Thromboelastography and Mean Platelet Volume As Prognostic Markers in Sepsis

Thromboelastography and mean platelet volume as prognostic markers in sepsis:

an observational study

DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF

THE RULES AND REGULATIONS FOR THE MD GENERAL

MEDICINE EXAMINATION OF THE TAMILNADU DR. M.G.R.

MEDICAL UNIVERSITYTO BE HELD IN MAY 2019

DECLARATION

This is to declare that the dissertation entitled “Thromboelastography and mean platelet volume as prognostic markers in sepsis: an observational study” is my original work done in partial fulfilment of rules and regulations for the MD General Medicine examination of the Tamil Nadu Dr.M.G.R Medical University, Chennai to be held in May, 2019.

Dr Fibi Ninan K

Post Graduate student

Department of General Medicine

Christian Medical College

Vellore

October 2018

BONAFIDE CERTIFICATE

This is to certify that the dissertation entitled “Thromboelastography and mean platelet volume as prognostic markers in sepsis: an observational study” is a bona fide original work done by Dr Fibi Ninan K during her academic term April 2016 to March 2019, at

Christian Medical College, Vellore in partial fulfilment of rules and regulations for the

MD General Medicine examination of the Tamil Nadu Dr.M.G.R Medical University,

Chennai to be held in May, 2019. This work was carried out under my guidance in the department.

Dr Ramya I

Professor

Department of General Medicine

Christian Medical College

Vellore

BONAFIDE CERTIFICATE

Christian Medical College, Vellore in partial fulfilment of rules and regulations for the

MD General Medicine examination of the Tamil Nadu Dr.M.G.R Medical University,

Chennai to be held in May, 2019.

Principal Head of the department

Dr Anna B Pulimood Dr Thambu David Sudarsanam

The Principal Head of the Department

Christian Medical College Department of General Medicine

Vellore Christian Medical College Vellore

ACKOWLEDGEMENT

“Thus far has the Lord helped us....”

I express my sincere gratitude to all who contributed to this thesis:

Dr. Ramya I for her expert guidance from the conceptualization of the theme, till the final full stop; there is not one area of this thesis where her hands or mind have not touched.

Dr. John Victor Peter for providing patients from the ICU and for his help in valuable critique and suggestions,

Dr.SukeshChandran for guiding me through the analysis of results of

Thromboelastography,

Dr.Thulasi Geevar for her support in counter checking thromboelastography results,

Ms Preethi Lilly, for promptly providing thromboelastography and mean platelet volume results,

Mr BijeshYadav for helping me with the statistics,

All the consultants for their constant encouragement,

My fellow registrars for being very helpful and considerate all throughout,

My husband Dr. Justin and our parents for their constant support, encouragement and prayers all throughout our lives,

My sister Dr Fini for her constant support in writing up the thesis, 6

My relatives and my fellowship members of Christian Revival Fellowship for constant prayers and well wishes,

Last but not least, I thank all my patients for their co-operation and trust. Without them my training would be incomplete and this thesis would not have happened.

ANTIPLAGIARISM CERTIFICATE

This is to certify that this dissertation work titled - “Thromboelastography and mean platelet volume as prognostic markers in sepsis” of the candidate Dr. Fibi Ninan K with registration Number 201611457 has submitted her dissertation for verification and I have personally verified the Urkund.com website for the purpose of plagiarism check. I found that the uploaded thesis file contains the introduction to conclusion pages and the analysis shows eight percentage of plagiarism in the dissertation.

Dr Ramya I

Professor

Department of General Medicine

Christian Medical College

Vellore 8

TABLE OF CONTENTS

INTRODUCTION...... …...... 14

AIM AND OBJECTIVES …….………….….……………………...... 17

LITERATURE REVIEW……….………….……………..………...... 19

MATERIALS AND METHODS………….……………………...... 49

RESULTS……………………………….…………………………...... 60

DISCUSSION……………………………….…………………………...... 75

CONCLUSIONS ………...…...……………………………………...... 85

LIMITATIONS OF THE STUDY..…….……………………………...... 88

REFERENCES…………………………..………………………...... 90

ANNEXURE I: IRB APPROVAL FORM………………….…...... 104

ANNEXURE II: INFORMATION SHEETS AND CONSENT FORMS...... 108

ANNEXURE III: CLINICAL RESEARCH FORM …………..…...... ….....125

ANNEXURE IV: EXCEL SHEET...... 127

ANNEXURE V: STROBE CHECK LIST...... 132

Abbreviations

ALI: Acute Lung injury

APTT: Activated partial thromboplastin time

CFT: Clot formation time

DAMA: Discharge against medical advice

DAMPS: Damage associated molecular patterns

DIC: Disseminated intravascular coagulation

ISTH: International Socitey on Thrombosis and Haemolysis

JMHLW: Japanese Ministry Health, Labour and Welfare

JAAM : Japanese Association of Acute Medicine

FFP: Fresh frozen plasma

MA: Maximum amplitude

MCF: Maximum clot formation

MOF: Multi organ failure

MPV: Mean platelet volume

PT: Prothrombin time 10

PAMPS: Pathogen associated molecular pattern

ROTEM: Rotational thromboelastometry

SAPS II: Simplified acute physiology score II

SOFA: Sequential organ failure assessment

TEG: Thromboelastography

TAFI: Thrombin activable fibrinolysis inhibitor

LIST OF TABLES AND FIGURES

List of figures

Fig 1: Demostrates the various signalling pathways involved in sepsis ………….....20

Fig2: Demonstrates endothelial dysfunction in sepsis: ……………………………. ..22

Fig 3: Demonstrates the conventional method of coagulation……………………...... 24

Fig 4: Demonstrates the initiation phase …………………………………………. ....25

Fig 5: Illustrates pathophysiology of DIC ……………………………………………..28

Fig 6: Demonstrates the principle of TEG………………...... ,...... 32

Fig 7: Demonstrates normal TEG tracing …………………………………………….33

Fig 8: Demonstrates TEG tracing in various clinical conditions…………………...... 35

Fig 9: Demonstrates the role of platelets in activation of immune system in sepsis…. 43 11

Fig 10: Shows a resting platelet and an activated platelet………………………….....44

Fig 11: Shows picture of TEG machine……………………………………………....52

Fig 12: Demonstrates tracing of TEG on the system ……………………………...... 53

Fig 13: Demonstrates analysis of TEG being done…………………………………...53

Fig 14: Detailed Diagrammatic Algorithm of the Study: …………………………….56

Fig 15: Pie diagram demonstrating gender distribution of patients …………………. 59

Fig 16: Demonstrates the aetiology of sepsis…………………………………………. 60

Fig 17: Demonstrates the primary outcome …………………………………………62

Fig 18: Summarises coagulation abnormalities in patients with severe sepsis based on various parameters in TEG ……………………………………………………….....65

List of tables

Table1: Demonstrates the ISTH score for DIC …………………………………….. 29

Table: 2 Illustrates definition of hyper and hypocoagulability based on TEG parameters

………………………………………………………………………………………..34

Table 3: Illustrates various TEG parameters in different clinical settings.....…...... …36

Table: 4 Illustrates transfusion of blood products based on TEG...... …………..38

Table 5: Various modifications in TEG …………………………………………..….42

Table 6: Parameters of platelets were studied in the past as markers of disease severity……………………………………………………………………………… 44 12

Table 7: Normal values of TEG parameters………………………………………… 51

Table 8: Calculation of sample size...... 54

Table 9: Age distribution of patients with severe sepsis …………………………….58

Table 10: Demonstrates the co-morbidities of the patients ………………………….59

Table 11: Shows the spectrum of patients with bacteraemia ………………………..61

Table 12: Demonstrates various coagulation parameters …………………………...61

Tables 13: Compares the mortality in bacteraemic and non bacteraemic patients

………………………………………………………………………………...... 62

Tables 14: Comparison of mortality in patients with hypercoagulable, normocoagulable and hypocoagulable state based on R time ………………………...... 63

Tables 15: Comparison of mortality in patients with hypercoagulable, normocoagulable and hypocoagulable state based on K time ……………………… ...... 63

Tables 16: Comparison of mortality in patients with hypercoagulable, normocoagulable and hypocoagulable state based on alpha angle………………...... …. 64

Tables 17: Comparison of mortality in patients with hypercoagulable, normocoagulable and hypocoagulable state based on maximum amplitude………...... 64

Table:19: Demonstrates correlation between TEG parameters and mortality

.………………………………………………………………………...... 66

Table 20: Demonstrates association of TEG parameters and requirement of transfusion

…………………………………………………………………………...... 67 13

Table 21: Demonstrates association of TEG parameters and requirement of transfusion of fresh frozen plasma …………………………………………………………...... …… 67

Table 22: Demonstrates association of TEG parameters and requirement of transfusion of platelets …………………………………………………………………………...... 68

Table 23: Demonstrates association of TEG parameters and requirement of transfusion of cryoprecipitate …………………………………………………………………...... 68

Table 24: Shows correlation between PT and TEG parameters……………………...... 69

Table 25: Shows correlation between APTT and TEG parameters ………………….. 69

Table 26: Shows correlation between Platelets and TEG parameters ……………...... 69

Table 27: Demonstrates correlation between various TEG parameters and ICU stay and hospital stay …………………………………………………………………...... 70

Table 28: Demonstrates correlation between various TEG parameters and SOFA score

………………………………………………………………………………...... 71

Introduction

Sepsis remains to be a life threatening condition despite having insight into its aetiology, pathophysiology and advances in early goal directed therapy(1). As per 2016 Society of

Critical Care Medicine and European Society of Intensive Care Medicine task force, sepsis is defined as ‘life threatening organ dysfunction caused by dysregulated host response to infection’(2). The annual incidence of sepsis is 20 million cases worldwide of which 5 million patients do not survive in the low and middle income countries(3).

The knowledge of pathophysiology of sepsis is incomplete till date. The key event in sepsis is endothelial dysfunction which causes microvascular dysfunction. This is associated with hypoxia, oxidative stress and release of cascade of inflammatory mediators and in turn multiorgan dysfunction syndrome(1,4). As part of this inflammatory response various coagulation abnormalities occur that ranges from minor drop in platelet counts to severe forms of coagulopathy like disseminated intravascular coagulation(5).

Coagulation system is activated by various proinflammatory mediators that are released as a host response to infection. The initial hypercoagulable state causes deposition of fibrin in the micro vasculature leading to multi organ dysfunction syndrome(5). Over a period of days platelets and various coagulation factors are consumed due to progressive generation of thrombin resulting in overt DIC(6). ISTH defined pre DIC as compensated coagulopathy, a stage before overt DIC sets in(7). The diagnosis of sepsis induced coagulopathy in its pre DIC stages may aid in early goal directed therapy.

Thromboelastograph is a single test which assesses various stages of coagulation cascade ranging from fibrin formation to platelet aggregation and fibrinolysis (8). Mean platelet volume (MPV) is a measure of average size of the platelets (9).We decided to determine 16

whether abnormal thromboelastography and mean platelet volume is associated with adverse outcome in patients with severe sepsis.

Kansuke et al in their study demonstrated that a single measurement of plasminogen activator inhibitor-1, thrombin-antithrombin complex, and protein C activity helps in the diagnosis of coagulopathy early in sepsis(6).The hypothesis is that severe sepsis is characterized by a pro-coagulant state in the initial stages, and hypocoagulation and disseminated intravascular coagulation (DIC) in the later stages. Thus hypercoagulation detected by thromboelastography (TEG) in early sepsis in patients without clinical bleeding could predict subsequent DIC and multi-organ dysfunction. This observation was noted in a preliminary study on a small sample population by Turani et al(10).Our study was determined to determine association of abnormal TEG (either hypercoagulable or hypocoagulable state) and mean platelet volume with adverse outcomes in patients with severe sepsis.

Aim and Objectives

Aim

To determine whether abnormal thromboelastography and mean platelet volume is associated with adverse outcome in patients with severe sepsis.

Objectives

1. To study the prevalence of abnormal thromboelastography and mean platelet volume

in patients with severe sepsis.

2. To evaluate if thromboelastography and mean platelet volume are associated with

number and severity of organ dysfunction as assessed by the sequential organ failure

assessment (SOFA) score.

3. To study the association between an abnormal thromboelastography and high mean

platelet volume, at the time of diagnosis of sepsis, on mortality and duration of ICU

stay and hospital stay in patients admitted with severe sepsis

Literature Review

Incidence and definition of sepsis

Sepsis is the leading cause of death in non coronary critical care unit(11) and has been termed as the ‘hidden public disaster’(12). There is a steady trend towards increase in the incidence of sepsis which reflects the aging population with multiple comorbid conditions(13). The global burden of severe sepsis ranges from 13-300/100,000 and the case fatality rate is as high as 50% (14). The incidence of sepsis in India as reported by

Todi et al is 16.5 % of all admissions and has a hospital mortality of 65.2% (11).

