Stuart W. Grant PhD Thesis final version

255 Pages·2014·5.22 MB·English

Risk prediction models in
cardiovascular surgery

A thesis submitted to the University of Manchester for
the degree of Doctor of Philosophy (PhD) in the Faculty
of Medical and Human Sciences.

2013

Stuart W. Grant
School of Medicine
Institute of Cardiovascular Sciences
LIST OF CONTENTS
List of contents 2
List of tables and figures 6
Abbreviations 11
Thesis abstract 13
Declaration 14
Copyright statement 14
Rationale for submitting the thesis in the alternative format 15
Acknowledgements 16
Dedication 16

SECTION 1: INTRODUCTION 17
Introduction to research studies and thesis structure 18

Chapter 1: Cardiovascular surgery 20
1.1 Introduction 20
1.2 Background, prevalence and aetiology of AAA 21
1.3 AAA growth and rupture 22
1.4 AAA screening and the indication for elective AAA repair 24
1.5 Elective AAA repair 25
1.6 Cardiac surgery 27
1.7 Coronary artery bypass grafting 28
1.8 Valve surgery 30
1.9 Thoracic aortic surgery 32

Chapter 2: Risk prediction models in cardiovascular surgery 34
2.1 Clinical risk prediction models 34
2.2 Risk prediction models in AAA repair 36
2.3 Risk prediction models in cardiac surgery 41

Overview of thesis objectives 45
Section one summary 46

SECTION 2: METHODS 47
Section two introduction 48

Chapter 3: Cardiovascular surgery databases 49
3.1 Background 49
3.2 Vascular Governance North West database 50
3.3 The National Vascular Database 53
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3.4 The SCTS National Adult Cardiac Surgery Audit database 55
3.5 Data pre-processing and cleaning 58
3.6 Ethical and legal considerations 61

Chapter 4: Developing and validating risk prediction models 63
4.1 Study design 63
4.2 Predictors 63
4.3 Outcomes 65
4.4 Missing data 66
4.5 Statistical techniques 67
4.6 Internal validation 69
4.7 Model assessment 70
4.8 External validation 72
4.9 Statistical software 73

Section two summary 74

SECTION 3: DEVELOPING AND ASSESSING RISK PREDICTION MODELS IN
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VASCULAR SURGERY
Section three introduction 76

Chapter 5: Logistic risk model for mortality following elective abdominal aortic aneurysm
77
repair
5.1 Abstract 78
5.2 Introduction 79
5.3 Methods 79
5.4 Statistical analysis 80
5.5 Results 81
5.6 Discussion 85
5.7 References 88

Chapter 6: What are the risk factors for renal failure following open elective abdominal
91
aortic aneurysm repair?
6.1 What this paper adds 92
6.2 Abstract 92
6.3 Introduction 93
6.4 Materials and methods 93
6.5 Statistical analysis 94
6.6 Results 95
6.7 Discussion 99
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6.8 References 102

Chapter 7: Evaluation of five risk prediction models for elective abdominal aortic
107
aneurysm repair using the UK National Vascular Database
7.1 Abstract 108
7.2 Introduction 109
7.3 Methods 110
7.4 Results 112
7.5 Discussion 117
7.6 References 119

Chapter 8: A national risk prediction model for elective abdominal aortic aneurysm
122
(AAA) repair; the British Aneurysm Repair (BAR) score
8.1 Abstract 123
8.2 Introduction 124
8.3 Methods 125
8.4 Results 127
8.5 Discussion 132
8.6 References 135

Chapter 9: Prospective validation of the BAR, Medicare and VGNW risk scores for
139
mortality following elective abdominal aortic aneurysm (AAA) repair
9.1 Abstract 140
9.2 Introduction 141
9.3 Materials and methods 141
9.4 Results 144
9.5 Discussion 148
9.6 References 151

Section three summary 154

SECTION 4: ASSESSING RISK PREDICTION MODELS IN CARDIAC SURGERY 155
Section four introduction 156

Chapter 10: Dynamic trends in cardiac surgery: why the logistic EuroSCORE is no longer
157
suitable for contemporary cardiac surgery and implications for future risk models
10.1 Abstract 158
10.2 Introduction 159
10.3 Materials and methods 159
10.4 Results 162
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10.5 Discussion 169
10.6 References 172

Chapter 11: How does EuroSCORE II perform in UK cardiac surgery; an analysis of
23, 740 patients from the Society for Cardiothoracic Surgery of GB and Ireland National 175
database
11.1 Abstract 176
11.2 Introduction 177
11.3 Materials and methods 178
11.4 Results 180
11.5 Discussion 185
11.6 References 188

Chapter 12: Performance of the EuroSCORE models in emergency cardiac surgery 191
12.1 Abstract 192
12.2 Introduction 193
12.3 Methods 194
12.4 Results 197
12.5 Discussion 207
12.6 References 208

Section four summary 214

SECTION5: GENERAL DISCUSSION 215
Section five introduction 216

Chapter 13: Contribution of thesis studies 217
13.1 Summary of the main findings 217
13.2 Key strengths and weaknesses of studies 220
13.3 Implications of findings 225
13.4 Future research 229
13.5 Final conclusions 230

References 232

Appendix A: Abstract for ‘Identifying the risk of renal failure following elective AAA repair’ 254
Appendix B: Abstract for manuscript ‘Preoperative cardiopulmonary exercise testing and risk of
255
early mortality following abdominal aortic aneurysm repair’

Word count – 74, 492 words
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LIST OF TABLES AND FIGURES
Chapter 1: Figure 1 (sub-section 1.2) 21
Different types of aneurysm. The shaded areas represent thrombus.

