data is collected prospectively from a number and variety of institutions,

which provides a large and diverse sample size11. Finally, all NSQIP data are collected in a standardized manner, with annual quality checks11, and data reporting achieves >95%

30-day outcome follow-up rate across consecutive cycle, with high accuracy and reproducibility11,22.

Conclusion

This study is the first, large, multi-institutional analysis of prospectively-collected data to

analyze the relationship between levels of preoperative anemia, alone and in combination

with multiple pre- and intra-operative factors, on 30-day outcomes in patients undergoing

elective spine surgery. While patients with moderate anemia had the greatest risk for

adverse outcomes, all levels of anemia were associated with prolonged LOS and poorer

operative or 30-day outcomes in patients undergoing elective spine surgery. Our

findings, using a large multi-institutional sample of prospectively-collected data, suggests

105 that anemia is an independent risk factor for peri-operative and post-operative complications and deserves attention prior to elective spine surgery.

106 Chapter 5 References

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2. Beattie WS, Karkouti K, Wijeysundera DN, et al. Risk associated with preoperative anemia in noncardiac surgery: a single-center cohort study. Anesthesiology 2009;110:574-81.

3. Myers E, O'Grady P, Dolan AM. The influence of preclinical anaemia on outcome following total hip replacement. Arch Orthop Trauma Surg 2004;124:699-701.

4. Wu WC, Schifftner TL, Henderson WG, et al. Preoperative hematocrit levels and postoperative outcomes in older patients undergoing noncardiac surgery. JAMA 2007 13;297:2481-8.

5. Dunne JR, Malone D, Tracy JK, et al. Perioperative anemia: an independent risk factor for infection, mortality, and resource utilization in surgery. J Surg Res 2002;102:237-44.

6. Carson JL, Duff A, Poses RM, et al. Effect of anaemia and cardiovascular disease on surgical mortality and morbidity. Lancet 1996;348:1055-60.

7. Hu S. Blood loss in adult spinal surgery. European Spine Journal 2004;13:Suppl1:S3-S5.

8. Snider RK, Krumwiede NK, Snider LJ, et al. Factors affecting lumbar spinal fusion. J Spinal Disord 1999;12:107-14.

9. HCUP Nationwide Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). Agency for Healthcare Research and Quality, Rockville, MD. 2006-2010. Available at: www.hcup-us.ahrq.gov/nisoverview.jsp. Accessed Nov 2, 2012.

10. American College of Surgeons National Surgical Quality Improvement Project. User Guide for the 2011 Participant Use Data File. American College of Surgeons, October 2012.

11. Khuri S, Henderson W, Daley J, et al. Principal Site Investigators of the Patient Safety in Surgery Study: The Patient Safety In Surgery Study: Background, Study Design, and Patient Populations. J Am Coll Surg 2007;204:1089-102.

12. Shander A, Knight K, Thurer R, et al. Prevalence and outcomes of anemia in surgery: a systematic review of the literature. Am J Med 2004;116; Suppl 7A:58S-69S.

13. Rosenbaum PR, Rubin D. The central role of the propensity score in observational studies for causal effects. Biometrika 1983;70:41–55.

14. Bergstralh E, Kosanke J. Computerized matching of cases to controls. Technical Report

107 Serial No. 56. Minnesota: Mayo Clinic Section of Biostatistics, 1995.

15. Ostadal B, Kolar F. Cardiac adaptation to chronic high-altitude hypoxia: beneficial and adverse effects. Respir Physiol Neurobiol 2007;158:224-36.

16. Kennedy C, Leonard M, Devitt A, et al. Efficacy of preoperative autologous blood donation for elective posterior lumbar spinal surgery. Spine 2011;36:E1736-43.

17. Wass CT, Long TR, Faust RJ, et al. Changes in red blood cell transfusion practice during the past two decades: a retrospective analysis, with the Mayo database, of adult patients undergoing major spine surgery. Transfusion 2007;47:1022-7.

18. Shapiro GS, Boachie-Adjei O, Dhawlikar SH, et al. The use of Epoetin alfa in complex spine deformity surgery. Spine 2002;27:2067-71.

19. Copley LA, Richards BS, Safavi FZ, et al. Hemodilution as a method to reduce transfusion requirements in adolescent spine fusion surgery. Spine 1999;24:219-22; discussion 223-4.

20. Albert TJ, Desai D, McIntosh T, et al. Early versus late replacement of autotransfused blood in elective spinal surgery. A prospective randomized study. Spine 1993;18:1071-8.

21. Khanna MP, Hébert PC, Fergusson DA. Review of the clinical practice literature on patient characteristics associated with perioperative allogeneic red blood cell transfusion. Transfus Med Rev 2003;17:110-9.

22. Glance LG, Dick AW, Mukamel DB, et al. Association between intraoperative blood transfusion and mortality and morbidity in patients undergoing noncardiac surgery. Anesthesiology 2011;114:283-92.

23. Goodnough LT, Maniatis A, Earnshaw P, et al. Detection, evaluation, and management of preoperative anaemia in the elective orthopaedic surgical patient: NATA guidelines. Br J Anaesth 2011;106:13-22.