Sepsis has been referred to as ‘garbage code’ being a pathway leading to death from an infection. However most of these patients die from sepsis than from the infection as such(15). As per the third international consensus, sepsis is defined as ‘life-threatening organ dysfunction caused by a dysregulated host response to infection’ and organ dysfunction is defined as ‘acute change in total SOFA score ≥2 points consequent to the infection(13). Septic shock is defined as the condition in which a patient requires vasopressors to maintain a mean arterial pressure > 65 mm of Hg and serum lactates >

2mmol /L in the absence of hypovolemia. Patients with organ dysfunction is known to have an in hospital mortality >10%. Septic shock is associated with in hospital mortality

>40%(13).

Pathophysiology of sepsis

The normal physiological response of the body helps in eradication of pathogens.

Sepsis is characterized by inappropriate regulation of these mechanism(16). Hence the 21

degree of damage depends both the pathogenicity of the invading organisms and the exuberant host response which causes exaggerated tissue damage(12).

The pathophysiology of sepsis can be explained under the following headings a)Inflammation

Bacteria, virus and fungi release various substances like endotoxins and betaglucans which are called pathogen associated molecular patterns (PAMPS). Similarly there are various damage associated molecular patterns (DAMPS) which are endogenous molecules released from damaged host cells like ATP, mitochondrial DNA etc. Various pattern recognition receptors are located in the cell receptors or in the cytosol , toll like receptors

/NOD like receptors, to name a few of them. Innate immune system is activated by PAMS and DAMPS through pattern recognition receptors and thereby initiating transcription of cytokines like TNF alpha, IL-6, IL-1 etc. These inflammatory mediators help in programmed cell death and when it exceeds a certain threshold it can lead to activation of complement cascade , widespread thrombosis and release of reactive oxygen species(17).

In sepsis, various signalling pathways are activated leading to expression of several genes involved in inflammation. Various pro inflammatory cytokines are released in recognition of various bacteria, fungi and viruses which in turn lead to phosphorylation of JAK, MAK,

NFkb etc. These mediators activate various early activation gene.(18).

Fig: 1: Demostrates the various signalling pathways involved in sepsis

(12) 23

b)Early activation gene

Early activation genes are interleukins, IL-1, IL12 and interferon alpha that are produced in response to nuclear translocation of NF kb. These inflammatory mediators release a cascade of inflammatory mediators like IL-6,IL-8 and suppression of components of adaptive immunity (18). c)Microvascular dysfunction

Another mechanism of sepsis is the alteration of the microcirculation which consists of an area of 1000m2 (17). Microcirculation which is embedded in various organs consists of pre capillary arterioles, arterioles and post capillary venules. These vessels help in regulation of blood flow, oxygenation and tissue perfusion and blood pressure (4). In fact in the year

2010 sepsis was redefined as ‘severe endothelial dysfunction syndrome leading to reversible or irreversible injury to micro circulation and thereby multiple organ dysfunction syndrome’ Hence any injury to the microcirculation can cause serious injury in various organs leading to multi organ dysfunction syndrome (19).

d)Endothelial barrier dysfunction

Endothelial barrier dysfunction is fundamental event in sepsis. In normal state endothelium acts as anticoagulant surface in the blood vessels and it maintains normal flow of various molecules. Its integrity is maintained by actin, intercellular adhesion molecules which form tight junctions and various support proteins(18). 24

Microvascular leak in the endothelium is produced by various inflammatory mediators like cytokines, chemokines and direct action of microbial virulence factors like LPS and staphylococcal toxin. Similarly host endogenous products released from the vascular cells cause a deadly blow to microvascular endothelial cells (4).

In addition, endothelial cells are covered by a glycoprotein polysaccharide layer called glycocalyx. It maintains the tight junctions and supports the anticoagulant state. In sepsis, various inflammatory mediators target the glycococalyx and disrupt the barrier. Due to leaky capillaries large amount of protein is lost into the extra vascular compartment. There is diffuse vasodilatation leading to alteration in microvascular blood flow and there by poor tissue perfusion and shock (18).

Fig 2: Demonstrates endothelial dysfunction in sepsis

(20) 25

Prognostic markers in sepsis

As sepsis involves high incidence of mortality, early recognition of patients who are at risk of rapid progression of sepsis is imperative. Early goal directed therapy is imperative for better outcomes of patients (21). Much attention has been given to the inflammatory markers in sepsis that precedes organ dysfunction and mortality in sepsis. The inflammatory response may provide protective effect against pathogenic organism, but when there is an exaggerated response it becomes counterproductive and harmful, leading to multi-organ dysfunction(22).

Different parameters have been studied in the past as prognostic markers in sepsis. In a study conducted in Iran it was found that age, sex, low albumin and diastolic blood pressure <52 mm of Hg were indicators of rapid progression of sepsis (23). Another prospective study done over a period of 6 years showed older age, rise in serum lactate and elevated procalcitonin was associated with increase in mortality(21).

As sepsis is known to be associated with coagulation abnormalities, studies were done to assess causality between various determinants of coagulation and sepsis.

Sepsis and coagulation system

Coagulation abnormalities are almost universal in sepsis. Inflammation and coagulation abnormalities are tightly linked together that, each sends a positive feedback to the other.

The coagulopathy in acute sepsis can range from florid thrombo-embolic disease to microvascular fibrin deposition (22).

The mechanism of coagulation can be explained by the conventional coagulalation pathways and new coagulation pathways. 26

Conventional coagulation pathway

Fig 3: Demonstrates the conventional method of coagulation

(24) 27

Mechanism of coagulation involves primary haemostasis followed by activation of the intrinsic and extrinsic coagulation pathways. Primary haemostasis is involved in platelet plug formation secondary to complex interactions between platelets, vessel wall and complex proteins as illustrated above.(25)

New coagulation pathway

Current evidence supports that extrinsic pathway initiates thrombin formation and the intrinsic pathway augments the process. This is in contrast to the classical teaching where extrinsic and intrinsic pathways were thought to get activated in a parallel manner. Various steps involved in the process are initiation, amplification, propagation and stabilisation.(26)

Initiation phase

The tissue factor in damaged vessel bind to factor VIIa which in turn activates factor IX and factor X simultaneously.

Fig 4: Demostrates the initiation phase

Amplification phase

Trace amount of thrombin that is generated in the initiation phase is inadequate for clot formation. Various positive feedback loops exist that bind thrombin and platelets.

Thrombin activates factor VIII and V which in turn activates factor II.

Propagation phase

Enzyme complexes like tenase complex and prothrombinase complex on platelet surface causes platelet activation and thrombin formation. This ensures generation of sufficient amount of thrombin , fibrin and later blood clot.

Stabilisation phase

Thrombin stabilises the clot through 2 mechanisms

1. It activates the clot stabilizing factor(factor XIII) . It covalently links fibrin

polymers and provides stability to the fibrin.

2. It stimulates the thrombin activable fibrinolysis inhibitor (TAFI) which inhibits

fibrinolysis.(25)

The above mentioned pathways are deranged in sepsis. The pathogenesis of coagulopathy in sepsis is due to activation of the procoagulant pathway, downregulation of anticoagulantion mechanisms and impraired fibrinolysis as mentioned below.

A)Activation of the coagulation

In sepsis there is direct activation of the coagulation pathway via both extrinsic and intrinsic pathway. Various toxins cause upregulation of tissue factor. The tissue factor directly activates factor VII of the extrinsic pathway leading to thrombin formation and formation of fibrin clots. Factor VIIa activates factor IX of the intrinsic pathway and hence formation of thrombin (27).

Coagulation system is also activated by activation of the complement pathway.

Complement mediated shedding of the microvescicles releases various tissue factors that are prothrombotic (18).

A) Downregulation of anticoagulation mechanisms

Various molecules that promote anticoagulation are embedded in the endothelial surface.

Various inflammatory mediators released in sepsis leads to endothelial injury (28). This

leads to breech in the endothelium. The damaged glycocalyx layer exposes the collagen

underneath which activates the von willibrand factor and in turn the platelets. Platelets

activate coagulation cascade by activation of thrombin. Thrombin converts insoluble

firbrinogen in to fibrin. Platelets and strands of fibrin form the backbone of clot which

gets deposited in microcirculation leading to reduction in perfusion and multi organ

dysfunction syndrome.(18)

C)Reduction in fibrinolysis

Thrombin releases thrombin–activable fibrinolysis inhibitor (TAFI) which helps in

reduction of fibrinolysis. Thus thrombin not only causes clot formation but also inhibits its

removal.(27) 30

The activation of coagulation system, down regulation of anticoagulant mechanisms and

inhibition of fibrinolysis ultimately leads to disseminated intravascular coagulation (29).

Fig 5: Illustrates pathophysiology of DIC

Consumption of platelets

(30)

Conventional tests for coagulation in sepsis

In sepsis there is widespread activation of the coagulation cascade and inhibition of

the fibrinolytic pathway leading to widespread thrombosis and MODS. Haemostatic

factors like fibrinogen, factors V and VIII, platelets, protein C and anti thrombin III are 31

consumed as part of widespread thrombin formation in sepsis. Compensatory thrombolysis is caused by tissue plasmin activator which is released by endothelial cells of occluded vessels. As a result conventional tests of coagulation may show thrombocytopenia and prolongation of prothrombin time and activated partial thromboplastin time. The byproducts of thrombolysis such as fibrin degradation products or D-dimer are usually elevated in severe sepsis(31). The diagnosis of DIC by conventional methods is based on 3 different criteria, International Socitey on Thrombosis and Haemolysis (ISTH), Japanese

Ministry Health, Labour and Welfare (JMHLW) and Japanese Association of Acute

Medicine (JAAM ).

Table1: Demonstrates the ISTH score for DIC

Parameters Score

Platelets x 109/L >100 0

≤100 1

<50 2

PT (s) <3 0

≥3 and <6 1

≥6 2

Fibrin related marker, mg/L D dimer <1 0

1.0 ≤D dimer<5 1

D dimer ≥5 2

Fibrinogen , g/L >1.0 0

≤1.0 1

(7) 32

A score ≥5 is suggestive of overt DIC. However a score ≤ 5 is indicative of DIC but not confirmatory.

Traditional tests of coagulation depend on extrinsic and intrinsic pathway and the number of platelets. However clot formation involves interaction between myriad other factors like vascular endothelium, von willibrand factor, pro-coagulant and anti coagulant factors and blood flow. For effective haemostasis there should be adequate thrombin generation

(platelets and coagulation factors), enough fibrin and clot stability. Only <5% of the thrombin that would have been generated during anticoagulation is formed at the time of testing in conventional tests and it does not represent the overall haemostasis

(32).Conventional tests for coagulation tests various parts of the coagulation cascade in isolation and it may not reflect the in vivo coagulopathy (10).

The various fallacies in conventional tests of coagulation are

1. PT, APTT reflects overall decrease in coagulation factors but it does not reflect the

nature of the coagulation defect.

2. State of hypercoagulability cannot be assessed

3. Spurious values in conditions like anti phospholipid antibody syndrome(33).

4. Conventional tests do not account endogenous anticoagulant factors and cellular

elements.

5. Moreover it does not account for different thrombin dependent reactions like

activation of the platelets(32).

Muzaffar et al in his study compared conventional tests with TEG. It was found that among patients with INR >1.6, 60% had a normocoagulable state where as 20% had hypercoagulable state. Similarly normocoagulable state was found in 81% of the patients with platelets <1,00,000 (34). This reiterates the need for alternative tests to assess the coagulation. HheseMoreover these abnormalities are manifested in conventional tests only after occurrence of DIC by then it is too lat

Thromboelastography a novel diagnostic tool

TEG was first conceived by Helmut Hartert in Germany in the year 1948 at the Heidelberg

University of Medicine (35). TEG is a real time visco-elastic assay which sums the effect of various factors involved in coagulation and provides a global assessment of haemostatic function (31,36).

TEG is performed by placing the 340µl whole blood sample in a cup which oscillates 4°45′ every 5 seconds at 37o C. A stationary pin is suspended from torsion wire in to the cup. The oscillations in the cup mimic the sluggish flow in the venous circulation. The coagulation process is activated leading to the formation of fibrin strands. These strands couple the motion of cup and pin together. The electromagnetic transducer detects increased tension in the wire and the electrical signal is amplified to create a trace in the computer screen (37).

Free rotation corresponds to an amplitude of 0 mm and no rotation corresponds to an amplitude of 100 mm (38).

ROTEM (Rotational thromboelastometry) is a modification of TEG in which the cup containing 340µL of blood remains static while pin oscillates on a ball bearing mechanism.

As the fibrin forms on the pin, the oscillation of the pin is impeded .This is detected on an optical based system (38). 34

Fig 6: Demonstrates principle of TEG

(39)

Fig 7: Demonstrates normal TEG tracing

(40)

There are 4 important variables in TEG:

R time: It is the time from the initiation of the study to initiation of clot formation. It is analogous to PT/APTT.

K time: Denotes R time till the time till enough fibrin cross linkages occur to produce amplitude of 20mm. Clotting at this time is dependent on fibrin cleavage and fibrin polymerisation. 36

Alpha angle: It is the angle between the baseline and a tangent to the curve of the TEG. It expresses the kinetics of clot formation. Higher angle represents greater rate of clot strength formation and vice versa. Alpha angle depends upon fibrinogen concentration and function.

