symptom presentation in myocardial infarction, ambulance … · symptom presentation in myocardial...
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Symptom Presentation in Myocardial
Infarction, Ambulance Times and
Prehospital Delay
Linda L. Coventry
RN, DipAppSc, BSc, MS
This thesis is presented for the degree of
Doctor of Philosophy
of The University of Western Australia
School of Population Health
School of Primary, Aboriginal and Rural Health Care
2015
i
Abstract Background
Early prehospital recognition of presenting symptoms of myocardial infarction (MI) is
time-critical because reperfusion and medical therapies improve patient outcomes.
Failure to recognize symptoms of MI may lead to longer delays in both prehospital and
medical care. Some previous studies have identified that women are less likely to
present with chest pain, however, findings from these studies have been inconsistent.
Aims
The aims of this doctoral research were fivefold: (1) to investigate if men and women
present equally with chest pain as a symptom of MI and whether there were sex
differences in other presenting symptoms of MI; (2) to determine if the symptoms
reported during the emergency telephone call, in particular chest pain, and ambulance
response times are the same for men and women with MI; (3) to determine if paramedic
records, compared with hospital medical records, are a reliable source of information
about presenting symptoms of MI and onset-time of symptoms; (4) to compare patient
characteristics from the hospital medical records and patient outcomes for patients
presenting with and without chest pain; and (5) to describe prehospital delay time for
MI patients transported by ambulance and identify patient characteristics and presenting
symptoms which contribute to prehospital delay for MI patients.
Methodology
To address aim 1, a systematic review and meta-analysis were conducted. Aims 2 to 5
were addressed by retrospective cohort studies of patients with an emergency
department (ED) discharge diagnosis of MI, who were transported by ambulance to one
of the seven metropolitan EDs in Perth, between January 2008 and October 2009.
Symptoms of MI were transcribed from audio tapes of the emergency telephone call to
the ambulance service and the text description in the paramedic patient care record
(PCR). To validate the accuracy of the paramedic documentation of presenting
symptoms and symptom onset-time of MI, the patients’ hospital medical records were
reviewed at a single teaching hospital. The following statistical methodologies were
employed: multivariable linear and logistic regression; McNemar tests; kappa and
adjusted kappa statistics, sensitivity, specificity, and positive and negative predictive
values; and Kaplan-Meier curves and Cox regression.
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Results
Meta-analysis of 27 studies (1,654,588 patients) showed women with MI had lower
odds (OR 0.63, 95% CI 0.59-0.68) and a lower rate (RR 0.93, 95% CI 0.91-0.95) of
presenting with chest pain than men. Women were significantly more likely to present
with fatigue, neck pain, syncope, nausea, right arm pain, dizziness and jaw pain.
In age-adjusted regression analyses of emergency calls to the ambulance service
(n=1681), women were less likely than men to report chest pain (OR 0.70, 95% CI 0.57-
0.88); and although ambulance times did not differ between men and women with chest
pain, women with chest pain were less likely than men with chest pain to be allocated a
priority 1 (lights and sirens) (OR 0.39, 95% CI 0.18-0.87) ambulance response.
In the comparison of paramedic PCRs with hospital medical records (n=400 pairs of
records), the majority (71.4%) of 21 documented MI symptoms had adjusted Kappa
statistics greater than 0.75, and observed agreement greater than 90%. For the symptom
of chest pain, sensitivity, specificity, positive predictive value and negative predictive
value were all greater than 85%. Where symptom onset-time was recorded in both the
paramedic PCR and the hospital medical record (n=196 pairs of records), it agreed
exactly in 60% of the records, and the times were within 30 minutes in over 80% of the
records.
In the comparison of patient characteristics and survival outcomes for patients who
presented with and without chest pain (n=382), the adjusted odds of presenting without
chest pain were increased for women (OR 1.67, 95% CI 0.99-2.82), and patients aged
70-79 years (OR 4.33, 95% CI 1.50-12.5) and aged over 80 years (OR 7.54, 95% CI
2.81-20.3) compared with patients less than 60 years. The adjusted hazard (median
follow-up time 2.2 years) of presenting without chest pain was not significantly
associated with survival.
For patients with a recorded onset-time (n=829) median delay was 2.2 hours. Decreased
delay was associated with age less than 70 years, presenting with chest pain, and
diaphoresis. Increased delay was associated with being with a primary health care
provider, if the patient was at home, and if the person who called the ambulance was
anyone other than the spouse. For patients with onset-times recorded as word
descriptions (n=174), 37% of patients delayed 1-3 days and 64% of patients described
their symptoms as intermittent and/or of gradual onset.
iii
Conclusions
This doctoral thesis contributes to the evidence about sex differences in symptoms of
MI presentation: women were less likely to present with chest pain and more likely to
present with other symptoms of MI. Women were also less likely to include the
symptom of chest pain in their emergency telephone call to the ambulance service, as
were older patients. Furthermore, it contributes to our knowledge of factors that affect
prehospital delay: older age and presenting without chest pain or diaphoresis were
associated with increased delay. Given that for MI the symptom of chest pain differs
with age, between men and women, and prehospital delay times remain longer than is
recommended, public awareness of symptoms, including education of health
professionals, should be enhanced to reduce time from symptom onset to definitive care.
iv
v
Table of Contents Abstract .............................................................................................................................. i
List of Tables.................................................................................................................. xiii
List of Figures ................................................................................................................. xv
Acknowledgements ....................................................................................................... xvii
Publications and Awards ................................................................................................ xix
Statement of Candidate Contribution ........................................................................... xxiii
List of Abbreviations..................................................................................................... xxv
Chapter 1: Introduction 1
1.1 Background to the Study ..................................................................................... 1
1.2 Context of the Study ........................................................................................... 2
1.2.1 Perth: Geography and Demography ........................................................ 2
1.2.2 The Western Australian Ambulance Service .......................................... 2
1.2.3 The Emergency Call ................................................................................ 3
1.2.4 SJA-WA Communication Officers ......................................................... 4
1.2.5 SJA-WA Paramedics ............................................................................... 4
1.3 Statement of Problem .......................................................................................... 5
1.4 Research Questions ............................................................................................. 6
1.5 Significance of the Study .................................................................................... 6
1.6 Structure of the Thesis ........................................................................................ 7
Chapter 2: Sex Differences in Symptom Presentation in Acute Myocardial
Infarction: A Systematic Review and Meta-analysis 9
2.1 Introduction ......................................................................................................... 9
2.2 Abstract ............................................................................................................... 9
2.2.1 Background ............................................................................................. 9
2.2.2 Methods ................................................................................................... 9
2.2.3 Results ..................................................................................................... 9
2.2.4 Conclusions ........................................................................................... 10
2.2.5 Key Words ............................................................................................ 10
2.3 Background ....................................................................................................... 10
2.4 Methods............................................................................................................. 11
2.4.1 Search Strategy...................................................................................... 11
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2.4.2 Inclusion and Exclusion Criteria ........................................................... 12
2.4.3 Quality Assessment ............................................................................... 12
2.4.4 Data Extraction ..................................................................................... 12
2.4.5 Statistical Analysis ................................................................................ 13
2.5 Results ............................................................................................................... 14
2.5.1 Included Studies Characteristics ........................................................... 14
2.5.2 Chest Pain ............................................................................................. 21
2.5.3 Associated Symptoms of AMI .............................................................. 24
2.5.4 Age and Other Adjustments .................................................................. 27
2.5.5 Co-morbidity ......................................................................................... 29
2.5.6 Heterogeneity ........................................................................................ 31
2.5.7 Publication Bias .................................................................................... 31
2.6 Discussion ......................................................................................................... 32
2.7 Limitations of the Review ................................................................................. 33
2.8 Implications for Clinical Practice / Policy ........................................................ 34
2.9 Implications for Future Research ...................................................................... 34
2.10 Conclusion ........................................................................................................ 34
Chapter 3: Methods to Link Data 37
3.1 Introduction ....................................................................................................... 37
3.2 Data Linkage ..................................................................................................... 37
3.3 Data Sources ..................................................................................................... 38
3.3.1 EDIS ...................................................................................................... 38
3.3.2 SJA-WA ................................................................................................ 38
3.3.3 Transcribed Symptoms of MI from the Emergency Telephone Call and
the Paramedic PCR ............................................................................... 39
3.3.4 Mortality Data ....................................................................................... 39
3.3.5 Patient Hospital Medical Record Data .................................................. 39
3.4 The Process of Data Extraction and Merging of the Data ................................ 39
3.5 Data Validation ................................................................................................. 42
3.5.1 Validation of Data Entry of Symptom of MI in the SJA-WA Telephone
call Data ................................................................................................ 42
3.5.2 Validation of the Linked Data Set – EDIS and SJA-WA ..................... 43
3.6 Conclusion ........................................................................................................ 44
Chapter 4: Myocardial Infarction: Sex Differences in Symptoms Reported to
Emergency Dispatch 45
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4.1 Introduction ....................................................................................................... 45
4.2 Abstract ............................................................................................................. 45
4.2.1 Background ........................................................................................... 45
4.2.2 Objective ............................................................................................... 45
4.2.3 Methods ................................................................................................. 45
4.2.4 Results ................................................................................................... 46
4.2.5 Conclusion ............................................................................................ 46
4.2.6 Key Words ............................................................................................ 46
4.3 Background ....................................................................................................... 46
4.4 Methods............................................................................................................. 47
4.4.1 Study Setting and Cohort ...................................................................... 47
4.4.2 Statistical Methods ................................................................................ 49
4.5 Results ............................................................................................................... 50
4.5.1 Sex Differences in Chest Pain Reported for Patients with Myocardial
Infarction during the Emergency Telephone Call ................................. 52
4.5.2 Differences in Other Symptoms Reported for Patients with Myocardial
Infarction during the Emergency Telephone Call ................................. 54
4.5.3 Sex Differences in Ambulance Times................................................... 54
4.5.4 Sex Differences in Priority Allocation Total Time from Emergency Call
to Hospital for Each Priority Response ................................................. 57
4.6 Discussion ......................................................................................................... 59
4.6.1 Sex Differences in Chest Pain ............................................................... 59
4.6.2 Sex Differences in Ambulance Times................................................... 60
4.6.3 Sex Differences in Priority Allocation .................................................. 60
4.7 Limitations ........................................................................................................ 61
4.8 Conclusion ........................................................................................................ 62
Chapter 5: Symptoms of Myocardial Infarction: Concordance between Paramedic
and Hospital Records 63
5.1 Introduction ....................................................................................................... 63
5.2 Abstract ............................................................................................................. 63
5.2.1 Background ........................................................................................... 63
5.2.2 Objectives .............................................................................................. 63
5.2.3 Methods ................................................................................................. 64
5.2.4 Results ................................................................................................... 64
5.2.5 Conclusion ............................................................................................ 64
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5.2.6 Key Words ............................................................................................ 64
5.3 Background ....................................................................................................... 65
5.4 Methods ............................................................................................................ 66
5.4.1 Setting, Participants and Study Design ................................................. 66
5.4.2 Data Sources ......................................................................................... 66
5.4.3 Data Analysis ........................................................................................ 67
5.5 Results ............................................................................................................... 69
5.5.1 Cohort Characteristics ........................................................................... 69
5.5.2 Symptom Documentation: Paramedic PCR and Hospital Medical
Record ................................................................................................... 69
5.5.3 Chest Pain ............................................................................................. 71
5.5.4 Other Symptoms of MI ......................................................................... 71
5.5.5 Symptom-onset Time: Paramedic PCR and Hospital Medical Record 72
5.6 Discussion ......................................................................................................... 76
5.6.1 Symptom Documentation: Paramedic PCR and Hospital Medical
Record ................................................................................................... 76
5.6.2 Chest Pain ............................................................................................. 77
5.6.3 Other Symptoms of MI ......................................................................... 77
5.6.4 Symptom-onset Time: Paramedic and Medical Record ....................... 77
5.7 Limitations ........................................................................................................ 78
5.8 Conclusions ....................................................................................................... 79
Chapter 6: Characteristics and Outcomes for Myocardial Infarction Patients Who
Present with and without Chest Pain 81
6.1 Introduction ....................................................................................................... 81
6.2 Abstract ............................................................................................................. 81
6.2.1 Background ........................................................................................... 81
6.2.2 Objectives.............................................................................................. 81
6.2.3 Methods ................................................................................................. 81
6.2.4 Results ................................................................................................... 82
6.2.5 Conclusion ............................................................................................ 82
6.2.6 Key Words ............................................................................................ 82
6.3 Introduction ....................................................................................................... 82
6.4 Method .............................................................................................................. 83
6.4.1 Setting and Participants ......................................................................... 83
6.4.2 Study Design and Data Sources ............................................................ 83
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6.4.3 Statistical Analysis ................................................................................ 85
6.5 Results ............................................................................................................... 86
6.5.1 Cohort Characteristics ........................................................................... 86
6.5.2 Presenting without Chest Pain .............................................................. 86
6.5.3 Primary PCI or any Cardiac Procedure ................................................. 91
6.5.4 Survival Outcomes ................................................................................ 94
6.6 Discussion ......................................................................................................... 96
6.6.1 Presenting without Chest Pain .............................................................. 96
6.6.2 Primary PCI or any Cardiac Procedure ................................................. 97
6.6.3 Survival Outcomes ................................................................................ 97
6.7 Limitations ........................................................................................................ 98
6.8 Implications for Practice, Research, Policy and Education .............................. 99
6.9 Conclusions ....................................................................................................... 99
Chapter 7: The Effect of Presenting Symptoms and Patient Characteristics on
Prehospital Delay in MI Patients Presenting to ED by Ambulance: A
Cohort Study 101
7.1 Introduction ..................................................................................................... 101
7.2 Abstract ........................................................................................................... 101
7.2.1 Background ......................................................................................... 101
7.2.2 Objectives ............................................................................................ 102
7.2.3 Methods ............................................................................................... 102
7.2.4 Results ................................................................................................. 102
7.2.5 Conclusion .......................................................................................... 102
7.2.6 Key Words .......................................................................................... 102
7.3 Introduction ..................................................................................................... 102
7.4 Methods........................................................................................................... 103
7.4.1 Study Design, Setting and Participants ............................................... 103
7.4.2 Data Sources........................................................................................ 104
7.4.3 Data Analysis ...................................................................................... 104
7.5 Results ............................................................................................................. 105
7.5.1 Characteristics of the Cohort ............................................................... 105
7.5.2 Multivariable Analysis ........................................................................ 110
7.6 Discussion ....................................................................................................... 111
7.7 Strengths and Limitations ............................................................................... 112
7.8 Recommendations for Future Study ............................................................... 113
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7.9 Conclusions ..................................................................................................... 114
Chapter 8: Discussion 115
8.1 Introduction ..................................................................................................... 115
8.2 Overview of Major Findings ........................................................................... 115
8.3 Strengths of the Study ..................................................................................... 118
8.4 Limitations of the Study ................................................................................. 119
8.5 Implications of Thesis Findings ...................................................................... 121
8.5.1 Implications for Public Health ............................................................ 121
8.5.2 Implications for Professional Practice ............................................... 121
8.6 Areas for Future Research .............................................................................. 122
8.7 Conclusion ...................................................................................................... 123
References 125
Appendices 143
Appendix A: Sex Differences in Symptom Presentation in Acute Myocardial
Infarction: A Systematic Review and Meta-analysis ...................................... 145
Appendix B: Myocardial Infarction: Sex Differences in Symptoms Reported to
Emergency Dispatch ....................................................................................... 161
Appendix C: Symptoms of Myocardial Infarction: Concordance between Paramedic
and Hospital Records ...................................................................................... 171
Appendix D: Characteristics and Outcomes of MI Patients with and without Chest
Pain: A Cohort Study ...................................................................................... 181
Appendix E: The Effect of Presenting Symptoms and Patient Characteristics on
Prehospital Delay in MI Patients Presenting to ED by Ambulance: A Cohort
Study ............................................................................................................... 191
Appendix F: Abstract for Cardiac Society of Australia and New Zealand conference
titled - Sex Differences in Symptom Presentation in Acute Myocardial
Infarction: A Systematic Review and Meta-analysis ...................................... 199
Appendix G: Poster for American Heart Association conference titled - Sex
Differences in Symptoms Reported to Emergency Medical Dispatch in Acute
Myocardial Infarction Patients - Impact on Pre-hospital Delay ..................... 201
Appendix H: Abstract for American Heart Association conference titled - Sex
Differences in Symptoms Reported to Emergency Medical Dispatch in Acute
Myocardial Infarction - Impact on Prehospital Delay .................................... 203
Appendix I: Poster for Paramedics Australasia conference titled - Gender
Differences in Emergency ‘000’ Calls and Ambulance Response for Acute
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Myocardial Infarction (AMI) Patients ............................................................ 205
Appendix J: Abstract for Paramedics Australasia Conference titled – Gender
differences in Emergency ‘000’ Calls and Ambulance Response for Acute
Myocardial Infarction (AMI) Patients ............................................................ 207
Appendix K: The University of Western Australia Human Research Ethics
Committee – Ethics Approval ......................................................................... 209
Appendix L: Sir Charles Gairdner Hospital Human Research Ethics Committee –
Ethics Approval .............................................................................................. 211
Appendix M: Reciprocal The University of Western Australia Ethics for Sir Charles
Gairdner Hospital Study ................................................................................. 213
Appendix N: Government of Western Australia Department of Health Human
Research Ethics Committee Conditional Approval ........................................ 215
Appendix O: Government of Western Australia Department of Health Human
Research Ethics Committee Final Approval ................................................... 217
Appendix P: Cohesion – Mysteries of the Heart Continue to Confound our Response
......................................................................................................................... 219
Appendix Q: Australian Doctor - GP Visits Delay Heart Attack Treatment ........... 223
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List of Tables
Table 1: Summary of Characteristics of Included Acute Myocardial
Infarction Studies (ordered alphabetically by the first author)………. 16
Table 2: Newcastle-Ottawa Quality Assessment……………………………… 22
Table 3: Pooled Estimates of the Effect of Sex on Chest Pain and other
Presenting Symptoms in Patients with Acute Myocardial Infarction
(from meta-analyses of individual studies)………………………….. 26
Table 4: Comparison of the Effect of Adjustment for Age and Other
Variables on the Crude Effect Measure in Studies Reporting Sex
Differences in Presenting Symptoms in Patients with Acute
Myocardial Infarction………………………………………………... 28
Table 5: Pooled Estimates of the effect of Sex on Comorbid conditions in
Patients with Acute Myocardial Infarction (from meta-analyses of
individual studies)……………………………………………………. 30
Table 6: Study Flow Chart for Data Extraction and Merging of the Data…….. 40
Table 7: Reasons for Differences between SJA-WA Data and EDIS Data…… 43
Table 8: Sex Differences in the Descriptive Characteristics of the Emergency
Phone Calls for Patients with Myocardial Infarction………………... 52
Table 9: Sex Differences in Symptoms Reported for Patients with Myocardial
Infarction during the Emergency Telephone Call…………………… 53
Table 10: Sex Differences in Ambulance Times for Patients with Myocardial
Infarction who had Chest Pain and those who did not have Chest
Pain…………………………………………………………………... 56
Table 11: Sex Differences in Ambulance Priority Response and Total Time
from Call to Hospital for Patients with Myocardial Infarction who
had Chest Pain and those who did not have Chest Pain……………... 58
Table 12: Formulae to Calculate Statistics……………………………………... 68
Table 13: Prevalence of Symptom Documentation of Myocardial Infarction:
Paramedic PCR and Hospital Medical Record………………………. 71
Table 14: Observed and Chance Agreement, Kappa and PABAK Statistic of
Symptom Documentation of Myocardial Infarction: Paramedic PCR
and Hospital Medical Record………………………………………... 73
Table 15: Sensitivity, Specificity, PPV and NPV of Symptom Documentation
of Myocardial Infarction: Paramedic PCR and Hospital Medical
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Record (hospital medical record was considered the gold standard)... 74
Table 16: Characteristics of Patients with Myocardial Infarction by Clinical
Presentation: No Chest Pain Compared with Chest Pain……………. 89
Table 17: Process of Care and Outcomes of Patients with Myocardial
Infarction by Clinical Presentation: No Chest Pain Compared with
Chest Pain……………………………………………………………. 90
Table 18 Main Symptoms for Patients without Chest Pain………………….. 90
Table 19: Odds Ratio Estimates (from unadjusted and adjusted logistic
regression analyses) of the Associations between Patient
Characteristics and Myocardial Infarction with No Chest Pain……... 92
Table 20: Odds Ratio Estimates from Multiple Logistic Regression Analysis
of the Associations between Patient Characteristics and Having a
Primary PCI or a ‘Cardiac Procedure’……………………………….. 93
Table 21: Hazard Ratio Estimates (from unadjusted and adjusted Cox
regression analyses) for Characteristics Associated with Myocardial
Infarction without Chest Pain………………………………………... 95
Table 22: Characteristics of the Sample (n=829), and Median Prehospital
Delay…………………………………………………………………. 107
Table 23: Multivariable Linear Regression Log Delay Time in Minutes………. 110
Table 24: Categorised Time Intervals from Non-Numeric Symptom Onset-
Times and Relationship with Intermittent or Gradual Onset of
Symptoms (yes/no)…………………………………………………... 111
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List of Figures
Figure 1: Flow Diagram of Search Results and Study Selection………………….. 15
Figure 2: Forest Plot of Studies Using OR in Comparing Chest Pain as a
Presenting Symptom of AMI in Women and Men (in alphabetical
order)……………………………………………………………………. 23
Figure 3: Forest Plot of Studies Using RR Comparing Chest Pain as a Presenting
Symptom of AMI in Women and Men (in alphabetical order)…………. 24
Figure 4: Funnel Plot for the Pooled OR of Chest Pain…………………………… 32
Figure 5: Study Flow Diagram……………………………………………………. 51
Figure 6: Boxplot Showing Sex Differences in Times for Each Component of
Prehospital Time for Men and Women (n=1681)………………………. 55
Figure 7: Study Flow Diagram……………………………………………………. 70
Figure 8: Flow Diagram of Symptom-onset Time: Paramedic PCR and hospital
Medical Record…………………………………………………………. 75
Figure 9: Symptom-onset Time Difference (minutes): Paramedic PCR and
Hospital Medical Record, n = 196………………………………………. 76
Figure 10: Study Flow Diagram……………………………………………………. 88
Figure 11: Kaplan-Meier Survival Plot for Patients with and without Chest Pain…. 94
Figure 12: Study Flow Diagram…………………………………………………... 106
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Acknowledgements
Completing this study has been a personal journey of learning, facing challenges,
stresses and, importantly, many rewarding experiences. The final thesis would not have
been possible without the support, encouragement and guidance of many people who
were instrumental in assisting me to achieve my goals.
Thanks must go to my supervisory team: Associate Professor Alexandra Bremner,
Professor Judith Finn, Assistant Professor Teresa Williams, and Professor Antonio
Celenza. I wish to extend my sincere gratitude to Alex, without whom this thesis would
not exist. I am forever grateful for your unwavering support and encouragement and I
have benefited from your professionalism, knowledge and wisdom. Judith without your
early guidance and encouragement I would never have commenced this thesis. Your
insight, invaluable suggestions and professional supervision along this journey have
been appreciated. Teresa and Tony thank you for your comments, support, constructive
feedback, and critical review. My sincere thanks go to Professor Ian Jacobs who was
influential especially in the early stages of this thesis. Ian passed away before
completion of this thesis. I recognise Ian’s support and contribution.
This thesis could not have been completed without the support and cooperation of the St
John Ambulance (Western Australian) Service and the Department of Emergency
Medicine of The University of Western Australia. Thanks go to Ms Lorraine Salo and
Dr Nick Gibson for access to data. Nick I appreciate your initial help with syntax and I
now consider you a colleague, a friend, and a mentor. I also acknowledge the financial
support of the National Health and Medical Research Council for the Postgraduate
Research Scholarship and the Nursing and Midwifery office, Department of Health,
Government of Western Australia for the Academic Support Grant. These scholarships
allowed me the privilege of being able to study full-time.
I extend my gratitude to my work colleagues in the Centre for Nursing Research and
Roz Jaworski for their support, rapport, humor, and encouragement throughout the
highs and lows of this rollercoaster ride. To all my friends who stood on the sidelines
cheering me on, I was so grateful you stopped asking when I would finish.
Family support is a vital element in achieving a PhD. I give special thanks to my mum
xviii
and my sister for encouraging me to keep going and assisting me in caring for my young
children. To my amazing Mum, how I valued all your help with house chores, washing,
ironing and school pick-up. To my children Caleb, Sam, and Matthew, most of the time
you probably did not know where or what mummy was doing. The most important
person who has coped with all the emotions of this experience is my partner Steve. His
belief in me never faltered, his patience and willingness to care for our children and run
our home has been a massive sacrifice. Your unwavering support and endless patience
can never be matched by mere words written on this page. I can honestly say I would
never have finished this thesis without you.
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Publications and Awards
The following papers published in peer reviewed journals resulted from this study:
1. Coventry LL, Finn J, Bremner AP. Sex differences in symptom presentation in
acute myocardial infarction: A systematic review and meta-analysis. Heart &
Lung. 2011;40:477-491.1
See Appendix A, manuscript reprinted with permission from Elsevier. Available from
http://www.sciencedirect.com/science/article/pii/S0147956311002706
DOI: 10.1016/j.hrtlng.2011.05.001
2. Coventry LL, Bremner AP, Jacobs IG, Finn J. Myocardial Infarction: Sex
differences in symptoms reported to Emergency dispatch. Prehospital
Emergency Care. 2013;17:193-202.2
See Appendix B, manuscript reprinted with permission from Routledge, Taylor &
Francis Group. Available from http://informahealthcare.com
DOI:10.3109/10903127.2012.722175
3. Coventry LL, Bremner AP, Williams TA, Jacobs IG, Finn J. Symptoms of
Myocardial Infarction: Concordance between Paramedic and Hospital Records.
Prehospital Emergency Care. 2014;18:393-401.3
See Appendix C, manuscript reprinted with permission from Routledge, Taylor &
Francis Group. Available from
http://informahealthcare.com.ezproxy.ecu.edu.au/doi/pdf/10.3109/10903127.2014.8910
64 DOI: 10.3109/10903127.2014.891064
4. Coventry LL, Bremner AP, Williams TA, Celenza A, Jacobs IG, Finn J.
Characteristics and outcomes of MI patients with and without chest pain: A
cohort study. Heart, Lung and Circulation. 2015; xx: 1-10.4
See Appendix D, manuscript published with permission from Elsevier. Available from
http://ac.els-cdn.com.qelibresources.health.wa.gov.au/S1443950615000530/1-s2.0-
xx
S1443950615000530-main.pdf?_tid=ab9f368e-ee11-11e4-b56a-
00000aacb362&acdnat=1430272219_86a53ba75d68070de88c29c22a101180
DOI: 10.1016/j.hlc.2015.01.015
5. Coventry LL, Bremner AP, Williams TA, Celenza A. The effect of presenting
symptoms and patient characteristics on prehospital delay in MI patients
presenting to ED by ambulance: A cohort study. Heart, Lung and Circulation.
2015; xx: 1-8.5
See Appendix E, manuscript published with permission from Elsevier. Available from
http://ac.els-cdn.com.qelibresources.health.wa.gov.au/S144395061500164X/1-s2.0-
S144395061500164X-main.pdf?_tid=a07fe7b6-ee12-11e4-bd6d-
00000aacb362&acdnat=1430272629_1e465cd168275493209f655f3e9729b5
DOI: 10.1016/j.hlc.2015.02.026
Awards and recognition
During this study the student received:
• National Health Medical Research Council Post Graduate PhD Scholarship (30
June 2008 to 28 December 2011),
• Cardiac Society of Australia and New Zealand, Finalist in Best Nursing
Presentation, Perth, Australia. “Sex differences in symptom presentation in acute
myocardial infarction: a systematic review and meta-analysis.” 2011
• Paramedics Australasia, Finalist in Best Poster Award, Sydney, Australia.
“Gender differences in emergency ‘000’ calls and ambulance response for acute
myocardial infarction patients.” 2011
• Young Investigators Award, Sir Charles Gairdner Hospital, Perth Western
Australia. “Sex differences in symptom presentation in acute myocardial
infarction: a systematic review and meta-analysis.” 2011
• Academic Research Grant, The Nursing and Midwifery Office, Western
Australia, 2014
xxi
Conference presentations
Oral presentations
Coventry LL, Finn J, Bremner AP. Sex differences in symptom presentation in acute
myocardial infarction: A systematic review and meta-analysis. Population Health
Postgraduate Society, seminar, University of Western Australia, 26 October 2010,
Perth, Western Australia.
Coventry LL, Finn J, Bremner AP. Sex differences in symptom presentation in acute
myocardial infarction: a systematic review and meta-analysis. Young Investigators
Award, Sir Charles Gairdner Hospital, October 2011, Perth, Western Australia.
Coventry LL, Finn J, Bremner AP. Sex differences in symptom presentation in acute
myocardial infarction: a systematic review and meta-analysis. Cardiac Society of
Australia and New Zealand Annual Scientific Meeting 2011, 11 August-14 August
2011, Perth, Western Australia.
Abstract 1
Coventry LL, Finn J, Bremner AP. Sex differences in symptom presentation in acute
myocardial infarction: A systematic review and meta-analysis. Heart, Lung and
Circulation. 2011;20 Suppl 2: S6.
See Appendix F, abstract available from
http://www.sciencedirect.com.qelibresources.health.wa.gov.au/science/article/pii/S1443
950611003556#
Poster presentations
Coventry LL, Jacobs IG, Bremner AP, Finn J. Sex differences in symptoms reported to
emergency medical dispatch in acute myocardial infarction patient – impact on pre-
hospital delay. Population Health Postgraduate Society, seminar, University of Western
Australia, 8 November 2011, Perth, Western Australia.