24. The International Federation of Health Plans. 2011 Comparative Price Report: Medical and Hospital Fees by Country. Available at: http://www.ifhp.com/documents/2011iFHPPriceReportGraphs_version3.pdf. Accessed January 10, 2013.

108 Chapter 5 Tables

Table 1: Patient demographics, comorbidities, preoperative lab values, and intraoperative factors by anemia status (N = 24,473)

Severe Moderate Mild No Anemia Anemia Anemia Anemia (N = (N = 88) (N = 314) (N = 5,477) 18,594) 0.4% 1.3% 22.4% 76.0% Age, years, mean ± SD 60 ± 15 63 ± 13 61 ± 15 55 ± 14 Female 55.7% 61.2% 70.5% 41.8% Caucasian 68.2% 67.8% 72.3% 78.5% Admitted from home 85.2% 78.0% 95.4% 98.6% Smoking status Current 22.7% 16.2% 18.0% 28.4% Previous 44.3% 48.1% 44.8% 38.9% Never 32.9% 35.7% 37.2% 32.7% >2 drinks per day 1.1% 3.2% 1.9% 3.0% Partially or fully dependent 20.4% 32.2% 9.6% 3.8% functional status ASA classification 1 + 2 34.1% 14.7% 43.5% 60.9% 3 + 4 65.9% 85.0% 56.3% 39.1% 2 27.7 ± 29.7 ± 6.3 BMI, kg/m , mean ± SD 28.9 ± 7.5 29.3 ± 7.0 6.9 Pulmonary comorbidities 6.8% 10.2% 5.4% 3.8% Cardiovascular comorbidities 8.0% 11.5% 9.0% 6.3% Hypertension requiring 56.8% 63.7% 59.6% 46.3% medication Dyspnea 9.1% 9.6% 8.4% 5.8% CNS comorbidities 12.5% 21.3% 10.2% 6.5% Renal comorbidities 6.8% 4.1% 1.3% 0.1% Diabetes mellitus 23.7% 28.3% 22.1% 13.0% Disseminated cancer 6.8% 13.7% 3.3% 0.6% Open wound 5.7% 10.8% 2.6% 0.6% Weight loss >10% in 6 months 1.1% 3.8% 1.3% 0.4% prior to surgery Steroid use for chronic condition 3.4% 8.9% 5.3% 3.5% Preoperative chemo and/or 2.3% 4.1% 1.1% 0.15% radiotherapy Preoperative sepsis 11.4% 15.0% 3.1% 1.4% Bleeding disorder 3.4% 9.2% 2.6% 1.4% Prior operation within 30 days 8.0% 15.0% 2.5% 0.4% Abnormal albumin 33.0% 38.2% 9.1% 3.6%

109 Abnormal alkaline phosphates 11.4% 12.1% 3.0% 1.0% Abnormal bilirubin 4.6% 3.5% 1.3% 1.3% Abnormal BUN 31.8% 43.0% 30.4% 18.4% Abnormal creatinine 17.1% 19.1% 11.6% 5.7% Abnormal INR 9.1% 13.4% 3.1% 1.2% Abnormal platelet count 21.6% 24.5% 7.6% 4.8% Abnormal SGOT 12.5% 14.0% 5.6% 5.4% Abnormal sodium 17.1% 23.2% 10.7% 4.9% Abnormal WBC count 22.7% 27.1% 16.7% 13.1% Fusion surgery 44.3% 39.5% 42.5% 39.1% Total operation time, minutes, 172 ± 183 ± 131 163 ± 108 150 ± 97 mean ± SD 101 Intra and postoperative 29.6% 36.0% 11.7% 3.8% transfusions ASA = American Association of Anesthesiologists; BMI = body mass index; BUN =

blood urea nitrogen; CNS = central nervous system; INR = international normalized

ratio; SD = standard deviation; SGOT = serum glutamic oxaloacetic transaminase; WBC

= white blood cell

*P values that are significant (<0.05) are bolded

110 Table 2: 30-day post-operative outcomes, stratified by anemia status (N = 24,473)

Severe Moderate Mild Anemia No Anemia Anemia Anemia (N = 5,477) (N = 18,594) (N = 88) (N = 314) 22.4% 76.0% 0.4% 1.3% Total length of hospital stay, days mean ± SD 10.8 ± 25.0 11.0 ± 13.1 4.8 ± 9.9 2.8 ± 8.1 median 4.0 8.0 3.0 2.0 Prolonged LOS 2,232 4,181 45 (51.1%) 253 (80.6%) (>9 days) (40.8%) (22.5%) Minor postoperative 8 (9.1%) 40 (12.8%) 249 (4.6%) 482 (2.6%) complications† Major postoperative 13 (14.8%) 73 (23.2%) 422 (7.7%) 829 (4.5%) complications‡ Any postoperative 16 (18.2%) 96 (30.6%) 583 (10.6%) 1,150 (6.2%) complication§ Return to the OR 4 (4.6%) 36 (11.5%) 202 (3.7%) 507 (2.7%) 30 day mortality 3 (3.4%) 17 (5.4%) 44 (0.8%) 37 (0.2%) SD = standard deviation; LOS = Length of Stay; OR = operating room *P values that are significant (<0.05) are bolded. †Having any one or more of the following complications within 30 days postoperatively: superficial surgical site infection, urinary tract infection, deep venous thrombosis (DVT) or thrombophlebitis. ‡Having any one or more of the following complications within 30 days postoperatively: deep incision surgical site infection, organ or space surgical site infection, wound disruption, pneumonia, unplanned intubation, pulmonary embolism, >48 hour postoperative ventilator-assisted respiration, progressive renal insufficiency, acute renal failure, cardiovascular accident with neurological deficit, coma of > 24 hours, peripheral nerve injury, cardiac arrest requiring CPR, myocardial infarction, graft, prosthesis or flap failure, sepsis, septic shock, and/or 30 day return to the operating room (OR). §Having any 1 or more minor or major complications