Maximum amplitude: It is the width in millimetres of the widest gap in the tracing and it indicates maximum strength of clot formation. MA depends upon platelet number and function as well as on the fibrinogen. Around 20% of the clot strength depends on fibrinogen and 80% depends on platelets.

Lysis 30: It is the standard measure of fibrinolysis. It denotes percentage reduction in clot strength 30 min after achieving MA(35).

TEG gives holistic picture of clot tensile strength over time: clot formation, clot strength and clot stability(32).

Table: 2 Illustrates definition of hyper and hypocoagulability based on TEG parameters

R time K time Alpha angle Maximum

amplitude

Hypercoagulable state

Hypocoagulable state

(37) .

Fig 8: Demonstrates TEG tracing in various clinical conditions

(41)

Table 3: Demonstrates various TEG parameters in different clinical situitations

Haemostatic abnormality R time Alpha angle MA

Clotting factor deficiency High Low / normal Low/normal

Fibrinogen deficiency Normal Low Low/normal

Low platelet counts Normal Normal Low

Primary hyperfibrinolysis Normal Normal Low

Hypercoagulability with late Low High High fibrinolysis: Early DIC

DIC late High Low Low

(42).

Thromboelastogram and its uses

Diagnostic purposes

TEG has been used to prognosticate cerebrovascular events. In 246 patients with acute ischemic stroke it was noted that hypercoagulability as demonstrated with reduced R time was associated with early neurological deterioration (43). In a study conducted in China among post-operative patients it was noted that R value of TEG was significantly different in patients who had venous thromboembolism and patients who had bleeding. Hence thromboelastogram could be used as a guide to predict post-operative complications (44).

TEG was used to analyse coagulopathy in patients with dengue. It was noted that factor deficiency followed by platelet dysfunction was the most common coagulopathy(45). In a study in paediatric patients with snake bite and it was noted that an abnormal TEG was a 39

better predictor for clinical bleeding than INR with a sensitivity of 94.4% and specificity of 45.5% (46). However TEG did not predict mortality, risk of bleeding or thrombosis or liver transplantation in patients with liver cirrhosis (47).

Another area visco elastic tests may of use is in the monitoring of newer oral anticoagulant agents. In a small study done in patients on dabigatran showed strong correlation ROTEM values (activated by reagents of EXTEM and FIBTEM) with dabigatran levels. However these tests did not show any correlation with vitamin K antagonists or with other direct oral anticoagulant drugs like rivaroxaban (38).

Therapeutic purposes a)TEG and its use to tailor transfusions

Thromboelastogram has been studied to as a tool to determine transfusion requirements.

1. Prolonged R time indicates clotting factor deficiency.

2. Prolonged K time and low alpha angle indicates fibrinogen deficiency and /or fibrin production or function.

3. Low MA indicates lack of clot formation by fibrin platelet mesh demonstrating the need for platelet transfusions (48).

Table: 4: Illustrates use of TEG in transfusion of blood products 40

Potential therapeutic intervention Finding on TEG

Plasma or prothrombin concentrate Prolonged R value (>7 minutes)

Cryoprecipitate / fibrinogen concentrate Low or flat angle(<45)

Platelets+/cryoprecipitate/fibrinogen Narrow MA (<48mm) concentrate

Anti fibrinolytic agent Increased LY 30 (>7.5%)

(48)

TEG has been used in various clinical settings as a test for coagulation and as a guide to transfusion of blood products. In a systematic review that included 17 randomised control trials, TEG guided therapy was found to reduce need for transfusion of all types of blood products. However it was noted that the overall quality of these studies were low(49).

TEG has been studied in various populations.

-In patients undergoing liver transplantation, assessing TEG to monitor and treat hyperfibrinolysis in patients helped to reduce blood transfusions (50).

- In cardiac surgery transfusion tailored according to TEG results resulted in significantly lower incidence of blood transfusion in comparison to transfusions based on standard tests for coagulation (78.5% versus 86.5%) (51). However a systematic review in patients post cardiac surgery did not show reduction in all cause mortality or reduction in transfusion of platelets with TEG guided transfusions(52). 41

-It has been studied in trauma induced coagulopathy. It was noted that in these group of patients 28 day mortality was better in patients who received TEG guided therapy (53).

-However various studies that looked into the role of TEG in predicting bleeding in patients with aspirin and LMWH, found that TEG cannot be used as a guide to titration of dose of LMWH (54).

Thromboelastography as a prognostic factor in sepsis

Thromboelastography has been studied as a predictor of mortality. However the quality of evidence supporting TEG as prognostic marker in sepsis is low to moderate.

(22). There has been wide variation in TEG parameters in patients with sepsis (34). The reasons for this wide variation would be

1. The time when TEG was done. Initial phase of sepsis is characterised by formation of micro thombi in small vessels and later hypocoagulability due to consumptive coagulopathy.

2. There is lack of universal reference ranges for TEG.

3. Differences in disease severity in different study groups (42).

One of the important uses of TEG was in prediction of neonatal sepsis. In a prospective trial that included 103 children TEG was found to have 96 % sensitivity and specificity and positive predictive value of 88% and negative predictive value of 98% (55).

Adamzik et al compared TEG with SOFA score and SAPS II. There was 4.1-fold increase in 30-day mortality in patients, when there was at least one pathological 42

thromboelastometry finding. SAPS II and SOFA score were not different among survivors and non survivors where as mean CFT, MCF (parameters in ROTEM) and alpha angle was significantly different between the 2 groups. Hence TEG could be used as a prognostic factor in sepsis (56).

As mentioned earlier TEG can differentiate between hypocoagulable state and hypercoagulable state. Hence it is important to know what state of coagulopathy is associated with adverse prognosis. In a study by Brenner et al, TEG demonstrated a hypocoagulable state in patients with DIC and hypercoagulable state in non-overt DIC (9).

Similar results were shown in a study by Sivula et al and it was postulated that hypercoagulable state in non overt DIC was due to increase in fibrinogen level as an acute phase reactant (57).

Early hypocoagulability was found to be an independent risk factor for 28 day mortality and higher risk for MODS. Patients with normal coagulation at admission who progressed to hypocoagulation later had a mortality rate of 80% (22) .

Limitations of thromboelastogram

As with any other tests thromboelastogram is associated with its limitations

1. The method is not standardized and hence there is lot of inter laboratory variability

in the results. It involves manual pipetting and mixing of reagents which are

operator dependent.

2. Vibration on the surface where the TEG machine is kept may introduce artifacts. 43

3. Citrated samples needs to be rested for fixed amount of time before analysis and

hence it may be time consuming.

4. The results of the TEG may vary depend on multiple factors like haematocrit,

platelet count, infusion of colloids or crystalloids etc.

5. There are no reference values for different populations like males, females,

parturients.

6. The test involves cost and expertise which precludes multiple analysis for a single

patient (58).

Modifications of TEG to overcome the limitations

Various modifications have been made to TEG for the ease of analysis. Addition of various re-agents aid in overcoming the limitations involved in TEG.

Table 5: Various modifications in TE

Outcome Reagent

Citrate Enables prolonged storage of samples before analysis

Heparin Inhibits thrombin, allowing the contribution of fibrin and platelets to be studied

Heparinase Reverses the effects of heparin

Activators (celite, kaolin, Increase speed of result acquisition tissue factor) 44

Glycoprotein IIb/IIIa Inhibits platelet function inhibitors allowing the contribution of fibrinogen to be assessed

Antifibrinolytic drugs Reverses fibrinolysis (tranexamic acid)

Reptillase and factor Activates fibrin formation without affecting platelets XIIIIa

Arachadonic acid Activates platelets via production of thromboxane A2

ADP Activates platelets via P2Y1 and P2Y12 receptors

(59)

As mentioned in the table addition of citrate reduces the need for immediate analysis of the sample which may of use in transport of the sample to referral centres. Similarly addition of heparinise allows use of the test in patients who are on prophylaxis of deep vein thrombosis.

Mean platelet volume and sepsis

Platelets play an important role in the pathophysiology of sepsis. Platelets cause activation of the innate immune system as mentioned in figure below. Hence thrombocytopenia may be associated with dysregulated host response. (60).

Fig 9: Demonstrates the role of platelets in activation of immune system in sepsis.

(60)

Even though low platelet count is common in sepsis, cause of death is rarely due to bleeding. Platelets release various cytokines that interact with leukocytes and endothelium to cause micro thrombi formation. These mechanisms are useful in containing sepsis in localised infection whereas in severe infections it becomes maladaptive and dysregulated leading to multiorgan dysfunction. (61)

Thrombocytopenia in sepsis is caused by decreased production or increased destruction of platelets. The etiology of thrombocytopenia is multi-factorial. However the most common cause of thrombocytopenia is platelet activation followed by platelet consumption, platelet destruction or thrombus formation(62). The bone marrow tries to compensate this by 46

increase in platelet production which leads to release of immature platelets into peripheral circulation (36).Young platelets have large surface area. Moreover platelets change their shape from discoid to spherical along with formation of pseudopods during platelet activation to achieve a large surface area (63).

Fig 10: Shows a resting platelet and an activated platelet.

(64)

Thrombocytopenia is known to be an adverse prognostic factor in sepsis. However it is unclear whether thrombocytopenia causes adverse outcome or whether it is a biomarker of disease severity (60). Various studies have been done that looked at various platelet indices and its association with mortality and multi-organ dysfunction as mentioned in the table below.

Table 6: Platelet parameters as markers of disease severity.

Biomarker Outcome

Thrombocytopenia Mortality

Impaired platelet function MOF

Impaired platelet aggregation MOF and mortality

Immature platelet fraction Sepsis progression

TPO MOF

Platelet neutrophil aggregates MOF

(62)

Mean platelet volume is a simple and cost effective platelet index that measures the average volume of platelets. The vertical volume of the platelet is analysed by deformation of the electric field based on impedence technology (64). Destructive thrombocytopenia is characterised by high MPV levels where as hypoproliferative thrombocytopenia is characterised by low MPV levels. High mean platelet volume was associated with statistically significant difference between survivors and non survivors in a study from

China among patients with septic shock (36).

Zang et al in their study found that patients with high MPV had high APACHE and SOFA scores. High MPV was useful in predicting mortality with a sensitivity of 58.2% and specificity of 90.2% (65). In another study done among patients admitted with nosocomial sepsis it was noted that patients high MPV was associated with gram positive bacteraemia for the first 3 days and gram negative sepsis for the first 5 days . Fungal septicaemia had a strong association with MPV(66). 48

TEG and MPV are automated tests. If abnormal TEG and MPV predict poor outcomes in sepsis, incorporation of these in evaluation of sepsis in secondary care centres may facilitate early detection of DIC and MOF and referral to higher centres. Similarly if TEG can predict requirement of blood transfusions, blood products may be kept arranged before clinical bleeding occurs in centres with no facilities for blood products. Hence it is worthwhile to study correlation between these tests and mortality in sepsis.

Materials

and

Methods

Study design

This was a hospital-based prospective study.

Patient Selection

Patients with a diagnosis of severe sepsis who were admitted under the Department of

General Medicine in the medical ICU/HDU of Christian Medical College, Vellore, from

April 2017 to June 2018, were screened for eligibility for enrolment in the study.

Inclusion Criteria

All patients with severe sepsis admitted in to the medical/HDU with no clinical bleeding were screened.

Exclusion criteria

- Age under 18 years

-Usage of oral anticoagulants,

-Treatment with platelet inhibitors

- Pre existent haematological or hepatic disorders

-Patients with malignancy

-Patients who received transfusions

-Patients who received haemodialysis prior to sampling

-Patients not recruited for >24 hours

-Patients with any clinical bleeding 51

-Envenomation

-Patients who received heparin for prophylaxis of deep vein thrombosis

Definition of terms

Severe sepsis was defined as suspected or confirmed infection and fulfilling ≥ 1 of the following criteria for sepsis with atleast 1 organ dysfunction.The criteria for sepsis was

(67)

General variables

-Fever: Core temperature >38o C

-Hypothermia: Core temperature<36 OC

-Elevated heart rate >90 bpm

-Tachypnoea

-Altered mental status

-Substantial edema/positive fluid balance (>20ml/kg body weight over 24 hours)

-Hyperglycemia (plasma glucose> 120 mg/dl in the absence of diabetes)

Inflammatory variables

-Leukocytosis (white cell count >12,000 /mm3)

-Leukopenia (white cell count <4,000/mm3)

-Normal white cell count >10% immature forms 52

-Elevated C reactive protein (>2 SD above the upper limit of normal)

-Elevated procalcitonin (2 SD above the upper limit of normal)

Tissue perfusion variables

Elevated lactates>1mmol/litre

Decreased capillary refill or mottling

Organ dysfunction was defined as presence of one or more of the following features.