Coventry LL, Jacobs IG, Bremner AP, Finn J. Sex differences in symptoms reported to
emergency medical dispatch in acute myocardial infarction patient – impact on pre-
hospital delay. Poster Presentation, American Heart Association Scientific Sessions, 12
November -16 November 2011, Orlando, USA.
xxii
See Appendix G
Abstract 2
Coventry LL, Jacobs IG, Finn J. Abstract 12314: Sex differences in symptoms reported
to emergency medical dispatch in acute myocardial – impact on prehospital delay.
Circulation. 2011;124 Suppl 1
See Appendix H, Abstract available from
http://circ.ahajournals.org.qelibresources.health.wa.gov.au/cgi/content/meeting_abstract
/124/21_MeetingAbstracts/A12314?sid=0dbeebda-54e6-4af5-884d-bf4dc4051a24
Coventry LL, Jacobs IG, Bremner AP, Finn J. Gender differences in emergency ‘000’
calls and ambulance response for acute myocardial infarction patients. Paramedics
Australasia, 5 October- 8 October 2011, Sydney, Australia
See Appendix I
Abstract 3
Coventry, L., Finn, J., Jacobs, I. Gender differences in emergency ‘000’ calls and
ambulance response for acute myocardial infarction patients. Australasian Journal of
Paramedicine. 2011:10:34
See Appendix J, Abstract available on page 34 from
http://ro.ecu.edu.au/cgi/viewcontent.cgi?article=1428&context=jephc
xxiii
Statement of Candidate Contribution
This thesis contains published work and work prepared for publication, some of which
has been co-authored. The bibliographical details of the work, a description and
estimated percentage of the contribution of each author and where it appears in the
thesis are outlined below.
Publication 1
Coventry LL, (70%), Finn J, (15%), Bremner AP (15%). Sex differences in symptom
presentation in acute myocardial infarction: A systematic review and meta-analysis.
Heart & Lung. 2011;40:477-491.1
Linda Coventry conducted the systematic review of the literature, appraised every
article for quality, extracted data from every eligible study, interpreted the results and
drafted the manuscript. Judith Finn contributed to the conception and critically reviewed
the manuscript. Alexandra Bremner provided statistical advice and critically reviewed
the manuscript. This publication represents Chapter 3 of the thesis.
Publication 2
Coventry LL, (70%), Bremner AP, (15%), Jacobs IG, (5%), Finn J. (10%). Myocardial
Infarction: Sex differences in symptoms reported to Emergency dispatch. Prehospital
Emergency Care. 2013;17:193-202.2
Linda Coventry designed the study, collected and analysed the data, interpreted the
results and drafted the manuscript. Alexandra Bremner provided statistical advice and
critically reviewed the manuscript. Ian Jacobs and Judith Finn contributed to the
conception and critically reviewed the manuscript. This publication represents Chapter
4 of the thesis.
Publication 3
Coventry LL, (70%), Bremner AP, (15%), Williams TA, (5%), Jacobs IG, (5%), Finn J.
(5%). Symptoms of Myocardial Infarction: Concordance between Paramedic and
Hospital Records. Prehospital Emergency Care. 2014;18:393-401.3
Linda Coventry designed the study, collected and analysed the data, interpreted the
xxiv
results and drafted the manuscript. Alexandra Bremner provided statistical advice and
critically reviewed the manuscript. Teresa Williams, Ian Jacobs, and Judith Finn
critically reviewed the manuscript. This publication represents Chapter 5 of the thesis.
Publication 4
Coventry LL, (70%), Bremner AP, (15%), Williams TA, (3%), Celenza A, (3%), Jacobs
IG, (3%), Finn J. (5%). Characteristics and outcomes of MI patients with and without
chest pain: A cohort study. Heart, Lung & Circulation. 2015; xx:1-10.4
Linda Coventry designed the study, collected and analysed the data, interpreted the
results and drafted the manuscript. Alexandra Bremner provided statistical advice and
critically reviewed the manuscript. Teresa Williams, Antonio Celenza, Ian Jacobs and
Judith Finn critically reviewed the manuscript. This publication represents Chapter 6 of
the thesis.
Publication 5
Coventry LL, (70%), Bremner AP, (20%), Williams TA, (5%), Celenza A, (5%). The
effect of presenting symptoms and patient characteristics on prehospital delay in MI
patients presenting to ED by ambulance: A cohort study. Heart, Lung & Circulation.
2015; xx: 1-8.5
Linda Coventry designed the study, collected and analysed the data, interpreted the
results and drafted the manuscript. Alexandra Bremner provided statistical advice and
critically reviewed the manuscript. Teresa Williams and Antonio Celenza critically
reviewed the manuscript. This publication represents Chapter 7 of the thesis.
The thesis is my own composition, all sources have been acknowledged and my
contribution is clearly identified in the thesis. For any work in the thesis that has been
co-published with other authors, all authors have given permission for published and
submitted manuscripts to be included as part of this thesis.
The declaration to this effect is signed by my Coordinating Supervisors and myself.
xxv
List of Abbreviations
ABS
Australian Bureau of Statistics
ACC/AHA American College Cardiologist / American Heart Association ACS Acute Coronary Syndrome AMI Acute Myocardial Infarction AOR Adjusted Odds Ratio CABG Coronary Artery Bypass Graft CAD Coronary Artery Disease CI Confidence Interval CT Computerized Tomography CVD Cardiovascular Disease ECG Electrocardiograph ED Emergency Department EDIS Emergency Department Information System EMS Emergency Medical Service FMC First Medical Contact HCP Health Care Provider HR Hazard Ratio HTN Hypertension ICD-10-AM International Classification of Disease, 10th Revision, Australian
Modification IQR Interquartile Range n Number NOS Newcastle Ottawa Scale NPV Negative predictive Value NSTEMI Non ST Segment Elevated Myocardial Infarction MI Myocardial Infarction OR Odds Ratio PCI Percutaneous Coronary Intervention PCR Patient Care Record PPV Positive Predictive Value RFDS Royal Flying Doctor Service RR Rate Ratio SCGH Sir Charles Gairdner Hospital SD Standard Deviation SJA-WA St John Ambulance – Western Australia SPSS Statistical Package for the Social Sciences STEMI ST Segment Elevated Myocardial Infarction TOPAS The Open Patient Admission System UA Unstable Angina UMRN Unit Medical Record Number WA
Western Australia
xxiv
1
Chapter 1: Introduction
1.1 Background to the Study
Cardiovascular disease is the leading cause of death among women and men in the
world6 and in Australia.7 In Australia, it causes 31%8 of all deaths and is the most
expensive disease, comprising 12% of direct health care expenditure at over $7,605
million.9 One of the most common types of cardiovascular disease is acute coronary
syndrome (ACS). ACS represents a range of conditions including unstable angina, and
myocardial infarction (MI).
The underlying problem of MI in most cases is a condition called atherosclerosis where
abnormal build-up of fat cholesterol and fibre-like substances called plaque line the
arteries. Plaque causes narrowing of the blood vessels of the heart, which limits the
blood supply, a condition called angina.9 MI occurs when plaque ruptures and causes
thrombosis in the lumen of the coronary artery and completely blocks the blood flow to
the heart muscle. If the clot is not treated, some of the heart muscle will die,9 resulting
in a life-threatening situation, in which the patient may experience severe chest pain,
arrhythmias, heart failure or sudden death.9
A person who is having a MI (often referred to as a ‘heart attack’) is commonly
believed to present with a sudden onset of crushing, central chest pain, which causes
them to clutch their chest and collapse.10 This “Hollywood-like” portrayal of a MI does
indeed occur, but not in all cases and possibly less so in older patients and female
patients. Symptoms of MI may also include arm, shoulder, neck, jaw, abdominal and
back pain; shortness of breath; sweating; syncope and collapse; and nausea and
vomiting.
Minimising the time from onset of symptoms to definitive care (coronary artery
revascularisation) has consistently been shown to reduce both patient mortality and
damage to the heart muscle.11-15 Patient delay in recognising the symptoms of MI and
appropriately responding (activating emergency services such as calling “000” for an
ambulance) account for a major component of the delay from symptom onset to
definitive care. International and national public education campaigns16,17 have
attempted to reduce this patient delay by stressing the importance of responding
2
appropriately to chest pain. However, this may not be sufficient, as research has shown
that as many as one in three women and one in four men18 do not experience chest pain
and little is known about the characteristics of MI without chest pain.
The diagnosis of a MI is based on a combination of clinical symptoms,
electrocardiograph changes, elevation of cardiac biomarkers e.g., troponin and creatine
kinase-MB19 and in fatal cases, autopsy findings.20 The Australian Heart Foundation21
recommends, if you have chest pain or other warning signs of a heart attack that are
severe, get worse quickly, or last 10 minutes, you need to get help fast, and make an
emergency telephone call by dialling triple zero (000) immediately. Current Australian
guidelines22 to reduce delay to reperfusion therapy for patients with ST-elevation MI
recommend ambulance triage and early activation of the catheterisation laboratory. In
addition, international guidelines23 recommend emergency medical services perform a
12-lead electrocardiograph at the site of first medical contact and recommend
emergency medical services transport the patient to a percutaneous coronary
intervention capable hospital. The ideal first medical contact-to-device time system goal
should be less than 90 minutes.24
1.2 Context of the Study
1.2.1 Perth: Geography and Demography
The land area of Australia is almost the same as that of the United States (excluding
Alaska) and about 50% greater than the area of Europe (excluding the former Union of
Soviet Socialist Republic).25 Western Australia (WA), the largest state in Australia,
comprises the western third of the continent. In 2014, the population of WA was
estimated at 2.57 million - approximately 11% of Australia’s population.26 Perth, the
capital of WA, contains over three quarters (79%) of the state’s total population.27
1.2.2 The Western Australian Ambulance Service
St John Ambulance WA (SJA-WA) covers the largest area of any single ambulance
service in the world – 2,525,500 square kilometres. SJA-WA is the sole provider of
emergency road ambulance services in WA. During 2012/13, SJA-WA received an
average of 1441 emergency calls per day and dispatched more than 190,000 ambulance
cases in the Perth metropolitan area.28,29
3
During the period of this study (January 2008 to October 2009), SJA-WA provided
emergency ambulance services to the greater Perth metropolitan area that extended from
Two Rocks, 63 km (39 miles) north, to Port Kennedy, 56 km (35 miles) south, and
Wundowie, 71 km (44 miles) east, of the city centre.30 This area had 24 ambulance
centres: 21 were staffed by approximately 500 paramedics and patient transport officers;
and three were staffed by volunteer ambulance officers. The metropolitan fleet consisted
of approximately 90 ambulances and 15 patient transport vehicles.28
SJA-WA, a not-for-profit-organisation, generates funds through the provision of
ambulance services as a ‘user-pays’ organisation. Private health funds provide insurance
against ambulance fees. SJA-WA provides these services under a contract with the
Department for Health, but operates independently. Funding is also provided through
grants from supporters such as Lottery West, and from business activities; for example,
industrial paramedical services and first aid training.28
1.2.3 The Emergency Call
Emergency assistance from the ambulance in Perth is accessed by dialing triple zero
(000). Calls are answered by an operator who asks the caller whether the emergency
requires “police, fire or ambulance.” Calls requesting an ambulance are immediately
transferred to a communications officer at the Ambulance Operation Centre located in
Belmont, Perth. The communications officer asks vital emergency call information and
allocates a priority to the call, as outlined below:
• Priority 1 represents a ‘potential for life to be at risk’ and entails a lights and
sirens ambulance response. Types of calls in this category are for patients with
chest pain and/or shortness of breath, unconscious patients, direct transfers to a
cardiac catheter laboratory, motor vehicle and industrial accidents, and childbirth.
The call is dispatched to the closest available ambulance and the response time to
the scene from the time the call is received by the ambulance service should be
<15 minutes for 90% of cases.
• Priority 2 represents ‘no immediate threat to life’. This category includes calls for
patients who have a medical problem or accident, but there is no immediate threat
to life. The call is dispatched to the most appropriate ambulance, and the response
time to the scene from the time the call is received by the ambulance service
4
should be <25 minutes for 90% of cases.
• Priority 3 includes the Royal Flying Doctor Service (RFDS) transfers and rescue
tasks. Ambulances need to be on time for the RFDS, and the call is dispatched to
the next available ambulance, taking into consideration appropriate paramedic
skill levels. The response time to the scene from the time the call is received by
the ambulance service should be <60 minutes for 90% of cases.
The communications officer takes details of the call using a computer aided dispatch
system which provides comprehensive geographical and incident information.28 The
computer aided dispatch system automatically records the time the call was received;
the time the call was dispatched to the ambulance; and the times the ambulance arrived
on the scene, departed the scene, and arrived at the hospital.
1.2.4 SJA-WA Communication Officers
At the time of the study, SJA-WA communications officers completed a two-week in-
house training course in dispatch and prioritising ambulance calls. The communications
officers were not medically trained and they followed written in-house protocols which
directed them to ask a series of scripted questions to establish location of the incident,
phone number of the caller, chief complaint, and other complaint-specific questions.
The American terminology for SJA-WA ‘communication officer’ is a ‘dispatch officer’
and these terms are used interchangeably in this thesis.
1.2.5 SJA-WA Paramedics
Training to become a SJA-WA paramedic in WA requires completion of a Bachelor of
Science (Paramedical Science) degree and can be accomplished in four years. After
successful completion of the first year of training, students are employed by SJA-WA as
student ambulance officers. During the next two years of training, at SJA-WA and
Curtin University, students work full time and undertake study in specially allocated
blocks or by distance education. On passing all course work and completing the on-road
requirements, the student ambulance officer completes a further 12 month internship
under the guidance of senior paramedics before graduating as a paramedic.28
5
1.3 Statement of Problem
The emergency ambulance is usually the quickest mode of transport to hospital, and
paramedics are equipped to treat life-threatening cardiac arrhythmias if they occur.
Patients base their decision to make an emergency call on the symptoms they
experience, and these symptoms are critical in determining pre-hospital and emergency
department triage.
The research questions addressed in this thesis evolved as the study progressed.
Initially, although previous reviews1,18 of sex differences in symptoms of MI had found
that presenting without chest pain was more common in women than in men, findings
about sex differences in symptoms have been inconsistent and meta-analysis had not
been conducted. Also, no studies were found that investigated sex differences in
symptoms of MI reported during the emergency telephone call to the ambulance
service.
After completing the study of sex differences in symptoms of MI during the emergency
phone call, it was realised that both men and women may not report chest pain as a
symptom of their MI. This finding led to the subsequent research question about what
are the characteristics of presenting without chest pain. However, to answer this
question it was necessary to extract patient comorbidity and reperfusion data from the
hospital medical record. When reviewing the hospital medical record the accuracy of
the paramedic documentation of MI symptoms and symptom onset-time was also
validated. No studies were found in the literature that had investigated the accuracy of
paramedic documentation of MI symptoms.
After validating the accuracy of paramedic documentation and extracting the patient
comorbidity data, the characteristics associated with presenting with and without chest
pain and survival outcomes could be investigated. Studies in the literature reporting
characteristics associated with and without chest pain and survival outcomes have also
been inconsistent.31-33
As there were no recent Australian published studies that investigated the effect of
symptoms and patient characteristics on prehospital delay, the time from symptom-
onset to arrival in the ED, was the focus of the final research question. This information
is important as identification of variables associated with prehospital delay may lead to
6
interventions that succeed in shortening delay time.
Thus, in summary, the statement of problem is that there were no existing published
meta-analyses of sex differences in MI presentation, no studies that reported sex
differences in the emergency telephone call, and no studies that investigated the
accuracy of paramedic documentation of MI symptoms. Furthermore, the findings from
studies that reported patient characteristics and survival outcomes associated with
presenting with and without chest pain were inconsistent, and there were no recent
Australian studies of prehospital delay.
1.4 Research Questions
1. Do men and women equally present with chest pain as a symptom of MI
and are there sex differences in other presenting symptoms of MI?
2. Are the symptoms, in particular chest pain, reported during the emergency
telephone call to SJA-WA and ambulance response times, the same for men
and women with MI?
3. Are paramedic records a reliable source of information about presenting
symptoms of MI and onset-time of symptoms compared with the
documentation in the hospital medical record?
4. Are patient characteristics and patient outcomes (survival and hospital
discharge diagnosis) of patients presenting with and without chest pain the
same?
5. What is the prehospital delay time for MI patients transported by
ambulance, and what are the patient characteristics and presenting
symptoms which contribute to prehospital delay?
1.5 Significance of the Study
Correct recognition of MI symptoms in the prehospital environment is crucial for the
ambulance dispatcher to allocate a priority 1 (lights and sirens) ambulance response.
Early symptom recognition of MI reduces patient delay in seeking treatment, ensures
timely diagnosis and definitive care. Early presentation and coronary revascularisation
have consistently been shown to reduce morbidity and mortality.14,15
Identifying sex differences and other patient characteristics associated with the
7
symptoms of MI, and the patient characteristics associated with prehospital delay, may
better inform future public health campaigns aimed at decreasing delay. This study is
important because time from onset of symptoms of MI to arrival at the hospital
continues to be far too long to achieve optimal benefit from reperfusion therapy in the
majority of cases.
1.6 Structure of the Thesis
The regulations of The University of Western Australia34 provide the option for
candidates for the Degree of Doctor of Philosophy to present their thesis as a series of
manuscripts which have been published in refereed journals, manuscripts that have been
submitted for publication but not yet accepted, or manuscripts that could be submitted.
This thesis is presented as a combination of published manuscripts and supporting text
description. As such, there is some repetition particularly in the Background and the
Methods sections. Also, there are minor variations in abbreviations and the use of
Australian English and American English throughout. An overview of each chapter
follows.
Chapter 2 is the Author’s Original Manuscript published in the Heart & Lung journal,
and it reports the findings of the systematic review and meta-analysis.1 This Chapter
contains the majority of the literature review for the study. The literature that has been
published post publication of this manuscript is updated in Chapter 8.
Although methods are briefly explained in each manuscript, Chapter 3 has been
included to expand on this information and provide an overview of the data sources
used and the linkage of the data. Chapter 4 is the Author’s Original Manuscript,
published in Prehospital Emergency Care journal, which outlines the sex differences in
symptoms reported to ambulance dispatch and ambulance times for patients with MI.2
This retrospective cohort study reviewed the emergency telephone call of all adult
patients with an ED discharge diagnosis of MI transported by SJA-WA to one of seven
Perth metropolitan EDs between January 2008 and October 2009.
Chapter 5 is the Author’s Original Manuscript published in Prehospital Emergency Care
journal. It reports the concordance of the symptoms and symptom-onset time
documented in the paramedic patient care record with those in the hospital medical
8
record for MI patients.3 This study was conducted at a single teaching hospital in Perth,
between January 2008 and October 2009.
Chapter 6 is the Author’s Original Manuscript, published in Heart, Lung and
Circulation, and it reports the characteristics and outcomes of MI patients with and
without chest pain.4 This study was conducted at a single teaching hospital in Perth,
between January 2008 and October 2009.
Chapter 7 is the Author’s Original Manuscript, published in Heart, Lung and
Circulation.5 This study describes the prehospital delay time of all adult patients with an
ED discharge diagnosis of MI transported by SJA-WA to one of seven Perth
metropolitan EDs between January 2008 and October 2009.
In the final chapter, Chapter 8, the major findings of the study are discussed, the
literature published post each publication is reviewed, and limitations of the study are
described. Recommendations for policy, practice and further research are made and
final conclusions are drawn.
9
Chapter 2: Sex Differences in Symptom Presentation in
Acute Myocardial Infarction: A Systematic Review and
Meta-analysis
2.1 Introduction
This chapter is the Author’s Original Manuscript published in Heart & Lung, 2011;
40:477-491 (Appendix A).1 The manuscript reports a systematic review and meta-
analysis of sex differences in symptom presentation of acute MI. The process adhered to
the Meta-analysis of Observational Studies in Epidemiology study guidelines.35 This
chapter aims to answer the first research question posed in Chapter 1, Section 1.4.
1. Do men and women equally present with chest pain as a symptom of MI
and are there sex differences in other presenting symptoms of MI?
This chapter provides most of the literature review for the study. The literature
published after the search was completed in October 2009 has been updated in Chapter
8.
2.2 Abstract
2.2.1 Background
Recognition of sex differences in symptom presentation of acute myocardial infarction
(AMI) is important for timely clinical diagnosis. This review examined whether women
are equally as likely as men to present with chest pain.
2.2.2 Methods
We conducted a systematic review and meta-analysis of English language research
articles published between 1990 and 2009.
2.2.3 Results
Meta-analysis showed women with AMI had lower odds and a lower rate of presenting
with chest pain than men (OR=0.63, 95% CI 0.59, 0.68; RR=0.93, 95% CI 0.91, 0.95).
10
Women were significantly more likely than men to present with fatigue, neck pain,
syncope, nausea, right arm pain, dizziness and jaw pain.
2.2.4 Conclusions
Health campaigns on symptom presentation of AMI should continue to promote chest
pain as the cardinal symptom of AMI, but also reflect a wider spectrum of possible
symptoms and highlight potential differences in symptom presentation between men
and women.
2.2.5 Key Words
Acute myocardial infarction, meta-analysis, sex differences, symptom presentation,
systematic review
2.3 Background
Despite heart disease being the leading cause of death worldwide in older women, there
is a misperception that heart disease is an affliction mainly of men.36 Heart disease is an
umbrella term for a variety of different diseases affecting the heart, including Acute
Coronary Syndrome (ACS). In turn, ACS represents a range of conditions including
unstable angina (UA) and acute myocardial infarction (AMI), commonly called a ‘heart
attack’. In the United States of America in 2006, an estimated 785,000 people had a new
AMI and 470,000 people had a recurrent AMI, and more than 76,000 men and 65,000
women died of an AMI.10
A person who has an AMI is commonly believed to present with a sudden onset of
crushing central sternal pain, with the person clutching his/her chest and collapsing.
This ‘Hollywood-like’ portrayal of AMI onset does indeed occur, but not in all cases
and possibly less so in women.10 It is recognised that the more atypical presentations of
AMI can result in a delay in seeking medical care. Correct recognition of AMI
symptoms by the person experiencing the event and the health care provider is vital,
because time to treatment is crucial in minimising myocardial damage37 and improving
morbidity and mortality outcomes.13-15
Current international16 and national10,17,38 public education campaigns tend to promote
chest pain as the cardinal symptom of an AMI, however, research has shown that fewer
women experience chest pain than men.39,40 Women may not be aware of both typical
11
and atypical heart attack symptoms and often delay in seeking medical care.41,42
Subsequently, women with AMI are more likely than men to be under-diagnosed and
under-treated.41,43-45
A number of reviews of sex differences in symptoms of ACS 18,39,46,47 have been
reported in the literature, albeit with inconsistent findings, perhaps because studies and
reviews combine patients with different diagnoses, for example, patients with AMI, UA
and non-cardiac chest pain. Also, the reviews of AMI symptoms include a number of
studies restricted to patients who presented with chest pain39,47,48 and thereby exclude all
potential AMI patients who presented with other symptoms. Previous reviews searched
a limited range of databases and used broad or heterogeneous inclusion / exclusion
criteria.39,47,48 Our article adds to the body of literature as we have narrowed the patient
population to only include AMI patients, performed a quality assessment of the research
articles, and used sophisticated statistical analysis to calculate odds ratios (ORs) and
risk ratios (RRs).
We conducted a systematic review of published quantitative research studies to compare
the presenting symptoms of men and women with a confirmed diagnosis of AMI. We
sought to address 2 main research questions: 1) Do men and women equally present
with chest pain as a symptom of AMI? 2) Are there sex differences in other presenting
symptoms of AMI?
2.4 Methods
2.4.1 Search Strategy
The search strategy adhered to the Meta-analysis of Observational Studies in
Epidemiology study guidelines35 and was undertaken using MEDLINE, CINAHL,
EMBASE, Cochrane Library, Current Contents and ISI Web of Knowledge. The search
was performed with the aid of a professional librarian using a combination of search
terms, including chest pain OR symptom OR atypical OR emergency medical service
AND gender OR women AND acute myocardial infarction. The search strategy was
adapted for the different databases and all terms were searched with Medical Subject
Headings and as key (text) words. In addition, the references of all retrieved articles
were checked, and other articles that cited the retrieved article were also checked using
citation alert with ISI Web of Knowledge.
12
2.4.2 Inclusion and Exclusion Criteria
We aimed to include all research studies published between January 1990 and October
2009 that were written in English and reported sex differences in presenting symptoms
in patients with a confirmed AMI. The method for confirmation of diagnosis of AMI
could include increased enzyme elevation of creatine kinase or troponin,
electrocardiogram changes or International Classification of Diseases diagnosis codes of
410 or I21, I22. Studies were excluded if they were qualitative, included patients who
presented with chest pain (n=11) and reported only ACS symptoms where it was not
possible to differentiate between AMI and UA (n=12). Studies of patients with UA were
excluded because the operational definition was not made clear in many of these studies
and as such risked increasing heterogeneity further, by the inclusion of “patients with
stable angina.” All selected studies were reviewed in full text by one author (L.L.C.).
2.4.3 Quality Assessment
The selected studies were assessed for quality using the Newcastle–Ottawa Scale (NOS)
for Assessing the Quality of Nonrandomized Studies in Meta-Analysis,49 which is a
quality assessment tool that awards stars based on 3 categories. The first category
allocates stars on the selection of cohort, the second category allocates stars on the
comparability of the study based on design or analyses, and the third category allocates
stars on the assessment of outcome of the study. The NOS was adapted for the purposes
of this review as follows: Representativeness of the cohort was given a half star if it was
somewhat representative, and a full star was given if truly representative of the exposed
cohort; for assessment of outcome, record linkage was considered to be data from
medical records, and self report was considered to be data from interview or
questionnaire. Studies were excluded from the review if they failed to achieve at least 5
of the possible 9 stars.
2.4.4 Data Extraction
The following data were extracted in duplicate (to check accuracy) by one author (LLC)
from the included studies:
• Study design: prospective or retrospective, method of collecting data (medical
record, interview, structured data form), and inclusion / exclusion criteria.
• Study setting, study years and sample size.
• Proportion of men and women with chest pain.
13
• Proportion of men and women with each symptom: fatigue, arm and shoulder
pain, indigestion, epigastric pain, neck pain, syncope, nausea, right arm pain,
abdominal pain, dyspnea, dizziness, jaw pain, palpitations, back pain, sweating,
weakness, vomiting, left shoulder pain, right shoulder pain, headache and left arm
pain.
• Proportion of men and women with comorbidity: angina, congestive heart failure,
hypertension, history of AMI, diabetes, and hypercholesteremia.
• Statistical analysis: adjustment for age or other covariates identified in the
particular study.
2.4.5 Statistical Analysis
Forrest plots were produced to display the effect measures of each study that were
expressed as prevalence, OR and RR with 95% confidence intervals (CIs). The OR is
the ratio of the odds of an event occurring in men to the odds of the event occurring in
women. The RR is the ratio of the probability of the event occurring in women divided
by the probability of the event occurring in men. A ratio of 1 implies the event is
equally likely in both men and women, a ratio of greater than 1 implies the event is
more likely in women and a ratio of less than 1 implies the event is less likely in
women.50 Both ORs and RRs were calculated to highlight the different results. When
the outcome or symptom is common (ie, > 10%-20%), it is recommended to use RR
because the OR is further from 1 compared with the RR.51,52 Statistical meta-analysis
was conducted using RevMan, version 5 for Windows by the Cochrane collaboration,53
and results were pooled using random effects models, which assume the different
studies estimate different yet related effects.51 Heterogeneity measures the variability
among the combined studies; if there is considerable variation in the combined or
pooled results, it may be misleading to report a combined summary measure.51 The chi-
square (χ2) test and I2 statistic were used to assess heterogeneity. The χ2 statistic was
used to test the null hypothesis that there is no heterogeneity, with a p-value of < 0.05
indicating heterogeneity. The I2 statistic describes the variability in effect measurements
that is due to heterogeneity rather than sampling error. The I2 value was interpreted as
follows: Less than 40% might not be important, 30% to 60% may represent moderate
heterogeneity, 50% to 90% may represent substantial heterogeneity and 75% to 100%
represents considerable heterogeneity.51 The pooled result was considered
heterogeneous if the I2 statistic was > 40% and the p-value was < 0.05.
14
Publication bias may occur when studies with non-significant findings are not submitted
by the investigator or are rejected by the editors of the journals.50 When 10 or more
studies were combined, publication bias was assessed using funnel plots and interpreted
by visual inspection.51 Missing data were assumed to be missing at random and
therefore not included in the analysis.51 To consistently compare women with men,
some ORs reported in the original studies were reversed and may have rounding errors.
Crude results were estimated from a figure in one study.40 When calculating the pooled
mean age, only studies that had no age restriction in their inclusion criteria were used. A
narrative review is presented for the studies that adjusted for age and other variables in
their analysis.
2.5 Results
2.5.1 Included Studies Characteristics
Figure 1 summarizes the study selection process that resulted in 27 studies32,40,54-78
being included in the meta-analysis. One study57 was not used in the pooled results for
chest pain because the torso was divided into 9 quadrants and we were unable to
accurately ascertain how chest pain was classified, however, this study57 was used in the
pooled results for the other associated symptoms of AMI (right arm, left arm, neck, and
back). Table 1 summarizes the descriptive data from these studies. Most of the studies
were conducted in the United States and Europe, and all were published between 1990
and 2009 but include study years spanning from 1978 to 2006. The majority of study
designs were cohort (78%) or cross-sectional (15%), and the method of enrolling
participants was mostly prospective (78%). Data were collected via medical record
review (67%) or combined interview / medical record review (15%) and the remaining
15% (5 studies) collected the data via a combination of medical record / questionnaire
(n=1); questionnaire (n=1); combination of questionnaire / interview (n=1); or interview
(n=2). Data were abstracted from tables of most of the studies. For the majority of the
studies (n=20, 77%) chest pain was described as “yes or no” with no other descriptors.
In 4 studies65,70,74,75 (15%) chest pain descriptors used included “pain, discomfort,
pressure, tightness, heaviness, squeezing or crushing.” One study54 used “chest pain or
discomfort” and one study72 used “chest discomfort.