111 Tables 3: Pre- and intraoperative factors by anemia status after stratification on propensity score

Mild No Severe Moderate Anemia Anemia Anemia Anemia P (N = (N = (N = 87) (N = 311) 5,420) 5,420) Age, y, mean ± SD 60 ± 15 63 ± 14 61 ± 15 60 ± 14 0.10 Female 56.3% 61.4% 70.5% 73.1% 0.01 Caucasian 67.8% 67.5% 72.1% 73.2% 0.46 Admitted from home 85.1% 78.1% 95.5% 96.8% <0.001 Smoking status Current 23.0% 16.4% 18.2% 18.1% Previous 43.7% 48.6% 44.8% 45.2% 0.92 Never 33.3% 35.1% 37.0% 36.6% >2 drinks per day 1.2% 3.2% 1.9% 1.7% 0.63 Partially or fully dependent functional 20.7% 31.8% 9.4% 7.6% <0.01 status ASA classification 1 + 2 34.5% 14.8% 43.8% 44.6% 0.60 3 + 4 65.5% 84.9% 56.1% 55.3% 29.4 ± 29.5 ± BMI, kg/m2, mean ±SD 27.9 ± 6.9 29.0 ± 7.6 0.14 7.0 6.8 Pulmonary 6.9% 10.3% 5.4% 5.6% 0.74 comorbidities Cardiovascular 8.1% 11.6% 8.9% 8.0% 0.09 comorbidities Hypertension requiring 56.3% 63.7% 59.3% 57.7% 0.08 medication Dyspnea 9.2% 9.7% 8.4% 7.8% 0.27 CNS comorbidities 12.6% 21.5% 10.1% 9.2% 0.10 Renal comorbidities 6.9% 4.2% 1.3% 0.4% <0.001 Diabetes mellitus 24.1% 28.6% 22.2% 20.7% 0.06 Disseminated cancer 6.9% 13.8% 3.3% 1.7% <0.001 Open wound 5.8% 10.9% 2.6% 1.3% <0.001 Weight loss >10% in 6 1.2% 3.9% 1.3% 0.8% 0.01 months prior to surgery Steroid use for chronic 3.5% 9.0% 5.3% 4.9% 0.27 condition Preoperative chemo 2.3% 4.2% 1.1% 0.4% <0.001 and/or radiotherapy Preoperative sepsis 11.5% 14.8% 3.1% 2.5% 0.08 Bleeding disorder 3.5% 9.0% 2.6% 2.2% 0.19

112 Prior operation within 8.1% 15.1% 2.5% 1.2% <0.001 30 days Abnormal albumin 33.3% 38.3% 9.1% 6.6% <0.001 Abnormal alkaline 11.5% 12.2% 3.0% 2.2% <0.01 phosphates Abnormal bilirubin 4.6% 3.5% 1.3% 0.8% 0.01 Abnormal BUN 31.0% 42.8% 30.1% 27.6% 0.02 Abnormal creatinine 17.2% 18.7% 11.5% 9.5% <0.01 Abnormal INR 9.2% 13.5% 3.1% 2.7% 0.22 Abnormal platelet count 21.8% 24.4% 7.5% 7.2% 0.72 Abnormal SGOT 12.6% 14.2% 5.7% 5.4% 0.11 Abnormal sodium 17.2% 23.5% 10.7% 9.0% <0.01 Abnormal WBC count 23.0% 27.0% 16.6% 15.8% 0.49 Fusion surgery 55.2% 39.6% 42.7% 43.5% 0.39 Total operation time, 163 ± 162 ± 172 ± 101 184 ± 131 0.94 minutes, mean ± SD 109 106 ASA = American Association of Anesthesiologists; BMI = body mass index; BUN = blood urea nitrogen; CNS = central nervous system; INR = international normalized ratio; SD = standard deviation; SGOT = serum glutamic oxaloacetic transaminase; WBC = white blood cell *Covariates with bolded p-values are considered unbalanced covariates and are included in Table 4 for each anemia group respectively.