Chapter 1: Figure 2 (sub-section 1.3) 23
Law of Laplace as applied to a cylinder

Chapter 2: Table 1 (sub-section 2.3) 43
Risk factors included in the EuroSCORE and EuroSCORE II models

Chapter 3: Figure 1 (sub-section 3.2) 50
Contributing hospitals to the VGNW project

Chapter 3: Figure 2 (sub-section 3.2) 51
VGNW structure and data collection process

Chapter 3: Table 1 (sub-section 3.2) 52
Current data fields collected by the VGNW programme

Chapter 3: Table 2 (sub-section 3.3) 54
Data fields collected by the NVD

Chapter 3: Figure 3 (sub-section 3.4) 56
Data flow for the SCTS NACSA database

Chapter 3: Table 3 (sub-section 3.4) 56
Data fields collected by the SCTS NACSA database

Chapter 3: Table 4 (sub-section3.5) 60
Mapping rules for the aortic pathology field for the SCTS NACSA database

Chapter 3: Table 5 (sub-section3.5) 60
Mapping rules for the aortic aetiology field for the SCTS NACSA database

Chapter 5: Table 1 (sub-section 5.5) 82
Association between preoperative characteristics and 30-day mortality after abdominal

aortic aneurysm repair in 1936 patients: univariable analysis

Chapter 5: Table 2 (sub-section 5.5) 83
Final logistic regression model for 30-day mortality after abdominal aortic aneurysm repair

Chapter 5: Figure 1 (sub-section 5.5) 84
Observed and expected 30-day mortality compared for ten groups of increasing risk in the

development data set

Chapter 5: Figure 2 (sub-section 5.5) 85
Observed and expected 30-day mortality compared for ten groups of increasing risk in the

validation data set
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Chapter 6: Table 1 (sub-section 6.6) 96
Association between pre-operative characteristics and the development of renal failure

following open elective AAA repair; univariate analysis (n= 2,347)

Chapter 6: Table 2 (sub-section 6.6) 97
Logistic regression model for post-operative renal failure following open elective AAA repair

Chapter 6: Figure 1 (sub-section 6.6) 97
Observed versus expected post-operative renal failure for groups of increasing risk

Chapter 6: Table 3 (sub-section 6.6) 98
Simple clinical risk score for post-operative renal failure following open elective AAA repair

Chapter 6: Figure 2 (sub-section 6.6) 99
Observed and expected post-operative renal failure for low-risk, medium-risk and high-risk

groups

Chapter 7: Table 1 (sub-section 7.4) 113
Data available for patients undergoing elective abdominal aortic aneurysm repair in the

National Vascular Database

Chapter 7: Figure 1 (sub-section 7.4) 114
Receiver operating characteristic (ROC) curves for the GAS, VBHOM, V-POSSUM,
Medicare and VGNW models for prediction of in-hospital mortality after elective abdominal
aortic aneurysm repair in the National Vascular Database.

Chapter 7: Table 2 (sub-section 7.4) 114
Discriminatory ability of five risk prediction models for in-hospital mortality assessed in the

National Vascular Database

Chapter 7: Figure 2 (sub-section 7.4) 115
Observed and expected in-hospital mortality rates for the VBHOM, V-POSSUM, Medicare
and VGNW models for elective abdominal aortic aneurysm repair in the National Vascular
Database

Chapter 7: Table 3 (sub-section 7.4) 116
Predicted and observed in-hospital mortality rates for elective abdominal aortic aneurysm
repair by quintile (derived using the ranked VGNW predicted risk) for four risk prediction
models assessed using the National Vascular Database

Chapter 7: Table 4 (sub-section 7.4) 116
Predicted and observed in-hospital mortality rates for elective abdominal aortic aneurysm
repair by quintile (derived using the ranked Medicare predicted risk) for four risk prediction
models assessed using the National Vascular Database

Chapter 8: Table 1 (sub-section 8.4) 128
Patient characteristics and univariable analysis

Chapter 8: Table 2 (sub-section 8.4) 129
Final risk factors by multivariate regression for the model
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Chapter 8: Table 3 (sub-section 8.4) 130
Hosmer-Lemeshow test demonstrates good calibration

Chapter 8: Figure 1 (sub-section 8.4) 130
Calibration plot comparing observed and predicted in-hospital mortality which demonstrates

good calibration for the BAR score

Chapter 8: Table 4 (sub-section 8.4) 131
Risk group assessment demonstrates good calibration

Chapter 8: Figure 2 (sub-section 8.4) 132
British Aneurysm Repair score-predicted mortality density plots for open abdominal aortic

aneurysm repair and endovascular aneurysm repair (EVAR) subgroups

Chapter 9: Table 1 (sub-section 9.3) 142
Risk factors included in the BAR score, Medicare model and VGNW model.