15
AM
I, ac
ute
myo
card
ial i
nfar
ctio
n; A
CS,
acu
te c
oron
ary
synd
rom
e,
NO
S, N
ewca
stle
-Otta
wa
Scal
e; U
A, u
nsta
ble
angi
na
Figu
re 1
: Fl
ow D
iagr
am o
f Sea
rch
Res
ults
and
Stu
dy S
elec
tion
N=3
,906
C
INA
HL
n=26
6
MED
LIN
E n=
620
EMB
ASE
n=90
5
CO
CH
RA
NE
n=14
0
CU
RR
ENT
CO
NTE
NTS
n=85
3
ISI W
EB O
F
KN
OW
LED
GE
n=1,
122
Scre
enin
g
abst
ract
and
title
n=55
n=
51
n=12
n=
8 n=
6
n=10
All
reta
ined
stud
ies
Dup
licat
es, n
=131
n=17
3
n=30
4
n=18
4
n=27
Elig
ible
for
furth
er re
view
Fo
und
by re
fere
nce
track
ing
and
cita
tion
aler
t, n=
11
Excl
uded
, n=1
53
• N
o A
MI s
ympt
oms,
n=76
• N
o se
x di
ffer
ence
s rep
orte
d, n
=20
• R
evie
w a
rticl
e, n
=18
• A
CS
sym
ptom
s, un
able
to d
iffer
entia
te
betw
een
AM
I and
UA
, n=1
2
• C
hest
pai
n on
ly p
atie
nts,
n=11
• R
epea
t stu
dy, n
=5
• O
ther
, n=1
1
Excl
uded
, n=4
Few
er th
an 5
/9 st
ars o
n
Qua
lity
Ass
essm
ent (
NO
S)
Elig
ible
for
full
text
revi
ew
Incl
uded
in
revi
ew
16
Tabl
e 1:
Su
mm
ary
of C
hara
cter
istic
s of I
nclu
ded
Acu
te M
yoca
rdia
l Inf
arct
ion
Stud
ies (
orde
red
alph
abet
ical
ly b
y th
e fir
st a
utho
r)
Stud
y C
ount
ry
Stud
y D
esig
n / m
etho
d of
en
rolli
ng
part
icip
ants
Met
hod
of
Col
lect
ing
Dat
a
Stud
y Y
ears
Sam
ple
Size
•
N
• M
en
• W
omen
Mea
n A
ge
(yea
rs)
• M
en
• W
omen
Age
/ O
ther
A
djus
tmen
t fo
r sy
mpt
om
pres
enta
tion
by se
x
Incl
usio
n E
xclu
sion
Ber
g
54
Swed
en
Pr
ospe
ctiv
e C
onse
cutiv
e M
edic
al
reco
rd
2001
–
2004
22
5 M
=173
W
=52
M=5
9.3
W
=61.
2 A
ge
25-7
4 ye
ars,
1st ti
me
AM
I
Cul
ic
55
Cro
atia
Pros
pect
ive
St
ruct
ured
da
ta fo
rm
and
Med
ical
re
cord
1990
–
1995
1,
996
M
=1,3
95
W=6
01
M=5
7 W
=63
Age
/ ris
k fa
ctor
s and
ca
rdia
c en
zym
e le
vel
1st ti
me
AM
I U
nabl
e to
ans
wer
qu
estio
ns,
Prev
ious
infa
rct
Dor
sch
56
U
K
Pros
pect
ive
Con
secu
tive
Med
ical
R
ecor
d Se
pt –
N
ov
1995
2,08
2 M
=1,2
66
W=8
16
1st e
vent
AM
I D
eath
Ever
ts
57
Swed
en
Pros
pect
ive
Con
secu
tive
Stru
ctur
ed
data
form
an
d M
edic
al
reco
rd
45
5
M=3
32
W=1
23
Ove
rall
65.4
D
eath
, phy
sica
l in
capa
city
, lac
k of
pa
in, c
ogni
tive
limita
tion,
and
oth
er
lang
uage
Fi
ebac
h
58
USA
R
etro
spec
tive
M
edic
al
reco
rd
1978
-19
82
1,12
2 M
=790
W
=332
M=5
8 W
=63
30
– 7
4 ye
ars
AM
I fol
low
ing
surg
ery
or tr
aum
a
Gol
dber
g 40
USA
R
etro
spec
tive
Med
ical
re
cord
1986
an
d 19
88
1,36
0 M
=810
W
=550
M=6
4.7
W=7
2.1
Age
/ m
edic
al
hist
ory,
&
sele
cted
AM
I ch
arac
teris
tics
A
MI f
ollo
win
g su
rger
y
17
Stud
y C
ount
ry
Stud
y D
esig
n / m
etho
d of
en
rolli
ng
part
icip
ants
Met
hod
of
Col
lect
ing
Dat
a
Stud
y Y
ears
Sam
ple
Size
•
N
• M
en
• W
omen
Mea
n A
ge
(yea
rs)
• M
en
• W
omen
Age
/ O
ther
A
djus
tmen
t fo
r sy
mpt
om
pres
enta
tion
by se
x
Incl
usio
n E
xclu
sion
Gol
dste
in 59
USA
Pr
ospe
ctiv
e
Inte
rvie
w
and
Med
ical
R
ecor
d
12-5
2 m
onth
fo
llow
-up
, ce
nsor
da
te
June
30
1987
2,46
4
M=1
,966
W
=498
25 –
75
year
s B
rady
card
ia,
sym
ptom
atic
hy
pote
nsio
n, o
r co
mpl
icat
ing
dise
ases
, med
icat
ed
with
cal
cium
cha
nnel
bl
ocke
rs, n
eede
d ca
rdia
c su
rger
y, in
tra-
oper
ativ
e A
MI,
maj
or
psyc
hiat
ric d
isor
der,
impa
ired
cons
ciou
snes
s, ch
roni
c na
rcot
ic u
se
or a
lcoh
olis
m
Gra
ce60
Can
ada
Pr
ospe
ctiv
e C
onse
cutiv
e Su
rvey
and
M
edic
al
Rec
ord
48
2
M=3
47
W=1
35
M=5
9.2
W=6
6.3
Illne
ss se
verit
y,
conf
usio
n, lo
w
Engl
ish
prof
icie
ncy,
un
cons
ciou
s, re
fusa
l H
endr
icks
61
USA
Pr
ospe
ctiv
e C
onse
cutiv
e M
edic
al
reco
rd
1996
27
0 M
=187
W
=83
M=6
1 W
=66
Her
litz62
Sw
eden
R
etro
spec
tive
Med
ical
re
cord
D
ec
1998
–
Feb
1999
130
M=8
5 W
=45
all t
rans
porte
d by
am
bula
nce
with
AC
S
Hira
kaw
a 32
Japa
n
Pros
pect
ive
Con
secu
tive
Med
ical
R
ecor
d 20
01 -
2003
2,
221
M=1
,712
W
=509
18
Stud
y C
ount
ry
Stud
y D
esig
n / m
etho
d of
en
rolli
ng
part
icip
ants
Met
hod
of
Col
lect
ing
Dat
a
Stud
y Y
ears
Sam
ple
Size
•
N
• M
en
• W
omen
Mea
n A
ge
(yea
rs)
• M
en
• W
omen
Age
/ O
ther
A
djus
tmen
t fo
r sy
mpt
om
pres
enta
tion
by se
x
Incl
usio
n E
xclu
sion
Isak
sson
63
Sw
eden
Pros
pect
ive
C
onse
cutiv
e
Med
ical
R
ecor
d 19
89 –
2003
6,
542
M=5
,072
W
=1,4
70
M=5
5.6
W=5
6.6
1985
-200
0 on
ly 2
5-64
yea
rs, 2
000-
2003
on
ly 2
5-74
yea
rs,
both
1st a
nd re
curr
ent
even
ts a
re in
clud
ed
Dea
th o
r in
card
iac
arre
st, n
o tim
e va
riabl
e co
ded
Kos
uge64
Japa
n
Pros
pect
ive
Con
secu
tive
Inte
rvie
w
& C
hart
revi
ew
2001
- 20
04
457
M=3
51
W=1
06
M=6
2 W
=72
ST
EMI o
nly
Car
diog
enic
shoc
k,
dem
entia
, ear
ly d
eath
, ot
her c
ondi
tions
pr
eclu
ding
the
asse
ssm
ent o
f pai
n
Lovl
ien65
N
orw
ay
Pros
pect
ive
Con
secu
tive
Que
stio
nna
ire
Med
ical
R
ecor
ds
2003
–
2004
53
3
M=3
84
W=1
49
M=5
8.5
W
=61.
2
Age
<76
year
s 1st
AM
I A
lread
y ho
spita
lised
pa
tient
s
Lusi
ani66
Italy
Ret
rosp
ectiv
e C
onse
cutiv
e
Med
ical
R
ecor
ds
1989
- 19
91
94
M=6
0 W
=34
Ove
rall
68.5
Mar
tin67
USA
Pros
pect
ive
.
Inte
rvie
w
and
ques
tionn
aire
14-
mon
th
perio
d
157
M
=109
W
=48
M=6
0.1
W=6
1.1
Una
ble
to re
call
the
deci
sion
to se
ek
med
ical
car
e,
diso
rient
ated
or
unab
le to
spea
k En
glis
h, w
ere
with
out
acce
ss to
a p
hone
M
ayna
rd 68
U
SA
Pros
pect
ive
Med
ical
re
cord
19
93
7 mon
th
perio
d
895
M=5
73
W=3
22
M=6
3 W
=69
30
yea
rs
Tr
aum
a, su
rgic
al
emer
genc
y, o
r cle
ar
non-
card
iac
caus
e,
trans
ferr
ed fr
om
anot
her h
ospi
tal
19
Stud
y C
ount
ry
Stud
y D
esig
n / m
etho
d of
en
rolli
ng
part
icip
ants
Met
hod
of
Col
lect
ing
Dat
a
Stud
y Y
ears
Sam
ple
Size
•
N
• M
en
• W
omen
Mea
n A
ge
(yea
rs)
• M
en
• W
omen
Age
/ O
ther
A
djus
tmen
t fo
r sy
mpt
om
pres
enta
tion
by se
x
Incl
usio
n E
xclu
sion
Miln
er69
USA
Pros
pect
ive
Con
secu
tive
Med
ical
R
ecor
d 19
97
and
1999
2,07
3 M
=1,1
92
W=8
81
Div
ided
in
to a
ge
grou
ps
Age
Mor
gan70
U
SA
Pr
ospe
ctiv
e
Inte
rvie
w
2001
- 20
02
98
M=6
2 W
=36
M=6
1
W=6
5
Sym
ptom
s beg
an o
ut
of h
ospi
tal,
curr
ent
in-p
atie
nt
Paul
71
USA
Pros
pect
ive
Med
ical
re
cord
1991
-19
92
561
M=3
83
W=1
78
M=6
4 W
=70
Penq
ue72
U
SA
Pros
pect
ive
Con
veni
ence
Inte
rvie
w
and
Med
ical
re
cord
12 –
m
onth
pe
riod
98
M=4
7 W
=51
M=5
6 W
=61
21 +
yea
rs, E
nglis
h sp
eaki
ng, a
dmitt
ed
via
ED, p
hysi
cian
’s
offic
e or
tran
sfer
fr
om ru
ral h
ospi
tal
with
in 6
hrs
of A
MI
Sudd
en c
ardi
ac d
eath
Sric
haiv
eth
73
Thai
land
Pros
pect
ive
Con
secu
tive
Med
ical
re
cord
20
02 –
20
05
3,83
6
M=2
,613
W
=1,2
23
M=5
9.7
W=6
7.5
ST
EMI o
nly
Sum
mer
s 74
USA
R
etro
spec
tive
Con
secu
tive
Med
ical
re
cord
3
year
pe
riod
166
M=8
1 W
=85
In
suff
icie
nt
info
rmat
ion
to
dete
rmin
e an
ear
ly
ches
t pai
n de
scrip
tion
Then
75
Can
ada
R
etro
spec
tive
:
Med
ical
re
cord
and
In
terv
iew
qu
estio
nna
ire
15
3 M
=105
W
=48
Div
ided
in
to a
ge
grou
ps
35
+ ye
ars,
Engl
ish
spea
king
, 1st ti
me
AM
I
Tran
sfer
red
from
an
othe
r hos
pita
l
Tuns
tall-
Pedo
e76
Scot
land
Pr
ospe
ctiv
e C
onse
cutiv
e M
edic
al
Rec
ords
19
85-
1991
5,
542
M=3
,991
W
=1,5
51
M=5
5.5
W=5
7
25-6
4 ye
ars
20
Stud
y C
ount
ry
Stud
y D
esig
n / m
etho
d of
en
rolli
ng
part
icip
ants
Met
hod
of
Col
lect
ing
Dat
a
Stud
y Y
ears
Sam
ple
Size
•
N
• M
en
• W
omen
Mea
n A
ge
(yea
rs)
• M
en
• W
omen
Age
/ O
ther
A
djus
tmen
t fo
r sy
mpt
om
pres
enta
tion
by se
x
Incl
usio
n E
xclu
sion
Vac
carin
o 77
USA
Pros
pect
ive
Con
secu
tive
Med
ical
re
cord
ab
stra
ctio
n
1994
–
2006
91
6,38
0 M
=
555,
965
W=
362,
415
A
MI s
econ
dary
to
surg
ery,
hyp
oten
sion
or
oth
er e
vent
s afte
r ho
spita
lisat
ion,
tra
nsfe
rred
from
an
othe
r hos
pita
l W
illic
h78
Ger
man
y
Pros
pect
ive
Con
secu
tive
Inte
rvie
w
1,
082
M
=804
W
=278
61
M, m
en; W
, wom
en; A
MI,
acut
e m
yoca
rdia
l inf
arct
ion;
AC
S, a
cute
cor
onar
y sy
ndro
me;
STE
MI,
ST-s
egm
ent e
leva
tion
myo
card
ial i
nfar
ctio
n; E
D, e
mer
genc
y de
partm
ent
.
21
The mean age varied from 57 to 72.1 years for women and from 55.5 to 64.7 years for
men, and sample sizes varied from 94 to > 900,000 participants. Inclusion criteria for
some of the studies involved age restrictions and limits to first-time AMI. Exclusion
criteria for some of the studies included AMI after trauma or surgery, death, impaired
cognition, and illness severity. Only 5 studies40,54,55,65,69 adjusted for age in the analysis
of the effect of sex on symptoms, and of these 3 studies40,55,69 also adjusted for other
factors. The results of the NOS quality assessment ranged from 5.5 to nine stars and are
presented in Table 2. The majority of the studies were allocated 7 of the possible 9 stars.
Four studies79-82 were excluded because they did not meet either of the quality criteria
for both representativeness of the cohort (eg, convenient sample and / or small sample
size) and methodology used for assessing the outcome (eg, interview 3 to 5 days after
AMI).
2.5.2 Chest Pain
Of the 26 studies used in the meta-analysis, 13 found that women with AMI had
significantly lower odds than men of experiencing chest pain. Figure 2 summarizes the
results from each study and the pooled OR. Overall, the pooled OR from the meta-
analysis indicated that women with AMI had lower odds of presenting with chest pain
than men (OR=0.63; 95% CI 0.59, 0.68). The I2 value was 34% suggesting an
acceptable level of heterogeneity between studies. The sample size of the studies ranged
from 94 to 916,380, with the largest study77 contributing approximately 20% of the
weight of the pooled effect. Given concerns about the potential for this study to
dominate the results, we re-ran the analysis excluding the study and found that the
pooled OR changed minimally (OR=0.62; 95% CI 0.58, 0.66).
When analyzing RRs for the 26 studies, 11 indicated that women with AMI were
significantly less likely than men to present with chest pain. Figure 3 summarizes the
results from each study and the pooled RR. Overall, the pooled RR from the meta-
analysis indicated that women with AMI had a lower rate of presenting with chest pain
than men (RR=0.93; 95% CI 0.91, 0.95); however, the I2 value of 87% suggests this
result must be interpreted with care due to heterogeneity.
22
Table 2: Newcastle-Ottawa Quality Assessment
Study
Newcastle – Ottawa Quality Assessment Scale Total Score - maximum 9 stars
Selection - maximum 4 stars
Comparability - maximum 2 stars
Outcome - maximum 3 stars
Berg54 8 Culic55 8 ½ Dorsch56 7 Everts57 6 Fiebach58 6 ½ Goldberg40 9 Goldstein59 7 Grace60 6 Hendricks61 6 ½ Herlitz62 6 Hirakawa32 7 Isaksson 63 7 Kosuge64 6 ½ Lovlien65 6 ½ Lusiani66 6 Martin67 5 ½ Maynard68 7 Milner69 8 Morgan70 5 ½ Paul71 6 Penque72 6 Srichaiveth73 7 Summers74 6 ½ Then75 6 ½ Tunstall-Pedoe76 7 Vaccarino77 7 Willich78 6
23
Figure 2: Forest Plot of Studies Using OR in Comparing Chest Pain as a Presenting
Symptom of AMI in Women and Men (in alphabetical order)
OR, odds ratio; M-H, Mantel-Haenszel; CI, confidence interval
Study or SubgroupBerg 2009Culic 2002Dorsch 2001Fiebach 1990Goldberg 1998Goldstein 1995Grace 2003Hendricks 1999Herlitz 2002Hirakawa 2006Isaksson 2008Kosuge 2006Lovlien 2006aLuisiani 1994Martin 2004Maynard 1996Milner 2004Morgan 2005Paul 1995Penque 1998Srichaiveth 2007Summers 2001Then 2001Tunstall-Pedoe 1996Vaccarino 2009Willich 1993
Total (95% CI)Total eventsHeterogeneity: Tau² = 0.01; Chi² = 37.89, df = 25 (P = 0.05); I² = 34%Test for overall effect: Z = 12.41 (P < 0.00001)
Events46
479586279418470
876936
3831188
94128
2042
270476
28119
481079
4636
1053249751
247
257478
Total52
601816332550498135
8345
5091385
106149
3448
322881
36178
511223
8548
1297362415
278
372157
Events164
12221075
703688
1879238160
7413864377
310353
4491
516822
53290
462435
4980
2730426886
740
447411
Total173
13951266
790810
1966347187
8517124846
351383
60109573
119262
38347
261381
1053237
553965804
577542
Weight0.4%5.6%7.0%3.2%5.1%2.4%2.6%1.0%0.5%6.3%8.8%1.1%1.4%0.6%0.5%2.7%8.6%0.5%2.9%0.1%6.4%1.3%0.8%9.3%
18.8%2.2%
100.0%
M-H, Random, 95% CI0.42 [0.14, 1.24]0.56 [0.43, 0.72]0.45 [0.36, 0.56]0.65 [0.45, 0.94]0.56 [0.43, 0.74]0.78 [0.50, 1.20]0.83 [0.55, 1.26]0.83 [0.41, 1.68]0.59 [0.23, 1.56]0.71 [0.57, 0.90]0.65 [0.54, 0.77]1.04 [0.52, 2.05]0.52 [0.29, 0.94]0.52 [0.21, 1.27]1.38 [0.51, 3.74]0.57 [0.38, 0.86]0.53 [0.44, 0.63]0.59 [0.21, 1.71]0.65 [0.44, 0.96]0.35 [0.03, 3.47]0.55 [0.43, 0.69]0.77 [0.42, 1.43]0.94 [0.42, 2.07]0.80 [0.68, 0.95]0.66 [0.65, 0.67]0.69 [0.44, 1.08]
0.63 [0.59, 0.68]
Women Men Odds Ratio Odds RatioM-H, Random, 95% CI
0.01 0.1 1 10 100Women Men
24
Figure 3: Forest Plot of Studies Using RR Comparing Chest Pain as a Presenting
Symptom of AMI in Women and Men (in alphabetical order)
RR, rate ratio; M-H, Mantel-Haenszel; CI, confidence interval
The pooled result of the meta-analysis showed women with AMI had lower odds and a
lower rate of presentation with chest pain than men. Two previous reviews of the
literature39,47 have shown that women present with significantly less chest pain than men
in 2 of 8 studies and a third review48 showed that women present with less chest pain
than men in 3 of 8 studies; no studies found more chest pain in women. A possible
limitation of previous reviews is they included studies of patients who presented with
only chest pain and thus excluded all other potential AMI patients who presented with
other symptoms. Also, by combining the results of all the studies in a meta-analysis, we
are able to give a more precise estimate of sex differences in chest pain.
2.5.3 Associated Symptoms of AMI
Table 3 summarizes the pooled results of the meta-analyses of studies reporting sex
differences in other presenting symptoms of AMI. As shown, compared with men,
women had significantly higher odds and rates of presentation with fatigue, neck pain,
Study or SubgroupBerg 2009Culic 2002Dorsch 2001Fiebach 1990Goldberg 1998Goldstein 1995Grace 2003Hendricks 1999Herlitz 2002Hirakawa 2006Isaksson 2008Kosuge 2006Lovlien 2006aLuisiani 1994Martin 2004Maynard 1996Milner 2004Morgan 2005Paul 1995Penque 1998Srichaiveth 2007Summers 2001Then 2001Tunstall-Pedoe 1996Vaccarino 2009Willich 1993
Total (95% CI)Total eventsHeterogeneity: Tau² = 0.00; Chi² = 196.05, df = 25 (P < 0.00001); I² = 87%Test for overall effect: Z = 6.05 (P < 0.00001)
Events46
479586279418470
876936
3831188
94128
2042
270476
28119
481079
4636
1053249751
247
257478
Total52
601816332550498135
8345
5091385
106149
3448
322881
36178
511223
8548
1297362415
278
372157
Events164
12221075
703688
1879238160
7413864377
310353
4491
516822
53290
462435
4980
2730426886
740
447411
Total173
13951266
790810
1966347187
8517124846
351383
60109573
119262
38347
261381
1053237
553965804
577542
Weight2.9%5.4%5.2%5.0%4.9%6.2%1.9%2.6%1.5%4.9%6.2%3.9%4.1%0.5%2.1%4.9%4.1%1.1%2.5%3.8%6.3%0.7%1.2%6.0%6.6%5.3%
100.0%
M-H, Random, 95% CI0.93 [0.84, 1.04]0.91 [0.87, 0.95]0.85 [0.81, 0.89]0.94 [0.90, 1.00]0.89 [0.85, 0.95]0.99 [0.96, 1.01]0.94 [0.81, 1.09]0.97 [0.87, 1.09]0.92 [0.78, 1.09]0.93 [0.88, 0.98]0.95 [0.93, 0.97]1.00 [0.93, 1.09]0.93 [0.87, 1.00]0.80 [0.58, 1.10]1.05 [0.92, 1.20]0.93 [0.88, 0.98]0.78 [0.73, 0.84]0.91 [0.74, 1.11]0.88 [0.78, 0.99]0.96 [0.89, 1.04]0.95 [0.93, 0.97]0.89 [0.69, 1.16]0.98 [0.81, 1.20]0.96 [0.93, 0.99]0.89 [0.89, 0.90]0.97 [0.92, 1.01]
0.93 [0.91, 0.95]
Women Men Risk Ratio Risk RatioM-H, Random, 95% CI
0.01 0.1 1 10 100Women Men
25
nausea, syncope, right arm pain, dizziness and jaw pain. In meta-analyses with a higher
degree of heterogeneity (I2>40%, see table 3), there were significantly higher odds and
rates of women presenting with palpitations, back pain, dyspnea, vomiting and left arm
pain; and lower odds and rate of presenting with sweating.
We found women were more likely than men to experience fatigue (RR 1.19; 95% CI
1.06, 1.33), and 2 previous reviews39,48 showed significantly greater fatigue in women in
2 of 3 and 1 of 2 studies. We found women were more likely than men to experience
neck pain (RR 1.54; 95% CI 1.38, 1.73). Two reviews,39,48 also found women were
more likely than men to experience neck pain in 3 of 5 studies. We found women were
more likely than men to experience syncope (RR 1.37; 95% CI 1.11, 1.70). One
review48 found no significant difference between sexes in 6 studies and one review39
found significant differences in 1 of 3 studies.
We found that women were more likely than men to experience nausea (RR 1.42; 95%
CI, 1.35, 1.51). Two reviews39,47 combined the symptoms of nausea and vomiting, thus
not enabling comparison. The third review48 found women were more likely than men
to experience nausea in 5 of 8 studies. We found women were more likely than men to
experience right arm pain (RR 1.20; 95% CI 1.07, 1.33). One review48 found a
significant difference between sexes in only 1 of 3 studies. We found women were more
likely than men to experience dizziness (RR1.22; 95% CI 1.02, 1.46). Two reviews39,48
found significant differences in 1 of 4 and 1 of 6 studies. We found women were more
likely than men to experience jaw pain (RR 1.39; 95% CI 1.01, 1.92). Three
reviews39,47,48 found significantly greater jaw pain in women in 1 of 3, 1 of 5, and 2 of 4
studies.
26
Tabl
e 3:
Po
oled
Est
imat
es o
f the
Eff
ect o
f Sex
on
Che
st P
ain
and
othe
r Pre
sent
ing
Sym
ptom
s in
Patie
nts w
ith A
cute
Myo
card
ial I
nfar
ctio
n
(fro
m m
eta-
anal
yses
of i
ndiv
idua
l stu
dies
)
Stud
ies i
nclu
ded
in
the
met
a-an
alys
is
Sym
ptom
W
omen
No.
of
eve
nts
(%)
Men
No.
of
even
ts (%
) Po
oled
Odd
s Rat
io
(95%
CI)
W:M
Het
erog
enei
ty
Pool
ed R
isk
Rat
io
(95%
CI)
W:M
Het
erog
enei
ty
Chi
2 p -
valu
e I2 %
C
hi2 p
- va
lue
I2 %
32,4
0,54
-56,
58-7
8 C
hest
Pai
n 25
7,47
8 (6
9)
447,
411
(77)
0.
63 (0
.59-
0.68
)*
0.05
34
0.
93 (0
.91-
0.9
5)*
0.00
001
87
54,6
0,62
,65,
67,7
0,72
Fa
tigue
22
7 (4
4)
412
(34)
1.
43 (1
.14-
1.80
)*
0.64
0
1.19
(1.0
6-1.
33) *
0
.48
0 54
,67,
70
Arm
& sh
ould
er p
ain
86 (6
3)
196
(57)
1.
31 (0
.87-
1.97
) 0.
75
0 1.
11 (0
.95-
1.31
) 0
.73
0 60
,70,
72
Indi
gest
ion
62 (2
8)
109
(2)
1.13
(0.8
9-1.
65)
0.57
0
1.08
(0.8
3-1.
40)
0.5
3 0
40,5
5,62
,64
Epig
astri
c Pa
in
128
(10)
32
4 (1
2)
0.82
(0.6
6-1.
03)
0.86
0
0.84
(0.6
9-1.
02)
0.8
7 0
40,5
4,55
,57,
72,7
8 N
eck
pain
37
6 (2
3)
566
(16)
1.
74 (1
.49-
2.04
)*
0.40
2
1.54
(1.3
8-1.
73) *
0
.56
0 40
,54,
55,6
0,62
,64,
65,6
8,72
,78
Nau
sea
1,09
7 (4
8)
1,70
6 (3
4)
1.83
(1.6
2-2.
07)*
0.
25
21
1.42
(1.3
5-1.
51) *
0
.43
1 40
,60,
62,6
5,68
,70,
76
Sync
ope
170
(61)
25
9 (4
) 1.
41 (1
.11-
1.78
)*
0.33
13
1.
37 (1
.11-
1.70
) *
0.35
11
40
,55,
57,6
4,65
R
ight
arm
pai
n 49
9 (3
3)
925
(60)
1.
32 (1
.11-
1.57
)*
0.27
23
1.
20 (1
.07-
1.33
) *
0.32
16
54
,60,
65,6
7,68
,70,
78
Abd
omin
al p
ain
153
(15)
32
6 (1
3)
1.23
(0.9
3-1.
62)
0.20
30
1.
18 (0
.96-
1.46
) 0.
23
26
54,5
5,60
,65,
68,7
0,72
D
izzi
ness
24
5 (1
8)
432
(14)
1.
31 (1
.02-
1.67
)*
0.15
37
1.
22 (1
.02-
1.46
) *
0.15
37
40
,54,
55,6
4,67
,72
Jaw
pai
n 14
0 (1
0)
196
(7)
1.45
(1.0
2-2.
05)*
0.
14
40
1.39
(1.0
1-1.
92) *
0.
12
43
54,6
2,65
,72
Palp
itatio
ns
79 (2
6)
92 (1
3)
2.05
(1.0
8-3.
89)*
0.
12
49
1.75
(1.0
3-2.
96) *
0.
11
50
40,5
4,55
,64,
65,6
7,72
B
ack
pain
28
9 (1
8)
322
(10)
2.
19 (1
.66-
2.89
)*
0.06
50
1.
89 (1
.51-
2.35
) *
0.06
51
40
,54,
55,6
0,64
,65,
67,7
0,78
Sw
eatin
g 96
4 (4
9)
2,58
3 (5
8)
0.78
(0.6
4-0.
94)*
0.
02
57
0.90
(0.8
3-0.
97) *
0.
03
53
55,6
0,72
W
eakn
ess
367
(47)
81
6 (4
6)
1.13
(0.7
8-1.
65)
0.08
60
1.
07 (0
.88-
1.30
) 0.
07
62
40,5
4,55
,60,
62,6
4,65
,67,
68,7
0,
72,7
3,78
D
yspn
ea
1,64
3 (4
6)
2,67
4 (3
4)
1.58
(1.4
0-1.
77)*
0.
12
33
1.26
(1.1
5-1.
37) *
0.
0005
66
54,5
5,60
,62,
64,6
8,78
V
omiti
ng
342
(22)
52
7 (1
4)
1.88
(1.3
9-2.
55)*
0.
007
66
1.69
(1.3
1-2.
18) *
0.
005
67
40,5
5,64
Le
ft sh
ould
er p
ain
353
(28)
75
4 (2
9)
1.16
(0.8
1-1.