113 Table 4: Anemia status comparisons for adverse outcomes using different analysis methods

Groups Compared Patients Severe to Outcomes Analyses Moderate to Mild to Included No No Anemia No Anemia Anemia Logistic 3.6 14.3 2.4 All patients Regression (2.4-5.5) (10.8-18.9) (2.2-2.5) No intra or Logistic post 2.1 11.3 2.1 Regression operative (1.3-3.6) (8.2-15.6) (2.0-2.3) transfusion Propensity- 1.1 3.1 1.4 Matched All patients (0.6-2.1) (2.2-4.4) (1.3-1.6) Prolonged Sample LOS (>9 No intra or Propensity- days) post 1.3 3.2 1.4 Matched operative (0.6-2.9) (2.1-4.9) (1.2-1.5) Sample transfusion Propensity- Matched Sample 1.1 2.5 1.3 All patients plus all (0.6-2.1)† (1.6-3.8)‡ (1.2-1.4)§ unbalanced covariates Logistic 3.8 5.5 1.8 All patients Regression (1.8-7.8) (3.9-7.7) (1.5-2.1) No intra or Logistic post 2.1 4.2 1.6 Regression operative (0.6-6.6) (2.6-6.9) (1.4-1.9) transfusion Propensity- 2.1 1.2 Matched All patients 2.1 (1.2-3.8) (0.6-7.3) (1.0-1.5) Minor Sample postoperative No intra or Propensity- complications post 1.0 1.2 Matched 1.3 (0.6-2.8) operative (0.2-5.2) (0.9-1.5) Sample transfusion Propensity- Matched Sample 2.1 1.9 1.1 All patients plus all (0.6-7.3)† (1.0-3.5)‡ (0.9-1.4)§ unbalanced covariates

114 Logistic 3.7 1.8 All patients 6.5 (4.9-8.5) Regression (2.0-6.7) (1.6-2.0) No intra or Logistic post 1.6 1.5 5.9 (4.1-8.4) Regression operative (0.6-4.5) (1.3-1.8) transfusion Propensity- 1.5 1.2 Matched All patients 1.9 (1.2-2.8) (0.6-3.8) (1.0-1.4) Major Sample postoperative No intra or Propensity- complications post 0.8 1.2 Matched 2.6 (1.4-4.8) operative (0.2-4.2) (1.0-1.4) Sample transfusion Propensity- Matched Sample 1.5 1.4 1.1 All patients plus all (0.6-3.8)† (0.9-2.3)‡ (0.9-1.2)§ unbalanced covariates Logistic 3.4 1.8 All patients 6.7 (5.2-8.6) Regression (2.0-5.8) (1.6-2.0) No intra or Logistic post 1.5 1.6 5.8 (4.2-8.0) Regression operative (0.6-3.6) (1.4-1.8) transfusion Propensity- 1.7 1.2 Matched All patients 2.3 (1.5-3.3) (0.7-4.1) (1.1-1.4) Sample Any No intra or complication Propensity- post 0.8 1.2 Matched 2.6 (1.5-4.4) operative (0.2-2.8) (1.1-1.4) Sample transfusion Propensity- Matched Sample 1.7 1.7 1.1 All patients plus all (0.7-4.1)† (1.1-2.7)‡ (1.0-1.3)§ unbalanced covariates Logistic 1.7 1.4 All patients 4.6 (3.2-6.6) Regression (0.6-4.6) (1.1-1.6) No intra or 30 day return Logistic post 2.0 1.2 4.7 (3.0-7.5) to the OR Regression operative (0.6-6.3) (1.0-1.4) transfusion Propensity- 0.8 1.0 All patients 1.5 (0.9-2.6) Matched (0.2-3.0) (0.8-1.3)

115 Sample No intra or Propensity- post 3.1 1.0 Matched 3.4 (1.4-8.2) operative (0.3-30.7) (0.8-1.2) Sample transfusion Propensity- Matched Sample 0.8 1.2 (0.6- 0.9 All patients plus all (0.2-3.0)† 2.1)‡ (0.8-1.2)§ unbalanced covariates Logistic 17.7 28.7 4.0 All patients Regression (5.3-59) (16.0-51.2) (2.6-6.3) No intra or Logistic post 10.1 35.7 3.6 Regression operative (1.4-75.3) (17.6-72.4) (2.1-6.0) transfusion Propensity- 3.1 4.4 2.5 Matched All patients (0.3-30.1) (1.5-13.3) (1.4-4.4) Sample 30 day No intra or mortality Propensity- post 5.8 2.6 Matched NA operative (1.3-26.4) (1.3-5.4) Sample transfusion Propensity- Matched Sample 3.1 3.4 1.7 All patients plus all (0.3-30.1)† (1.0-11.4)‡ (1.0-3.2)§ unbalanced covariates ASA = American Association of Anesthesiologists; BMI = body mass index; BUN = blood urea nitrogen; CNS = central nervous system; INR = international normalized ratio; LOS = length of hospital stay; OR = operating room; SD = standard deviation;

SGOT = serum glutamic oxaloacetic transaminase

*Odd ratios that are significant are bolded.