-Acute oliguria< 0.5mL/kg/hr for more than 2 hrs despite adequate fluid resuscitation

-Arterial hypoxemia Pao2/Fio2 <300

-Increase in creatinine> 0.5mg/dL from the baseline

-Total bilirubin > 4mg/dL

-Platelet count < 100,000 µL

- Coagulopathy (international normalized ratio > 1.5 or APTT>60 sec

-Paralytic ileus

Community acquired pneumonia:

Patient with shortness of breath, cough with or without expectoration, pleuritic chest pain with atleast one of the following symptoms(viz malaise, fever, chills and rigors) with new chest signs not explained by any other illness(68).

Nosocomial pneumonia: 53

When there were new opacities on the chest radiograph with 2 of the following , new onset or worsening cough or dyspnoea or altered mental status in the elderly, new onset purulent sputum or change in sputum character, worsening gas exchange, fever, leukocytosis or leucopenia and no other cause identified.

Acute central nervous system (CNS) infection:

Patient with two of the following symptoms (viz, headache, fever, dizziness, change in level of consciousness or confusion , localizing neurological signs AND one of the following (organism identified on microscopic examination of cerebrospinal fluid, brain tissue, abscess OR imaging suggestive of acute CNS infection OR diagnostic antibodies for an organism)(69).

Scrub typhus :Positive scrub IgM ELISA and defervesence within 48hrs of initiation of

Doxycycline or Azithromycin therapy or with the presence of an eschar and a positive IgM

ELISA(70). Other infections will be diagnosed based on standard guidelines.

Among nosocomial infections that develop in ICU, only patients who developed catheter related blood stream infections were included in the study. A diagnosis of catheter related blood stream infection(CRBSI) was made when there was systemic inflammatory response attributed to an intravascular catheter with differences in growth between catheter and peripheral blood cultures or by quantitative culture of the catheter tip(71).

However as most of these patients had received heparin for deep vein thrombosis, such patients could not be included.

Normal values in TEG

The variables considered in TEG were r time, k time, alpha angle, maximum angle and lysis.

Table 7: Normal values of TEG parameters as on our accredited lab

r time: 3-8 minutes,

k time 1-3 minutes,

alpha angle: 55-78 degrees, maximum amplitude 51-69 mm, ly30 0-8%.

The normal value of mean platelet volume of our laboratory is 5-10 fl.

Hypercoagulable state was defined as TEG values with reduced k and r times and increased maximum amplitude and alpha angle .Hypocoagulable state was defined as prolonged r and k times and reduced MA and alpha angle(37) .

It was a prospective observational study which was conducted among patients admitted under the department of General medicine in the medical ICU/HDU from April 2017 to

June 2018 after obtaining approval of the Institutional review board.

All patients with a diagnosis of severe sepsis without clinical bleeding were included in the study. An informed consent was taken from the patients prior to enrolment. Data collection was done using a clinical research form. The form included baseline characters and details for calculation of SOFA score. 2.8ml of blood was collected in 2 citrated tubes for 55

assessment of TEG and 2 ml of blood was drawn in 1 EDTA tube for measurement of mean platelet volume through vacutainer. These were sent immediately to the clinical pathology lab for doing TEG and MPV analysis. These patients were followed up till discharge from the hospital. The duration of ICU stay and duration of hospital stay were noted. The number of blood products transfused was also noted. Data was collected from

ICU records and from the electronic workstation.

Fig 11: Shows picture of TEG machine

Fig 12: Demonstrates tracing of TEG on the system 56

Fig 13: Demonstrates analysis of TEG being done

Sample size calculation

The sample size to study the abnormal TEG in patients with severe sepsis was found to be

85 patients, as per the formula given below:

2 푍훼/2푃푄 푛 = 푑2

P – prevalence of severe sepsis

Q – 100 – P d – precision

Table 8: Estimation of sample size

Standard Deviation 1.65 1.65 1.65 1.65

Absolute Precision 0.2 0.3 0.35 0.4

Desired confidence level (%) 95 95 95 95

Required sample size 261 116 85 65

Based on KILIC et al (2012), the mean(standard deviation) of thromboelastography in

sepsis was 3.37(1.65). With 0.35% precision level and 95% confidence level, the required

sample size was 85.

Statistical analysis

Data was screened for outliers and extreme values using Box-Cox plot and histogram (for shape of the distribution). Summary statistics was used for reporting demographic and clinical characteristics.

t-test was use for analysis of continuous data with Normal distribution and Mann-

Whitney U test for data with non- Normal distribution. Chi-square test was performed for categorical variables and the outcome variable. Differences were considered significant at p<0.05.

Univariate analysis was performed on the pre hoc likely to be associated with a poor outcome (mortality). This would include age, gender, severity of illness, lag time to presentation and organ dysfunction. In addition TEG and MPA were assessed on univariate analysis. All the statistical analysis was performed using SPSS 25

Fig 14: Detailed Diagrammatic Algorithm of the Study

Medical ICU/HDU from April 2017 to June 2018 : All patients with severe sepsis: 241

87 patients recruited in to the study

Excluded: 154

Clinical bleeding:26 • Informed consent Transfusions:8

Use of Heparin/aspirin:91 • Data collection using clinical research form Others :29

• Analysis for TEG and MPV

Analysis

TEG with outcome

TEG with SOFA

TEG with conventional tests

TEG with transfusion of blood products

Results

Demographic characters

A total of 241 patients were screened and 87 patients were included in the study. 91 patients were excluded in view of being administration of oral on parenteral anticoagulants

.26 patients were excluded in view of clinical bleeding.

Age distribution

The age of the patients in the study group ranged from16 to 85 years. Majority of patients were aged between 56-65 years.

Table 9: Age distribution of patients with severe sepsis

Age group (years) No: of patients (%)

16-25 9 (10.3%)

26-35 9(10.3%)

36-45 15(17.2%)

46-55 17(19.5%)

56-65 24(27.5%)

66-75 12(13.7%)

76-85 1(1.1%)

Gender distribution

There were 49 males (56.3%) and 38 females (43.7%) in the study.

Fig 15: Pie diagram demonstrates gender distribution of patients 62

38(43.7%) 49(56.3%) Males Females

Gender distribution

Comorbidities of the patients

Table 10: Demonstrates the comorbidties of the patients

Baseline characters Number

Charlson comorbidity index 1

Diabetes 35(40.2%)

Hypertension 32(36.7%)

SOFA score at admission(median and IQR) 8 (6-11)

Etiology of sepsis

Fig 16: Demonstrates the etiology of sepsis in our patients

25 Etiology of sepsis

Series1 5 Series2

Frequency of different types of infection

Table 11: Shows the spectrum of patients with bacteraemia

Blood culture positivity 25(28.7%)

Gram negative organisms 20(76%)

Multidrug Resistant organisms 10(38.4%)

Extended spectrum beta lactamase inhibitors(ESBL) 7

Carbapenem resistant organisms(CRO) 1

Colistin resistant organism 1

Methicillin resistant staphylococcus aureus(MRSA) 1

Baseline blood results

Table 12: Demonstrates various coagulation parameters

Baseline characters Mean

Hemoglobin 11.03mg/dL

Platelets (median and IQR) 1,43,000

(71,0000-2,41,000)

Prothrombin time 14.18

Activated prothrombin time 43

R time 6.9

K time 1.9 (1.2-3.4) 65

Alpha angle 58.9

Maximum amplitude 59.45

Mean platelet volume 10.7 fL

Primary outcome

Fig 17: Demonstrates the primary outcome

Outcome

5(5.7%)

21(24.1%) Alive Died 61(70.1%) DAMA

Mortality in bacteraemic patients

Tables 13: Demonstrates compares the mortality in bacteraemic and non bacteraemic patients

Mortality No mortality P value

Bacteraemia(n=25) 12 13 0.029

No bacteraemia(n=62) 15 47

Coagulation profile of patients based on R time

Tables 14: Comparison of mortality in patients with hypercoagulable, normocoagulable and hypocoagulable state based on R time

R time Total Death Alive A vs B B vs C

A Hypercoagulable 3(3.4%) 1(33.3%) 2(66.7%) 0.718

state (0-2.99)

B Normal(3-8) 58(66.7%) 14(24.1%) 44(75.9%)

C Hypocoagulable 26(29.9%) 12(46.2%) 14(53.8%) 0.04

state(>8)

Tables 15: Comparison of mortality in patients with hypercoagulable, normocoagulable and hypocoagulable state based on K time

K time(n=87) Total Death Alive A vs B B vs C

Hypercoagulable 8(9.3%) 3(37.5%) 5(62.5%) 0.437

A state (0-0.9)

Normal(1-3) 53(61.6%) 13(24.5%) 40(75.5%)

Hypocoagulable 25(29.1%) 10(40%) 15(65%) 0.074

C state(>3)

Tables 16:Comparison of mortality in patients with hypercoagulable, normocoagulable and hypocoagulable state based on alpha angle.

Alpha Total Death Alive A vs B B vs C

angle(n=86)

A Hypercoagulable 3(3.4%) 2(66.7%) 1(33.3%) 0.074

state(>78)

Normal(55-78) 60(69%) 13(21.7%) 47(78.3%)

Hypocoagulable 23 11(47.8%) 12(52.2%) 0.019

C state (0-54) (26.4%)

Tables 17: Comparison of mortality in patients with hypercoagulable, normocoagulable and hypocoagulable state based on maximum amplitude.

Maximum Total Death Alive A vs B B vs C

amplitude(n=85)

A Hypercoagulable 27(31.8%) 8 19(70.4%) 0.769 (29.6%)) state(>69)

Normal(51-69)) 38(44.7%) 10(26.3%) 28(73.7%)

Hypocoagulable 20 (23.5%) 8 (40%) 12(60%) .284

C state (0-50) 68

Fig 18: Summarises coagulation abnormalities in patients with severe sepsis based on various parameters in TEG

60 58 70.00% 53

60.00% 38

50.00% 27 26 25

40.00% 23 20

Hypercoagulable state Normal coagulation Hypocoagulable state 30.00% 8

3 3 20.00%

10.00%

0.00% R time K time Alpha angle Maximum amplitude

Secondary outcomes

Table: 18: Demonstrates various secondary outcomes

Duration of ICU stay (median and IQR) 7(4-10)

Duration of hospital stay 11.5(7-17.5)

Transfusions 28(32.1%)

Platelets 7

Fresh frozen plasma 9

Cryoprecipitates 3

Packed red cells 19

Primary outcome and TEG parameters

Table: 19: Demonstrates correlation between TEG parameters and mortality

No Mortality Mortality p value

R time 6.4253 8.0015 0.032

K value 2.5983 3.9726 0.090

Alpha angle 62.245 51.754 0.014

Maximum amplitude 61.260 55.465 0.099

Lysis 30 1.082 1.560 0.339

TEG parameters and transfusion of blood products

Table 20: Demonstrates association of TEG parameters and requirement of transfusion

Transfusions No transfusions p value

R time 7.3620 6.6789 0.344

K value 4.2743 2.3672 0.015

Alpha angle 54.444 61.040 0.182

Maximum amplitude 53.174 62.386 0.026

Lysis 30 1.807 .913 0.126

Transfusion of FFPs

Table 21: Demonstrates association of TEG parameters and requirement of transfusion of fresh frozen plasma

Transfusions No transfusions p value

R time 9.2180 6.6153 0.014

K value 5.5300 2.6995 0.015

Alpha angle 41.240 61.420 0.001

Mean amplitude 45.220 61.388 0.001

Lysis index 2.300 1.079 .082

Mean platelet volume 10.490 10.793 .517

Transfusion of platelets

Table 22: Demonstrates association of TEG parameters and requirement of transfusion of platelets

Transfusions No transfusions p value

R time 8.8333 6.6931 0.055

K value 8.5389 2.3886 0.000

Alpha angle 29.533 62.526 0.000

Mean amplitude 30.389 62.912 0.000

Lysis .667 1.288 .402

Mean platelet volume 10.356 10.805 .359

Transfusion of cryoprecipitates

Table 23: Demonstrates association of TEG parameters and requirement of transfusion of cryoprecipitates

Transfusions No transfusions p value

R time 9.8000 6.7754 .063

K value 12.0000 2.5923 0.000

Alpha angle 23.475 60.810 0.000

Mean amplitude 22.775 61.300 0.000

Lysis index .250 1.270 .343

Mean platelet volume 9.275 10.830 .027

Correlation between conventional tests of coagulation with TEG parameters

Table 24: Shows correlation between PT and TEG parameters

PT R time K time Alpha Maximum Lysis MPV

angle amplitude index

Pearson 0.207 0.103 -0.103 -0.209 0.95 -0.153 correlation p Value .059 .353 .098 .058 .395 .168

Table 25: Shows correlation between APTT and TEG parameters

APTT R time K time Alpha Maximum Lysis MPV

angle amplitude index

Pearson 0.26 0.18 -0.24 -0.35 0.32 -0.05 correlation p Value 0.016 0.102 0.027 0.001 0.003 0.626

Table 26: Shows correlation between Platelets and TEG parameters

Platelets R time K time Alpha Maximum Lysis MPV

angle amplitude index

Pearson correlation -0.266 -0.271 0.29 0.51 -0.12 -0.25 p value 0.013 0.011 0.005 0.000 .910 0.018 73

Correlation between TEG parameters and duration of hospital stay

Table 27 : Demonstrates correlation between various TEG parameters and ICU stay and hospital stay

ICU stay Hospital stay

Pearson p value Pearson p value

Correlation Correlation

R time -0.205 0.068 -0.175 0.104

K value -0.020 0.860 -0.077 0.479

Alpha angle 0.023 0.842 0.059 0.590

Maximum amplitude 0.078 0.497 0.048 0.658

Lysis index -0.034 0.768 -0.085 0.438

Mean platelet volume -0.083 0.465 -0.005 0.964

TEG parameters and its correlation with SOFA score

Table 28: Demonstrates correlation between various TEG parameters and SOFA score

SOFA score

Pearson Correlation p value

R time 0.222 0.070

K value 0.370 0.002

Alpha angle -0.389 0.001

Maximum amplitude -0.441 0.000

Lysis index -0.084 0.500

Mean platelet volume -0.025 0.840

Scrub typhus and TEG

Survivors Non survivors P Value

R time 7.09 7.75 0.749

K time 2.77 4.37 0.408

Alpha angle 59.35 54.90 0.696

Maximum 62.20 57.72 0.585 amplitude

Lysis index 0.81 1.80 0.354

MPV 11.48 10.94 0.464

Discussion

Epidemiology of sepsis

Sepsis is defined as life threatening organ dysfunction in response to dysregulated host response to infection(13). Even though it is difficult to ascertain, the global burden of sepsis is estimated to be around 30 million (72). There has been a trend towards increase in the reported incidence of sepsis due to various factors like increase in the elderly population, better identification and reporting of sepsis (13).