66)
0.05
67
1.
14 (0
.85-
1.52
) 0.
04
69
40,5
5,64
R
ight
shou
lder
pai
n
250
(20)
57
8 (2
3)
0.92
(0.7
7-1.
09)
0.01
77
0.
94 (0
.83-
1.07
) 0.
02
75
55,6
5,70
H
eada
che
102
(13)
14
4 (8
) 1.
34 (0
.61-
2.97
) 0.
002
84
1.31
(0.6
5-2.
67)
0.00
05
87
40,5
5,57
,64,
65
Left
arm
pai
n 77
1 (5
0)
1,44
9 (4
4)
1.70
(1.1
0-2.
64)*
0.
0000
1 88
1.
36 (1
.05-
1.77
) *
0.00
001
91
CI,
conf
iden
ce in
terv
al; M
, men
; W, w
omen
. *S
igni
fican
ce d
iffer
ence
27
2.5.4 Age and Other Adjustments
Across all studies, the pooled mean age of patients with AMI showed women were
older than men by a mean of 6.58 years (95% CI 5.42, 7.74, I2 69%). Table 4
summarizes the modification of effect sizes of the relationship between sex and AMI
symptoms with adjustment for age and other variables in the individual studies. For the
symptom of chest pain, the crude OR became nonsignificant after adjustment for age
and other variable(s) in 2 of 5 studies.40,69 The age-stratified study69 shows that
differences between men and women in chest pain presentation vary between older and
younger age groups.
In the majority of studies, adjusting for age and other variables made little difference to
the statistical significance or magnitude of the effect of sex on the other associated
symptoms of AMI. Non-significant crude ORs became significant after adjustment for
age or other variables for symptoms of dizziness65 and jaw pain.40 Significant crude
ORs became non-significant for the symptoms of sweating40 and left arm pain.65 For the
symptom of dyspnea, a significant OR became non-significant after age adjustment in
one study,40 and a non-significant OR became significant after age adjustment in
another study.65 Overall, the effect of adjustment for age and other variables was
equivocal for all of the other symptoms of AMI.
We found women who had an AMI were on average 6.58 years (95% CI 5.42, 7.74)
older than men. This finding is similar to that of Canto et al,18 who found that women
were approximately ten years older on average than men at the time of their initial
myocardial infarction.
Previous reviews18,39,47,48 have suggested that sex differences may decrease after
controlling for age and comorbidity. Our review is the first to compare sex differences
in symptoms of AMI after adjusting for age and other variables. We could only find five
studies40,54,55,65,69 that adjusted for age and other variables and that met our selection
criteria. The age-stratified study69 showed differences between men and women in chest
pain presentation in the “young” (<65) and the “old” (>75) but not the middle-age group
(65-74). The reason for this is not immediately obvious, and the authors69 did not offer
an explanation. Our results suggest that adjusting for age does not make a significant
difference to the direction or magnitude of effect measures of sex differences for the
majority of AMI symptoms.
28
Table 4: Comparison of the Effect of Adjustment for Age and Other Variables on the
Crude Effect Measure in Studies Reporting Sex Differences in Presenting
Symptoms in Patients with Acute Myocardial Infarction
Symptom Author Crude OR (95% CI) W:M
Age (years) Adjusted OR (95% CI) W:M
Other variable AOR (‡ items adjusted for in footnotes) (95% CI) W:M
Chest Pain Berg 54 0.42 (0.14-1.25) 0.42 (0.16-1.52) Culic55 0.56 (0.43-0.72) 0.62 (0.48-0.80) Goldberg40 0.56 (0.43-0.74) 0.86 (0.65-1.15)* 0.80 (0.59-1.09)* Lovlien65 0.81 (0.54-1.23) 0.84 (0.55-1.28) Milner69 0.53 (0.44-0.63) <65, 0.64 (0.42-0.97)
65-74, 0.85 (0.57-1.25)* ≥75, 0.65 (0.50-0.85)
Age < 65 RR 0.98 (0.93-1.06)* Age >=75 RR 0.92 (0.87-0.99)
Fatigue Berg54 1.89 (0.94-3.80) 1.84 (0.91-3.72) Lovlien65 1.36 (0.93-2.00) 1.43 (0.97-2.11)
Epigastric Pain
Culic55 0.80 (0.61-1.05) 0.95 (0.73-1.23) Goldberg40 0.85 (0.56-1.28) 0.88 (0.52-1.47) 0.91 (0.53-1.54)
Neck pain Berg54 1.18 (0.57-2.44) 1.19 (0.57-2.45) Culic55 1.75 (1.33-2.27) 1.56 (1.19-2.04) Goldberg40 1.47 (1.05-2.04) 1.75 (1.19-2.56) 1.92 (1.28-2.86)
Nausea Berg54 2.79 (1.48-5.27) 2.78 (1.47-5.25) Culic55 1.96 (1.61-2.38) 1.61 (1.33-1.96) Goldberg40 1.42 (1.13-1.78) 1.61 (1.28-2.08) 1.72 (1.33-2.22) Lovlien65 2.14 (1.45-3.16) 2.38 (1.59-3.56)
R arm pain Culic55 1.35 (1.11-1.64) 1.33 (1.09-1.61) Goldberg40 1.06 (0.80-1.40) 1.28 (0.94-1.75) 1.28 (0.93-1.78) Lovlien65 1.41 (0.94-2.13 1.52 (1.0-2.32)
Dyspnea Berg54 1.42 (0.73-2.75) 1.41 (0.73-2.75) Culic55 1.78 (1.49-2.17) 1.52 (1.23-1.82) Goldberg40 1.34 (1.07-1.67) 1.25 (0.99-1.56) * 1.16 (0.92-1.49) * Lovlien65 1.47 (1.00-2.16) 1.63 (1.1-2.42) †
Dizziness Berg54 2.58 (1.03-6.43) 2.60 (1.04-6.50) Culic55 1.41 (0.97-2.04) 1.22 (0.84-1.75) Lovlien65 1.32 (0.89-1.95) 1.54 (1.03-2.32) †
Jaw pain Berg54 0.82 (0.26-2.56) 0.80 (0.25-2.51) Culic55 1.72 (1.20-2.5) 1.47 (1.04-2.08) Goldberg40 1.27 (0.87-1.86) 1.89 (1.19-2.94) † 2.0 (1.23- 3.22) †
Back Pain Berg54 4.34 (2.17-8.69) 4.29 (2.14-8.62) Culic55 2.13 (1.54-3.12) 1.64 (1.16-2.27) Goldberg40 1.98 (1.44-2.71) 2.44 (1.69-3.57) 2.63 (1.78 – 3.85) Lovlien65 1.91 (1.2-3.02) 1.8 (1.12-2.89)
Sweating Berg54 0.71 (0.37-1.35) 0.75 (0.39-1.45) Culic55 0.62 (0.52-0.76) 0.73 (0.60-0.88) Goldberg40 0.72 (0.58-0.90) 0.79 (0.63-1.00)* 0.79 (0.62-1.00)* Lovlien65 1.08 (0.74-1.59) 1.28 (0.87-1.92)
Vomiting Berg54 2.09 (0.78-5.61) 2.06 (0.76-5.58) Culic55 1.25 (0.98-1.59) 1.14 (0.89-1.45)
L arm pain Culic55 1.28 (1.03-1.56) 1.32 (1.06-1.61) Goldberg40 1.01 (0.80-1.27) 1.22 (0.95-1.56) 1.20 (0.93-1.56) Lovlien65 3.79 (2.54-5.67) 1.34 (0.9-1.98)†
29
Abbreviations: OR: Odds Ratio; CI: Confidence Interval; W: Women; M: Men; AOR: Adjusted Odds Ratio; HTN: Hypertension; AMI: Acute Myocardial Infarction; RR: Risk Ratio; CHD: Coronary Heart Disease. * Significant crude ORs that becomes non-significant † Non-significant crude ORs that becomes significant ‡ Adjusted for age, angina, diabetes, hypertension, AMI characteristics40, Adjusted for age, risk factors, and cardiac enzyme levels55, Adjusted for age, history of heart failure, coronary heart disease, pulmonary disease, diabetes, hypertension and obesity69
2.5.5 Co-morbidity
Table 5 summarizes the pooled results from meta-analyses of individual studies
reporting the association between sex and various comorbid conditions in patients with
AMI. As shown, compared with men, women had statistically significantly higher odds
and rates of prior congestive heart failure. Other statistically significant differences
found, albeit within meta-analyses with a higher degree of heterogeneity between
studies, increased odds and rates of women with histories of hypertension and diabetes,
and a decreased odds and rate of previous AMI.
Women were more likely than men to have had a history of congestive heart failure (RR
1.64; 95% CI 1.44, 1.88). This finding is similar to that of Canto et al,18 who found on
average women were more likely to have a history of heart failure.
30
Tabl
e 5:
Po
oled
Est
imat
es o
f the
eff
ect o
f Sex
on
Com
orbi
d co
nditi
ons i
n Pa
tient
s with
Acu
te M
yoca
rdia
l Inf
arct
ion
(fro
m m
eta-
anal
yses
of
indi
vidu
al st
udie
s)
Stud
ies i
nclu
ded
in
the
met
a-an
alys
is
Cha
ract
erist
ic
Wom
en
No.
of
Eve
nts
(%)
Men
No.
of
Eve
nts
(%)
Pool
ed O
dds R
atio
(9
5% C
I) W
:M
Het
erog
enei
ty
Pool
ed R
isk
Rat
io
(95%
CI)
W
:M
Het
erog
enei
ty
Chi
2 p-
valu
e I2 %
C
hi2 p
- va
lue
I2 %
64,6
5,68
,76
Ang
ina
854
(40)
2,
096
(40)
1.
02 (0
.92-
1.13
) 0.
48
0 1.
01 (0
.95-
1.08
) 0.
44
0 58
,60,
61,6
7,69
,71
Con
gest
ive
Hea
rt Fa
ilure
35
4 (2
2)
348
(12)
1.
74 (1
.39-
2.20
)*
0.28
20
1.
64 (1
.44-
1.88
)*
0.43
0
58,6
0,61
,64,
67-6
9,71
,76
His
tory
of p
rior A
MI
1,02
4 (2
8)
2,47
5 (3
1)
0.83
(0.7
2-0.
97)*
0.
06
47
0.83
(0.7
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31
2.5.6 Heterogeneity
Most of the meta-analyses performed had a p-value ≥ 0.05 for the chi-square test of
heterogeneity, and approximately half of the meta-analyses performed had an I2≤40%;
thus, heterogeneity is not likely to be a concern. However, in the following meta-
analyses of sex differences, there was a moderate to substantial51 level of heterogeneity
(I2>40%): symptoms of chest pain (RR), palpitations, back pain, sweating, weakness,
dyspnea, vomiting, left and right shoulder pain, headache and arm pain, and the co-
morbid conditions: a history of hypertension, previous AMI, diabetes and
hypercholesteremia.
In our review, we did not combine groups of patients with the diagnoses of AMI and
UA, nor were studies of patients with only chest pain included. The RR for the
symptom of chest pain and both the OR and RR for some other symptoms of AMI and
co-morbidities that showed a moderate to substantial level of heterogeneity must be
interpreted with care because there is considerable variation in the combined or pooled
results, and it may be misleading to report a combined summary measure. Heterogeneity
may be due to the studies’ different geographical locations, study designs, data-
collection methods, sample selection, and inclusion and exclusion criteria.
The discrepancy in heterogeneity between the effect measures (OR and RR) was largest
for the symptoms of chest pain and dyspnea. We could not determine the reason for the
heterogeneity associated with the RR for chest pain (I2 87% and RR 0.93; 95% CI 0.91,
0.95), but by removing 3 studies28, 34, 37, the I2 was reduced to 29%, with an RR of 0.95
(95% CI 0.94, 0.96). For the symptom of dyspnea, removing 2 studies,38, 39 which unlike
the other studies only included patients with ST-segment elevation myocardial
infarction, reduced I2 from 66% to 39% and changed the RR from 1.26 (95% CI 1.15,
1.37) to 1.23 (95% CI 1.14, 1.33).
2.5.7 Publication Bias
Funnel plots were used to assess for publication bias when 10 or more studies were
combined. The plots all appeared symmetrical, suggesting that publication bias was not
a major concern. Figure 4 displays the funnel plot for the pooled OR of chest pain.
32
2.6 Discussion
Our systematic review updates previous reviews on sex differences in symptom
presentation of AMI with the inclusion of additional studies, a more precise inclusion
criterion, and a wider search strategy. In particular, this review has added to the Canto et
al,18 study of symptom presentation in ACS because we only reviewed studies with
confirmed AMI. The present review is the first to conduct meta-analyses of sex
differences in chest-pain and other symptoms of AMI, and thus helps to quantify
differences in AMI presentation between men and women.
There is debate within the literature about whether OR and RR is the better effect
measure to use.83,84 Because this issue is beyond the scope of this article, we have
presented both effect measures so that our results are as informative as possible. The
majority of studies in this meta-analysis used chi-square tests of proportions to analyze
sex differences in symptom presentation of AMI, 5 studies40,54,55,65,69 presented ORs and
1 study69 presented RRs.
Figure 4: Funnel Plot for the Pooled OR of Chest Pain
Abbreviations: SE(log[OR]): Standard Error (logarithm[Odds Ratio])
Previous systematic reviews did not pool results or perform meta-analyses, so we could
not compare our pooled results. However, we did compare our pooled results with the
0.01 0.1 1 10 100
0
0.5
1
1.5
2OR
SE(log[OR])
33
findings of the individual studies that comprise the previous systematic reviews. Only
statistically significant results were presented. Also, we explored the effect of
adjustment for age and other comorbidities on the magnitude and direction of the
association between sex and AMI symptom.
2.7 Limitations of the Review
Our systematic review and meta-analyses were conducted by one investigator (LLC)
who reviewed the literature and extracted the data. However, the search strategy,
inclusion/exclusion criteria, data to be extracted, and analysis were based on a
consensus approach among all 3 authors, and any uncertainty about whether to include
an article or not was resolved through discussion. It was also beyond the scope of this
article to discuss the instruments used to collect the data for the individual studies and to
discuss symptom assessment strategies. A recent review85 did conduct subgroup
analyses to identify whether symptom assessment strategies (medical record review,
self-reports, or mixed methods) were associated with different symptom reports, and
found for most symptoms, the measurement strategy had no effect on the outcome.
Limitations outside of the control of the review authors included the following. Many of
the studies in our review did not include infarct location or type of infarction. In some
studies, data were abstracted from medical records, which may have led to under-
reporting of patients’ presenting symptoms, whereas other studies used questionnaires
and interviews to collect descriptions of symptoms retrospectively and are thus subject
to recall bias. It was also not possible to distinguish the chief symptom from other
associated symptoms in any study. Furthermore, the lack of a standardized data-
collection instrument has resulted in other reviews and individual studies combining
symptoms, for example arm and shoulder pain, jaw and neck pain, nausea and vomiting,
which make comparison between studies difficult. In addition, many studies had age
restrictions and excluded patients > 75 years. This is an important limitation because
women with AMI are generally older than men. One study did not report numeric data,
and crude results were estimated from tables and figures. Finally, only a small number
of studies (n=5) adjusted for age and other comorbidities, and inconsistencies between
studies in adjusting for these variables made comparison between studies invalid.
34
2.8 Implications for Clinical Practice / Policy
Our systematic review and meta-analysis examine symptom difference between men
and women with confirmed AMI and challenges the stereotypic Hollywood depiction of
a heart attack as a dramatic onset of chest pain and collapse. In particular, we have
shown that women with AMI are typically older than men, more likely to have a history
of CHF, significantly less likely to present with chest pain, and more likely than men to
present with fatigue, neck pain, syncope, right arm pain, dizziness and jaw pain.
International and national public health campaigns need to inform women of the wider
spectrum of possible symptoms of AMI and highlight the possible differences in
symptom presentation between men and women. We recommend current and future
health care providers are educated about sex differences in presentation of symptoms of
AMI. Likewise, primary and secondary care clinicians need to explain the possible
variation in AMI symptom presentation to their at-risk patients, to assist them in
recognition of a medical emergency requiring prompt response. In addition, emergency
care personnel (pre-hospital and emergency department clinicians) need to appreciate
that just because a patient does not have central sternal crushing chest pain, this does not
exclude the possibility of an AMI.
2.9 Implications for Future Research
Future research into sex differences in AMI presentation ideally should be prospective
to increase reporting accuracy and use a standardized symptom presentation checklist,
with the chief symptom of AMI distinguished from associated symptoms. Also, because
symptoms of AMI often occur in clusters, further research is needed to define clusters
of symptoms and sex differences in their presentation. We recommend future studies
adjust for age and test for age-sex interactions and, if possible, adjust for comorbidity or
risk factors in a standardized way to allow for comparisons between studies.
2.10 Conclusion
The results of this review indicate there are sex differences in the symptoms of AMI.
Women are significantly less likely than men to present with chest pain. Women are
much more likely than men to present with fatigue, neck pain, syncope, right arm pain,
dizziness, and jaw pain. We recommend current and future health care providers are
35
educated about sex differences in the presentation of symptoms of AMI. In addition, we
recommend that current international and national health campaigns on symptom
presentation of AMI continue to promote chest pain as the cardinal symptom of AMI
but also reflect a wider spectrum of possible symptoms of AMI and highlight the
possible differences in symptom presentation between men and women.
36
37
Chapter 3: Methods to Link Data
3.1 Introduction
The systematic review and meta-analysis described in Chapter 2 provide important
information to answer the first research question posed in Chapter 1, Section 1.4. It was
necessary to merge data from a number of sources to address the four remaining
research questions. All four of these research questions used data from the Emergency
Department Information System and SJA-WA data. In addition, the second research
question used the transcribed symptoms of MI from the emergency telephone call. The
third research question used data from the patient hospital medical record. The fourth
research question used data from the patient hospital medical record and mortality data.
The fifth research question used data from the transcribed symptoms of MI from the
paramedic patient care record. In this chapter, the term ‘linked data’ is defined, the data
sources are described, and the merging of the data and checking procedures that were
used are explained.
3.2 Data Linkage
In 1946, Dunn introduced the concept of record linkage and proposed the idea that each
person create a “Book of Life”, which begins with birth, ends in death and includes
records of important health and social events.86 Data linkage is defined as “the bringing
together, from two or more different sources, of data that relate to the same individual,
family, place or event.”87
The benefits of linking health records for research purposes have been described
previously.88,89 Linked data is used in epidemiology, utilization and outcome of health
services, aetiologic research and disease surveillance.89 Throughout the world there are
a number of population-based data linkage systems; for example, the Manitoba
Population Health Information System,90 Oxford Record Linkage Study,91 Scottish
Record Linkage System,92 Rochester Epidemiology Project,93 the Centre for Health
Services and Policy Research in British Columbia,94 and the Western Australian Data
Linkage System.89
The process of data linkage consists of five practical steps: data preparation, blocking or
38
sorting files or records in the same order of the unique identifier, matching records,
storage and, finally, merging the linked data.95 A unique identifier is a unique value
assigned to an individual such as a Medical Record Number or an ambulance case
number. Partial identifiers are not completely unique and may include a person’s name,
date of birth or street address.95
Data preparation describes the data sources used. The data used in the thesis include the
Emergency Department Information System (EDIS), SJA-WA data, the transcribed
symptoms of MI from the emergency telephone call and the paramedic PCR, Mortality
data, and the data from the patient’s hospital medical record.
3.3 Data Sources
3.3.1 EDIS
The EDIS contains data on ED activity in WA’s public hospitals and includes all patient
presentations, transfers and discharges, and has patient time-tracking information. The
principal clinical diagnosis is a mandatory data field which is entered into the EDIS by
clinical staff on patient discharge from the ED. The clinical diagnosis is electronically
mapped to the International Statistical Classification of Diseases and Related Problems,
10th Revision, Australian Modification (ICD-10-AM) codes.96
3.3.2 SJA-WA
The SJA-WA data is a computerised record of all cases attended by metropolitan
ambulances in WA. The database includes data from the paramedic patient care record
(PCR) and the computer aided dispatch (CAD) system. Once the call is assigned to an
ambulance, a ‘case number’ for that event is generated. The SJA-WA data includes
patient demographics, clinical problem codes and problem urgency assessed by
paramedics, clinical management provided by paramedics, priority to scene and event
times from the CAD. The CAD event times include the time the call was received; the
time the call was dispatched to the ambulance; and the times that the ambulance arrived
on scene, departed the scene, and arrived at the hospital. The PCR is also scanned and
stored in the SJA-WA database.
39
3.3.3 Transcribed Symptoms of MI from the Emergency Telephone Call and the
Paramedic PCR
The symptoms of MI handwritten by the paramedic on the PCR and the symptoms of
MI from the emergency telephone call were transcribed verbatim. The process of how
this occurred is outlined below in Section 3.4.
3.3.4 Mortality Data
The Mortality data contains all deaths registered in WA by the Registry of Births,
Deaths and Marriages. The Births, Deaths and Marriage Registration Act 1998 require
that a person’s death is registered within 14 days of the date of death. The data that are
extracted from the death certificate completed by the attending physician include date of
death, cause of death (text and ICD-coded by the Australian Bureau of Statistics (ABS)
and place of death (for example, hospital or residential address).
3.3.5 Patient Hospital Medical Record Data
The symptoms of MI, symptom-onset time, type of MI (ST segment elevated MI
[STEMI] / Non STEMI), presence of comorbid conditions (e.g. diabetes, hypertension,
heart failure), and whether or not the patient had a percutaneous coronary intervention
were extracted from the patient medical record at a single hospital.
3.4 The Process of Data Extraction and Merging of the Data
Table 6 outlines the process of data extraction and merging of the data. All ED
presentations in the Perth metropolitan area from 1 January 2008 to 31 October 2009
with a principal ED discharge code related to MI (i.e. I21) in adults over the age of 18
years were extracted from the EDIS and saved in SPSS (IBM Corp. Released 2011.
IBM SPSS Statistics for Windows, Armonk, NY: IBM Corp) by the The University of
Western Australia Emergency Medicine Assistant Professor Nick Gibson. The patients
who were transported by ambulance to ED were identified from the EDIS ‘transport
variable’ and saved in an Excel file by Linda Coventry (LC).
In WA there is no common matching variable such as a unique patient identification
number. The public hospitals share an 8-character alpha-numeric medical record
number but SJA-WA has its own numeric case number. The variable ‘ambulance
record’ in the EDIS and the variable ‘case number’ in the SJA-WA data are, in theory,
40
the same number; i.e., the ‘case number’ and ‘ambulance record’ entries for each patient
admission to ED should be identical. However, the EDIS variable ‘case number’ is
often missing, so it was necessary to identify the correct ‘case number’ at SJA-WA. To
link the data from the EDIS with the SJA-WA data, it was necessary to confirm that
these entries were correct. The checking and matching processes were undertaken at
SJA-WA ambulance operation centre in Belmont (by LC).
Table 6: Study Flow Chart for Data Extraction and Merging of the Data
EDIS • 2009 • EDIS data: All patients with a confirmed discharge diagnosis of MI were
extracted from EDIS and saved to a SPSS file (by Assistant Professor Nick Gibson)
• All patients transported by ambulance (‘transport variable’) were extracted and saved to an Excel file by Linda Coventry (LC)
Note: The EDIS variable ‘ambulance record’ and the SJA-WA variable ‘case number’ are the same number. However, the EDIS variable is often missing, so it was necessary to identify the correct number at SJA-WA Belmont.
SJA-WA Belmont • The excel file was transferred to SJA-WA Belmont • Using SJA-WA intranet and the call-card inquiry, missing ‘ambulance record’
numbers were found and added to the EDIS data Xcel file (by LC) - A new study number was created for all patients - The emergency telephone recordings were retrieved and saved as a wave sound
file (by LC) - In 2008 the phone recordings were saved to disc - In 2009 the phone recordings were saved electronically • The pdfs of the paper PCR were retrieved and saved (by LC) The Excel file, the emergency telephone recording wave file, and the pdfs of the
paper PCR were transferred to Emergency Medicine (EM) at Sir Charles Gairdner Hospital (SCGH) (by Professor Ian Jacobs)
EM SCGH • Symptoms of MI data: - Using the new ‘study number’ as the identifier, the symptoms of MI from the
telephone recordings were transcribed into a string variable in a SPSS data base - The symptoms of MI from the PCR were transcribed into a different string
variable in the same SPSS data base (by LC) • SJA-WA data: Using the SJA-WA variable ‘case number’ the SJA-WA data
was extracted (by Ms Lorraine Salo, SJA-WA Data Manager) Linkage of EDIS data to SJA-WA data
• In the EDIS data the variable ‘ambulance record’ was copied and renamed ‘case number’ (by LC)
• The EDIS data and the SJA-WA data were sorted by ‘case number’ and merged by (by LC)
Linkage of EDIS / SJA-WA data to Symptoms of MI data
• The EDIS / SJA-WA data and the Symptoms of MI data were sorted by ‘study number’ and merged by (by LC)
DATA AVAILABLE FOR PAPERS 2 & 5 Note: Paper 5 was completed later as it was first necessary to validate the
symptoms of MI and symptom-onset time between the paramedic PCR & the hospital medical record (Paper 3)
Linkage of EDIS data / SJA-WA data / Symptoms of MI data to Mortality data
• 2012 • The EDIS data / SJA-WA data / Symptoms of MI data to Mortality data
were linked using Linkagewiz software (by Assistant Professor Nick Gibson)
EDIS data / SJA- • The SPSS File was saved and cut-down to include only patients who arrived at
41
WA data / Symptoms of MI data / Mortality data to patients hospital medical record
SCGH (by LC) • The patients hospital medical record were found in the medical record
department at SCGH (by LC) • Symptoms of MI, type of MI, symptom onset-time, presence of comorbid
conditions, and percutaneous coronary intervention data were extracted and entered into the SPSS data base (by LC)
DATA AVAILABLE FOR PAPERS 3 & 4
The checking and matching process occurred using the SJA-WA intranet, where a query
was submitted using the ‘call card enquiry’. The EDIS patient details (surname and
transport date) were submitted and a list was generated of all patients with similar letters
in their surname who had been transported on that date. The ED patient was matched to
their SJA-WA ‘case number’ by assessing agreement on a combination of surname,
home address, ambulance booking date, and hospital destination. A new ‘study number’
was created for each patient to enable removal of the ‘case number’ and ‘ambulance
record’, and other data such as patient name, address and date of birth, which could be
used to identify patients.
After identification of the ambulance ‘case number’, the paper PCR and, the emergency
telephone call recordings were retrieved. Two systems were in place to record the
emergency telephone calls during the study period. In the first system used in 2008, the
emergency telephone call was identified by inserting a disk that contained recordings of
all calls received during the specified time period. The correct emergency telephone call
was identified by matching a combination of surname, pickup address, and phone
number. The emergency telephone call was then saved as wave sound file. In the second
system used in 2009, the emergency telephone calls were saved electronically. The
emergency telephone call was identified and saved as a wave sound file.
The Excel file, the emergency telephone recording wave sound files, and the electronic
copies (PDFs) of the paper PCR were transferred securely to The University of Western
Australia Department of Emergency Medicine at SCGH by Professor Ian Jacobs.
The symptoms of MI described on the emergency telephone call were transcribed
verbatim into a string variable in SPSS (IBM Corp. Released 2011. IBM SPSS Statistics
for Windows, Armonk, NY: IBM Corp) at SCGH (by LC). No identifying information
was transcribed, such as name or contact details. Additional information collected from
the telephone call included sex of the caller, relationship of the caller to the patient, and
location of the call. The symptoms of MI and symptom onset-time from the paramedic
42
PCR were transcribed into a different string variable in the same SPSS file (by LC).
The SJA-WA data was extracted using the variable ‘case number’ by Ms Lorraine Salo
the SJA-WA data manager at SCGH. To link the EDIS to SJA-WA data, the variable
‘ambulance record’ in EDIS was copied and renamed ‘case number’. Files were sorted
by ‘case number’ and merged. To link the merged EDIS and SJA-WA data sets to the
transcribed symptom of MI from the telephone call and PCR, the files were sorted by
‘study number’ and merged.
In 2012 the data set (EDIS / SJA-WA / telephone and PCR data) was linked to mortality
data97 by Assistant Professor Dr Nick Gibson using Linkagewiz.98 The rationale for
linking the data later was to extend the censor date (to 1 September 2011) and assess
survival. Probabilistic matching99 was used to link the data, and three basic steps were
followed: blocking of records that have a potential relationship; matching to determine
if records within a block were likely to be related; and linking matched records. The
Linkagewiz program uses an iterative approach to mathematically link databases by
comparing data fields in two files with surname, first given name, and initial for second
given name, date of birth, sex, and address as the principal matching fields. Clerical
checking of additional information was undertaken (by LC) for possible matches of
uncertain links; i.e., those that fall within a ‘grey area’ between definite matches and
definite non-matches. There is a degree of uncertainty in probabilistic data linkage,
therefore the challenge is to minimise the number of bad links (false positives) without
increasing the number of missed true links (false negatives). Clerical checking found an
additional seven patients who were in both the EDIS / SJA-WA / telephone and PCR
data set and the death data.
3.5 Data Validation
3.5.1 Validation of Data Entry of Symptom of MI in the SJA-WA Telephone call
Data
To validate the accuracy of the data entry of the symptoms of MI, a random sample of
the emergency telephone calls were checked (by LC). Using the random case selection
function of SPSS, a sample of 200 (10%) cases was selected from the data. The
symptoms of MI contained in the transcribed phone call file were checked for accuracy
43
by comparing them with the original wave sound file. Of the 200 cases, 197 phone call
transcripts matched the original wave sound file resulting in a 98.5% accuracy of data
entry. There were 317 symptoms of MI reported for the 200 cases. Of these, 314 were
the same as those recorded in the original wave sound file, i.e. 99.0% accuracy of data
entry.