†There are no unbalanced covariates, same odd ratios as for the propensity-matched sample with all patients

116 ‡Unbalanced covariates included in the model are: age, gender, transfer status, ASA classification, hypertension, preoperative sepsis, prior operation within 30 days, and abnormal: albumin, INR, and platelet count

§Unbalanced covariates included in the model are: gender, transfer status, functional status, renal comorbidities, disseminated cancer, wound infection, weight loss, preoperative chemo and/or radiotherapy, prior operation within 30 days, and abnormal: albumin, alkaline phosphates, bilirubin, BUN, creatinine, and sodium

117 Table 5: Cost of excess length of hospitalization attributed to preoperative anemia in elective spine surgery patients in the USA per year, assuming our sample is representative of the 644,721 elective spine surgery cases done in the USA per year9 and that the average cost per day in the USA is $3,94924

Severe Moderate No Anemia Mild Anemia Anemia Anemia (N = (N = 5,477) (N = 88) (N = 314) 18,594) 22.4% 0.4% 1.3% 76.0% Number of elective spine surgery patients that fell into each 2,579 8,381 144,418 489,988 anemia category in the USA each year Difference in median 0 LOS between matched 1.0 4.0 1.0 groups, days* Excess hospitalization, attributed to anemia, 2,579 33,524 144,418 0 days Cost of excess hospitalization $10,184,471 $132,386,276 $570,306,682 0 attribuTable to anemia Total cost of excess hospitalization attribuTable to anemia in all patients $712,877,429 undergoing elective spine surgery in the USA per year LOS = length of hospital stay

*See Supplemental Digital Content (SDC) Table 1 for computation

118 Chapter 6: Conclusion

This dissertation is our first pass at using a large multi-center prospectively collected database to answer simple fundamental questions about the practice of neurosurgery. Each of the four paper that comprise this dissertation is intended to enhance clinician ability to make decisions and discuss treatment options with patients, improve patient outcomes, and limit waste in the healthcare system. I will provide some example of common scenarios in order to show how each of our studies is applicable to real world situations.

Scenario 1: Patient presents for neurosurgical evaluation. The patient has no family history of hemostasis abnormalities, no prior history of bleeding disorders, and is not taking any medications. Should the neurosurgeon order hemostasis lab testing prior to surgery?

According to Chapter 21, the answer is no. In our study, history was as predictive as laboratory testing for all outcomes, with higher sensitivity. Therefore, there is no reason to waste resources in ordering lab values in a patient with no clinical suspicion for abnormal hemostasis.

Scenario 2: Eighty-year old female patient presents to neurosurgery for evaluation of breast cancer metastasis to the brain. The patient already underwent breast surgery and recovered successfully. Her medical history is significant for hypertension, which is well controlled. Should the neurosurgeon perform craniotomy with resection of the metastatic brain tumor in this patient?

Prior studies have found prolonged survival and improved quality of life in patients with brain metastasis that underwent surgical resection of their tumor. The

119 ability to successfully pursue surgical resection depends on the location and size of the brain tumor in this patient. However, according to our findings in Chapter 32, the neurosurgeon should not be discouraged from operating on this relatively healthy patient just because of her advanced age.

Scenario 3: A 50-year old male presents with severe scoliosis requiring surgical correction via spine fusion. The patient is a current smoker with a 30 pack-year history.

Should the patient be worried about his risk for short-term complications after surgery due to his smoking status?

According to Chapter 4, no. While a number of prior studies have found that smoking is associated with worst healing rates and lower patient satisfaction with elective spine surgery procedures, we did not find any relationship between smoking status and short term postoperative outcomes in our study. Smoking detrimental to general health, and it is the responsibility of the clinical team caring for the patient to educate his on the risks of smoking and offer smoking cessation.

Scenario 4: A 45-year old female patient with no medical comorbidities is scheduled to undergo spine surgery for disk herniation. Two days prior to surgery,she is informed that her hematocrit is 32%, consistent with mild anemia. Should this finding impact the patient’s decision to go ahead with surgery?

Yes, according to Chapter 5 even mild anemia is a significant risk factor for adverse outcomes in elective spine surgery patients. In fact, patients with mild anemia have 2.5 times the risk for 30-day mortality compared to patients without anemia, keeping all other risk factors constant. Iron supplements are a cheap and often effective way of correcting anemia. The patient should delay her surgery and begin taking iron

120 supplements, then have her hematocrit rechecked prior to rescheduling the surgical

procedure.

The future of HSR in neurosurgery looks bright, as there appears to be increasing

interest in this area. The Neuropoint Alliance efforts to being multicenter data collection

of outcomes for common procedures, in the form of the N²QOD, are commendable3.

While information on the contents and details of the N²QOD is limited, this dataset holds

high promise in allowing for bigger and better HSR studies to be conducted using data

that contains covariates that are specific to the field of neurosurgery. Since data

collection has only just begun in 2012, it may be a few years yet before the N²QOD will be ready for use. In the meanwhile, there are still a number of clinically relevant questions that are important to address using the NSQIP database. These will provide additional studies for our team.

In summary, the high cost of healthcare in the United States combined with economical recession and an aging population elevates the notion of value-based healthcare from an ideal to a necessity. While neurosurgery is sophisticated and costly, its value cannot be overestimated for a number of conditions. Increased utility of HSR in neurosurgery will allow for better outcomes, in patients that have the potential to benefit from surgical intervention, at lower costs. HSR is still in its infancy in neurosurgery, but by working together, clinicians and researchers can produce immediate and tangible improvements in patient care.