In our study 56% of patients were males which were similar to many studies conducted in

India. 40% of the patients had diabetes and 36% of the patients had hypertension. The most common cause of sepsis in a study in India was respiratory tract infection(73). In our study the most common cause of sepsis was scrub typhus as the study was conducted during an outbreak of Scrub typhus followed by lower respiratory tract infection.

Bacteraemia was seen in 28.7% of the patients out of which 73% of the patient had gram negative bacteraemia. This was similar to a study by Chatterjee et al in India where 73.4% of the patients had gram negative sepsis (73).

Sepsis and coagulopathy: hypercoagulable state versus hypocoagulable state

Coagulation abnormalities play a pivotal role in sepsis. It can cause disseminated intravascular coagulation characterised by widespread thrombosis and major bleeding on the other side. In a study by Muzaffar et al patients with severe sepsis were either normocoagulable (56%), hypercoagulable (27%) or hypocoagulable(17%). It was found that patients without shock had a trend towards hypercoagulant state whereas patients with 77

shock showed a trend towards hypocoagulant state. Coagulation abnormality in these patients were assessed using the coagulation index. Coagulation index <3 was considered to be hypocoagulable and a coagulation index >3 was considered to be hypercoagulable state (34). Coagulation index was not available in our centre and hence statistical analysis was performed with individual parameters of TEG and the outcome. The results of our study showed that based on R, K, alpha angle between 61%-69% of the patients are normocoagulable where as only 44.7% had a normal coagulation based on MA. Even though these patients had no clinical bleeding at the time of recruitment 23-29% of the patients had a hypocoagulable state.

Muller et al in a systematic review found that patients with severe sepsis can have a hyper or hypocoagulable state and that patients with hypocoagulable profile showed a trend towards mortality which was similar in our study(74). The wide variability in TEG results can be explained by the pathophysiology of DIC in sepsis. The course of DIC has 3 consecutive stages.

1. The hypercoagulable state: The stage of active coagulation

2. The stage of coagulation exhaustion

3. The stage of hyper fibrinolysis characterised by clinical bleeding(75).

The coagulation abnormality in patients with severe sepsis may depend upon the time at which TEG was done. Serial assessment of TEG would give a holistic picture of the coagulation abnormality. Due to logistic reasons TEG was done only once within 24 hours of ICU admission. 78

Even though TEG analysis was done within 24 hours of ICU admission, majority of patients had a hypocoagulable profile. This could be due to various reasons. Due to limited availability of intensive care beds majority of these patients were managed in the general wards and are shifted to ICU at a later time. Being a tertiary care centre we render care to patients referred from other centres at later stages of sepsis. Another reason was that there was an outbreak of scrub typhus during the study period. 24% of patients had scrub typhus which is a haemorrhagic rickettsial fever(76).It is unclear that increased number of this group of patients would have led to alteration of results.

Another explanation for wide variability in coagulation profile is the presence of 2 entities namely overt DIC and non overt DIC as per the international society of thrombosis and haemostasis. Non overt DIC indicates subtle coagulation dysfunction that has not reached the decompensation stage whereas overt DIC indicates frank DIC with clinical bleeding

(77). In a study by Brenner et al it was shown that patients with non overt DIC had a hypercoagulant state and those with overt DIC had a hypocoagulant state (78). However our patients with no overt signs of DIC had a hypocoagulable state.

Another important use of TEG is its ability to predict fibrinolysis in earlier stages of DIC.

In a study thromboelastography was compared with procalcitonin, CRP and IL-6 as diagnostic tests for severe sepsis. It was noted that lysis index at a cut off of >96.5% had a sensitivity of 84.2% and a specifity of 94.2% in the diagnosis of severe sepsis (79).

However in our centre the lysis index was unavailable for many of the samples that the utility of this parameter in diagnosis of sever sepsis cannot be commended.

Sepsis and mortality

Sepsis is the second leading cause of mortality worldwide and it affects both developed and developing countries with equal ferocities(73,80). As per data in 2017 every year 6 million people die due to sepsis (81). The mortality rates in India in patients with severe sepsis are not very different. Mortality rates in northern part of India and southern part of

India were 63.5% and 67.5% respectively (73, 82). However the mortality rate in our study was only 24.1%. This would have been due to our strict inclusion criteria which excluded all patients with clinical bleeding and patients on aspirin. The mean Charlson comorbidity index of our patients was only 1 which could have also reduced the mortality rates.

Bacteraemia is known to be adverse prognostic marker in sepsis. 48% of our patients who had blood stream infection succumbed to their illness in comparison to 31% of patients with severe sepsis who were admitted due to other infections and this was found to be statistically significant. This was similar to study done by Mansur et al where it was found that primary bacteraemia was a significant covariate for mortality(83).

TEG as a prognostic factor

As sepsis is associated with a high mortality, correct judgement on the severity of the illness and early goal directed therapy is imperative. Various parameters have been studied in the past to assess the severity of sepsis. In a study among patients admitted with severe sepsis to intensive care unit it was found that need for mechanical ventilation, low platelet count, elevated levels of CRP were independent predictors of mortality(82). As severe sepsis is associated with coagulation abnormality we assessed the utility of thromboelastography as a prognostic marker in sepsis. 80

a)TEG and organ failure

Various parameters of TEG correlated well with organ failure. K time showed positive correlation with SOFA score with p value of 0.002 whereas alpha angle and maximum amplitude showed negative correlation with SOFA score with p values f 0.001 and 0.000 respectively. This was similar in a study by Haase et al where clot formation time, alpha angle and maximum amplitude showed moderate correlation with SOFA score (84). b)TEG and mortality

In our study it was noted that patients who had an adverse outcome had a hypocoagulable state.

R value is the time from the initiation of the study to the initiation of clot formation. It depends on the clotting factors and it is analogous to PT, APTT. In our study it was noted that patients who died had a prolonged R value in comparison to people with better outcome and this was found to be statistically significant (p:0.032).This was similar to studies conducted in patients with sepsis where increased clot formation time was associated with a hazard ratio of 6.03(84).

The next step in coagulation is clot formation. This is indicated by the K value and it depends upon the level of fibrinogen .K value was prolonged in patients with adverse outcome. This was not statistically significant. Similar results were obtained in a study by

Yang et al where K value did not show significant difference between the 2 groups(85). 81

Similarly the rate of clot formation was less in the patients succumbed to their illness which is indicated by the alpha angle which was statistically significant (p:0.014). It indicates reduced fibrinogen in the body. In a study done in 92 patients with sepsis R time and alpha angle was associated with increased mortality while in multivariate logistic regression analysis only R value came significant(85).

The last step in the coagulation pathway is clot stabilisation. Maximum amplitude which denotes the clot strength was comparatively lower in patients who died even though this was not statistically significant.

In a study that showed comparison between TEG, SAPS II scores and SOFA score, it was found that TEG is a better predictor of mortality(79). Similarly in a systematic review it was noted that weak clot strength and hyperfibrinolysis was associated with increased morbidity and mortality(86).

Haase et al in their study did TEG for initial 5 days in ICU. It was noted that any change in

TEG parameter towards hypocoagulable state even though they were within the normal range was associated with increase in mortality. It needs to be noted that there are no universal reference ranges for these visco elastic tests(84). c)TEG and duration of hospital stay

Our study did not find any difference in duration of hospital of ICU/ hospital stay among patients with abnormal TEG. This may be in part due to the fact that the patients who had abnormal parameters succumbed to their illness early thus reducing the duration of hospital stay.

TEG and its utility in predicting transfusions

TEG has been used to tailor transfusions in various studies. In our study it was found that prolongation of R time, K time, low alpha angle and low maximum amplitude was associated with increased number of transfusions of fresh frozen plasma which was statistically significant. Similarly patients who required transfusion of platelets and cryoprecipitates had abnormal K time, alpha angle and maximum amplitude and was statistically significant. The results were similar in a descriptive systemic review where it was noted that reduced alpha angle and maximum amplitude was associated with greater need for transfusion of platelets, FFPs and packed red cells(86). In our ICU transfusion is done only in case of clinical bleeding and platelet transfusions are done prophylactically if it is less than 20,000 to prevent intracranial bleeds. This indicates that these patients with hypocoagulable parameters on TEG would have had clinical bleeding during their stay in the ICU.

Various studies looked in to the outcome of patients who were transfused based on TEG parameters. Mohammed et al in a retrospective study compared TEG based transfusion with conventional transfusion strategies. It was noted that in TEG based transfusion caused reduction in transfusion of packed cells and FFPs while there was increase in transfusion of platelets. The patients with TEG based transfusion had a shorter ICU stay and hospital stay(87). Most of these studies are conducted on post trauma patients and there is limited data on patients with severe sepsis. Further studies are required in this regard.

TEG and its comparison to conventional tests of anticoagulation

In a study by Sherma et al on patients going for cardiac surgery it was noted that platelets and fibrinogen correlated well with MA and alpha angle(88). Another study conducted in intensive care unit noted significant correlation between various parameters in TEG and conventional tests of coagulation. However the consistency was weak(89).

In our study it was noted that PT did not correlate with various TEG parameters. R time, alpha angle , maximum amplitude and lysis index was abnormal when the APTT was prolonged and this was statistically significant. Similarly low platelets were associated with abnormal R time, K time, alpha angle and maximum amplitude. However it needs to be noted that few samples were not taken at the same time when TEG was done and hence the results needs to be interpreted with caution.

TEG and scrub typhus

TEG has been studied in haemorrhagic fevers. Mahopatra et al used TEG as a guide to diagnose early DIC in patients with malaria(90). TEG was studied in dengue patients and it was found that factor deficiency was the most common abnormality in dengue followed by platelet dysfunction and fibrinolysis. Platelet number did not correlate with platelet function(91).We did a subgroup analysis on patients with scrub typhus as 27% of the patients had a diagnosis of scrub typhus. It did not show any significant differences in

TEG parameters among the survivors and non survivors. However it needs mention that all patients with clinical bleeding at the time of admission were excluded from the study.

Hence it is unclear if there would be any differences in the parameters if this group of 84

patients are included in the study. To our best knowledge there are no studies where thromboelastography was used to assess patients with scrub typhus.

Mean platelet volume

Mean platelet volume is the average volume of platelets. Young platelets are larger than older platelets and they have higher thromboxane A2, p selectin ,glycoprotein IIIa and more granules. More the number of young platelets and thereby higher MPV indicates increased platelet production and inflammation (92).

Sadaka et al in their study on 450 patients with septic shock in the ICU found that MPV was not useful as a predictor in mortality(93).Similarly our study did not show any correlation between MPV and mortality. However systematic review revealed that gradual increase in mean platelet volume during the admission is associated with increase in mortality and that mean MPV at the time of discharge was higher in non survivors in comparison to survivors.(92).In our study MPV was done only once and repeated measurements were not done.

Various other studies showed that the ratio between MPV and platelet count was significantly associated with 28 day mortality. This is explained by the fact that large platelets and low platelet count is indicative of increased platelet reactivity and increased platelet destruction (94).

Mean platelet volume may depend on the type of analysing machine. MPV was done simultaneously in three different analysers and there was wide variation in the results. This also would have lead to error in the final analysis.

Conclusion

• Mortality in severe sepsis with no clinical bleeding was 24.1% in our tertiary care centre

25(28.7%) had bacteremia. Patients with bacteraemia are at higher risk of mortality than patients with severe sepsis due to other reasons.