3.5.2 Validation of the Linked Data Set – EDIS and SJA-WA
The linked data have been sourced from the EDIS, SJA-WA data, the emergency
telephone and PCR data. Before analysis could commence, it was necessary to validate
and ensure data integrity of the linkage. Patient surname, date of birth, and gender were
compared between the data sets to validate the linkage of the data from the EDIS to
SJA-WA data, and reasons for the differences are summarized in Table 7.
Table 7: Reasons for Differences between SJA-WA Data and EDIS Data
Surname
n (%) Date of birth
n (%) Gender n (%)
Incorrect entry into SJA-WA data 37 (49.2) 11 (61.1)
No PCR, unable to compare 3 (4.0) 5 (27.8)
Missing data on PCR 16 (11.7) 1 (1.3) 2 (11.1)
PCR and SJA-WA data match, but different to EDIS 3 (2.2) 35 (46.0)
Incorrect spelling 116 (84.7)
Totals 137 (100) 76 (100) 18 (100)
For the variable ‘surname’, there were 137 differences within the data sets. Reasons for
differences were incorrect spelling of the surname (n=116), no surname on the PCR
(n=16), and different surname in the data sets (n=3). All (n=135) of these differences
were reconciled via matching either home address, date of birth, or date and time of
arrival at a hospital. In two cases the merge was incorrect: in one case the ambulance
case number was incorrect, and in the other case the patient surname was incorrect.
These two cases were removed from the merged data set. In summary, the integrity
check of the merged data was 2072/2074 cases; i.e. 99.9% correct.
Seventy-six differences were found for ‘date of birth’ within the data sets. Reasons for
differences’ were incorrect data entry into SJA-WA data (n=37); PCR date of birth
matched SJA-WA data date of birth, but was different from EDIS date of birth (n=35);
44
no PCR, therefore unable to compare date of birth (n=3); and missing date of birth on
the PCR (n=1). All of these differences in date of birth were reconciled via matching
patients’ surnames and home addresses.
There were 18 differences in ‘gender’ within the data sets. Reasons for differences were
incorrect data entry into the SJA-WA data (n=11); no PCR, therefore unable to compare
(n=5); and missing data on PCR (n=2). All of these differences in gender were
reconciled via matching surnames and home addresses.
As correct age is vital to ensure that age adjustment is accurate in regression analysis we
also checked for age differences. When there were discrepancies between the date of
birth entered in the EDIS and the SJA-WA data, we assumed that the EDIS record was
correct. After validation of the data integrity all the identifiable patient details,
‘ambulance record’ and ‘case number’ were removed from the data set.
3.6 Conclusion
This chapter has defined the term ‘linked data’, and described the data sources, the data
extraction and the merging of the data and the validation procedures that were followed.
This information supplements the methodology included in Chapters 4, 5, 6, and 7. The
next chapters address the remaining research questions listed in Chapter 1, Section 1.4.
45
Chapter 4: Myocardial Infarction: Sex Differences in
Symptoms Reported to Emergency Dispatch
4.1 Introduction
This chapter is the Author’s Original Manuscript published in Prehospital Emergency
Care Journal, 2013; 17:193-202.2 This manuscript examines the symptoms of MI
reported during the emergency telephone call and the ambulance times for all patients
who presented to one of the seven Perth metropolitan hospital EDs over a 22 month
period. The symptoms of MI were extracted from the transcribed emergency telephone
call. This phase of the study aimed to answer the second research question posed in
Chapter 1, Section 1.4:
Are the symptoms, in particular chest pain, reported during the emergency
telephone call to SJA-WA and ambulance response times, the same for men
and women with MI?
To answer this question it was necessary to link the EDIS, SJA-WA data, and the
emergency telephone data. The detailed explanation of this data linkage in Chapter 3
expands on the brief description in this manuscript.
4.2 Abstract
4.2.1 Background
Emergency management of myocardial infarction (MI) is time critical, because
improved patient outcomes are associated with reduced time from symptom onset to
definitive care. Previous studies have identified that women are less likely to present
with chest pain.
4.2.2 Objective
We sought to measure the effect of sex on symptoms reported to the ambulance dispatch
and ambulance times for MI patients.
4.2.3 Methods
The Western Australia Emergency Department Information System (EDIS) was used to
46
identify patients with emergency department (ED) diagnoses of MI (ST-segment
elevation MI and non-ST-segment elevated MI) who arrived by ambulance between
January 1 2008 and October 31 2009. Their emergency telephone calls to the ambulance
service were transcribed to identify presenting symptoms. Ambulance data were used to
examine ambulance times. Sex differences were analysed using descriptive and age-
adjusted regression analysis.
4.2.4 Results
Of 3,329 MI patients who presented to Perth EDs, 2,100 (63.1%) arrived by ambulance.
After pre-defined exclusions, 1,681 emergency calls were analysed. Women (n=621,
36.9%) were older than men (p<0.001) and even after age-adjustment were less likely to
report chest pain (Odds Ratio [OR]=0.70; 95% Confidence Interval [CI] 0.57, 0.88).
After age-adjustment, ambulance times did not differ between male and female patients
with chest pain. Women with chest pain were less likely than men to be allocated a
‘priority 1’ (lights and sirens) ambulance response (Men 98.3% vs. Women 95.5%;
OR=0.39; 95% CI 0.18, 0.87).
4.2.5 Conclusion
Ambulance dispatch officers (and paramedics) need to be aware of potential sex
differences in MI presentation in order to ensure appropriate ambulance response.
4.2.6 Key Words
Emergency medical services; myocardial infarction; symptoms; sex differences;
emergency medical dispatch
4.3 Background
Current guidelines100,101 recommend prompt activation of the emergency medical
service (EMS) if a person is experiencing symptoms suggestive of a myocardial
infarction (MI). The emergency ambulance is usually the quickest mode of transport to
hospital, especially in urban areas. In addition, paramedics are trained to initiate
treatment and equipped to treat life threatening cardiac arrhythmias should they occur.
The time from onset of MI symptoms to treatment in a hospital influences survival, and
47
rapid reperfusion of an obstructed coronary artery is associated with reduced
mortality.102 Additionally, current Australian and American College of Cardiology and
American Heart Association (ACC/AHA) guidelines for the treatment of ST-segment
elevation myocardial infarction (STEMI) recommend the time from first medical
contact to percutaneous coronary intervention (PCI) to be as-soon-as-possible103 or less
than 90 minutes,19,24 with suggestions that EMS to PCI time should be less than 90
minutes as well.24,104 Many studies have investigated reasons for underuse of emergency
ambulances105,106 and delay in seeking treatment107,108 in MI patients. Research has
shown that pre-hospital median delays range from 84 to over 400 minutes.107
However, no studies were found that have investigated symptoms of MI reported during
the telephone call to emergency dispatch as a possible source of delay. Correct
recognition of symptoms of a MI is crucial for the ambulance dispatcher to allocate a
“priority 1” (lights and sirens) ambulance response. Most ambulance dispatch systems
are primed to rapidly respond to mention of chest pain as a symptom, but not all MI
patients experience chest pain as a symptom.109 Previous studies have identified that
women are less likely to present with chest pain1,18 and have prolonged prehospital
delays.107,110 Our primary aim was to compare symptoms, in particular chest pain,
reported during the emergency telephone call for men and women with MI. We also
compared the relationship between symptoms reported and ambulance responses in men
and women, with adjustment for age.
4.4 Methods
4.4.1 Study Setting and Cohort
This retrospective cohort study reviewed emergency telephone calls of all adult patients
with an emergency department (ED) discharge diagnosis of MI transported by St John
Ambulance (SJA) in Western Australia (WA) to one of the seven Perth metropolitan
EDs between January 1, 2008 and October 31, 2009. The Perth metropolitan area covers
an area over 5,000 square kilometers111 and has a population of 1.7 million, with 9.2%
aged ≥ 65 years and 3% aged ≥ 75 years.112 Two and a half per cent of the population
are indigenous (Aboriginal and Torres Strait Islander), with the overseas born
population largely of Asian (23%) and European (19%) descent.112 SJA-WA is the
single provider of prehospital emergency care and transport for WA and is staffed by
48
paramedics who attend over 200,000 calls per year.28 In WA (as for the whole of
Australia) the emergency telephone number is “triple zero” (0-0-0).28 Calls are
answered by an operator who asks whether the emergency requires “police, fire or
ambulance”. Calls requesting ‘ambulance’ are immediately transferred to the
Ambulance Operations Centre located at SJA-WA headquarters in Perth. All telephone
calls are recorded and stored permanently.
At the time of the study SJA-WA ambulance dispatch operators completed a two- week
in-house course in dispatch and prioritizing ambulances. The dispatch operators were
not medically trained. The dispatch operator followed a written in-house protocol asking
a series of scripted questions that establish location of the incident, phone number of the
caller, chief complaint, and other complaint-specific questions. A computer-aided
dispatch (CAD) System automatically records the time the call was received, the time
the call was dispatched to the ambulance, and the time the ambulance arrived on scene,
departed the scene, and arrived at the hospital. A priority is allocated to each call:
“Priority 1” (lights and sirens) response represents an emergency, “Priority 2” response
represents an urgent call, and “Priority 3” response represents a non-urgent call.28
Priority responses were assigned by the dispatch operator based on a list of predefined
conditions for each priority level, e.g. “chest pain” was allocated as a priority 1. Priority
allocation from scene to hospital is determined by the paramedic, based on patient’s
clinical status. During the study period, current practice of paramedics did not include
acquisition of a 12-lead electrocardiogram or direct transfer to a percutaneous coronary
intervention laboratory.
All adult patients with an ED discharge diagnosis of MI (STEMI and non-STEMI) who
were transported to ED by SJA-WA during the study period were identified from the
Perth Emergency Department Information System (EDIS). EDIS is a real-time patient-
tracking system containing utilization and patient disposition data for each ED in
Perth.113 The principal clinical diagnosis is a mandatory field entered by clinical staff on
patient discharge from the ED. The clinical diagnosis is electronically mapped to the
International Classification of Diseases and Related Problems, 10th Revision,
Australian Modification (ICD-10-AM) codes.96
Patient details identified from EDIS were used to retrieve the emergency phone call
made to SJA-WA, which was saved as a “.wav” file. Patient symptoms, as described by
49
the caller, were transcribed verbatim by one author (LLC). To assess transcription
accuracy a random sample of 200 phone calls were reviewed by the same author (LLC).
Of the 200 phone calls, 197 were accurate indicating 98.5% data-entry accuracy. Initial
lists of possible symptoms of MI were created from an extensive literature search and
clinical expertise, with additional symptoms added as required from the telephone
transcripts. Symptoms were coded “yes” if stated in the telephone call or “no” if
declared absent or not stated. Multiple symptoms for individual patients were possible.
Additional information pertaining to the call was collected, including sex of the caller
and their relationship to the patient, and location of the call.
The SJA-WA patient database contains computerised records of all cases attended by
ambulances in WA from the CAD system and the paramedic-completed patient care
record (PCR), which includes dispatch priority, clinical problem codes, and clinical
management. The EDIS data were linked to the SJA-WA database, together with the
transcribed symptoms from the emergency phone call to SJA. Only the index hospital
admission was included for patients who subsequently transferred to a second hospital.
Patients were excluded if they arrived by private transport, Royal Flying Doctor
Service, helicopter, or other voluntary transport services.
4.4.2 Statistical Methods
Data were presented as frequencies with percentages, or means ± standard deviations.
Ambulance times were described using means, standard deviations, medians and inter-
quartile ranges. Comparisons of baseline characteristics between men and women were
performed using chi-square tests for categorical variables, the Mann-Whitney test for
medians, and Student’s t tests for continuous variables.
For each symptom of MI, logistic regression was used to estimate the odds ratio (OR)
and its 95% confidence interval (CI) for the symptom being reported by women
compared with men. Models were subsequently adjusted for age (as a continuous
variable) and age-sex interaction was tested. For the symptom “chest pain”, a stratified
analysis that dichotomised age into < 70 years and ≥70 years, with men aged <70 years
as the comparison group was also conducted. Age 70 years was selected as the cutoff
based on previous research demonstrating that presentation with chest pain is less
common in individuals over 70 years of age.114,115
50
Linear regression was used to model sex differences in ambulance times for patients
with chest pain and patients without chest pain. Because model residuals were skewed,
time intervals were log transformed. Beta coefficients (and 95% CIs) that estimate the
difference in mean log time were reported. For patients with chest pain and patients
without chest pain logistic regression was used to compare the odds of women being
dispatched as a priority 1 ambulance response with those of men. Both linear and
logistic regression modeling included adjustment for age (as a continuous variable) and
testing for age-sex interaction.
All statistical analyses were performed in PASW Release Version 17.0 (IBM SPSS Inc.,
2008, Chicago, IL, www.spss.com). Two-sided p-values <0.05 were considered
significant. Ethics approval was obtained for this study from the University of Western
Australia, number RA/4/1/2428. See Appendix K.
4.5 Results
During the study period, January 2008 to October 2009, of the 3,329 (women, n = 1115;
men, n = 2214) patients who were discharged from a Perth ED with a diagnosis of MI,
63.1% (women, n = 759; men, n = 1341) arrived by ambulance. More women (68%)
than men (60%) arrived by ambulance (p<0.001). Following exclusions, as detailed in
Figure 5, 1,681 emergency telephone calls to SJA-WA were analyzed. Of these, 621
(36.9%) were for female patients.
Women were older than men (mean age 77.6 vs. 69.1 years, p<0.001). Differences in
the relationship of caller to patient and the location of patient at time of the emergency
call were found between men and women (Table 8).
51
Figure 5: Study Flow Diagram
EDIS Data
EDIS, Emergency Department Information System; MI, Myocardial Infarction; RFDS, Royal Flying Doctor Service; SJA-WA, St John Ambulance-Western Australia; PCR, Patient Care Record; ED, Emergency Department
EDIS confirmed discharge diagnosis of MI (Jan 1, 2008 to Oct 31, 2009)
n=3,329
Excluded 1,229 • private transport (n=1,155) • RFDS transfer (n=47) • other (n=20) • helicopter (n=5) • police (n=1) • voluntary transport (n=1)
Arrived by
ambulance
n=2,100
Excluded 26
• no SJA ambulance record
(transferred by another
transport service)
Excluded 32
• transferred to a second
hospital, counted at first
hospital
SJA-WA records
n=2,040
Excluded 198
No emergency call
• RFDS transfer (n=64)
• hospital transfer (n=18)
• ambulance flagged down (n=2)
• missing, error in recording
system (n=114)
SJA telephone
calls n=1,842
Excluded 161
• ED nurse call. Patient
used own transport to
first hospital and then
transferred to second
hospital (n=155)
• dispatcher call back, no
symptom information
(n=6)
Telephone calls
analysed
n=1,681
Men=1,060
Women=621
Integrity check of merged
EDIS data to SJA data
2072/2074 = 99.9% merge
Excluded 2
• wrong PCR (n=1)
• correct PCR but
wrong patient (n=1)
n=2,072
n=2,074
SJA-WA
Data
Telephone
Transcripts
52
Table 8: Sex Differences in the Descriptive Characteristics of the Emergency Phone
Calls for Patients with Myocardial Infarction
Characteristic Men (patients)
n=1060 Women (patients)
n=621 p-value
Mean Age, years (± SD), years 69.1 (14.4) 77.6 (12.8) <0.001* Duration of Phone Call - median (IQR), seconds
80.4 (67.8, 123.3) 79.2 (65.4, 123.6) 0.13
Sex of Caller, n (%) Male Female
322 (30.3) 738 (69.7)
179 (28.8) 442 (71.2)
0.50
Relation of Caller to Patient Self Spouse Family / Friend Professional† Other Bystander Unsure
129 (12.2) 294 (27.7) 226 (21.3) 321 (30.3)
13 (1.2) 27 (2.6) 50 (4.7)
59 (9.5)
48 (7.7) 204 (32.8) 252 (40.6)
8 (1.3) 11 (1.8) 39 (6.3)
0.09
<0.001* <0.001* <0.001*
0.91 0.30 0.17
Location of Patient at time of emergency call Home Relative / Friend / Work Medical Centre Nursing home‡ Other Unsure
714 (67.4) 53 (5.0)
127 (12.0) 89 (8.4) 61 (5.7) 16 (1.5)
403 (64.9) 17 (2.7) 46 (7.4)
133 (21.4) 19 (3.1)
3 (0.5)
0.18 0.02*
0.002* <0.001* <0.001*
0.68
Data are expressed as n (%) unless otherwise specified. *Statistical significant difference. †Includes health professional, medical receptionist and security personnel. ‡ Includes residential care facilities. IQR = inter-quartile range; SD = standard deviation.
4.5.1 Sex Differences in Chest Pain Reported for Patients with Myocardial
Infarction during the Emergency Telephone Call
As shown in Table 9, women were less likely than men to report chest pain (54% vs.
69%; OR=0.54; 95% CI 0.44, 0.67; p<0.001), even after age adjustment (OR=0.70;
95% CI 0.57, 0.88; p=0.002). There was no significant interaction between sex and age
(p=0.10); however, in age-stratified analysis, men aged ≥70 years (OR=0.48; 95% CI
0.37, 0.63; p<0.001) and women aged ≥70 years (OR=0.28; 95% CI 0.22, 0.37;
p<0.001) were less likely to have reported chest pain when compared with men aged <
70 years.
53
Tabl
e 9:
Se
x D
iffer
ence
s in
Sym
ptom
s Rep
orte
d fo
r Pat
ient
s with
Myo
card
ial I
nfar
ctio
n du
ring
the
Emer
genc
y Te
leph
one
Cal
l
Sym
ptom
*
Wom
en
n= 6
21
n (%
)
Men
n=
1,06
0
n (%
)
Una
djus
ted
OR
(9
5% C
I)
p-V
alue
A
ge-A
djus
ted
OR
(9
5% C
I)
p-V
alue
Che
st p
ain
33
8 (5
4.4)
72
8 (6
8.7)
0.
54 (0
.44,
0.6
7)
<0.0
01†
0.70
(0.5
7, 0
.88)
0.
002†
Le
ft ar
m p
ain
90 (9
.7)
105
(9.9
) 0.
97 (0
.70,
1.3
6)
0.87
1.
26 (0
.89,
1.8
0)
0.19
R
ight
arm
pai
n 40
(6.4
) 11
4 (1
0.8)
0.
57 (0
.39,
0.8
3)
0.00
3†
0.70
(0.4
8, 1
.04)
0.
08
Jaw
/ th
roat
/ ne
ck p
ain
26 (4
.2)
39 (3
.7)
1.14
(0.6
9, 1
.90)
0.
60
1.39
(0.8
2, 2
.37)
0.
22
Swea
tines
s or c
lam
min
ess
51 (8
.2)
136
(12.
8)
0.61
(0.4
3, 0
.85)
0.
004†
0.
71 (0
.50,
1.0
1)
0.06
Sh
ortn
ess o
f bre
ath
176
(28.
3)
273
(25.
8)
1.14
(0.9
1, 1
.42)
0.
25
1.05
(0.8
4, 1
.33)
0.
66
Abd
omin
al /
epig
astri
c pa
in
19 (3
.0)
24 (2
.3)
1.38
(0.7
6, 2
.50)
0.
29
1.02
(0.5
5, 1
.91)
0.
94
Nau
sea
31 (5
.0)
43 (4
.0)
1.24
(0.7
8, 1
.99)
0.
37
1.35
(0.8
2, 2
.22)
0.
23
Vom
iting
46
(7.4
) 52
(4.9
) 1.
55 (1
.03,
2.3
4)
0.04
† 1.
57 (1
.02,
2.4
1)
0.04
† Sy
ncop
e / c
olla
pse
/ unc
onsc
ious
54
(8.7
) 67
(6.3
) 1.
35 (0
.93,
1.9
2)
0.11
1.
42 (0
.96,
2.1
0)
0.08
W
eakn
ess
34 (5
.5)
28 (2
.6)
2.14
(1.2
8, 3
.56)
0.
004†
1.
62 (0
.95,
2.7
5)
0.08
B
ack
pain
28
(4.5
) 30
(2.8
) 1.
62 (0
.96,
2.7
4)
0.07
1.
62 (0
.93,
2.8
1)
0.09
U
nwel
lnes
s 42
(6.7
) 47
(4.4
) 1.
56 (1
.02,
2.4
0)
0.04
† 1.
28 (0
.82,
2.0
0)
0.29
Fa
ll 51
(8.2
) 37
(3.5
) 2.
47 (1
.60,
3.8
2)
<0.0
01†
1.40
(0.8
9, 2
.21)
0.
15
Con
fusi
on
26 (4
.2)
20 (1
.9)
2.27
(1.2
6, 4
.11)
0.
007*
1.
59 (0
.86,
2.9
4)
0.14
*Mul
tiple
sym
ptom
s pos
sibl
e.
† O
R si
gnifi
cant
ly d
iffer
ent f
rom
1.
CI =
con
fiden
ce in
terv
al; O
R =
odd
s rat
io (m
en a
s ref
eren
ce g
roup
).
54
4.5.2 Differences in Other Symptoms Reported for Patients with Myocardial
Infarction during the Emergency Telephone Call
As shown in Table 9, women were more likely than men to present with vomiting (7.4%
vs. 4.9%; OR=1.55; 95% CI 1.03, 2.34; p=0.04), even after age adjustment (OR=1.57;
95% CI 1.02, 2.41; p=0.04). Greater odds of vomiting in women persisted in subgroup
analyses of chest pain only patients, but not in patients who did not report chest pain.
In a subgroup analysis of patients who did not report chest pain there were no
statistically significant differences between other reported symptoms. The most
common symptoms in this subgroup included shortness of breath (38% women vs. 32%
men); a fall (17% women vs. 11% men); syncope, collapse or unconsciousness (17%
women vs. 18% men); feeling unwell (11% women vs. 8% men); weakness (9% women
vs. 7% men); confusion (8% women vs. 5% men); and vomiting (8% women vs. 8%
men).
4.5.3 Sex Differences in Ambulance Times
As shown in Figure 6, compared with men, women had statistically significantly longer
median on-scene time (19 vs. 17.7 minutes; p<0.001) and call to hospital time (48 vs.
46.5 minutes; p=0.009). The greatest component of pre-hospital time for both men and
women was on-scene time.
As shown in Table 10, there were no sex differences in any component of ambulance
times, except for on-scene time for the subgroup of MI patients with chest pain. The
mean on-scene time for women was 1 minute longer than it was for men (p=0.001), but
after age-adjustment, mean on-scene time did not differ by sex.
55
Figure 6: Boxplot Showing Sex Differences in Times for Each Component of
Prehospital Time for Men and Women (n=1681)
*Statistically significant difference, the Mann-Whitney test was used to examine differences in prehospital time. Box encloses the middle 50% of times (the IQR); the horizontal line marks the median. ⁰Outlier, value is between 1.5 and 3 IQR (box lengths) from the end of the box. Extreme outlier; value is more than 3 IQR from the end of the box. Data on one extreme outlier not shown, ‘Scene to hospital’ (180 minutes) and ‘Call to hospital’ (220 minutes).
56
Tabl
e 10
: Sex
Diff
eren
ces i
n A
mbu
lanc
e Ti
mes
for P
atie
nts w
ith M
yoca
rdia
l Inf
arct
ion
who
had
Che
st P
ain
and
thos
e w
ho d
id n
ot h
ave
Che
st
Pain
PA
TIE
NT
S W
ITH
CH
EST
PA
IN
Men
(n=7
29) W
omen
(n=3
37)
PAT
IEN
TS
WIT
HO
UT
CH
EST
PA
IN
Men
(n=3
31) W
omen
(n=2
84)
Am
bula
nce
Tim
e In
terv
al
Tim
e (m
inut
es)
Una
djus
ted
Bet
a C
oeff
icie
nt*
(95%
CI)
p-
Val
ue
Age
-adj
uste
d B
eta
Coe
ffic
ient
* (9
5% C
I)
p-V
alue
Tim
e (m
inut
es)
Una
djus
ted
Bet
a C
oeff
icie
nt*
(9
5% C
I)
p-V
alue
Age
-adj
uste
d B
eta
Coe
ffic
ient
* (9
5% C
I)
p-V
alue
M
ean
(±SD
) M
edia
n (I
QR
) M
ean
(±SD
) M
edia
n (I
QR
)
Cal
l to
on-s
cene
M
en
Wom
en
11
.8(8
.7)
11.2
(6.5
)
10
.1(7
.5, 1
3.2)
10
.0(7
.6, 1
2.6)
-0
.02(
-0.0
8, 0
.04)
0.
52
-0
.02(
-0.0
8, 0
.05)
0.
60
16
.7(1
3.3)
16
.8 (1
2.8)
12
.8(8
.8, 1
9.8)
12
.5(9
.1, 2
0.0)
0.
02(-
0.08
, 0.1
2)
0.67
-0
.04(
-0.1
4, 0
.06)
0.
44
On-
scen
e
Men
W
omen
18
.1(7
.2)
19.1
(5.9
)
17
.3(1
3.4,
22.
4)
18.7
(14.
9, 2
2.6)
0.
09(0
.03,
0.1
4)
0.00
1†
0.
04(-
0.02
, 0.0
9)
0.18
20
.4(9
.3)
21.1
(9.4
)
18
.8(1
4.3,
24.
8)
19.7
(14.
8, 2
6.2)
0.
04(-
0.05
,0.1
2)
0.40
-0
.02(
-0.1
0, 0
.07)
0.
74
On-
scen
e to
ho
spita
l M
en
Wom
en
17
.6(1
0.2)
17
.7(9
.5)
16
.0(1
0.8,
22.
6)
15.7
(11.
3, 2
2.9)
0.
01(-
0.07
, 0.0
8)
0.80
0.
02(-
0.06
, 0.1
0)
0.66
16
.7(1
2.6)
17
.2(9
.1)
14
.9(9
.8, 2
1.1)
15
.3(1
1.1,
21.
7)
0.
10(-
0.01
, 0.1
9)
0.06
0.
09(-
0.02
, 0.1
9)
0.10
C
all t
o ho
spita
l M
en
Wom
en
47
.6(1
6.6)
48
.0(1
3.6)
45
.4(3
7.3,
54.
3)
46.5
(38.
8, 5
6.1)
0.
02(-
0.02
, 0.0
6)
0.29
0.
01(-
0.04
, 0.0
5)
0.79
53
.8(2
1.2)
55
.1(2
0.0)
50
.1(3
9.7,
64.6
) 49
.8(4
2.1,
64.
4)
0.
04(-
0.02
, 0.1
0)
0.20
-0
.01(
-0.0
6,0.
06)
0.92
*Am
bula
nce
times
are
log
trans
form
ed.
† B
eta-
coe
ffici
ent s
igni
fican
tly d
iffer
ent f
rom
0 (m
en a
s ref
eren
ce g
roup
). C
I = c
onfid
ence
inte
rval
; IQ
R =
inte
r-qu
artil
e ra
nge;
SD
= st
anda
rd d
evia
tion.
57
4.5.4 Sex Differences in Priority Allocation Total Time from Emergency Call to
Hospital for Each Priority Response
As shown in Table 11, women with chest pain were less likely than men to be allocated
a priority 1 ambulance response after age-adjustment (98.3% vs. 95.5%; OR=0.39; 95%
CI 0.18, 0.87; p=0.02). Also shown in Table 11, there were no sex differences in total
time from emergency call to hospital for each priority response for patients with and
without chest pain. However, there was an increase in total call-to-hospital time for both
men and women who were allocated a priority 2 or 3 response compared with a priority
1 response.
58
Tabl
e 11
: Sex
Diff
eren
ces i
n A
mbu
lanc
e Pr
iorit
y R
espo
nse
and
Tota
l Tim
e fr
om C
all t
o H
ospi
tal f
or P
atie
nts w
ith M
yoca
rdia
l Inf
arct
ion
who
had
Che
st P
ain
and
thos
e w
ho d
id n
ot h
ave
Che
st P
ain
PA
TIE
NT
S W
ITH
CH
EST
PA
IN
Men
(n=7
29) W
omen
(n=3
37)
PAT
IEN
TS
WIT
HO
UT
CH
EST
PA
IN
Men
(n=3
31) W
omen
(n=2
84)
Prio
rity
Res
pons
e N
o. o
f ev
ents
n
(%)
Age
-adj
uste
d O
R
(95%
CI)
p-
valu
e
Tot
al ti
me
Cal
l to
Hos
pita
l T
ime
(min
utes
) N
o. o
f ev
ents
n
(%)
Age
-adj
uste
d O
R
(95%
CI)
p-
valu
e
Tot
al ti
me
Cal
l to
Hos
pita
l T
ime
(min
utes
)
Mea
n (S
D)
Med
ian
(IQ
R)
Mea
n (S
D)
Med
ian
(IQ
R)
Prio
rity
1
Men
W
omen
717
(98.
3)
322
(95.
5)
0.
39 (0
.18,
0.8
7)
0.02
*
47
.2 (1
5.9)
47
.5 (1
3.3)
45
.2 (3
7.2,
54.2
) 46
.1 (3
8.8,
55.
5)
175
(52.
9)
132
(46.
5)
1.01
(0.7
2, 1
.42)
0.
94
47
.8 (1
5.7)
48
.3 (1
2.9)
44
.9 (3
6.5,
57.
5)
46.6
(40.
0, 5
4.6)
Pr
iori
ty 2
M
en
Wom
en
6
(0.8
) 13
(3.9
)
4.
77 (1
.74,
13.
08)
0.00
2*
53
.7 (2
0.8)
57
.0 (1
7.0)
55
.3 (3
6.4,
70.
7)
57.8
(44.
5, 6
7.8)
10
4 (3
1.4)
10
4 (3
6.6)
1.
06 (0
.75,
1.5
1)
0.74
55
.6 (1
8.2)
56
.5 (2
0.6)
52
.2 (4
4.6,
69.
5)
51.1
(44,
64.
6)
Prio
rity
3
Men
W
omen
6
(0.8
) 2
(0.6
)
0.
56 (0
.11,
2.9
1)
0.49
79
.0 (4
7.1)
64
.7 (2
2.1)
60
.8 (4
5.2,
114
.8)
64.7
(49.
1, 8
0.3)
52
(15.