121 Chapter 6 References:

1. Seicean A, Schiltz NK, Seicean S, Alan N, Neuhauser D, Weil RJ. Use and utility of preoperative hemostatic screening and patient history in adult neurosurgical patients. J Neurosurg. 2012 May;116(5):1097-105.

2. Seicean A, Seicean S, Schiltz NK, Alan N, Jones PK, Neuhauser D, Weil RJ. Short-term outcomes of craniotomy for malignant brain tumors in the elderly. Cancer. 2013 Mar 1;119(5):1058-64.

3. The Neuropoint Alliance. The National Neurosurgery Quality and Outcomes Database (N²QOD). Available at http://www.neuropoint.org/NPA%20N2QOD.html . Accessed Jan 26, 2013.

122 Appendix

123 Chapter 4 Supplemental Digital Content

Introduction

Patients were considered to have undergone elective spine surgery if the pr1 variable,

which denotes ICD-9-CM code, was equal to any one of the following: 031, 038, 0302,

0309, 0353, 0359, 0390, 0396, 0399, 0522, 0523, 8050, 8051, 8052, 8053, 8054, 8100,

8101, 8102, 8103, 8104, 8105, 8106, 8107, 8108, 8130, 8131, 8132, 8133, 8134, 8135,

8136, 8137, 8138, 8139, 8480, 8481, 8482, 8483, 8484, 8485. Total number of spine

surgery procedures done in the US each year was estimated to be five times the number

of procedures captured in the NIS database each year2 (3.176 million).

Materials and Methods

Smoking: The NSQIP database contains two smoking variables: current smoker, defined as smoking within 1 year prior to surgery, and smoking duration as determined by total number of pack-years. Current smoker was defined as a patient with yes for the NSQIP current smoker variables and having either a missing value or a value > 0 for pack-years. Prior smoker was defined as having a no for the current smoker variable and a value > 0 for pack-years. Never smoker was defined as having a no for the current smoker variable and a value of

0 or missing for the pack- year variable. Pack-years were used as a categorical variable in increments of 20 years24; increments of 10 years were used for

sensitivity analyses.

Patient History Covariates: Transfer status was dichotomized as being admitted from

home vs. being transferred from another facility (any of: an acute care hospital, chronic

124 care facility, and outside emergency department). Alcohol intake was recorded as having consumed ≥ 2 drinks per day in the 2 weeks prior to admission. Functional status captures the ability to perform activities of daily living within 30 days prior to surgery and was dichotomized as independent vs. partially or totally dependent. American

Society of Anesthesiologists (ASA) physical status classification values were dichotomized as 1 and 2 indicative of normal healthy patient or patient with mild disease, and 3 and 4 as having severe systemic disease that is not / is life threatening. Patients that required ventilator-assisted respiration during the 48 hours prior to surgery, had been diagnosed with chronic obstructive pulmonary disease (COPD), and/or had evidence of pneumonia at the time of surgery were considered to have pulmonary comorbidities.

Cardiovascular comorbidities were considered positive for patients with: diagnosis of congestive heart failure (CHF) within 30 days prior to surgery, myocardial infarction

(MI) in the 6 months prior to surgery, percutaneous coronary intervention (PCI), previous cardiac surgery, self-reported angina in the month prior to surgery, angioplasty or revascularization procedure for atherosclerotic peripheral vascular disease (PVD), and/or was experiencing rest pain or gangrene. Dyspnea was self-reported as difficult, painful, or labored breathing with moderate exertion. Patients with acute or chronic renal failure requiring treatment with peritoneal dialysis, hemodialysis, hemofiltration, hemodiafiltration, or ultrafiltration within 2 weeks prior to surgery were considered to have renal comorbidities. Central nervous system (CNS) comorbidities were reported positive for patients having had coma for ≥ 24 hours, hemiplegia, transient ischemic attacks (TIA), cerebrovascular accident, paraplegia, or quadriplegia. Chemotherapy and radiotherapy for cancer within 90 days prior to surgery were individually captured. Self-

125 reported patient history of abnormal bleeding, self-reported family history of bleeding disorders, vitamin K deficiency, and a comprehensive list of medications that pose a risk for bleeding abnormalities were captured through the NSQIP variable bleeding disorders.

Preoperative hemostatic screening lab values were recorded in the NSQIP database if drawn within 90 days prior to the surgical procedure. Intraoperative variables assessed included wound classification and level of residency supervision in the operating room

(OR). Intra and postoperative transfusions (yes/no) were aggregated, using RBC amount given of ≥ 250 cc as indicative of transfusion.

Outcomes of Interest: Prolonged LOS was defined as LOS >75% of the patients in the sample, which was 4 days. Postoperative complications were defined as occurring within

30 days of surgery. Minor complications were one or more of: superficial surgical site infection, urinary tract infection, deep venous thrombosis (DVT) or thrombophlebitis.