• Majority (44-69%) of patients with severe sepsis with no clinical bleeding had a normocoagulable state based on TEG parameters. Between 23%-29% of the patients had a hypocoagulable state. These patients were at increased risk of mortality.

• Non survivors of sepsis had prolonged R time and K time and reduction in alpha angle and maximum amplitude. This was statistically significant for R time (p:0.032) and alpha angle

(p:0.014). TEG parameters may be used as prognostic factors in sepsis.

• There was positive correlation with K time and SOFA score (p:0.002)and negative correlation with alpha angle(p:0.001) and maximum amplitude(p:0.000) and may be used as determinants of organ dysfunction.

• Various parameters in TEG showed correlation with conventional tests of coagulation.

APTT showed positive correlation with R time and lysis index and negative correlation with alpha angle and maximum amplitude. Platelets showed negative correlation with R time, K time and MPV and positive correlation with alpha angle and maximum amplitude. However in all the samples conventional tests were not done simultaneously with TEG. 87

• All the TEG parameters were significantly different between patients who received FFPs and who did not require FFPs. K value, alpha angle and MA was significantly different between the 2 groups who received platelets and cryoprecipitates.

• Various parameters of TEG were unable to predict duration of ICU stay or hospital stay.

This may be due to the fact that sick patients were succumbed to their illness early

• TEG parameters were not different among the survivors and non survivors of scrub typhus.

However only patients without clinical bleeding were included in the study. Further studies are required to assess the coagulablity in scrub typhus.

• Thromboelastography is an expensive test and it requires expertise. However it may be used as a prognostic factor in sepsis. With the use of citrated samples these blood samples can be stored before analysis. This may permit transfer of samples to referral centre for analysis. TEG may be used as a guide to tailor transfusions. If it can be incorporated into secondary care centre settings it may used as a test to decide on referral to another centre or making arrangements for blood products early before clinical bleeding sets in. Lysis index is useful in recognition of early DIC. ROTEM may be a better technology for assessment of the same.

• Mean platelet volume was not different between the survivors and non survivors. It cannot be used as a guide for transfusion of cryoprecipiates or FFPs. 88

Limitations

Of the

Study

-Large proportion of adult patients could not be included because they were on aspirin or they received heparin prior to inclusion. These patients could have been included with addition of heparinise in the sample.

-Conventional coagulation parameters were not done simultaneously in all the samples.

Correlation of TEG parameters with conventional tests for anticoagulation may not be accurate.

-Patients who were included did not have clinical bleeding at the time of inclusion, but they were not followed up to assess for clinical bleeding

-Due to logistic reasons TEG was done only at the time of admission. Serial TEG measurements would have given a better picture of the coagulopathy in sepsis.

-The results of lysis index were unavailable for significant amount of samples. Lysis index is important in the diagnosis of early phases of DIC. Lysis index is better available in

ROTEM.

-There was wide variability in mean platelet volume done in 3 different analysers.

Standardised values are required for analysis.

-There were few missing TEG variables from the lab that culd have altered the resuts.

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Sep 11];2016. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4757676/

93. Mean Platelet Volume is not a Useful Predictor of Mortality in Septic Shock. J

Blood Disord Transfus. 2014 Jan 9;5(2):1–3.

94. Oh GH, Chung SP, Park YS, Hong JH, Lee HS, Chung HS, et al. Mean Platelet

Volume to Platelet Count Ratio as a Promising Predictor of Early Mortality in Severe

Sepsis. Shock. 2017 Mar;47(3):323.

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ANNEXURE I: IRB APPROVAL FORM

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•

106

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108

ANNEXURE II: INFORMATION SHEET AND CONSENT FORMS:

Title: Thromboelastography and mean platelet volume as prognostic factors in sepsis

INFORMATION SHEET

NAME OF PARTICIPANT:

You are invited to take part in this study. The information in this document is meant to help you decide whether or not to take part in the study. Please feel free to ask if you have any queries or concerns.

What is the study about?

Severe sepsis is a disease condition caused by infection. Severe infection in later stages can cause bleeding and death. Early diagnosis of infection helps in early initiation of antibiotics and prevention of complications.

Thromboelastography is a test used to study clotting mechanism of the body. Mean platelet volume is a test that helps to know the average size of platelets. Abnormal values in this test can predict poor outcomes.

Our study is to look for association between abnormal thromboelastography and mean platelet volume and adverse outcome in patients with severe sepsis.

If you take part, what will you have to do?

If you take part in the study, 5 ml of blood will be taken for analysis on the day of admission. No more blood samples will be taken for study purpose. 109

Are there any risks for you if you take part in the study?

Participation in the study only involves only withdrawal of 5ml of blood. We do not expect any injury to happen to you.

Do you have to pay?

The cost of the test will be covered in special funds and you will not have to pay for the blood test.

What are the benefits to you if you take part in the study?

Thromboelastography and mean platelet volume results will be available to the treating team. It will help them to tailor blood transfusions and other treatments based on these reports.

What are the possible benefits to other people?

If abnormal values in TEG and MPV on the day of admission predict adverse outcomes it would help in early up gradation of antibiotics .

Can you decide not to participate?

Your participation in this study is entirely voluntary and you are also free to decide to withdraw permission to participate in this study. If you do so, this will not affect your usual treatment at this hospital in any way.Your doctor will still take care of you and you will not lose any benefits to which you are entitled.

Will your personal details be kept confidential? 110

The results of this study may be published in a medical journal, but you will not be identified by name in any publication or presentation of results. However, your medical notes may be reviewed by people associated with the study, without your additional permission, should you decide to participate in this study.

If you have any further questions, please contact Dr.FibiNinan K (Ph: No:

7639718294) or email: [email protected]

111

CONSENT FORM

TITLE:Thromboelastography and mean platelet vlume as prognostic markers in sepsis

Study Title:

Thromboelastography and mean platelet volume as prognostic markers in sepsis: an

observational study

Study Number:

Participant’s name: CMC Hosp No:

Date of Birth / Age (in years):

I______

______, son/daughter/husband/wife of ______

(Please tick boxes)

Declare that I have read the information sheet provided to me regarding this study and have clarified any doubts that I had. [ ]

I also understand that my participation in this study is entirely voluntary and that I am free to withdraw permission to continue to participate at any time without affecting my usual treatment or my legal rights. [ ]

I understand that I will receive free treatment for any study related injury or adverse event, but I will not receive any other financial compensation. [ ] 112

I understand that the study staff and institutional ethics committee members will not need my permission to look at my health records even if I withdraw from the trial.

I agree to this access. [ ]

I understand that my identity will not be revealed in any information released to third parties or published. [ ]

I voluntarily agree to take part in this study. [ ]

Signature (or Thumb impression) of the Subject/ Legally Acceptable

Representative:______

Date: _____/_____/______

Signatory’s Name: ______

Signature of the Investigator: ______

Date: _____/_____/______

Study Investigator’s Name: ______

Signature of the Witness: ______

Date:_____/_____/______

Name of the Witness: ______

113

INFORMATION SHEET AND CONSENT FORM IN TAMIL

114

115

ஆய்வில்பங்கேற்ேஒப்ꯁதல்ப羿வம்:

ஆய்ퟁஎண்: ______

பங்கேற்பவரின்믁தலெ폁த்鏁க்ேள்: ______

பங்கேற்பவரின்லபயர்: ______

பிறந்தகததி / வய鏁: ______

(பங்கேற்பவர்)

(i) நான் ______கததியிட்டகேகெ埂றப்பட்翁ள்ளஆய்ퟁதேவல்தாளளப羿த்鏁ꯁரிந்鏁லோள் ளퟁம்ேற்쟁ம்கேள்விேளளகேட்ேퟁம்வாய்ப்ꯁேிளடத்த鏁என்쟁உ쟁திஅளிக் ேிகறன்.

(ii) இந்தஆய்வில்என்பங்埁தன்னார்வோன鏁என்쟁ம், எந்தோரண믁ம்இல்ொேல், எந்தகநரத்தி쯁ம்இந்தஆய்விெி쏁ந்鏁நான்விெேிலோள்ள믁羿뿁ம்என்쟁ம்ே ற்쟁ம்என்ே쏁த்鏁வேவனிப்ꯁஅல்ெ鏁சட்டஉரிளேேள்இதனால்பாதிக்ேப்ப டா鏁என்쟁ம்அறிந்தி쏁க்ேிகறன்.

(iii) நான்ஆய்விெி쏁ந்鏁விெேிவிட்டா쯁ம்埂ட, தற்கபாளதயஆய்ퟁேற்쟁ம்அ鏁சம்பந்தோேநடத்தப்ப翁ம்埂翁தொனஆரா ய்ச்சிலதாடர்பாே, இந்தே쏁த்鏁வ믁ளறகசாதளனயின்பான்சர், பான்சர்சார்பில்கவளெலசய்ேிறவர்ேள், ஆய்ퟁலநறி믁ளற埁폁ேற்쟁ம்ேட்翁ப்பாட்翁அதிோரிேள்என்ே쏁த்鏁வபதிퟁ ேளளபதிகவ翁ேள்பார்க்ேஎன்அꟁேதிகதளவயில்ளெஎன்쟁ம்அறிந்தி쏁க்ேி கறன். அퟍவா쟁பார்ப்பதற்埁நான்ஒப்ꯁத쯁ம்அளிக்ேிகறன்.எனிꟁம், 믂ன்றாம்தரப்பிற்埁அல்ெ鏁பிர毁ரதிற்埁லோ翁க்ேப்ப翁ம்எந்ததேவெி쯁ம்எ ன்அளடயாளம்லவளியிடப்படோட்டா鏁என்쟁ம்நான்அறிந்தி쏁க்ேிகறன்.

(iv)இந்தஆய்விெி쏁ந்鏁ேிளடக்埁ம்எந்ததேவல்ேள்அல்ெ鏁믁羿ퟁேளளஅறி வியல்கநாக்ேத்திற்ோேேட்翁ம்பயன்ப翁த்ததளடயில்ளெஎன்쟁ஒப்ꯁதல்அ ளிக்ேிகறன்.

(V) நான்கேகெ埂றப்பட்翁ள்ளஆய்வில்பங்கேற்ேஒப்ꯁதல்அளிக்ேிகறன்.

பங்கேற்பவரின் / சட்டꯂர்வோேஏற்ேத்தக்ேவரின்ளேலயாப்பம் (அல்ெ鏁லப쏁விரல்கரளே )

கததி: _____ / _____ / ______116

ளேலயாப்பேி翁பவரின்லபயர்: ______ளேலயாப்பம்:

அல்ெ鏁

பிரதிநிதி : ______

கததி: _____ / _____ / ______

ளேலயாப்பேி翁பவரின்லபயர்: ______

ஆய்ퟁலசய்பவரின்ளேலயாப்பம்: ______

கததி: _____ / _____ / ______

ஆய்ퟁலசய்பவரின்லபயர்: ______

சாட்சிளேலயாப்பம்: ______அல்ெ鏁

கததி: _____ / _____ / ______

சாட்சியாளரின்லபயர்ேற்쟁ம்믁ேவரி: ______

INFORMATION SHEET AND CONSENT FORMS IN HINDI 117

118

119

अवगतसहमतत

सहमततफामम

परिक्षणशीष्रक:

परिक्षणकानाम:

परिक्षणकाक्रंमांकं :

핍य啍तीकाकु 쥍नाम: 핍य啍तीकानाम:

जन्मतारिख / उम्र

(भागीदाि)

1. मेननशचित셁पसेइसपेपिकोपढाऔिसम啍ताहुुँ, तारिख______|

इसपरिक्षणके लियेप्रशणप浍ु नके ाअवसिददयागयाहै|

2. मैअपनेइछासेइसपरिक्षाकामेभागलिया हुुँऔिकलमभीबिनाककसीलभ

कािणछोडसकताहुुँ| इसेमेिाउपिािमैककसीप्रकािकीिा饍दानहीहोगी|

3. मसै म啍ताहुुँककपरिक्षणके दोिानयाजोपरिक्षाकितेहैअयवायेचिकिसलमनतिाननयन्रण

अददकािीमिे ारिकोडदेखनेके लियेमेिाअनमु नतिने ाअवशकनहीहै|

मयै ेभीजानताहुुँककमेिापरिियगप्ु तिखाजायेगा|

4. परिक्षणमेजोभीरिपोटलमिेगीमैउसकोवैजाननकउपयोचगककेलियेिाधानहीक셂गा|

5. मइै सपरिक्षणमेभागिंग ा| 120

दतखतमरिजकाअिवाककसीभीरितेदािⴂका______

तारिख______

दतखतकारिकानाम______

परिक्षणकारिकादतखत______

तारिख______

परिक्षणऔिअनध्ु यानकारिकाहताक्षि______

साक्षीकाहताक्षि______

साक्षीकानाम______

तारिख______

ఆ롋దంతెలుపుఫో రం

: అధ్యయనం�ర్షిక

121

TELUNGU INFORMATION SHEET

: ꡍరో టోకా졍సంఖ్య : �ర్షిక సెప్స స్ోర ꡍరో గ్నసిసకాారకా졍ుగాథ్ోంబె졍ాస్ిర గ్ఫర ీమర్షయు례డియంప్ో లటో లటవా졍యయ롍