7)
48 (1
6.9)
0.
89 (0
.57,
1.39
) 0.
60
70
.6 (3
1.4)
70
.6 (2
5.2)
68
.1 (5
4.6,
76.
3)
71.6
(49.
9, 8
8.4)
*OR
sign
ifica
ntly
diff
eren
t fro
m 1
. C
I = c
onfid
ence
inte
rval
; IQ
R =
inte
r-qu
artil
e ra
nge;
OR
= o
dds r
atio
(men
as r
efer
ence
gro
up);
SD =
stan
dard
dev
iatio
n.
59
4.6 Discussion
To our knowledge, this is the first study to analyze sex differences in symptoms
reported during the emergency telephone calls for (ED confirmed) MI patients. Even
after age-adjustment women were much less likely than men to report chest pain.
Additionally, women were less likely than men to have a priority 1 ambulance response.
Also, the median total time from emergency call to hospital for men and women who
were allocated a priority 2 or 3 ambulance response was longer. Finally, less than two-
thirds of MI patients utilized EMS for transport to the hospital. Other studies that have
examined emergency telephone calls either have not focused on confirmed MI cases or
have not investigated sex differences. We believe these findings add to the literature on
MI patients transported by EMS and offer an opportunity to improve care by stimulation
awareness of potential sex differences in MI presentation.
4.6.1 Sex Differences in Chest Pain
The reasons why women with MI experience less chest pain and are more likely to
report vomiting than men are not entirely understood. Numerous studies have examined
sex differences in symptom presentation of MI, but most have abstracted data from
medical records or interviewed patients after MI. Recent studies1,116 found that women
were less likely than men to experience chest pain. Men and women with MI may have
different locations of obstructing lesions,117,118 and women have been reported to have
less obstructive coronary disease at angiography.119-121 This may lead to different
combinations of sympathetic and vagal stimulation, resulting in differences in the
reporting of pain and vomiting.122,123 Also, it is well known that women with MI are
older1,119,122 and have more co-morbid conditions such as diabetes,1,119,122
hypertension1,77,119 and heart failure,1,77,119 and these conditions have been associated
with MI without pain.64,122,124
For patients who did not report chest pain, there were no sex differences in the
symptoms reported, possibly due to insufficient statistical power due to small numbers.
The most common non-chest pain symptoms for both men and women were shortness
of breath, a fall, or collapse, syncope or unconsciousness. These symptoms are similar
to those found in a study109 from a large multi-centre prospective trial of patients
presenting to ED with suspected acute coronary syndrome but without chest pain. The
two most common symptoms at presentation in this study were shortness of breath and
60
syncope.109
4.6.2 Sex Differences in Ambulance Times
Although on-scene time and total ambulance time intervals were statistically
significantly longer in women compared with men, this is unlikely to be clinically
significant. Other studies analysing ambulance times have found the longest component
of pre-hospital time is on-scene time.125-127
Only one study126 reported sex differences in ambulance times and found women were
delivered to hospital 2.3 minutes slower on average than men.
4.6.3 Sex Differences in Priority Allocation
For patients with chest pain, even after age adjustment, women were less likely than
men to be allocated a ‘priority 1’ ambulance response Other studies have found women
with MI were less likely than men to be allocated an Advanced Life Support ambulance
(76% vs. 92%)128 or a ‘priority 1’ ambulance (67% vs. 81%).62 As to be expected
irrespective of chest pain status we have shown both men and women with MI who
were not allocated a ‘priority 1’ ambulance response had longer median total time from
emergency call to hospital. Further research is required to investigate strategies to better
identify patients who do not present with classic MI symptoms, otherwise they are
unlikely to be allocated to a high priority response and thus will have increased delay to
definitive treatment.
On closer analysis of specific phone calls, the reason why some of the patients with
chest pain were not allocated a priority 1 ambulance response was they were not
experiencing chest pain at time of the emergency call. Some had experienced chest pain,
they had taken sublingual nitrate, and their chest pain had resolved. Several had
experienced chest pain earlier and had consulted their general practitioner, who had
identified changes on the electrocardiogram or a positive test for troponin. While
telephone dispatchers were instructed to ask whether the patient was experiencing chest
pain at time of the call, some dispatchers allocated a priority 2 response to patients if
their chest pain had resolved, contrary to existing SJA-WA policy. Even though
allocating a priority 2 response was incorrect, after these 19 calls were removed from
the analysis, we found no difference in ‘priority 1’ response between men and women.
61
Recently, SJA-WA has introduced dispatch protocols (Medical Priority Dispatch
System129 – Version 12 AUE-std) with specific scripted dispatcher-asked questions,
which ensures that all patients who have had chest pain are allocated a priority 1
response.
Finally, this study found a persistent underuse of emergency ambulance for the whole
cohort (63%), with significantly more women (68%) than men (60%) using an
ambulance. This finding is comparable to the 53% to 70% of MI patients transported by
emergency ambulances in other studies.105,106 Also, consistent with other studies,
women were more often transported by ambulance than men, possibly a reflection of the
fact women tended to be older.106,130 Nonetheless, reasons that more than 35% of all MI
patients in Perth chose not to call an ambulance is of concern and warrants further
exploration. It is recommended that all patients experiencing symptoms of an MI call
the emergency ambulance.100,101
4.7 Limitations
The strength of our study is that it is a population-based cohort of patients with ED-
confirmed MI (STEMI / non-STEMI), drawn from all public hospital EDs in the Perth
metropolitan area. Whilst we are confident in sex differences found in the MI patients
experiencing chest pain, some caution is required in the interpretation of sex differences
in other symptoms, including vomiting. It is important to note that the ambulance
dispatch officer did not attempt to elicit the full spectrum of symptoms experienced by
the patient. If chest pain was mentioned, the need for a priority 1 response was
established and further questioning about other symptoms was unlikely. As such,
patients without chest pain were likely to report more of the other symptoms.
Also, SJA-WA had no formalised or routine call taker quality assurance program
undertaken during the study period. Variations may have been caused by different
subjective interpretations of the symptoms reported between dispatch operators. We
also need to highlight the caller was often not a first party caller (i.e., self) and the
majority of calls were from a second- or third-party caller. In three other studies,131-133
first-party callers comprise 5 – 11%; as such, we would suggest our data is similar. The
relationship of the caller to the patient and the location of the patient at the time of the
emergency call were also different for male and female patients.
Another limitation is that we did not include MI patients for whom an ambulance was
62
called but who were pronounced dead by the paramedics and not taken to an ED.
Although unlikely, it is possible that such patients may have reported a different pattern
of symptoms. Also, the ambulance record (n=26) and the emergency telephone call
(n=198) were missing for a number of patients and could not be analyzed.
We were also unable to identify patient co-morbid conditions or location of the
obstructed coronary artery that may be associated with atypical symptom presentation
of MI. However, our primary research question was to determine sex differences in
symptoms (particularly chest pain) during the emergency telephone call in MI patients
and examine the effect of such differences on ambulance response.
4.8 Conclusion
During the emergency telephone call for an ambulance, women with an ED-confirmed
diagnosis of MI were less likely than men to report chest pain as a symptom. Women
with chest pain were also less likely to be allocated a priority 1 ambulance response.
Overall, ambulance times did not differ between men and women, although women had
a marginally longer on-scene time. Ambulance dispatch officers and paramedics need to
be aware of the potential sex differences in MI presentation, in order to ensure
appropriate ambulance response.
63
Chapter 5: Symptoms of Myocardial Infarction: Concordance
between Paramedic and Hospital Records
5.1 Introduction
This chapter is the Author’s Original Manuscript published in Prehospital Emergency
Care Journal, 2013; 18:393-401.3 This manuscript examines the accuracy of the
paramedic patient care record (PCR) at a single hospital. The symptoms of MI were
extracted from the paramedic PCR and the hospital medical record. The next phase of
the study aims to answer the third research question posed in Chapter 1, Section 1.4:
Are paramedic records a reliable source of information about presenting
symptoms of MI and onset-time of symptoms compared with the
documentation in the hospital medical record?
This phase of the study was important as it validated the accuracy of the paramedic
documentation that was used to answer the remaining research questions. To answer
this question it was necessary to link the EDIS data, SJA-WA data, PCR data, and
hospital medical record data. The detailed explanation of this data linkage in Chapter 3
expands on the brief description in this manuscript.
5.2 Abstract
5.2.1 Background
To further reduce time to definitive therapy for acute myocardial infarction (MI)
patients, the focus of research needs to be on better understanding prehospital delay in
recognition and response to symptoms. Paramedic clinical records can serve as a
convenient source of data for such studies, but their accuracy needs to be established.
5.2.2 Objectives
This study aimed to determine the concordance of the symptoms and symptom-onset
time recorded in the paramedic patient care record (PCR) with those recorded in the
hospital medical record for MI patients.
64
5.2.3 Methods
A retrospective review of paramedic and hospital medical records was undertaken
between January 1, 2008 and October 31, 2009 for all patients with an emergency
department (ED) discharge diagnosis of MI at a single teaching hospital in Perth,
Western Australia. The symptoms of MI and onset times documented in the paramedic
PCR were compared with those recorded in the hospital medical record, which was
considered the “gold standard.” The study assessed differences in documentation using
McNemar’s tests, and concordance was described by kappa and adjusted kappa
statistics, sensitivity, specificity, positive, and negative predictive value (PPV, NPV).
5.2.4 Results
Of 810 patients with an ED discharge diagnosis of MI, 584 (71%) patients arrived by
ambulance and 509 patients had a paramedic PCR. After exclusions, 400 patients had
both paramedic PCR and hospital medical records available for review. Of 21
documented MI symptoms, the majority (71.4%) had adjusted Kappa statistics greater
than 0.75, and observed agreement greater than 90%. For the symptom of chest pain,
sensitivity, specificity, PPV and NPV were all over 85%. Where recorded in both
records (n = 196, 49%) the symptom-onset time agreed exactly for 118 (60.2%) records,
differed by 1-15 minutes for 24 (12.2%) records, and differed by 16-30 minutes for 22
(11.2%) records.
5.2.5 Conclusion
Our study demonstrated that documentation of the common symptoms of MI and
symptom-onset time was similar between the paramedic and hospital records, justifying
the use of paramedic PCRs as a source of data for research in prehospital MI patient
delay. Further research is required to investigate why symptom-onset time was not
routinely documented for all patients with chest pain.
5.2.6 Key Words
Myocardial infarction; symptoms; documentation; concordance; onset-time
65
5.3 Background
Over the last two decades there has been considerable success in reducing the delay
between hospital arrival and definitive therapy for acute myocardial infarction patients
(MI), i.e., the so-called ‘door-to-needle’ or ‘door-to-balloon’ time.134 The focus on MI
research has moved from door-to-balloon, to emergency medical service (EMS)-to-
balloon, to first medical contact-to-balloon, and may even progress to ‘symptom onset’-
to-balloon times. Previous research has demonstrated paramedics can reliably interpret
prehospital electrocardiograms,135,136 activate the cardiac catheter laboratory, and
decrease EMS-to-balloon time137-140 and first medical contact-to-balloon time.138
However, the prehospital delay between MI symptom onset and arrival at hospital still
remains problematic.141-143 In the prehospital environment, correct identification of the
symptoms of MI is crucial to ensure activation of the appropriate prehospital protocol,
thus minimizing time to the commencement of appropriate care. Symptom-onset time is
particularly important for patients experiencing MI because shorter time between
symptom onset and revascularisation has been shown to reduce mortality.102
Moreover, an increasing volume of emergency medical services research relies on the
accuracy of prehospital patient care records (PCRs), which are usually completed by
paramedics. A prehospital study144 of a cohort of patients with chest pain reported
documentation of history and physical characteristics varied considerably among four
ambulance services – with as few as 51% of records reporting the symptom-onset time.
A major criticism of relying on PCRs as the source of data for prehospital research is
they may not be complete or accurate. For example, documentation of vital parameters
is often poor or incomplete.145,146
While a number of studies that have examined concordance of diagnosis (diagnostic
accuracy) by comparing paramedics’ diagnoses with those documented in hospital
medical records,147-161 only a limited number of studies that have investigated
concordance of documentation of symptoms between the paramedic PCRs and the
hospital medical records.148,156 Two studies have investigated paramedic documentation
of symptoms involving patients with stroke and documentation of facial and arm
weakness and slurred speech and both showed good agreement between paramedic and
physician assessment.148,156 We did not find any studies in the literature that compared
66
paramedic documentation symptoms of MI and symptom-onset time with the hospital
medical record. Our study aimed to establish whether paramedic records are a reliable
source of information about presenting symptoms in patients with MI. We measured
concordance of symptom documentation in the prehospital PCR and hospital medical
records, and compared the documentation of symptom-onset time.
5.4 Methods
5.4.1 Setting, Participants and Study Design
Perth is the capital city of Western Australia (WA). It has a population of 1.7 million,
with 12% over 65 years.112 St John Ambulance Western Australia (SJA-WA) is the
single provider of prehospital emergency care in WA and is staffed by paramedics,
whose training consists of a 3-year bachelor of paramedic science degree program.28 Sir
Charles Gairdner Hospital (SCGH) is a metropolitan tertiary referral centre.
This study is a retrospective review of prospectively collected paramedic PCR and
hospital medical record documentation. The cohort (n=810) was identified from a
previous study2 and included all adult patients who were discharged from SCGH
emergency department (ED) with a diagnosis of MI between January 1, 2008 and
October 31, 2009. Of these, 584 patients arrived by SJA-WA ambulance. Of the 509
SJA-WA patient records 400 patients had pairs of paramedic PCRs and hospital medical
records available for review. The hospital medical record included the ED record and
also the initial admission records to the ward, as some patients bypassed ED and were
transferred directly to the cardiac catheter laboratory. Only information on presenting
symptoms was extracted. Ethics approval (with waiver of patient consent) was obtained
for this study from The University of Western Australia (RA/4/1/2428) and from the
SCGH Human Research Ethics Committee (# 2012-146). See Appendix K and L.
5.4.2 Data Sources
The Emergency Department Information System (EDIS),113 a patient-tracking system
containing patient demographic and disposition data, was used to identify patients for
this study. The principal clinical diagnosis is a mandatory field entered by clinical staff
on patient discharge from the ED. It is electronically mapped to the International
Statistical Classification of Diseases and Related Problems, 10th Revision, Australian
67
Modification (ICD-10-AM) codes.96 All adult patients discharged from the SCGH ED
with a discharge diagnosis of MI, code I21.9 (including both ST segment elevated MI
and Non ST segment elevated MI) were identified from EDIS.
In a previous study,2 EDIS data were linked to the SJA-WA database, which contains
data from the emergency call recorded by the SJA-WA Ambulance Operations Centre
using a computer-aided dispatch system and clinical data collected by the paramedics on
a paper based PCR.28 Only index patient ED presentations were included, i.e., the first
ED presentation during the study period for patients with more than one ED
presentation to SCGH. Patients were excluded if we could not locate their emergency
telephone call, if they transferred from another hospital or were transferred to another
hospital. For this study additional data on the symptoms of MI and their onset times
were extracted from the patient’s paramedic-completed prehospital PCR and the
hospital medical record. The data were extracted by one author (LLC), who entered the
data into a SPSS database (IBM SPSS Inc., 2008, Chicago, IL; www.spss.com).
A random sample of 10% of the records was reviewed by the same author (LLC) to
assess transcription accuracy: 5% were hospital medical records and 5% were
paramedic PCRs. Overall, data were collected on 486 comparisons with 99.4% data-
entry accuracy.
5.4.3 Data Analysis
Data are summarised as frequencies (number and percentage) and means. For this study,
the symptom of chest pain was operationally defined to include right-sided chest pain,
central chest pain, left-sided chest pain, chest tightness and chest heaviness. For each
symptom, McNemar’s test was used to determine whether the documented proportions
with the symptom differed between the hospital medical record and the paramedic PCR.
A p-value less than 0.05 indicates that the proportions in the two records differ
significantly.
Kappa statistics and their 95% confidence intervals (CIs) were used to quantify
agreement in documentation of symptoms of MI between the hospital medical records
and the paramedic PCRs. Observed and chance agreement probabilities are also
reported. See Table 12 for details of how statistics were calculated.162,163 A few
68
studies164,165 have reported that the Kappa statistic is not always satisfactory for
assessing agreement and recommend that bias and prevalence be taken into account
when the magnitude of one or both of their indices is close to one. We have therefore
also calculated bias and prevalence indices and the Prevalence Adjusted Bias Adjusted
Kappa (referred to as adjusted Kappa).164 Kappa (and adjusted Kappa) values of less
than 0.40 represent poor agreement, 0.40 to 0.75 represents fair to good agreement, and
over 0.75 represents excellent agreement.166
Table 12: Formulae to Calculate Statistics
Symptom documented in PCR
Symptom documented in hospital medical record
Yes No Total
Yes A B B1=A+B No C D B2=C+D Total A1=A+C A2=B+D N Sensitivity = A / A1 Specificity = D/ A2 Positive predictive value = A / B1 Negative predictive value = D/ B2 Observed agreement = A + D / N Chance agreement = (A1 x B1 + A2 x B2) / N2
We have reported documentation concordance as sensitivity, specificity, positive
predictive value (PPV) and negative predictive value (NPV), with 95% CIs calculated
using the modified Wald method recommended by Agresti and Coull.167 We have
assumed that the hospital medical record documentation of symptoms of MI was the
‘gold standard.’ Sensitivity represents the proportion of patients with the hospital
medical record documented symptom that are also documented to have the symptom in
the paramedic PCR. Specificity represents the proportion of patients without a hospital
medical record documented symptom that also do not have the symptom documented by
the paramedic PCRs. The PPV is the proportion of patients with a paramedic PCR
documented symptom also identified in the hospital medical record, and the NPV is the
proportion of patients for whom a specific symptom is not recorded in the paramedic
PCR and not identified in the hospital medical record.
Differences (in minutes) between the documented symptom-onset times were calculated
by subtracting the paramedic PCR time from the hospital medical record time and
grouped as follows: 0, ±(1-15), ±(16-30), ±(31-60), ≤-61 and ≥61 minutes.
69
5.5 Results
5.5.1 Cohort Characteristics
Of the 810 patients discharged from SCGH ED with a diagnosis of MI between January
2008 and October 2009, 584 (71%) arrived by ambulance. Following exclusions,
detailed in Figure 7, 422 patients were identified. Paramedic PCR and hospital medical
records were located for 400 (95%) of these patients. Men (n = 243, 61%) were younger
than women (mean age 71.5 vs. 77.2 years).
5.5.2 Symptom Documentation: Paramedic PCR and Hospital Medical Record
Prevalence of the symptoms of MI that were documented in the hospital medical
records and the paramedic PCRs are presented in Table 13. For the majority of
symptoms there was no significant difference between the hospital medical records and
paramedic PCRs in the proportion of patients documented to have the symptom;
exceptions were left shoulder pain (8.5% hospital medical records vs. 4.3% PCR), and
fatigue and lethargy (3% hospital medical records vs. 6% PCR).
70
Figure 7: Study Flow Diagram
EDIS = Emergency Department Information System; MI = myocardial infarction; PCR = patient care record; SJA-WA = St John Ambulance-Western Australia.
EDIS confirmed discharge diagnosis of MI (Jan 1, 2008 to Oct 31 2009)
n = 810
Arrived by ambulance
n = 584
Excluded, n = 75
• Missing (Industrial action, n = 37)
• Missing (No PCR, n = 38)
SJA-WA PCR
n = 509
Excluded, n = 87
• No emergency phone call, n = 37
• Transfer from other hospital, n = 33
• Not Index admission, n = 10
• Transfer to other hospital, n = 7
Patients admitted
n = 422
Excluded, n = 22
• Unable to locate hospital record
Hospital record review
n = 400
Men = 243
Women = 157
71
Table 13: Prevalence of Symptom Documentation of Myocardial Infarction: Paramedic
PCR and Hospital Medical Record
Symptom Paramedic PCR n (%)
Hospital Medical Record, n (%) P-value
Chest Pain 290 (72.5) 294 (73.3) 0.58 Shortness of breath 201 (50.3) 211 (52.6) 0.38 Sweaty or clammy 132 (33.0) 121 (30.3) 0.29 Nausea 105 (26.3) 98 (24.4) 0.54 Left arm pain 104 (26.0) 90 (22.4) 0.09 Jaw, throat or neck pain 53 (13.3) 57 (14.3) 0.66 Right arm pain 46 (11.5) 40 (10.0) 0.40 Dizziness 42 (10.5) 40 (10.0) 0.88 Vomiting 36 (9.0) 35 (8.8) >0.99 Syncope, collapse, unconscious 31 (7.8) 35 (8.8) 0.45 Left shoulder pain 17 (4.3) 34 (8.5) <0.01* Back pain 33 (8.3) 29 (7.3) 0.60 Abdominal / epigastric pain 29 (7.3) 24 (6.0) 0.40 Unwell 15 (3.8) 21 (5.3) 0.33 Confusion 15 (3.8) 20 (5.0) 0.31 Right shoulder pain 12 (3.0) 20 (5.0) 0.10 Fall 19 (4.8) 17 (4.3) 0.69 Weakness 17 (4.3) 16 (4.0) >0.99 Fatigue, lethargy 24 (6.0) 12 (3.0) 0.02* Belching, indigestion, heartburn 13 (3.3) 6 (1.5) 0.14 Headache 6 (1.5) 3 (0.8) 0.45
PCR=Patient Care Record; *statistically significant difference; McNemar’s Test was used to examine the difference in symptom documentation between the paramedic PCR and hospital medical record.
5.5.3 Chest Pain
Chest pain was the most common symptom of MI documented in the paramedic PCR
(72%) and hospital medical record (73.3%). The observed agreement was 94%, Kappa
was 0.84 and adjusted Kappa was 0.87. Sensitivity, specificity, PPV, and NPV were 94,
88, 96 and 85% respectively.
5.5.4 Other Symptoms of MI
Kappa and adjusted Kappa statistics for agreement between the hospital medical record
and paramedic PCR documentation for each symptom of MI are presented in Table 14.
Although bias had little effect in this study, the prevalence index was high for most
symptoms and justified use of the adjusted Kappa. The majority of symptoms of MI
(n=17, 81%) had adjusted Kappa statistics greater than 0.75, indicating excellent
agreement between the hospital medical record and paramedic PCR. Four symptoms
(19%), including shortness of breath, sweating, nausea and left arm pain, had adjusted
Kappa statistics between 0.40 and 0.75, indicating fair to good agreement.166
72
The sensitivity, specificity, PPV, NPV comparing documentation of symptoms of MI
between the hospital medical record and paramedic PCR (assuming the hospital medical
record is the gold standard) are presented in Table 15. For the majority of the
symptoms, specificity and NPV were greater than 90%. Shortness of breath had the
lowest values of 75% and 71% respectively, but all were greater than 70%. Sensitivity
and PPV varied as symptom prevalence reduced.
5.5.5 Symptom-onset Time: Paramedic PCR and Hospital Medical Record
The flow diagram of symptom-onset time is presented in Figure 8. In the hospital
medical record, patients with chest pain (n = 294, 74%) had a documented symptom-
onset time in 235 (80%) records. In the paramedic PCR, patients with chest pain (n =
290, 72%) had a documented symptom-onset time in 195 (67%) records. Overall,
hospital medical records had 275 (68.8%) documented symptom-onset times and
paramedic PCRs had 226 (56%). Symptom-onset time was available from both the
hospital medical record and the paramedic PCR for only 196 (49%) of the cohort.
Documented symptom-onset times of MI in the paramedic PCR and hospital medical
records are presented in Figure 9. Symptom-onset time agreed exactly for 118 (60.2%)
records, differed by 1-15 minutes for 24 (12.2%) records, and differed by 16-30 minutes
for 22 (11.2%) records. Eight (4.0%) records reported times that differed between 31 to
60 minutes. Twenty four (12.2%) records reported symptom-onset times that differed by
more than 60 minutes.
73
Tabl
e 14
: Obs
erve
d an
d C
hanc
e A
gree
men
t, K
appa
and
PA
BA
K S
tatis
tic o
f Sym
ptom
Doc
umen
tatio
n of
Myo
card
ial I
nfar
ctio
n: P
aram
edic
PC
R
and
Hos
pita
l Med
ical
Rec
ord
Sym
ptom
O
bser
ved
Agr
eem
ent
%
Cha
nce
Agr
eem
ent
%
Bia
s In
dex*
Pr
eval
ence
In
dex†
K
appa
(9
5%C
I)
Adj
uste
d K
appa
Che
st p
ain
93.5
60
.6
-0.0
1 0.
46
0.84
(0.7
7, 0
.90)
0.
87
Shor
tnes
s of b
reat
h 74
.0
50.0
-0
.02
0.03
0.
48 (0
.39,
0.5
7)
0.48
Sw
eaty
77
.8
56.7
0.
03
-0.3
7 0.
49 (0
.39,
0.5
8)
0.56
N
ause
a 76
.2
62.1
0.
02
-0.4
9 0.
37 (0
.27,
0.4
8)
0.52
Le
ft ar
m p
ain
85.5
63
.2
0.04
-0
.52
0.61
(0.5
1, 0
.70)
0.
71
Jaw
, thr
oat o
r nec
k pa
in
88.0
76
.3
-0.0
1 -0
.72
0.49
(0.3
7, 0
.62)
0.
76
Rig
ht a
rm p
ain
91.0
80
.8
0.02
-0
.78
0.53
(0.4
0, 0
.67)
0.
82
Diz
zine
ss
89.0
81
.6
0.00
-0
.80
0.40
(0.2
6, 0
.54)
0.
78
Vom
iting
92
.8
83.8
0.
00
-0.8
2 0.
55 (0
.41,
0.7
0)
0.86
Sy
ncop
e, c
olla
pse
or u
ncon
scio
us
96.0
84
.8
-0.0
1 -0
.84
0.74
(0.6
1, 0
.86)
0.
92
Left
shou
lder
pai
n 93
.2
88.0
-0
.04
-0.8
7 0.
44(0
.25,
0.6
3)
0.86
B
ack
pain
92
.0
85.7
0.
01
-0.8
4 0.
44 (0
.28,
0.6
0 0.
84
Abd
omin
al o
r epi
gast
ric p
ain
94.2
87
.6
0.01
-0
.87
0.54
(0.3
7, 0
.70)
0.
88
Unw
ell
93.5
91
.4
-0.0
2 -0
.91
0.24
(0.0
5, 0
.44)
0.
87
Con
fusi
on
94.2
91
.6
-0.0
1 -0
.91
0.31
(0.1
0, 0
.52)
0.
88
Rig
ht sh
ould
er p
ain
95.5
92
.3
-0.0
2 -0
.92
0.42
(0.2
3, 0
.60)
0.
91
Fall
98.5
91
.4
0.00
-0
.91
0.83
(0.6
9, 0
.96)
0.
97
Wea
knes
s 94
.2
92.1
0.
00
-0.9
2 0.
27 (0
.06,
0.4
8)
0.88
Fa
tigue
or l
etha
rgy
94.0
91
.4
0.03
-0
.91
0.31
(0.1
0, 0
.51)
0.
88
Bel
chin
g, in
dige
stio
n or
hea
rtbur
n 95
.8
95.3
0.
02
-0.9
5 0.
09 (0
.10,
0.2
8)
0.92
H
eada
che
98.2
97
.8
0.01
-0
.98
0.21
(0.0
2, 0
.40)
0.
96
PCR
= Pa
tient
Car
e R
ecor
d; C
I = c
onfid
ence
inte
rval
*T
he b
ias i
ndex
is th
e di
ffer
ence
in p
ropo
rtion
s of “
yes”
bet
wee
n th
e pa
ram
edic
PC
R a
nd h
ospi
tal m
edic
al re
cord
; it h
as a
min
imum
of -
1 an
d m
axim
um o
f 1.
†The
pre
vale
nce
inde
x (P
I) is
the
diff
eren
ce in
pre
vale
nce
of “
yes”
and
“no
”, p
reva
lenc
e be
ing
calc
ulat
ed a
s mea
ns fo
r par
amed
ic P
CR
and
hos
pita
l med
ical
reco
rd.
PI h
as a
min
imum
of -
1 an
d m
axim
um o
f 1 a
nd is
0 w
hen
the
mea
n pr
eval
ence
of “
yes”
is 5
0%
.