Major complications were one or more of: deep incision surgical site infection, organ or space surgical site infection, wound disruption, pneumonia, unplanned intubation, pulmonary embolism, >48 hour postoperative ventilator-assisted respiration, progressive renal insufficiency, acute renal failure, cardiovascular accident with neurological deficit, coma of >24 hours, peripheral nerve injury, cardiac arrest requiring CPR, myocardial infarction, graft, prosthesis or flap failure, sepsis, septic shock, and/or 30-day return to the OR. Return to the OR (yes/no) was defined as any unplanned return to the OR for a surgical procedure within 30 days postoperatively. Days of operation until death was used to dichotomize mortality at 30 days postoperatively.

Discussion

126 Interpretations in the Context of the Literature: Two studies have assessed the

association between smoking and surgical outcomes in general by aggregating all

surgical specialties captured in the NSQIP database28 and the Veterans Affairs Surgical

Quality Improvement Project database24. Using 2005-2008 data, Turan et al28 compared

current to never smokers and found current smokers to have increased likelihood of

postoperative complications. They reported no difference in morbidity between light

current smokers and never smokers, but found that smoking longer than 10 pack-years

was associated with more complications. Hawn et al24 reported similar findings, with current smokers were significantly more likely to suffer from postoperative pneumonia, surgical-site infection, and death compared to prior and never smokers and a dose-

dependent relationship between pack-year exposure and each of the outcomes. There are

two possible explanations for the differences in our findings. First, spine surgery patients

comprise <10% of each study sample, making it impossible to generalize their findings to

this subsample. Secondly, the Turan et al28 study uses exclusion criteria inconsistent with our own: excluding 18% of surgical cases because of baseline comorbidities, an additional 12% for having missing values for pack-years, and another 21% of current smokers that could not be matched. Such broad exclusions make it difficult to generalize study findings to the clinical setting, where patients frequently present for surgical evaluation with a number of comorbidities.

127 Table 1: P Values for pack-years by smoking status at baseline (N = 14,500) Current Prior Never (N = 3,914) (N = 2,057) (N = 8,529) 27.0% 14.2% 58.8% 0 pack-years 0% 0% 100% 1-20 pack-years 38.3% 53.9% 0% 21-40 pack-years 24.2% 27.4% 0% 41-60 pack-years 10.3% 11.0% 0% >60 pack-years 5.2% 7.7% 0% * Pearson's chi-square test comparing current and prior smokers yielded a P value of <0.001

128 Table 2: Pack-years comparison for adverse outcomes using logistic regression at baseline prior to stratification on propensity scores

Adverse Outcomes Odds Ratios (95% CI) Prolonged 30 day Minor Major 30 day LOS return to complications complications mortality (>4 days) the OR 0 pack- years 1.0 1.0 1.0 1.0 1.0 (never smoker) 1-20 pack- 1.1 (0.9- 0.3 (0.1- 0.8 (0.7-0.9) 0.9 (0.7-1.2) 1.0 (0.9-1.3) years 1.4) 0.9) 21-40 1.1 (0.8- 1.2 (0.6- 0.9 (0.8-1.1) 1.0 (0.7-1.3) 1.1 (0.9-1.4) pack-years 1.4) 2.6) 41-60 1.5 (1.0- 1.1 (0.3- 1.0 (0.8-1.2) 1.0 (0.6-1.6) 1.4 (1.0-1.9) pack-years 2.2) 3.6) >60 pack- 1.0 (0.5- 3.9 (1.6- 1.3 (1.0-1.6) 0.7 (0.3-1.4) 1.3 (0.9-2.0) years 1.8) 9.3) CI = Confidence Interval; OR = operating room

* Odd ratios that are significant are bolded

129

Table 3A: Pack-years comparison for adverse outcomes after stratification on propensity score* and age in current and never smokers (N=7,518)

Adverse Outcomes Odds Ratios (95% CI) Prolonged 30 day Minor Major 30 day LOS return to complications complications mortality (>4 days) the OR 0 pack-years (never 1.0 1.0 1.0 1.0 1.0 smoker) 1-20 pack- 0.8 (0.7- 0.9 (0.7- 0.4 (0.1- 0.9 (0.7-1.4) 0.9 (0.7-1.1) years 0.9) 1.3) 1.6) 21-40 pack- 0.9 (0.8- 0.8 (0.5- 1.5 (0.5- 1.2 (0.8-1.8) 0.9 (0.6-1.2) years 1.1) 1.2) 4.1) 41-60 pack- 0.9 (0.7- 0.9 (0.5- 1.5 (0.3- 0.4 (0.6-1.6) 0.9 (0.6-1.5) years 1.2) 1.7) 6.5) >60 pack- 1.5 (1.1- 0.8 (0.3- 4.6 (1.3- 0.7 (0.1-1.0) 1.3 (0.7-2.4) years 2.1) 1.9) 16.1) CI = Confidence Interval; OR = operating room

* Propensity score consists of all factors significant in Table 1

† Odd ratios that are significant are bolded

130 Table 3B: Pack-years comparison for adverse outcomes after stratification on propensity

score* and age in prior and never smokers (N=4,086)