సమాచారషీ籍 PARTICIPANT NAME: 뱊కా

1. ? దాꀿగ్ుర్షం栿అధ్యయనంఏ렿టి . 遀వ్ోమ ైనసెప్ససఅనేదిసంకరమణవ్졍నసంభవంచేవ్ాయధిపర్షససి逿 . తరువ్ా逿దశ졍లో遀వ్ోఅంటువ్ాయధిరకతస్ాోవ్ంమర్షయుమరణాꀿకికారణంకావ్桍చు సంకరమణ뱊కాꡍాోరంభర్ోగ్ꀿర్ాారణꡍాోరంభయాంటీబయాటికసమర్షయుసమసయ졍ꀿవ్ారణకుసహాయప . డుత ంది . శర్ీరగ్డడకటిటవధానంఅధ్యయనంచేయడాꀿకిథ్ోంబె졍ాస్ిర గ్ఫసఅనేదిఒకపర్ీక్షర . ప్లోటలోటవా졍యయ롍అంటటఫ졍వ్찿క졍뱊కాసగ్టుపర్షమాణాꀿనతె졍ుసచకోవ్డాꀿకిసహాయపడేఒకపర్ీక్ష . ఈపర్ీక్ష졍లఅస్ాధారణవ졍ువ్졍ుప్ల졍వ్మ ైనఫ젿తా졍నచఅం桍నావ్ేస్ాతయి అస్ాధారణఅధ్యయనముమర్షయుఅసమానమ ైనశ్లోష్మంతోబవధ్పడుత ననర్ోగ్ు졍졍లప్లోటలోటవా졍యయమమర్ష . యుపో逿కయ졍ఫ젿తంమధ్యఅస్ర ససయిేష్నకాసం桍ూడండి

2. , ? 례రుꡍా졍గొనడాꀿకి 례రుఏ렿చేయా젿 , 5 . . 례రుఈఅధ్యయనం졍లꡍా졍గొంటట 렿 졀రకతంపోవ్ేశప్ెటిినర్ో灁నవశ్లోష్ణకోసం遀సచకోబడుత ంది . అధ్యయనపో뱋జనంకోసంరకతనమూనా졍ు遀సచకోబడవ్ు 3. , ? 례రుఅధ్యయనం졍లꡍా졍గొంటట 례కుఏవ్ ైనాపోమాదా졍ుఉనానయా 5ml . ఈఅధ్యయనం졍లꡍా졍గొనడం రకతంమాతోమేఉపసంహర్షం桍చకుంటుంది

례కుహాꀿజరగ్దꀿమేముకోరుకోము 4. ? 례రుచె젿ోంచా졍ా . పర్ీక్షఖ్రుుపోతేయకꀿధ్చ졍졍లకవ్쁍ఉంటుందిమర్షయు례రురకతపర్ీక్షచె젿ోంచా젿సనఅవ్సరం졍ేదచ

5. , ? 례రుఅధ్యయనం졍లꡍా졍గొంటట 례కుఏపో뱋జనా졍ునానయి 6. థ్ోంబె졍ాస్ిర గ్ఫర ీమర్షయుసగ్టుప్ో లటో లటవా졍యయమఫ젿తా졍ు栿కితసబ ందాꀿకిఅందచబవటు졍లఉంటవ . యి ఈꀿవ్ేదిక졍ప్ెైఆధారపడినరకతమార్షిడిమర్షయుఇతర栿కితస졍కుఇదిసహాయపడుత ంది 122

7. , ? 례రుఅధ్యయనం졍లꡍా졍గొంటట 례కుఏపో뱋జనా졍ునానయి 8. థ్ోంబె졍ాస్ిర గ్ఫర ీమర్షయుసగ్టుప్ో లటో లటవా졍యయమఫ젿తా졍ు栿కితసబ ందాꀿకిఅందచబవటు졍లఉంటవ . యి ఈꀿవ్ేదిక졍ప్ెైఆధారపడినరకతమార్షిడిమర్షయుఇతర栿కితస졍కుఇదిసహాయపడుత ంది 9. ? ఇతరపోజ졍కుస్ాధ్యమ ైనపో뱋జనా졍ుఏ렿టి 10. TEG MPV పోవ్ేశప్ెటిినర్ో灁న మర్షయు 졍లఅస్ాధారణవ졍ువ్졍ుపో逿కయ졍ఫ젿తా졍నచఅం桍నావ్ేసలతఅదియాంటీబయాటిక్సొకాꡍాోరంభవ్

దిి졍లసహాయపడుత ంది 11. ? 례రుꡍా졍గొనవ్దిꀿꀿరణయిం桍చకునానర్ా 12. ఈఅధ్యయనం졍ల례భవగ్స్ాామయంపూర్షతగాసా桍ఛందంగాఉందిమర్షయు례రుఈఅధ్యయనం졍లꡍా . , 졍గొనడాꀿకిఅనచమ逿ꀿఉపసంహర్షం桍చకోవ్ా졍ꀿకయడాꀿరణయిం桍చకుంటవరు 례రుఅ졍ాచేసలత . ఈఆసచప逿ో졍ల례స్ాధారణ栿కితసనచఏవధ్ంగాన ైనాపోభవవతంచేయదచ 례డాకి쁍ఇంకా례గ్ుర్షం栿జాగ్తర తగా桍ూసచకుంటవడుమర్షయు례రుఎటువ్ంటిపో뱋జనా졍నచకో

졍లితారు 13. ? 례వ్యకితగ్తవవ్ర్ా졍ురహసయంగాఉం桍బడుత ందా , ఈఅధ్యయనం뱊కాఫ젿తా졍నచమ డిక졍జరన졍లోపో桍చర్షం桍వ్桍చు . , కాꁀఫ젿తా졍పో桍చరణ졍ేదాప్ెోజ ంటటష్నకో례రుప్లరునచగ్ుర్షతం桍졍ేరు అయితే , , ఈఅధ్యయనం졍లꡍా졍గొనడాꀿకి례రుꀿరణయిం桍చకుంటట 례అదనపుఅనచమ逿졍ేకుండా . 례మ డిక졍లన籍సఅధ్యయనంతోసంబంధ్ంఉననవ్యకుత졍ుస례呍ిం桍వ్桍చు 례కుఏవ్ ైనాపోశన졍ు , . ( : : 7639718294) : ఉంటట దయచేససడా ఫస뀿నననేా ప్స కాదచ 졍ేదాఇమ యి졍 [email protected] నచసంపోదిం桍ండి

CONSENT FORM

: అధ్యయనంన ంబ쁍

: ______: ______కరతకుꀿ뱊కాకుదిం栿నప్లరుో కరతకుꀿప్లరు

/ _____ పుటిినతేది వ్యసచ 123

( ) కరతకుడు

(i) ______నేనచప్ెైనఅధ్యయనంకోసం తేదీనవ్ాోయబడినసమాచారంషీటుదివఅరించేసచకునానన

ꀿమర్షయుపోశన졍ుఅడిగేఅవ్కాశంక젿గషఉనాననచఅꀿꀿర్ాిర్షం桍చ桍చనాననచ

(ii) నేనచఅధ్యయనం졍లనాꡍా졍గొనడంసా桍ఛందమꀿమర్షయునావ్ ైదయసంరక్షణ졍ేదా桍టిపరమ ైనహ , , కుా졍ుపోభవవతం졍ేకుండా ఏకారణంఇవ్ాకుండ

ఏసమయం졍లనేనాఉపసంహర్షం桍చకోవ్桍చనꀿఅరిమయినది

(iii) , , నేనచఈకిోꀿక졍ిరయ졍గయకాస్ర ినస쁍 స్ాినసరతరపునపꀿచేయుఇతరు졍ు ఎథికసక렿టీమర్షయుꀿయంతోణఅధికారు졍ుపోసచతతఅధ్యయనంమర్షయుఈఅధ్యయన졍లఏతదచ , పర్షపర్షశ్ోధ్నꀿరాహ ం桍చటꀿ렿తహమునాఆర్ోగ్యర్షకారుడ졍桍ూడటవꀿకి . నేనచవచారణనచండిఉపసంహర్షం桍చకోనననచనాఅనచమ逿అవ్సరం졍ేదచఅꀿఅరిమయినది . , నేనచఈయాక సఅంగీకర్షసచతనాననచ యితే నేనచనాగ్ుర్షతంపుమూడవ్ꡍార్ీి졍కువడుద졍చేయబడడదꀿపో桍చర్షం栿నఏదెైనాసమాచార్ామ్లోబహ రొ . తంచెయయబడదచఅꀿఅరించేసచకునాననచ

(iv)

నేనచఈఅధ్యయనం졍లనచండిఉతిననమయిేయఅ졍ాంటిఒకడటే వ졍ేదాఫ젿తా졍ుశ్ాసతీయీ పో뱋జనం ( ) . 졍ు కోసంఉప뱋గ్ంపర్ష렿తంచేయనꀿఆంగషకర్షం桍చ桍చనాననచ

(v) . నేనచప్ెైనఅధ్యయనం졍లꡍా졍గొనేందచకుఅంగీకర్షసచతనాననచ

/ ( ) :______కరతకుꀿ 졀గ్졀ోఆమ్లదꁀయమ ైనపో逿ꀿధి뱊కాసంతకం 졍ేదాథంబుమదో

: _____ / _____ / ______తేది 124

: ______సంతకారుꀿప్లరు

: ______పర్షశ్ోధ్కుడిꀿ뱊కాసంతకం

: _____ / _____ / ______తేది

: ______అధ్యయనంపర్షశ్ోధ్కుడిꀿప్లరు

: ______వటలనస్య యకాసంతకం

:_____/_____/______తేదీ

: ______వటలనసలిరు

ANEXURE III: CLINICAL RESEARCH FORM TEMPIS STUDY : IRB No: 10422

• Serial Number

• Name ______• Hospital Number • Information significant ______• Age • Sex Gender (1 = male, 2= female) • Comorbidities • Charlson's comorbidity index ##

• Diagnosis ______• Infection (1= Urosepsis, 2= Pneumonia, 3= Meningoencephalitis, 4=CRBSI ,5= AGE, 6=Undifferentiated febrile illness, 7= IE , 8=others) • Growth in blood culture # (1=yes 2=No) 125

• Blood culture organism # (1=GNB 2=Gram positive organism 3=fungus) • Drug resistence #(1=CRO, 2= ESBL ,3= MRSA , 4= Colistinresistent) • SOFA score

Heparin use (1= yes, 2=No)

Hemoglobin

Platelets

APTT

Fibrinogen

R time 126

K time

Alpha angle

Maximum amplitude

Lysis index

Mean platelet volume

Transfusion(1= Yes, 2= No)

Blood products(1=FFPs, 2= Platelsts, 3= cyoprecipitates, 4= packed cell

Outcome (1=death, 2 =discharged alive , 3= DAMA)

Duration of ICU stay

Duration of hospital stay

ANNEXURE IV: EXCEL SHEET

name h h1 inclusion age sex comobs1 comobs2 comobs3 cm dx inf bld Kankasha 199501 h 1 18 2 0 PUO 2 1 Pappihara 934558 g 1 45 2 0 0 TEN, septic shock 8 1 Rathana 586147 g 1 60 2 1 4 Urosepsis 1 1 Abdul Mallick 934558 g 1 58 1 1 3 5 5 TB M 3 2 Streptococcal Ayyappan 704017 f 1 28 1 7 0 septicaemia 1 1 Babu 4 packed cells 520072 f 1 56 1 7 0 Klebsiella menngitis 3 1 Shanmugam 937248 g 1 75 1 0 Scrub typhus 2 2 Mahalakshmi 906344 g 1 33 2 0 TB abdomen 8 2 Nooruliah 185126 H 1 48 1 1 1 Undifferentiated AFI 2 1 Zahida 936960 G 1 35 2 1 2 2 AFI 8 2 Gurusamy 583561 g 1 56 1 1 2 Nec fascitis limb 8 2 Pllaiyar 185517 h 1 42 1 0 Necrotising fascitis 8 Tallapaaka Invasive fungal Devi 567745 g 1 45 2 0 0 sinusitis 8 1 Birender Choudhary 936739 g 1 45 1 1 1 Disseminated TTB 2 2 Necrotising John S 246752 F 1 50 1 1 2 3 pneumonia 2 2 127