Chapter 9: Figure 1 (sub-section 9.4) 144
Calibration plots for the Medicare, VGNW and BAR risk models.

Chapter 9: Table 2 (sub-section 9.4) 145
Patient characteristics for the study population

Chapter 9: Table 3 (sub-section 9.4) 146
Calibration of the BAR score in defined risk groups according to the BAR score

Chapter 9: Table 4 (sub-section 9.4) 146
Calibration of the VGNW model in defined risk groups according to the VGNW model

Chapter 9: Table 5 (sub-section 9.4) 146
Calibration of the Medicare model in defined risk groups according to the VGNW model

Chapter 9: Figure 2 (sub-section 9.4) 147
Receiver operating characteristic (ROC) curves for the British Aneurysm Repair Score,

Medicare and Vascular Governance North West (VGNW) models

Chapter 10: Figure 1 (sub-section 10.4) 162
Percentage of missing data year-on-year for each EuroSCORE risk factor

Chapter 10: Figure 2 (sub-section 10.4) 163
Top panel: the observed mortality proportion and expected mortality proportion according
to the logistic EuroSCORE. Bottom panel: observed-to-expected mortality ratio (as
determined by the logistic EuroSCORE model) ratios calculated for each annual quarter

Chapter 10: Figure 3 (sub-section 10.4) 164
Area under the receiver operating characteristic curves for the logistic EuroSCORE over

time (95% CI – vertical black lines)

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Chapter 10: Figure 4 (sub-section 10.4) 165
Time series (red lines) and fitted trend curves (blue curves) to patient characteristic risk

factors included in the logistic EuroSCORE

Chapter 10: Figure 5 (sub-section 10.4) 166
Time series (red lines) and fitted trend curves (blue curves) to patient characteristic risk

factors included in the logistic EuroSCORE

Chapter 10: Figure 6 (sub-section 10.4) 167
Time series (red lines) and fitted trend curves (blue curves) to procedure classes which

affect the operative risk factors included in the logistic EuroSCORE

Chapter 10: Figure 7 (sub-section 10.4) 168
Change in EuroSCORE logistic regression linear determinants demonstrating that patient
age and surgery other than isolated CABG have contributed most to the calibration drift of
the logistic EuroSCORE

Chapter 10: Figure 8 (sub-section 10.4) 168
Left panels: time series plots (red lines) of calibration intercept and slope parameters and
fitted trend curves (blue curves). Right panel: calibration curves for each annual quarter.
Black dashed line shows perfect calibration.

Chapter 11: Table 1 (sub-section 11.4) 181
Patient characteristics for the study population

Chapter 11: Table 2 (sub-section 11.4) 182
Operative details for the study population

Chapter 11: Figure 1 (sub-section 11.4) 183
EuroSCORE II calibration plot for the overall cohort

Chapter 11: Table 3 (sub-section 11.4) 183
EuroSCORE II calibration data for the overall cohort

Chapter 11: Table 4 (sub-section 11.4) 184
Summary and performance statistics of EuroSCORE II by weight of intervention

Chapter 12: Table 1 (sub-section 12.4) 198
Frequency and percentage of logistic EuroSCORE risk factors for all, non-emergency and

emergency cardiac surgery procedures performed between 1st April 2008 and 31st March

2011 (overall cohort) following imputation.

Chapter 12: Table 2 (sub-section 12.4) 200
Frequency and percentage of logistic EuroSCORE II risk factors for all, non-emergency
and emergency cardiac surgery procedures performed between 26th July 2010 and 31st
March 2011 following imputation.

Chapter 12: Figure 1 (sub-section 12.4) 202
Receiver-operating characteristic curves for the logistic EuroSCORE and EuroSCORE II in

3 groups of patients: all cardiac surgery, non-emergency surgery, and emergency surgery.
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Chapter 12: Figure 2 (sub-section 12.4) 203
Calibration plots for the logistic EuroSCORE and the EuroSCORE II.

Chapter 12: Table 3 (sub-section 12.4) 204
Model performance summary statistics for the logistic EuroSCORE and EuroSCORE II
models (applied to the appropriate data subsets) across the three groups: all cardiac
surgery, non-emergency cardiac surgery and emergency cardiac surgery.

Chapter 12: Table 4 (sub-section 12.4) 206
Risk factors for in-hospital mortality following emergency cardiac surgery derived from an
updated model fit of the logistic EuroSCORE model using multiple logistic regression with
backwards model selection applied.

Chapter 13: Figure 1 (sub-section 13.3) 227
Web-calculator for the BAR score

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