Adverse Outcomes Odds Ratios (95% CI) Prolonged 30 day Minor Major 30 day LOS return to complications complications mortality (>4 days) the OR 0 pack-years (never 1.0 1.0 1.0 1.0 1.0 smoker) 1-20 pack- 0.8 0.9 0.9 (0.6-1.3) 0.9 (0.7-1.3) 0.1 (0-1.1) years (0.7-1.0) (0.6-1.3) 21-40 pack- 0.9 0.8 0.6 0.8 (0.5-1.3) 0.9 (0.7-1.4) years (0.8-1.2) (0.5-1.4) (0.1-2.5) 41-60 pack- 1.1 1.8 0.7 1.5 (0.8-2.7) 1.8 (1.2-2.8) years (0.8-1.5) (1.0-3.2) (0.1-5.4) >60 pack- 1.1 0.5 3.1 0.5 (0.1-1.5) 0.9 (0.4-1.7) years (0.8-1.5) (0.2-1.6) (0.9-10.9) CI = Confidence Interval; OR = operating room

* Propensity score consists of all factors significant in Table 1

† Odd ratios that are significant are bolded

131 Chapter 5 Supplemental Digital Content

Introduction

Patients were considered to have undergone elective spine surgery if the PR1 variable, which denotes International Classification of Disease, Ninth Revision, Clinical

Modification (ICD-9-CM) procedure code, was equal to any one of the following: 03.1,

03.8, 03.02, 03.09, 03.53, 03.59, 03.90, 03.96, 03.99, 05.22, 05.23, 80.50, 80.51, 80.52,

80.53, 80.54, 81.00, 81.01, 81.02, 81.03, 81.04, 81.05, 81.06, 81.07, 81.08, 81.30, 81.31,

81.32, 81.33, 81.34, 81.35, 81.36, 81.37, 81.38, 81.39, 84.80, 84.81, 84.82, 84.83, 84.84,

84.85. Total number of spine surgery procedures done in the US each year was estimated using the sum of the NIS discharge weight (DISCWT variable) (HCUP 2012) (644,721 procedures captured in the NIS dataset between 2006 and 2010; sum of DISCWT is

3,176,255 for the same time period).

Materials and Methods

Patient History Covariates: We dichotomized both transfer and functional status respectively as admitted from home vs. transferred from any facility and as independent vs. partially or totally dependent. American Society of Anesthesiologists (ASA) physical status classification values were dichotomized as 1 and 2 indicative of normal healthy patient or patient with mild disease, and 3 and 4 as having severe systemic disease that is not / is life threatening. Patients that required ventilator-assisted respiration during the 48 hours prior to surgery, had been diagnosed with chronic obstructive pulmonary disease, and/or had evidence of pneumonia at the time of surgery were considered to have pulmonary comorbidities. Cardiovascular comorbidities were considered positive for

132 patients with: congestive heart failure that was diagnosed or was symptomatic within 30

days prior to surgery, self-reported angina in the month leading up to surgery, myocardial

infarction within the 6 months prior to surgery, percutaneous coronary intervention, prior

cardiac surgery, angioplasty or revascularization procedure for atherosclerotic peripheral

vascular disease, and/or was experiencing rest pain or gangrene. Patients with acute or

chronic renal failure requiring treatment with peritoneal dialysis, hemodialysis,

hemofiltration, hemodiafiltration, or ultrafiltration within 2 weeks prior to surgery were

considered to have renal comorbidities. Central nervous system comorbidities were

reported positive for patients having had coma for ≥ 24 hours, hemiplegia, transient ischemic attacks, cerebrovascular accident, paraplegia, or quadriplegia. We merged chemotherapy and radiotherapy for cancer within 90 days prior to surgery into one variable. Self-reported patient history of abnormal bleeding, self-reported family history of bleeding disorders, vitamin K deficiency, and a comprehensive list of medications that pose a risk for bleeding abnormalities were captured through the NSQIP variable bleeding disorders. Preoperative hemostatic screening lab values were recorded in the

NSQIP database if drawn within 90 days prior to the surgical procedure. Patients were considered to have undergone intra- / post-operative transfusion if they received one or more of the following for any reason: ≥ 250 cc packed or whole red blood cells (RBC) or cell savage reinfused blood during the surgery, > 5 units of packed RBC within 72 hours

of surgery, and/or > 4 units of shed blood, autologous blood, cells saver blood or

pleurovac postoperatively within 72 hours of surgery.

133 Table 1: Anemia status comparisons for total length of hospital stay after matching on propensity scores

Mild No Severe No Moderate No Anemia Anemia Anemia Anemia Anemia Anemia (N = (N = (N = 87) (N = 87) (N = 311) (N = 311) 5,420) 5,420) Total LOS, days 10.9 ± 10.0 ± 10.0 ± mean ± SD 5.8 ± 8.9 4.8 ± 10.0 3.6 ± 8.6 25.2 39.2 13.2 median 4.0 3.0 8.0 4.0 3.0 2.0 Difference in median LOS between 1.0 4.0 1.0 matched groups, days SD = standard deviation; LOS = length of hospital stay

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