Mani 522232 f 1 51 1 2 TB Meningitis 8 2 Nisar 935328 G 1 59 1 1 2 2 Staph pneumonia 2 1 Savithramma 181716 h 1 50 2 1 Nocardiosis 2 Acute interstitial Priyankha 567678 g 1 22 2 0 0 pneumo 2 2 Neela 561132 g 1 60 2 2 2 LRI Septic shock 2 1 Chittamma 948239 g 1 40 1 0 0 NFGNB Sepsis 8 1 Sumathi 585226 g 1 45 1 0 0 Scrub typhus 2 2 Jyotsna 566023 g 1 42 2 1 2 Pneumonia 2 aspiration Palani 564344 g 1 47 1 0 pneumonia 2 1 MRSA CAP Ramudu 938534 g 1 35 1 0 0 empyema 2 2 Kumarasamy 428923 f 1 57 1 1 2 PULM TB 2 2 Sathana 937376 g 1 21 2 0 0 Scrub 2 2 Siva Priya 578483 g 1 16 2 0 Disseminated TB 2 2 Emphysematous Ganesan 939120 g 1 74 1 1 2 4 pyelonephri 1 1 Malleshwari 576915 g 1 45 2 0 0 Scrub typhus 2 Anala 935033 g 1 29 2 0 0 Scrubtyphus 2 2 Dileep Kumar 934948 g 1 22 1 0 0 Enteric fever 8 1 Lakshmiammal 202777 d 1 56 2 0 0 Meningoencephalitis 3 Noorjhan 939138 g 1 58 2 1 2 2 Scrub 3 2 VIRAL fever ppt Basheeeruissa 404982 f 1 65 2 1 2 4 heart fal 2 2 Bhagwan Das 714125 g 1 66 1 2 7 2 PUO, H1N1 2 2 Sankarappa 186732 h 1 67 1 7 5 CAP 2 2 Manomani 185233 h 1 45 2 1 2 1 Urosepsis 1 1 Vidhya 183039 h 1 25 2 0 Disseminated TB 2 2 Lakshmanan 183532 H 1 54 1 1 2 2 CRBSI ARDS 2 1 Usharani 591243 g 1 57 2 2 0 Scrub 2 Skull base Ekambaram 183484 h 1 55 1 1 3 osteomyelitis 8 1 Vijaykumar 619404 f 1 52 1 1 7 2 Celulitis 8 2 Enteric fever,heat Sarath Kumar 549268 g 1 18 2 0 illnes 8 2 Parimala 549552 g 1 63 2 1 5 Acute pyelonephritis 1 2 Venkata Subbamma 576266 g 1 42 2 0 Scrub typhus 2 Rama Thilagam 930179 g 1 44 2 0 0 Scrub typhus 2 2 Asthamoorthy N k 566615 g 1 75 1 3 5 7 Pyeloneprhitis 1 2 Lymphocytic Menin Jincy 576203 g 1 34 2 1 1 Pneumon 2 2 Tamilarasan 480856 g 1 51 1 1 2 CAP 2 1 John Vishwasam 764036 1 60 1 0 0 Meliodosis 2 1 Jayanthi 931593 g 1 26 2 0 0 Scrub with MODS 2 Trilochan Singh 561106 g 1 52 1 1 2 6 TBM 3 2 Bharathi 549843 G 1 22 2 0 CAP with ARDS 2 2 Urosepsis with Lizzy Maria 559473 g 1 66 2 1 4 shock 1 1 Usha 910354 d 1 47 2 0 0 Scrub Udhaya Kumar 547642 g 1 46 1 1 1 Scrub typhus 2 2 Saravanan 585442 g 1 47 1 0 0 Scrub typhus 2 2 LRI,MSSA Babu T 564649 G 1 21 1 0 0 blood,osteomyeli 2 1 Ananda Raj 591734 g 1 60 1 1 2 3 Scrub typhus 2 Alimuthu 503416 g 1 85 1 1 2 5 Pre septalcellulitis 8 2 Sarojamma 430711 c 1 75 2 1 2 7 4 Pneumonia 2 2 Infective exacerbat Kousalya 440238 a 1 73 2 2 7 4 COPD 2 Arifa 542188 f 1 33 2 1 2 1 Scrub typhus 2 Pyogenic liver Sankari 623881 f 1 67 2 0 3 abscess 8 2 128

Community acquired Daras 867956 A 1 70 2 2 4 pneumo 2 2 Itta Kiran Kumar 936826 g 1 48 1 0 Dengue fever 2 Jayaseelan 564705 g 1 35 1 0 0 Viral encephalitis 3 2 Anna purna 566947 g 1 58 2 5 2 Urosepsis 1 1 Eshani 278590 c 1 65 2 7 0 Pyelonephritis 1 1 Munirathinam 82500 h 1 75 1 1 2 4 COPD 2 Anand G 892955 C 1 41 1 0 Scrub 2 2 Fr Velankanni 961441 c 1 44 1 1 1 Liver abscess 8 1 Mahaboob Basha 579839 g 1 58 1 2 0 Urosepsis 1 1 Prob amoebic liver Rajnish 566844 g 1 25 1 0 absces 8 2 Suresh 593999 g 1 36 1 3 0 Pneumonia 2 2 Velmurugan 579008 g 1 45 1 0 Scrub tyhpus 3 2 Kesavuliu 350098 H 1 71 1 1 4 Scrub 2 2 AGE,steroid Manila 558936 g 1 55 2 2 1 use,pancreati 8 2 Rani 576373 g 1 52 2 1 2 2 Scrub typhus 3 2 Sathiya Moorthi 558829 g 1 65 1 2 Cholangitis 8 2 scrub and Saraswathi 939247 g 1 65 2 1 2 3 pyelonephritis 1 2 Aspiration Nandlal 564867 g 1 56 1 1 pneum,b12defic 2 2 Mahalingam 558845 G 1 49 1 0 DSH: Bacteraemia 8 1 MRSA blood, orbital Munusamy G 930951 g 1 58 1 2 cellu 8 1 Munisamy 579059 G 1 60 1 2 0 Scrub typhus 3 2 Pneumococcal Nethangi 183555 h 1 24 1 0 meningitis 3 2

or rs so hep hb plts pt ap r k al ma ly mp traf pdts prts1 pdts2 pts3 ome d d 2 6 108000 13 50 9 4 54 43 6 11 1 4 1 2 2 1 1 10 2 9 86000 11 18 1 4 1 3 3 1 2 8 2 8 199000 13 45 18 6 32 52 0 10 1 1 1 4 4 2 11 19000 25 83 15 7.4 17 0 8 1 1 2 3 1 4 13 2 0 14 222000 14 41 5 2 64 54 8 13 1 1 1 6 6 1 0 8 2 8 393000 16 45 4 1 78.5 76 0 9 1 4 1 7 7 14 13 18000 13 55 10 7 35 33 3 13 1 1 2 1 7 7 6 193000 17 41 9 22 19 21 0 9 1 1 2 3 4 1 13 16 1 0 5 11 218000 36 42 9 4 50 52 0 10 2 1 2 2 11 2 17 279000 15 33 5 2 65 64 0 10 2 1 2 2 13 2 11 186000 7 2 66 60 0 11 2 1 2 2 9 16 186000 15 47 8 5 0 46 1 10 2 1 3 3 2 0 7 2 13 113000 11 34 6 2 58.2 57 0 11 2 1 4 4 16 2 14 43000 29 80 20 16 0 28 1 11 2 1 5 5 0 5 2 12 391000 13 48 7 1 76 78 5 10 2 1 7 7 11 2 8 86000 17 49 7 2 59.4 58 0 11 2 1 7 7 3 2 13 189000 9 33 8 2 71 81 1 12 2 1 13 13 10 245000 19 54 7 0 58 58 10 2 1 13 13 5 2 11 210000 10 31 4 1 75.7 68 0 10 2 1 16 16 1 0 10 2 9 84000 13 38 9 3 57.4 70 0 13 2 1 1 4 5 2 11 472000 16 28 3 1 66 70 0 11 2 1 6 6 7 2 8 52000 22 34 5 2 67 53 2 14 2 2 4 13 4 13 713000 13 42 5 1 76.4 76 0 10 2 2 3 6 129

1 0 8 13 258000 13 25 5 1 76.4 76 0 10 2 2 14 19 3 2 15 86000 44 110 6 2 64 56 9 10 1 1 2 4 16 6 2 6 438000 26 47 6 1 78 70 0 9 1 1 4 2 4 29 6 2 10 100000 9 40 7 2 72 68 2 12 1 4 2 4 7 6 8 149000 32 50 9 2 64 60 0 12 1 4 2 5 35 1 2 8 2 13 40000 11 43 8 6 55 35 0 11 1 2 2 5 9 11 2 10 14000 13 72 9 15 26.5 23 0 9 1 3 2 4 2 5 9 4 2 9 174000 13 34 5 1 73 64 2 11 2 2 7 10 1 5 2 9 22000 13 51 13 11 38 32 1 13 1 1 2 7 15 8 2 8 321000 10 35 3 1 77.4 76 0 11 1 4 2 7 12 11 2 10 74000 9 30 3 1 76 69 0 10 1 4 2 7 11 13 7 320000 12 37 5 1 74 68 2 9 1 4 2 7 17 7 8 285000 10 38 9 2 70 79 0 12 1 4 2 10 29 13 42000 11 53 8 4 51 43 0 11 1 2 2 10 35 1 2 14 11 88000 11 31 4 2 66 67 5 12 1 4 2 12 29 8 8 50000 12 39 7 0 65 47 1 10 1 4 2 14 24 1 11 10 314000 14 34 3 2 70 73 2 9 1 4 2 31 69 7 2 12 105000 10 31 5 2 70 70 0.8 12 1 4 2 24 34 1 0 14 241000 13 32 6 3 0 42 2 9 1 1 2 2 21 34 13 143000 13 39 8 4 51 43 0 11 2 2 2 9 6 2 12 64000 18 41 2 2 3 8 7 2 12 163000 23 30 4 1 69.6 64 0 10 2 2 3 7 7 2 9 9000 14 55 6 3 56 49 4 9 2 2 4 5 0 0 12 2 10 12000 14 46 9 6 39.1 39 0 7 2 2 5 8 1 2 6 2 9 165000 7 2 70.5 72 0.1 11 2 2 6 13 9 2 10 388000 12 86 4 1 79 68 5 10 2 2 6 10 2 0 4 2 14 303000 10 39 10 0 65 72 3 11 2 2 7 16 1 0 5 2 14 146000 12 29 5 2 72 65 1 10 2 2 7 18 11 2 9 80000 11 44 8 2 56.3 68 1 9 2 2 7 8 17 2 10 67000 12 31 5 2 56 58 0 12 2 2 7 21 6 2 10 119000 10 38 4 2 65.4 74 0 13 2 2 8 8 1 2 9 2 11 128000 20 36 12 4 47.6 66 0 12 2 2 8 16 11 12 102000 10 38 5 2 69 65 1 11 2 2 8 9 14 2 9 33000 11 48 9 6 43 41 2 9 2 2 8 11 15 2 11 19000 11 50 10 5 48 43 1 11 2 2 8 12 2 0 3 2 13 303000 11 38 10 2 2 10 14 6 2 13 153000 11 40 6 2 62.7 69 0 12 2 2 10 14 10 11 124000 11 47 7 2 62.5 68 0 12 2 2 14 15 0 0 10 2 10 160000 12 40 5 1 62.8 62 0 10 2 2 17 30 2 2 11 350000 10 30 2 1 68.8 71 0 9 2 2 15 15 5 2 11 114000 9 41 4 1 71.6 73 0 12 2 2 2 7 5 2 10 300000 10 40 15 3 47.1 72 0 11 2 2 5 6 6 12 153000 13 4 1 73.6 78 0 13 2 2 7 7 2 11 71000 15 44 5 2 72 68 0 13 2 2 30 7 2 14 248000 5 2 61.2 67 0 10 2 2 27 1 0 9 2 11 223000 15 41 13 4 49.2 65 0 10 2 2 5 1 2 9 2 11 75000 10 52 8 2 67 53 2 14 2 2 4 8 10 2 10 42000 11 49 4 2 72 61 2 12 2 2 11 16 110000 13 133 6 3 60 52 5 11 2 2 7 1 0 10 184000 11 40 8 2 64.3 68 0 12 2 2 23 1 2 12 100000 16 45 4 1 73 71 0 11 2 2 15 8 9 145000 14 34 5 1 73.9 74 0 13 2 2 3 24 2 16 356000 10 34 8 4 42.4 63 0 10 2 2 4 6 10 50000 11 38 6 2 64.6 58 0 12 2 2 2 11 10 55000 14 50 8 2 62.7 60 0 11 2 2 2 9 7 2 13 290000 18 49 6 2 68.3 70 0 12 2 2 3 12 11 2 12 205000 10 42 7 1 76 70 5 11 2 2 5 7 12 2 6 43000 18 44 5 2 67.8 51 0 9 2 2 5 14 9 2 10 53000 11 35 7 3 58 47 0 11 2 2 23 31 2 6 79000 11 27 5 1 79 72 7 12 1 4 3 14 18 1 0 11 19 195000 11 23 9 8 30.9 29 0 11 1 2 3 18 40 2 3 13 14 92000 13 57 9 3 53.3 61 0 13 1 4 3 19 30 15 27000 14 47 10 4 40.8 46 0 10 2 3 10 13 130

4 13 270000 11 31 4 1 74 71 7 9 2 3 12 12

ANNEXURE V :STROBE CHECKLIST 131