74
Tabl
e 15
: Sen
sitiv
ity, S
peci
ficity
, PPV
and
NPV
of S
ympt
om D
ocum
enta
tion
of M
yoca
rdia
l Inf
arct
ion:
Par
amed
ic P
CR
and
Hos
pita
l Med
ical
Rec
ord
(hos
pita
l med
ical
reco
rd w
as c
onsi
dere
d th
e go
ld st
anda
rd)
Sym
ptom
Se
nsiti
vity
(%)
(95%
CI)
Sp
ecifi
city
(%)
(95%
CI)
PP
V (%
) (9
5% C
I)
NPV
(%)
(95%
CI)
Che
st p
ain
94 (9
1, 9
6)
88 (8
2, 9
4)
96 (9
3, 9
8)
85 (7
8, 9
2)
Shor
tnes
s of b
reat
h 73
(66,
79)
75
(68,
81)
76
(70,
82)
71
(65,
77)
Sw
eaty
67
(59,
76)
82
(77,
86)
62
(54,
70)
85
(81,
89
Nau
sea
55 (4
5, 6
5)
83 (7
8, 8
7)
51 (4
2, 6
1)
85 (8
0, 8
9)
Left
arm
pai
n 74
(66,
84)
88
(84,
92)
65
(56,
74)
92
(89,
95)
Ja
w, t
hroa
t or n
eck
pain
54
(41,
67)
93
(90,
96)
58
(45,
71)
92
(89,
95)
R
ight
arm
pai
n 61
(46,
76)
94
(91,
96)
54
(40,
68)
95
(93,
98)
D
izzi
ness
48
(32,
63)
93
(90,
96)
46
(31,
61)
94
(91,
96)
V
omiti
ng
60 (4
3, 7
5)
95 (9
3, 9
8)
58 (4
1, 7
4)
96 (9
4, 9
8)
Sync
ope,
col
laps
e, &
unc
onsc
ious
69
(54,
86)
98
(96,
99)
77
(62,
92)
97
(95,
99)
Le
ft sh
ould
er p
ain
37 (2
0, 5
3)
98 (9
7, 1
00)
67 (4
4, 8
9)
94 (9
1, 9
6)
Bac
k pa
in
52 (3
3, 7
0)
95 (9
2, 9
7)
46 (2
9, 6
3)
96 (9
4, 9
8)
Abd
omin
al &
epi
gast
ric p
ain
61 (4
1, 8
0)
96 (9
4, 9
8)
52 (3
3, 7
0)
97 (9
5, 9
9)
Unw
ell
28 (9
, 47)
97
(95,
99)
37
(12,
61)
95
(93,
98)
C
onfu
sion
33
(13,
54)
97
(96,
99)
42
(17,
67)
96
(94,
98)
R
ight
shou
lder
pai
n 38
(16,
59)
98
(97,
100
) 56
(28,
84)
96
(94,
98)
Fa
ll 81
(62,
100
) 98
(97,
98)
74
(54,
94)
99
(98,
100
) W
eakn
ess
35 (1
2, 5
8)
96 (9
4, 9
8)
33 (1
1, 5
6)
97 (9
5, 9
8)
Fatig
ue &
leth
argy
50
(22,
78)
95
(93,
97)
29
(10,
47)
98
(96,
99)
B
elch
ing,
indi
gest
ion
& h
eartb
urn
30 (0
, 67)
96
(95,
98)
18
(0, 3
8)
98 (9
7, 1
00)
Hea
dach
e 43
(0, 9
0)
98 (9
7, 1
00)
30 (0
, 67)
99
(98,
100
)
CI =
con
fiden
ce in
terv
al; P
PV =
pos
itive
pre
dict
ive
valu
e; N
PV =
neg
ativ
e pr
edic
tive
valu
e
75
Figure 8: Flow Diagram of Symptom-onset Time: Paramedic PCR and hospital
Medical Record
Hospital medical record Paramedic PCR
Patients with Chest pain Patients with Chest pain
Yes, n = 294 (73.5%) No, n = 106 (26.5%) Yes, n = 290 (72.5%) No, n = 110
(27.5%)
Documented Symptom-onset time Documented Symptom-onset time
Yes, n = 235 (79.9%) Yes, n = 40 (37.7%) Yes, n = 195 (67%) Yes, n = 31
(11.3%)
Hospital medical record Paramedic PCR
n = 275 (68.8%) n = 226 (56%)
Both hospital medical record and paramedic PCR symptom-onset
n = 196 (49%) Missing, n = 204 (51%)
Hospital medical symptom-onset only,
n = 79 (38.7%)
Paramedic PCR symptom-onset only,
n = 30 (14.7%)
No symptom-onset for both hospital
medical and paramedic PCR,
n = 95 (46.6%)
76
Figure 9: Symptom-onset Time Difference (minutes): Paramedic PCR and Hospital
Medical Record, n = 196
5.6 Discussion
5.6.1 Symptom Documentation: Paramedic PCR and Hospital Medical Record
While other studies148,156 have investigated documentation of symptoms for stroke
patients between paramedic and hospital medical records, to our knowledge, this is the
first study to analyse the documentation of symptoms for MI patients. Accurate
prehospital documentation of the symptoms of MI on the paramedic PCR is essential for
the ED to ensure time critical revascularisation treatment from a medico-legal
standpoint and as a data source for research. We found the concordance of paramedic
PCR documentation of the symptom of chest pain was excellent, and for all but two
other symptoms there were no differences in the proportions of patients documented to
have the symptom. Overall the measure of agreement between the two records was
excellent and we observed a trend for higher specificity than sensitivity.
77
5.6.2 Chest Pain
For the symptom of chest pain in this study, the sensitivity, specificity, PPV, NPV
values are all above 85%, the observed agreement is 94%, and Kappa and adjusted
Kappa indicate excellent agreement. Statistically these results are impressive; however,
clinically we were concerned that the sensitivity and PPV were 94% and 96%. Further
examination of PCRs revealed that the paramedics were unable to obtain the
information because the patient had collapsed or was unconscious (n = 5), the patient
did not speak English (n = 1), or the paramedic described the pain as “epigastric” (n =
3). The actual anatomic location of “chest” and “epigastric” pain is very similar, despite
different connotations about the underlying pathology.
5.6.3 Other Symptoms of MI
Observed agreement in documentation of the majority of the symptoms of MI between
the two records is high (most > 88%) and the adjusted Kappa reflects excellent
agreement. A study156 that investigated identification of facial and arm weakness and
speech disturbance reported observed agreement of 78% for facial weakness, 98% for
arm weakness and 89% for speech disturbance, and Kappa scores of 0.49, 0.77, and
0.69 respectively. Our study has similar Kappa values, but the adjusted Kappa values
that take symptom prevalence into account indicate excellent inter-observer agreement
between the paramedic PCRs and the hospital medical records.
Our study has a wide range of values for PPV and sensitivity. The most likely reason for
this is that low prevalence of a symptom decreases PPV, and 13 symptoms had less than
10% prevalence. Specificity, which represents the proportion of patients without a
hospital medical record-documented symptom that also do not have the symptom
documented by the paramedic PCRs, tended to be higher than sensitivity, which
represents the proportion of patients with the hospital medical record documented
symptom that are also documented to have the symptom in the paramedic PCR.
5.6.4 Symptom-onset Time: Paramedic and Medical Record
Our study also identified the low rate of documentation of the symptom-onset time of
MI in both the paramedic PCR and the hospital medical record. Other studies107,144,168-
172 have reported missing data on onset times for 9% to 73% of occasions. Further
78
examination of the PCRs for the patients with chest pain who did not have a
documented date and symptom-onset time (n = 95) revealed that onset was missing with
no reason (n = 33); onset was described as either “gradual,” “intermittent,” or over the
last 1-7 days (n = 33); onset time was described as “sudden onset” (n = 9), “awoke with
chest pain” (n = 4), “collapsed” (n = 4), or “patient picked up from doctor’s surgery” (n
= 11); and in one case because the patient was confused. The paramedics may have
presumed that “sudden onset,” “awoke with chest pain,” and “collapsed” meant that the
onset time was similar to their arrival / patient pick up time.
It was concerning that there was no obvious reason why symptom-onset time was not
documented for 33 (11%) of the patients who had chest pain. Documentation of the
symptom-onset time is extremely important as it guides medical decisions and treatment
options. We found that when symptom-onset was documented, the time in the
paramedic PCR was consistently similar to the time in the hospital medical record for
the majority of records.
Our findings add to the growing body of EMS MI evidence and suggest paramedics
accurately identify chest pain and symptom-onset time. Future studies should include
paramedic ‘symptom onset’-to-balloon times.
5.7 Limitations
Our study has several limitations. The data from this study were collected at a single
hospital, which may limit the generalizability of the results. However, the cohort size
was substantial and there is no reason to suspect that hospital medical documentation of
symptoms of MI would differ in other similar tertiary-level metropolitan hospitals.
Furthermore, SJA-WA is the single provider of prehospital emergency care for all
hospitals in WA and at the time of the study patients with chest pain were transported to
the closest tertiary hospital.
The study is a retrospective review of prospectively collected paramedic PCR and
hospital medical record documentation. A standardised data collection instrument was
not used to document symptoms in the paramedic PCR or hospital medical record and
the patient may not have been asked about all the symptoms of MI, for example,
weakness and fatigue. The patient may not have remembered all of their symptoms, and
79
there may have been progression or change of symptoms from the time the paramedic
assessed the patient to the time the patient was assessed in hospital.
We assumed the hospital medical record of the symptom documentation and onset time
was the gold standard and this may not be the case. Some of the presenting symptoms of
MI may not have been considered relevant and, consequently, not documented by
medical staff. In particular, for paramedics the presence of chest pain alone is sufficient
to trigger a “priority one” (lights and siren) response and the need for a full enumeration
of all symptoms may not be deemed essential. It was also assumed that the ED
discharge diagnosis of MI was accurate and there is a possibility that further in-patient
assessment may have resulted in an alternative final diagnosis.
5.8 Conclusions
Our study showed good to excellent concordance in the reporting of the symptoms
between the paramedic PCR and the hospital medical record among patients with an ED
diagnosis of MI. Symptom-onset time agreed exactly for 60% of the records and for
over 80% of the records the times were within 30 minutes. Although our results are not
necessarily applicable to other emergency medical systems, our findings support the
utility of prehospital PCRs as an acceptable means of obtaining data for the
investigation of prehospital delay in MI patients. Further investigation is required to
understand why symptom-onset time is not routinely documented for patients with chest
pain.
80
81
Chapter 6: Characteristics and Outcomes for Myocardial
Infarction Patients Who Present with and without Chest Pain
6.1 Introduction
This chapter is the Author’s Original Manuscript that has been published in Heart, Lung
and Circulation.4 This manuscript examines the patient characteristics and survival
outcomes of those who present with and without chest pain at a single hospital. The
symptoms of MI for this study were extracted from the hospital medical record. This
phase of the study aimed to answer the fourth research question posed in Chapter 1,
Section 1.4:
Are patient characteristics and patient outcomes (survival and hospital
discharge diagnosis) of patients presenting with and without chest pain the
same?
To answer this question it was necessary to link the EDIS, SJA-WA data, and hospital
medical record data. The detailed explanation of this data linkage in Chapter 3 expands
on the brief description in the manuscript.
6.2 Abstract
6.2.1 Background
There are conflicting data on patient characteristics and outcomes of myocardial
infarction (MI) patients presenting with and without the symptom of chest pain.
6.2.2 Objectives
Compare the characteristics and survival of patients stratified by the symptom chest
pain.
6.2.3 Methods
This retrospective cohort study identified patients with an emergency department
discharge diagnosis of MI, who arrived by ambulance at a teaching hospital in Perth,
Western Australia, between January 2008 to October 2009. The cohort was linked to
82
hospital data and the state-based death register; clinical data were extracted by medical
record review. Patient characteristics were compared using logistic regression models
and survival analysis using Kaplan-Meier curves and Cox regression models.
6.2.4 Results
Of 382 patients, 26% presented without chest pain. The odds of presenting without
chest pain were increased if aged 80+ (OR 7.54; 95%CI 2.81-20.3) and aged 70-79
years (OR 4.33; 95% CI 1.50-12.5), and female (OR 1.67; 95%CI 0.99-2.82). The
adjusted hazard (median follow-up time 2.2 years) of presenting without chest pain was
not significantly associated with survival (HR 1.03; 95%CI 0.71-1.48).
6.2.5 Conclusion
Characteristics differed between patients with and without chest pain. However, the
symptom of chest pain was not associated with survival.
6.2.6 Key Words
Myocardial infarction, symptoms, atypical presentation, patient outcomes, survival
6.3 Introduction
Early symptom recognition of myocardial infarction (MI) is vital to reduce patient delay
in seeking treatment, ensure timely diagnosis and receive definitive care. Early
presentation and coronary revascularisation have consistently been shown to reduce
both mortality and morbidity.14,15 Although the hallmark symptom of MI is chest pain, a
recent literature review1 of symptom presentation in MI found that as many as one in
three women and one in four men did not experience chest pain. Other studies have
reported similar findings.18,31,116
Patients base their decision to seek medical care on the symptoms they experience, and
these symptoms are critical in determining appropriate pre-hospital and emergency
department triage.2,116 Patients and health professionals are less likely to recognise MI
when it occurs without chest pain.31,173 This causes patients to delay seeking medical
treatment,114 and health professionals may treat the patient less aggressively.174 Studies
have shown that MI patients without chest pain are less likely to receive evidence based
83
medical therapies and invasive cardiac procedures.31,56,174 In addition, the absence of
chest pain is associated with increased mortality.33,175
Understanding the demographic and clinical characteristics of patients who have a MI
without chest pain may help facilitate earlier detection and appropriate medical
treatment within the first 24 hours. The aim of this cohort study were to (1) compare
patient characteristics and (2) outcomes (survival and discharge diagnosis) of
emergency department (ED) diagnosed MI patients presenting with and without chest
pain.
6.4 Method
6.4.1 Setting and Participants
Perth is the capital city of Western Australia (WA) and 12% of the population of 2.29
million are over 65 years old.112 Sir Charles Gairdner Hospital (SCGH), one of three
adult tertiary referral hospitals in Perth, has over 53,000 ED presentations annually
(Celenza 2014 personal communication). The cohort was identified from a previous
study2 and included all adult patients who arrived by ambulance at SCGH between 1
January, 2008 and 31 October, 2009 and had an ED discharge diagnosis of MI. Only the
first ED presentation during the study period was included for patients with more than
one ED presentation at SCGH. Patients were excluded if they were transferred to or
from another hospital.
6.4.2 Study Design and Data Sources
A retrospective cohort study of prospectively collected data was examined by data
linkage and medical chart review. The data sources used in this study were (1)
Emergency Department Information System (EDIS), (2) St John Ambulance Western
Australia (SJA-WA), (3) WA Death Register, (4) The Open Patient Admission System
(TOPAS), and (5) medical chart review. EDIS,113 an ED patient-tracking system that
contains patient demographic and disposition data, was used to identify all adult patients
discharged from the SCGH ED between 1 January, 2008 and 31 October, 2009 with a
discharge diagnosis of MI, the International Statistical Classification of Diseases and
Related Problems, 10th Revision, Australian Modification96 code I21.9 (including both
STEMI [ST segment elevated MI] and NSTEMI [Non STEMI]). These data were linked
84
to the SJA-WA database,28 which contains data from the emergency call and clinical
data collected by the paramedics to form the study cohort, which was then linked to the
WA Death Register97 by probabilistic matching using Linkagewiz.98 Patients were
assumed to be alive at 1 September 2011 if there was no record of their death. Hospital
discharge diagnoses and procedure codes for the study cohort were extracted from
TOPAS,176 which contains records of all patient admissions, transfers and discharges.
The data extracted from the patient hospital medical record by one of the authors (L.C.)
included whether or not the patient presented with the symptom chest pain and other
presenting symptoms of MI. The symptom of chest pain was operationally defined to
include right-sided chest pain, central chest pain, left-sided chest pain, chest tightness
and chest heaviness. Other data extracted included the type of MI (STEMI / NSTEMI),
presence of co-morbid conditions (e.g. diabetes, hypertension, heart failure) and
whether or not patients had a primary percutaneous coronary intervention (PCI). Data
extraction accuracy has been previously reported3: in summary, a random sample of
10% of the records was reviewed by the same author (LC) and data-entry accuracy was
99.4%.
Two processes of care variables were considered in this study: ‘Primary PCI’ and any
‘cardiac procedure’. Primary PCI data were extracted from medical record review. A
Primary PCI is an emergency protocol, and a patient with a ST segment elevated MI,
during the study period was given aspirin, clopidogrel, and heparin 5000 units
intravenously in ED and rapidly transferred to the cardiac catheter laboratory for
immediate angiogram and PCI if required.
‘Cardiac procedure’ data were extracted from TOPAS discharge data. The ‘cardiac
procedure’ could have occurred anytime during the patient’s hospital stay. These data
were categorised into five groups: (1) no cardiac procedure, (2) angiogram only, (3) PCI
(with angiogram), (4) coronary artery bypass surgery (CABG) (with angiogram ± PCI),
and (5) computerised tomography (CT) angiography. A binary variable ‘cardiac
procedure’ was created by grouping angiogram, PCI, CABG and CT angiography
(categories 2-5) as ‘yes’, and no cardiac procedure as ‘no’. Patients who were first
treated under the Primary PCI protocol in ED were also included in either category 2, 3,
or 4 of the ‘cardiac procedure’ variable.
Outcome variables were hospital discharge diagnostic category and survival status at 1
85
September 2011. Hospital discharge diagnoses were categorised by the ICD-10-AM
codes: (1) MI (I21), (2) unstable angina (I20.0), (3) angina (I20.8, I20.9), (4) chest pain
(R07.3, R07.4), (5) other cardiac diagnoses, and (6) non-cardiac diagnoses. A binary
variable ‘hospital discharge diagnosis’ was created such that the first category, MI, was
‘yes’ and the remaining categories, unstable angina, angina, chest pain, other cardiac
diagnoses, and non-cardiac diagnoses (categories 2-6) were grouped as ‘no’.
Ethics approval (with waiver of patient consent) was obtained for this study from The
University of Western Australia (RA/4/1/2428, RA/4/1/2567) and from the SCGH
Human Research Ethics Committee (# 2012-146). See Appendix K, L, N and O.
6.4.3 Statistical Analysis
Data were stratified by presence or absence of chest pain on presentation and
summarised as frequencies (numbers and percentages) or means and standard deviations
(SDs). Differences between patient groups with and without chest pain were assessed by
χ2 tests or Fisher’s exact tests for categorical variables and t tests for continuous
variables.
Logistic regression was used to determine the odds of not experiencing chest pain
associated with specified patient characteristics. Characteristics considered included the
following: demographics (age, age-squared, sex, age-sex interaction); medical history
(diabetes, hypertension, dyslipidaemia, family history of coronary artery disease [CAD],
angina, previous MI, CAD, heart failure, previous PCI, previous CABG, and stroke);
and type of MI (STEMI or NSTEMI); and hospital discharge diagnosis (MI, Other).
Characteristics associated with the presence/absence of chest pain were initially tested
in unadjusted models. Age-squared was significantly associated with chest pain
indicating that the relationship between age and chest pain was not linear. For ease of
interpretation of its curved relationship with the log odds of chest pain, age was
categorised into decades in subsequent analyses. All characteristics with p<0.20 in
unadjusted analysis were included in the adjusted model. This model was simplified in a
stepwise fashion by removing the characteristic with the highest p-value and refitting
the model until only characteristics with p-values <0.10 were retained. As a final check,
all excluded characteristics were retested one at a time in this adjusted logistic model.
Logistic regression was also used to determine whether chest pain was associated with
86
processes of care: Primary PCI, or any cardiac procedure. Models were adjusted for
chest pain, age group, sex, type of MI, and hospital discharge diagnosis type, family
history of CAD, and previous stroke, heart failure, and angina; and analyses were
conducted as above. A post hoc sample size calculation was conducted using
methodology described by Peduzzi et al.177
Kaplan-Meier curves were produced, and the log rank test was applied to determine
whether chest pain was associated with survival. The effect of chest pain on survival
was also modelled in separate unadjusted and adjusted Cox regression models with data
stratified by (1) Primary PCI and (2) any cardiac procedure. Hazard ratios (HR)
compare patients who present without chest pain to those who present with chest pain.
All statistical analyses were performed with IBM SPSS Statistics Version 20.0 (IBM
Corp. Released 2011. IBM SPSS Statistics for Windows, Version 20.0 Armonk, NY:
IBM Corp) and statistical significance was set at 5%.
6.5 Results
6.5.1 Cohort Characteristics
Of the 810 patients discharged from SCGH ED with a diagnosis of MI between January
2008 and October 2009, 584 (71%) arrived by ambulance. Following exclusions, 382
patients remained (see Figure 10). Of these, 99 (25.9%) patients presented without chest
pain.
6.5.2 Presenting without Chest Pain
Patient characteristics are shown in Table 16. Patients without chest pain were more
likely to be older (mean age 82.3 years vs. 70.8 years), female, have had a previous
stroke; and have had a NSTEMI. Patients with chest pain were more likely to have a
family history of CAD.
Patient processes of care and outcomes are shown in Table 17. In unadjusted analyses
patients who presented without chest pain were less likely to have a Primary PCI, an
angiogram, a PCI during hospital admission, a hospital discharge diagnosis of MI, and
were less likely to survive the first 24 hours, 30-days, 1-year, and 2-years than patients
who presented with chest pain.
87
The mean recorded number of symptoms for patients with chest pain was 3.3 (SD 1.6)
and for patients without chest pain was 2.0 (SD 1.1). The main presenting symptoms for
the patients without chest pain are shown in Table 18. The most common symptom was
shortness of breath (44.4%); followed by syncope, collapse or unconsciousness
(22.2%); confusion (18.1%); a fall (14.1%); nausea (13.1%); and dizziness (12.1%).
88
Figure 10: Study Flow Diagram
EDIS = Emergency Department Information System; MI = myocardial infarction; PCR = patient care record; SJA-WA = St John Ambulance-Western Australia.
Arrived by ambulance
n = 584
EDIS confirmed discharge diagnosis of MI (Jan 1, 2008 to Oct 31 2009)
n = 810
Excluded, n = 75
• Missing (SJA-WA industrial action, n = 37)
• Missing (No PCR, n = 38)
SJA-WA PCR
n = 509 Excluded, n = 87
• No emergency phone call, n = 37
• Transfer from other hospital, n = 33
• Not Index admission, n = 10
• Transfer to other hospital, n = 7
Patients admitted to ED
n = 422
Excluded:
• Unable to locate hospital record, n = 22
• Transferred to private hospital, n = 14
• Discharged to nursing home, n = 2
• Discharged home, n = 2
Hospital record review
n = 382
Men = 233
Women = 149
89
Table 16: Characteristics of Patients with Myocardial Infarction by Clinical
Presentation: No Chest Pain Compared with Chest Pain
Variable No Chest Pain (n = 99)
Chest Pain (n = 283) P Value*
Demographic and baseline characteristics, Age, mean (SD), y
82.3 (11.5)
70.8 (14.0)
<0.001
Age groups, n (%) ≥80 years 70 to 79 years 60 to 69 years ≤59 years
68 (68.7) 22 (22.2)
4 (4.0) 5 (5.1)
96 (33.9) 61 (21.6) 62 (21.9) 64 (22.6)
<0.001
Women 51 (51.5) 98 (34.6) 0.003 Coronary heart disease risk factors, n (%) Diabetes
27 (27.3)
70 (24.7)
0.62
Hypertension 62 (62.6) 176 (62.2) 0.94 Dyslipidemia 34 (34.3) 117 (41.3) 0.22 Family history of CAD 4 (4.0) 58 (20.5) <0.001 Previous angina 1 (1.0) 12 (4.2) 0.20 Previous MI 21 (21.2) 58 (20.5) 0.88 Previous CAD 40 (40.4) 106 (37.5) 0.60 Previous heart failure 18 (18.2) 31 (11.0) 0.06 Previous PCI 7 (4.1) 17 (6.0) 0.71 Previous CABG 11 (11.1) 22 (7.8) 0.31 Previous stroke 18 (18.2) 23 (8.1) 0.005 Type of MI, n (%) STEMI NSTEMI Missing
15 (15.2) 64 (64.6) 20 (20.2)
110 (38.9) 139 (49.1) 34 (12.0)
<0.001
* p value from independent t-test, χ2 test or Fisher Exact Test CABG = coronary artery bypass graft; CAD = coronary artery disease; MI = myocardial infarction; NSTEMI = non ST segment elevated myocardial infarction; PCI = percutaneous coronary intervention; SD = standard deviation; STEMI = ST segment elevated myocardial infarction; y = years.
90
Table 17: Process of Care and Outcomes of Patients with Myocardial Infarction by
Clinical Presentation: No Chest Pain Compared with Chest Pain
Variable No Chest Pain (n = 99)
Chest Pain (n = 283) P Value*
Primary PCI, n (%) 5 (5.1) 96 (33.9) <0.001
Hospital cardiac procedure, n (%) No cardiac procedure Angiogram only PCI (including angiogram) CABG (including angiogram, ±PCI) CT Angiography only
88 (88.9)
2 (2.0) 8 (8.1) 0 (0.0) 1 (1.0)
125 (44.2) 37 (13.1)
113 (39.9) 6 (2.1) 2 (0.7)
<0.001 0.001
<0.001 0.35 0.60
Hospital discharge diagnosis (ICD-10-AM code) Myocardial infarction (I21) Unstable angina (I20.0) Stable angina (I20.8, I20.9) Chest pain (R07.3, R07.4) Other cardiac diagnoses Non-cardiac diagnoses
51 (51.5)
4 (4.0) 1 (1.0) 2 (2.0) 7 (7.1)
34 (34.3)
227 (80.2)
9 (3.2) 13 (4.6) 14 (4.9) 12 (4.2) 8 (2.8)
<0.001
0.75 0.13 0.26 0.26
<0.001
Mortality, n (%) ≤ 24 hours ≤ 30 days ≤ 1 year ≤ 2 years
6 (6.1)
18 (18.2) 37 (37.4) 44 (44.4)
4 (1.4)
17 (6.0) 50 (17.7) 72 (25.4)
0.02
<0.001 <0.001 <0.001
* p value from χ2 test or Fisher Exact Test PCI = percutaneous coronary intervention; CABG = coronary artery bypass graft; CT = computerized tomography; ICD-10-AM = International Statistical Classification of Diseases and Related Problems, 10th Revision, Australian Modification.
Table 18 Main Symptoms for Patients without Chest Pain
Symptom* Percent of total (n=99)
Shortness of breath 44.4 Syncope, collapse or unconscious 22.2 Confusion 18.2 Fall 14.1 Nausea 13.1 Dizziness 12.1 Abdomen or epigastric pain 11.1 Unwell 11.1 Fatigue or lethargy 10.1 Weakness 10.1 Vomiting 9.1 Sweaty & clammy 7.1 Left arm pain 5.1 Jaw, throat or neck pain 4.1 Back pain 3.0
*Multiple symptoms possible
91
Odds ratio estimates from logistic regression analyses of the associations between
patient characteristics and MI without chest pain are presented in Table 19. The adjusted
model estimated that the odds of not experiencing chest pain were 7.54 (95% CI, 2.81-
20.3) times higher in patients aged 80 years or more, and 4.33 (95%CI, 1.50-12.5) times
higher in patients aged 70 to 79 years compared with patients under 60 years of age, and
the odds of women not experiencing chest pain were 1.67 (95% CI, 0.99-2.82) times
higher than those of men. Compared with patients who had an MI hospital discharge
diagnosis, the odds of not experiencing chest pain were 3.43 (95% CI, 2.01-5.85) times
higher for patients who had other hospital discharge diagnoses.
6.5.3 Primary PCI or any Cardiac Procedure
In adjusted analyses, for patients presenting without chest pain, the odds of not having a
Primary PCI were 81% lower (OR 0.19; 95% CI, 0.05-0.75), and the odds of not having
any cardiac procedure were 78% lower (OR 0.22; 95% CI, 0.08-0.51) compared with
patients with chest pain (see Table 20).
The post hoc calculation of minimum sample size for a logistic regression model with 7
covariates indicated that 269 patients were required from a population in which the
proportion with chest pain was 0.26.
92
Tabl
e 19
: Odd
s Rat
io E
stim
ates
(fro
m u
nadj
uste
d an
d ad
just
ed lo
gist
ic re
gres
sion
ana
lyse
s) o
f the
Ass
ocia
tions
betw
een
Patie
nt C
hara
cter
istic
s and
Myo
card
ial I
nfar
ctio
n w
ith N
o C
hest
Pai
n
Una
djus
ted
mod
els
Adj
uste
d m
odel
s
OR
95
% C
I P
valu
e O
R
95%
CI
P va
lue
Age
gro
ups,
≥80
year
s
70 to
79
year
s
60 to
69
year
s
<60
year
s Fe
mal
e se
x Ty
pe o
f MI (
STEM
I, N
STEM
I)
Fam
ily h
isto
ry o
f CA
D
Prev
ious
Stro
ke
H
eart
failu
re
A
ngin
a H
ospi
tal d
isch
arge
dia
gnos
is (M
I, ot
her)
9.
07
4.62
0.
83
1.00
2.
01
3.38
0.
16
2.
51
1.80
0.
23
3.82
3.
47-2
3.7
1.64
-13.
0 0.
21-3
.22
1.
26-3
.19
1.82
-6.2
5 0.
06-0
.46
1.
29-4
.89
0.96
-3.4
0 0.
03-1
.80
2.34
, 6.2
3
<0.0
01
<0.0
01
0.00
4 0.
78
0.
003
<0.0
01
0.00
1 0.
007
0.07
0.
16
<0.0
01
7.
54
4.33
0.
71
1.00
1.
67
0.
17
3.43
2.
81-2
0.3
1.50
-12.
5 0.
18-2
.84
0.
99-2
.82
0.
02-1
.38
2.01
-5.8
5
<0.0
01
<0.0
01
0.00
7 0.
63
0.
05
0.
10
<0.0
01
CA
D =
cor
onar
y ar
tery
dis
ease
; CI =
con
fiden
ce in
terv
al; M
I = m
yoca
rdia
l inf
arct
ion;
NST
EMI =
non
ST
segm
ent e
leva
ted
myo
card
ial i
nfar
ctio
n; O
R =
odd
s rat
io;
STEM
I = S
T se
gmen
t ele
vate
d m
yoca
rdia
l inf
arct
ion.
M
odel
adj
uste
d fo
r: ch
est p
ain,
age
gro
ups,
sex,
type
of M
I, fa
mily
his
tory
of C
AD
, pre
viou
s stro
ke, h
eart
failu
re &
ang
ina,
and
hos
pita
l dis
char
ge d
iagn
osis
.
93
Tabl
e 20
: Odd
s Rat
io E
stim
ates
from
Mul
tiple
Log
istic
Reg
ress
ion
Ana
lysi
s of t
he A
ssoc
iatio
ns b
etw
een
Patie
nt C
hara
cter
istic
s and
Hav
ing
a Pr
imar
y PC
I or a
‘Car
diac
Pro
cedu
re’
A
djus
ted
mod
el fo
r Prim
ary
PCI
Adj
uste
d m
odel
for c
ardi
ac
proc
edur
e
OR
95
% C
I P
valu
e O
R
95%
CI
P va
lue
No
ches
t pai
n A
ge g
roup
s,
≥8
0 ye
ars
70
to 7
9 ye
ars
60
to 6
9 ye
ars
<6
0 ye
ars
Type
of M
I (ST
EMI v
s. N
STEM
I)
Fam
ily h
isto
ry o
f CA
D
Prev
ious
hea
rt fa
ilure
H
ospi
tal d
isch
arge
dia
gnos
is (M
I, ot
her)
0.19
0.13
0.
93
2.10
1.
00
0.00
3 0.
61
0.05
-0.7
5
0.04
-0.4
6 0.
24-3
.68
0.44
-9.9
9
<0.0
01-0
.01
0.
08-4
.89
0.02
<0
.001
0.
001
0.92
0.
35
<0
.001
0.64
0.22
0.06
0.
64
0.74
1.
00
0.09
2.
36
0.24
0.
21
0.08
-0.5
1
0.02
-0.1
8 0.
21-1
.95
0.23
-2.4
2
0.04
-0.1
9 0.
92-6
.11
0.06
-0.9
7 0.
07-0
.66
0.00
2 <0
.001
<0
.001
0.
43
0.62
<0.0
01
0.08
0.
04
0.00
8
CA
D =
cor
onar
y ar
tery
dis
ease
; CI =
con
fiden
ce in
terv
al; M
I = m
yoca
rdia
l inf
arct
ion;
NST
EMI =
non
ST
segm
ent e
leva
ted
myo
card
ial i
nfar
ctio
n; O
R =
odd
s rat
io;
STEM
I = S
T se
gmen
t ele
vate
d m
yoca
rdia
l inf
arct
ion.
M
odel
adj
uste
d fo
r: ch
est p
ain,
age
gro
ups,
sex,
type
of M
I, fa
mily
his
tory
of C
AD
, pre
viou
s stro
ke, h
eart
failu
re &
ang
ina
and
hosp
ital d
isch
arge
dia
gnos
is
94
6.5.4 Survival Outcomes
The cohort of patients with an ED discharge diagnosis of MI were followed up for a
median time of 2.2 years (IQR 1.8-2.8 years, range 0-3.75 years). The log rank test for
equality of survival curves indicated patients who presented without chest pain had
significantly poorer survival than those who presented with chest pain. See Figure 11.
Figure 11: Kaplan-Meier Survival Plot for Patients with and without Chest Pain
In the multivariable Cox regression model, chest pain was not associated with survival
(HR 1.00; 95% CI, 0.69-1.46) (see Table 21). When data were stratified by Primary
PCI, chest pain was not associated with survival (No Primary PCI: HR 1.10; 95% CI,
0.75-1.61, and Yes Primary PCI: HR 0.74; 95% CI, 0.08-7.40). When data were
stratified by cardiac procedure, chest pain was not associated with survival (No ‘cardiac
procedure: HR 1.26; 95% CI, 0.86-1.85, and Yes ‘cardiac procedure’: HR 1.04; 95% CI,
0.18-5.98).
95
Tabl
e 21
: Haz
ard
Rat
io E
stim
ates
(fro
m u
nadj
uste
d an
d ad
just
ed C
ox re
gres
sion
ana
lyse
s) fo
r Cha
ract
eris
tics
Ass
ocia
ted
with
Myo
card
ial I
nfar
ctio
n w
ithou
t Che
st P
ain
U
nadj
uste
d m
odel
A
djus
ted
mod
el
H
R
95%
CI
p va
lue
HR
95
% C
I p
valu
e
No
Che
st p
ain
Age
gro
ups
≥8
0 ye
ars
70
to 7
9 ye
ars
60
to 6
9 ye
ars
<6
0 ye
ars
Fem
ale
sex
Type
of M
I (ST
EMI v
s. N
STEM
I)
Fam
ily h
isto
ry o
f CA
D
Prev
ious
Stro
ke
H
eart
failu
re
A
ngin
a H
ospi
tal d
isch
arge
dia
gnos
is (M
I, ot
her)
2.16
11.9
5.
52
0.80
1.
00
1.28
3.
00
0.16
2.02
3.
93
0.62
1.
70
1.52
-3.0
8
4.84
-29.
3 2.
13-1
4.3
0.22
-3.0
0
0.90
-1.8
0 1.
88-4
.80
0.06
-0.3
9
1.28
-3.2
0 2.
65-5
.81
0.20
-1.9
4 1.
20-2
.43
<0.0
01
<0.0
01
<0.0
01
<0.0
01
0.74
0.17
<0
.001
<0
.001
0.00
3 <0
.001
0.
41
0.00
3
1.00
7.49
3.
69
0.64
1.
00
0.
37
2.
29
1.
14
0.69
-1.4
6
2.95
-19.
0 1.
40-9
.74
0.17
-2.4
0
0.15
-0.9
4
1.53
-3.4
1
0.79
-1.6
5
0.99
<0
.001
<0
.001
0.
008
0.51
1.
00
0.
04
<0
.001
0.47
HR
= h
azar
d ra
tio; C
I = c
onfid
ence
inte
rval
; STE
MI =
ST
segm
ent e
leva
ted
myo
card
ial i
nfar
ctio
n; N
STEM
I = n
on S
TEM
I; C
AD
= c
oron
ary
arte
ry d
isea
se.
Mod
el a
djus
ted
for:
ches
t pai
n, a
ge g
roup
s, se
x, ty
pe o
f MI,
fam
ily h
isto
ry o
f CA
D, p
revi
ous s
troke
, hea
rt fa
ilure
& a
ngin
a an
d ho
spita
l dis
char
ge d
iagn
osis
.
96
6.6 Discussion
Some previous reviews 1,18 of sex differences in symptoms of MI found that presenting
without chest pain was more common in women than in men. However, findings from
other studies have been inconsistent: perhaps due to combining patients with different
diagnoses 39,46,47 (e.g. MI, unstable angina, and chest pain); or being restricted to
patients who presented with chest pain, or were within a particular age range; many
have small sample sizes; and many did not adjust for age, gender, interactions, and
comorbidity. 1,18
The major finding of this study were that MI without chest pain is common, and it is
associated with being over 70 years, and being female. Furthermore, presenting
with/without chest pain was not associated with survival after adjustment for covariates.
6.6.1 Presenting without Chest Pain
We found 26% of our MI cohort presented without chest pain, this is similar to other
large studies 1,18,31,116 whom also report 25% to 35% of patients present without chest
pain. This study demonstrates there are clear differences in demographic and clinical
characteristics between MI patients with and without chest pain. Our findings are
consistent with those in the literature that identify the following characteristics of MI
without chest pain include older age, 31,56,109,114,174 and female sex. 31,56,122 The reasons
why older patients experience MI without chest pain is not clearly understood. Possible
explanations include older patients may have more comorbidities, decreased pain
perception, or have cognitive changes (e.g. dementia). 178 Comorbid conditions of
diabetes, hypertension, and heart failure have been associated with MI without chest
pain. 178 The reason why women experience MI without chest pain is also not clearly
understood. Women have been reported to have less obstructive coronary disease at
angiography 120,121 and may have different locations of obstructing lesions. 117 This may
lead to different combinations of sympathetic and vagal stimulation, resulting in
differences in the reporting of pain. 123 Women with MI are also older and may also
have more comorbid conditions. 123 Another reason why older people and/or women
have less chest pain may be the way they express or report their symptoms. Some
studies179,180 have reported women use different language than men when describing
their symptoms of MI.
97
We also found differences in ED discharge diagnosis and hospital discharge diagnoses
between MI patients presenting with and without chest pain. This is not unexpected as
highly sensitive troponin assays can detect elevated troponin in the absence of MI. 181 If
a patient in ED has an elevated troponin they are more likely to have an ED discharge
diagnosis of MI. However, other clinical conditions (e.g. heart failure and renal failure)
may be associated with elevated cardiac troponin levels. 181 Further investigations
during the patient’s hospitalisation may result in a different hospital discharge
diagnosis.
6.6.2 Primary PCI or any Cardiac Procedure
We found patients were less likely to have a Primary PCI if they presented without
chest pain, consistent with the existing literature. 32,116,122,175 The Primary PCI activation
criteria at SCGH includes symptom onset less than 12 hours, electrocardiogram (ECG)
evidence of STEMI, less than 80 years, ongoing pain, and that the patient is mobile and
independent. However, clinicians are informed that the activation criteria are not
absolute and that patients who have typical ECG changes and other clinical features of
MI (e.g. shortness of breath, hypotension, malignant arrhythmias) should also be
considered for activation. This occurred in our study for five patients who presented
without chest pain and had a Primary PCI. Their symptoms included; collapse and
cardiac arrest prior to hospital arrival (n=2), severe shortness of breath (n=1), abdominal
pain and vomiting (n=1), and back pain radiating to left arm (n=1).
We also found patients were less likely to have a cardiac procedure during their
hospitalisation if they presented without chest pain. These findings are also consistent
with the literature, patients without chest pain are less likely to undergo an angiogram 31,32,56,173 and PCI 31,116,173 during hospital admission.
6.6.3 Survival Outcomes
Like others, we found that MI without chest pain was associated with decreased survival
in unadjusted analyses. 31-33,56,109,122,173-175 However, after multivariable adjustment we
did not find MI without chest pain was associated with survival. Two other studies 32,182
had similar results. One study, 32 only examined in-hospital survival. The other
longitudinal cohort study, 182 had a median follow-up of 5.4 years, however the
inclusion criteria to identify individuals with unrecognised MI was self-report and the
potential for recall bias was a limitation in this study. In contrast, many studies
98
31,33,56,109,122,173,174 after multivariable adjustment have found MI without chest pain to be
associated with poor survival. Our study only had a median follow-up of 2.2 years. The
loss to follow-up is expected to be low because of low emigration rates in WA, and
deaths out of the state have been shown to be less than 2%. 183 It is possible that, with
longer follow-up, significant differences in survival between patients with and without
chest pain may have emerged.
Identifying the symptoms of MI other than chest pain is vital for successful
management and timely treatment for patients who present atypically. The dominant
‘other’ presenting symptoms were shortness of breath; collapse, syncope or
unconsciousness; confusion; a fall; nausea; and dizziness. These findings are similar to
other studies, 56,114,173 which also found shortness of breath and collapse were the most
common presentation symptoms of MI without chest pain. However, these ‘symptoms’
are not specific to MI and can reflect a wide spectrum of patient conditions; which
poses a challenge for prehospital triage and triage in the ED.184
6.7 Limitations
Our study has several limitations. Data from this study were collected at a single
hospital and only included patients who arrived by ambulance which may limit the
generalisability of the results. There is no reason to suspect that hospital medical
documentation of symptoms of MI would differ in other similar tertiary-level
metropolitan hospitals. However, patients who did not arrive by ambulance may present
with a different symptom profile. Although, accuracy of data abstraction from the
medical notes was over 99%, 3 this was a retrospective cohort study and the available
data depends on the quality of the information recorded in the medical record. Our
sample size was small and we may have been unable to detect significant differences in
other patient characteristics (e.g. diabetes and hypertension) because of insufficient
statistical power. We also acknowledge ‘type of MI’ had missing data and the logistic
and Cox regression modelling excluded the missing data. Additionally, of all the
patients with an ED discharge diagnosis of MI, only 73% had a hospital discharge
diagnosis of MI. We decided a priori to include all patients with an ED discharge
diagnosis of MI, as during their ED admission and initially on the ward they were
managed as patients with suspected MI. We have also adjusted for type of hospital
discharge diagnosis in all of our models.
99
6.8 Implications for Practice, Research, Policy and Education
The current study supports the need to be able to better identify the high risk patient
who presents without chest pain. Using a standardised symptom assessment /
questionnaire to identify other symptoms of MI may assist in early identification of such
patients. Future studies should focus on ways to identify these high risk patients and
optimise their care. This is particularly important as our population continues to age,
and with women living longer than men, it is likely that patients without chest pain will
make up an increasing proportion of those having a MI.
Implications for policy include health campaigns that reflect a wide spectrum of
symptoms of MI and highlight possible differences in symptom presentation between
men and women. Advice not to exclude a diagnosis of MI in the absence of chest pain,
particularly in older patients and females, should be incorporated in the education of
professionals, including paramedics, General Practitioners, nursing and medical
personnel and those who give health advice and answer emergency telephone lines.
6.9 Conclusions
We compared the clinical and demographic characteristics and survival outcomes of
patients transported by ambulance with an ED discharge diagnosis of MI who presented
with and without chest pain. Older age and female sex were associated with presenting
without chest pain. After adjustment, we found no differences in survival between
patients who presented with and without chest pain.
100
101
Chapter 7: The Effect of Presenting Symptoms and Patient
Characteristics on Prehospital Delay in MI Patients
Presenting to ED by Ambulance: A Cohort Study
7.1 Introduction
This chapter is the Author’s Original Manuscript that has been published in Heart,
Lung, and Circulation.5 This manuscript describes prehospital delay times and the
presenting symptoms of MI that contribute to delay for all patients who presented to one
of the seven hospitals over a 22 month period. The symptoms of MI were extracted
from the paramedic patient care record (PCR). This final phase of the study aimed to
answer the fifth research question posed in Chapter 1, Section 1.4:
What is the prehospital delay time for MI patients transported by
ambulance, and what are the patient characteristics and presenting
symptoms which contribute to prehospital delay?
There were only 10 studies185-194 of prehospital delay that were published in Australia.
The inclusion criteria for these studies differed, in that some studies included only
patients who presented with chest pain,191,194 while others included patients admitted to
a coronary care unit,185,186 or patients with acute coronary syndrome.188,189,192 Of the
acute coronary syndrome studies, two188,192 reported prehospital delay in MI patients;
one188 combined Australian and New Zealand patients, and the other192 had only 15
patients with MI. The three studies187,190,193 that included patients with MI were all
conducted before 1999 and at this time, different criteria were used to define MI.20
There was only one Australian study187 published in 1995 that examined symptom
presentation and delay time. The lack of recent published Australian literature on
prehospital delay contributed to the motivation to answer this final question.
7.2 Abstract
7.2.1 Background
Despite extensive literature on prehospital delay, there is little recent information about
prehospital delay time for Australian patients with myocardial infarction (MI).
102
7.2.2 Objectives
The aims of this study were to: (1) describe prehospital delay time for Western
Australian patients with MI; (2) identify variables and presenting symptoms of MI
which contribute to the delay.
7.2.3 Methods
This retrospective cohort study identified patients with an emergency department (ED)
discharge diagnosis of MI, transported by ambulance to one of the seven metropolitan
EDs in Perth, Australia between January 2008 and October 2009. Prehospital delay
times were analysed using univariable and multivariable linear regression models. Non-
numeric (word descriptions) of delay time were categorised.
7.2.4 Results
Of 1,633 patients, symptom onset-time was available for 1,003. For the 829 patients
with a numeric onset-time, median delay was 2.2 hours; decreased delay was associated
with age <70 years, presenting with chest pain, and diaphoresis. Increased delay was
associated with being with a primary health care provider, and if the patient was at
home and if the person who called the ambulance was anyone other than the spouse. Of
the 174 patients with non-numeric onset-times, 37% patients delayed 1-3 days and 110
(64.0%) patients described their symptoms as intermittent and/or of gradual onset.
7.2.5 Conclusion
Given that prehospital delay times remains longer than is optimal, public awareness of
MI symptoms should be enhanced in order to decrease prehospital delay.
7.2.6 Key Words
Myocardial infarction, prehospital delay, symptom presentation, emergency
7.3 Introduction
Over 49,000 patients per year have a myocardial infarction (MI) in Australia - about
135 per day - and nearly 40% of these events are fatal.195 Reperfusion therapy of an
103
obstructed coronary artery decreases myocardial damage and is vital in decreasing
mortality and morbidity; however, this intervention is time-critical and delays decrease
its efficacy.11,12
There has been considerable success in decreasing hospital delay times for MI patients
(i.e. door-to-treatment),196 but reducing prehospital delay, i.e. the total amount of time
taken by patients to present at the emergency department (ED) following acute
symptom onset, has been less successful.107,188 Australian studies185-194 on prehospital
delay report median prehospital delays of 1.2 to 6.4 hours. Internationally, overall
duration of prehospital delay has remained relatively unchanged over the last two
decades,107,169,188 and public educational campaigns185,197 and targeted education and
counselling141,197 have had little success in reducing prehospital delay.
Identification of variables associated with prehospital delay may lead to interventions
that succeed in shortening delay time. With the exception of increased delay time
associated with contacting a primary health care provider (HCP)80,107,198 and being alone
or at home107,199 at symptom onset, consistent factors that influence delay have not
emerged. There is an abundance of research focussing on prehospital delay but, of the
six studies80,187,198-201 that have investigated the effect of MI symptoms on delay time,
only one187 from 1995 specifically investigates Australian patients with MI, so an
update is timely. The aims of this study were to: (1) describe prehospital delay time in
Western Australian patients with an ED discharge diagnosis of MI who were
transported by ambulance; and (2) identify patient characteristics and presenting
symptoms of MI which contribute to this delay.
7.4 Methods
7.4.1 Study Design, Setting and Participants
A secondary analysis was performed on data originally collected for a study that
examined sex differences in symptoms of MI reported to ambulance dispatch.2 This
retrospective cohort study reviewed prospectively collected paramedic patient care
records (PCRs) and the emergency telephone calls of all adult patients with an ED
discharge diagnosis of MI transported by St John Ambulance Western Australia (SJA-
WA) to one of the seven Perth metropolitan public EDs between January 1, 2008 and
October 31, 2009. The Perth metropolitan area is over 5000 square kilometres and has a
104
population of 1.7 million.111 SJA-WA is the single provider of emergency road
ambulance for WA and is staffed by paramedics. Ethical approval was obtained for this
study from The University of Western Australia (RA/4/1/2428). See Appendix K.
7.4.2 Data Sources
Two databases were linked: the Emergency Department Information System113 (EDIS)
and the SJA-WA database. EDIS, an ED patient-tracking system containing patient
demographic and disposition data, was used to identify all adult patients with an ED
discharge diagnosis of MI during the study period. The SJA-WA patient database
contains records of all cases attended by ambulances in WA and the paper-based,
paramedic-completed PCRs. Data from the emergency phone call to SJA-WA was
retrieved and transcribed. Data collected included patient characteristics, time variables
and symptoms on presentation.
Symptoms reported on presentation and symptom onset-times were extracted from the
paramedics’ PCRs. If the onset-time was not available from the paramedic’s PCR, the
emergency phone call transcript was searched. Presenting symptoms of MI included:
chest pain; left arm; right arm; jaw, throat and neck pain; diaphoresis; shortness of
breath; abdominal or epigastric pain; nausea; vomiting; syncope, collapse or
unconscious; dizziness; weakness; fatigue; back pain; and a fall. Chest pain was
operationally defined to include right-sided, left-sided, and central chest pain, chest
tightness, and chest heaviness. Individual patients could experience multiple symptoms.
Additional information pertaining to the emergency phone call was collected, including
the day of the week (weekday or weekend), time of the day (0600-1159, 1200-1759,
1800-2359, 000-0559), the relationship of the caller to the patient and the patient’s
location. ‘Other location’ included sporting venues, shopping centres, hotels, education
centres, and the side of the road. Hospital arrival time was obtained from the EDIS.
7.4.3 Data Analysis
For patients with numeric symptom onset-times (e.g. 1-Jan 2008 15:30), prehospital
delay time was calculated by subtracting their ED arrival time from their symptom
onset-time. As delay times were skewed, they were described using medians and
interquartile ranges (IQR) and log transformed for further analyses. Each variable was
initially tested for association with delay time in a univariable linear regression model.
Multivariable linear regression was used to determine variables independently
105
associated with prehospital delay time. The initial multivariable model, which included
the variables listed in Table 22, was simplified in a stepwise fashion by removing the
variable with the least significant p-value and refitting the model until only variables
with p-values <0.10 were retained. As a final check, all excluded variables were retested
one at a time in the final multivariable model. Exponential beta coefficients [exp(B)]
and 95% confidence intervals (CIs) were reported. These values correspond to changes
in the ratio of the expected geometric means of the original delay time. Data were
analysed using SPSS version 22 (IBM Corp. Released 2011. IBM SPSS Statistics for
Windows, Version 22.0 Armonk, NY: IBM Corp) and significance was set at 0.05.
Non-numeric symptom onset-times (e.g. yesterday, three days ago, last week), were
categorised by two members of the research team (LC & AB). To enhance credibility
and auditability, data were categorised independently, categories were confirmed, and
disagreements were resolved by discussion until consensus was reached. Categories
included: ≤1 hour; >1 to 6 hours; >6 hours to 1 day; >1 day to 3 days; >3 days to 1
week; >1 week to 2 months. Categories were dichotomised (yes/no) if presenting
symptoms were intermittent and/or had a gradual onset.
7.5 Results
7.5.1 Characteristics of the Cohort
During the study period, January 2008 to October 2009, of the 3,329 patients who were
discharged from a Perth ED with a diagnosis of MI, 1,633 patients arrived by
ambulance (see Figure 12). Patients who were missing a symptom onset-time (n=630,
38.6%) were older (mean age 73.8 vs.70.8 years, p<0.001), and less likely to present
with chest pain (46.8% vs.73.7%. p<0.001). Of the 1,003 patients with prehospital delay
time available, 829 patients had a numeric symptom onset-time documented in the PCR
or the telephone transcript. The median prehospital delay time was 2.2 hours (IQR 1.3-
5.4; range 0.5-73.8), and 11.7% (n=97) of patients arrived in the ED within 1 hour of
symptom onset. Patients with a non-numeric symptom onset-time (n= 174, 17.3%) were
older (74.3 vs.70.1 years, p<0.001), less likely to present with chest pain (55.2%
vs.77.6%, p<001) and more likely to be women (44.3% vs.35.0%, p=0.02) than those
with numeric onset-times.
106
Figure 12: Study Flow Diagram
EDIS = Emergency Department Information System; MI = myocardial infarction; PCR = patient care record; SJA-WA = St John Ambulance-Western Australia.
As shown in Table 22, patients with longer delay times were more likely to be older,
female, have had a fall, have a symptom onset-time between 1200-1759 hours, be at a
primary HCP or a nursing home, and if the patient was at home and the person who
called the ambulance was anyone other than the spouse. Patients with shorter delay
times were more likely to present with symptoms of chest pain, diaphoresis, and nausea.
EDIS confirmed discharge diagnosis of MI (Jan 1, 2008 to Oct 31, 2009)
n = 3,329
Arrived by ambulance
n = 2,100 Excluded, n = 419
• Transferred to a second hospital, included at first hospital (n = 32)
• Missing (No PCR, n = 28) • No emergency telephone call (n = 198) • ED nurse call. Patient used own transport to first
hospital and then transferred to second hospital (n = 161)
SJA-WA PCR & emergency telephone call
n = 1,681
Excluded, n = 48 • Not first admission
Index patients n = 1,633
Excluded, n = 630 • No delay time (n = 453) • No PCR due to industrial action (n = 117) • Missing PCR (n = 60)
Delay time n = 1,003
Date time variable for delay time n = 829
Men, n = 539 Women, n = 290
Descriptive words for delay time n = 174
Men, n = 97 Women, n = 77
107
Tabl
e 22
: Cha
ract
eris
tics o
f the
Sam
ple
(n=8
29),
and
Med
ian
Preh
ospi
tal D
elay
Var
iabl
e
n (%
) Pr
ehos
pita
l Del
ay
(Hou
rs)
Med
ian
(IQ
R)
Uni
varia
ble
linea
r reg
ress
ion
Exp(
B) (
95%
CI)
p-v
alue
Age
≥80
year
s
70 to
79
year
s
60 to
69
year
s
<60
year
s G
ende
r (M
ale=
0, F
emal
e=1)
Mal
e
Fem
ale
Pres
entin
g sy
mpt
oms r
epor
ted
(No=
0, Y
es=1
)
Che
st p
ain
Yes
N
o
Left
arm
pai
n
Y
es
No
R
ight
arm
pai
n
Y
es
No
Ja
w, t
hroa
t or n
eck
pain
Y
es
No
D
iaph
ores
is
Yes
N
o
Shor
t of b
reat
h
Y
es
No
257
(31.
0)
194
(23.
4 17
3 (2
0.9)
20
5 (2
4.7)
53
9 (6
5.0)
29
0 (3
5.0)
64
3 (7
7.6)
18
6 (2
2.4)
10
3 (1
2.4)
72
6 (8
7.6)
10
3 (1
2.4)
72
6 (8
7.6)
40
(4.8
) 78
9 (9
5.2)
11
4 (1
3.8)
71
5 (8
6.2)
38
7 (4
6.7)
44
2 (5
3.3)
3.0
(1.6
, 6.6
) 2.
4 (1
.4, 5
.4)
1.9
(1.2
, 4.5
) 1.
8 (1
.1, 3
.8)
2.0
(1.3
, 4.9
) 2.
6 (1
.5, 6
.0)
2.1
(1.3
, 4.8
) 2.
7 (1
.4, 7
.5)
1.9
(1.3
, 4.3
) 2.
2 (1
.3, 5
.6)
2.4
(1.4
, 6.3
) 2.
2 (1
.3, 5
.4)
2.0
(1.2
, 7.0
) 2.
2 (1
.3, 5
.4)
1.6
(1.2
, 2.8
) 2.
4 (1
.4, 5
.9)
2.1
(1.3
, 5.5
) 2.
2 (1
.3, 5
.4)
1.47
1.
23
1.09
1.
00
1.15
0.
80
0.89
1.
10
0.98
0.
63
1.02
(1.2
4, 1
.74)
(1
.03,
1.4
7)
(0.9
0, 1
.31)
(1
.00,
1.3
1)
(0.6
8, 0
.92)
(0
.74,
1.0
8)
(0.9
0, 1
.33)
(0
.73,
1.3
2)
(0.5
3, 0
.76)
0.
90-1
.16
<0.0
01
<0.0
01
0.02
0.
37
0.04
0.
003
0.25
0.
35
0.89
<0
.001
0.
79
108
Var
iabl
e
n (%
) Pr
ehos
pita
l Del
ay
(Hou
rs)
Med
ian
(IQ
R)
Uni
varia
ble
linea
r reg
ress
ion
Exp(
B) (
95%
CI)
p-v
alue
Abd
omin
al o
r epi
gast
ric p
ain
Yes
N
o N
ause
a
Y
es
No
V
omiti
ng
Yes
N
o Sy
ncop
e, c
olla
pse
or u
ncon
scio
us
Yes
N
o
Diz
zine
ss
Yes
N
o
Wea
knes
s
Y
es
No
Fa
tigue
Y
es
No
B
ack
pain
Y
es
No
Fa
ll
Y
es
No
Day
of t
he w
eek
(Wee
kday
=0, W
eeke
nd=1
)
Wee
kday
Wee
kend
18 (2
.2)
811
(97.
8)
280
(33.
8)
549
(66.
2)
108
(13.
0)
721
(87.
0)
28 (3
.4)
801
(96.
6)
77 (9
.3)
752
(90.
7)
27 (3
.3)
802
(96.
7)
27 (3
.3)
802
(96.
7)
92 (1
1.1)
73
7 (8
8.9)
15
(1.8
) 81
4 (9
8.2)
60
0 (7
2.4)
22
9 (2
7.6)
2.7
(1.4
, 5.2
) 2.
2 (1
.3, 5
.4)
2.1
(1.3
, 4.1
) 2.
3 (1
.3, 5
.9)
2.1
(1.4
, 4.6
) 2.
2 (1
.3, 5
.5)
2.9
(1.5
, 4.6
) 2.
2 (1
.3, 5
.4)
1.9
(1.4
, 4.4
) 2.
2 (1
.3, 5
.4)
2.6
(1.6
, 10.
0)
2.2
(1.3
, 5.4
) 3.
8 (1
.6, 6
.4)
2.2
(1.3
, 5.4
) 2.
2 (1
.4, 6
.5)
2.2
(1.3
, 5.4
) 4.
6 (2
.1, 1
0.0)
2.
2 (1
.3, 5
.4)
2.2
(1.3
, 5.5
) 2.
1 (1
.4, 5
.3)
1.05
0.
86
0.91
1.
24
0.88
1.
38
1.23
1.
12
1.64
1.
01
0.68
-1.6
2 (0
.75,
0.9
8)
(0.7
6, 1
.10)
(0
.87,
1.7
6)
(0.7
1, 1
.10)
(0
.97,
1.9
7)
(0.8
6, 1
.76)
(0
.92,
1.3
8)
(1.0
2, 2
.64)
(0
.87,
1.1
6)
0.83
0.
03
0.34
0.
23
0.27
0.
08
0.26
0.
25
0.04
0.
92
109
Var
iabl
e
n (%
) Pr
ehos
pita
l Del
ay
(Hou
rs)
Med
ian
(IQ
R)
Uni
varia
ble
linea
r reg
ress
ion
Exp(
B) (
95%
CI)
p-v
alue
Tim
e of
Day
0600
-115
9
1200
-175
9
1800
-235
9
0000
-055
9
Loca
tion
of p
atie
nt ±
who
cal
led
the
ambu
lanc
e
Hom
e &
spou
se c
alle
d
Hom
e &
Fam
ily/fr
iend
/nei
ghbo
r/wor
k co
lleag
ue c
alle
d
Hom
e &
a p
rofe
ssio
nal c
alle
d
Hom
e &
the
patie
nt c
alle
d
Hom
e &
not
sure
who
cal
led
Fam
ily/fr
iend
/nei
ghbo
r/or w
ork
plac
e
Prim
ary
HC
P
Nur
sing
hom
e
O
ther
loca
tion
277
(33.
4)
192
(23.
2)
189
(22.
8)
171
(20.
6)
200
(24.
1)
171
(20.
6)
98 (1
1.8)
10
3 (1
2.4)
37
(4.5
) 30
(3.6
) 80
(9.7
) 58
(7.0
) 52
(6.3
)
2.4
(1.4
, 5.6
) 2.
4 (1
.3, 8
.1)
1.9
(1.2
, 4.7
) 2.
2 (1
.2, 4
.2)
1.7
(1.1
, 3.5
) 2.
6 (1
.4, 5
.7)
3.0
(1.6
, 7.0
) 2.
2 (1
.3, 5
.2)
2.6
(1.4
, 6.6
) 1.
3 (1
.0, 1
.9)
5.1
(2.4
, 11.
6)
2.7
(1.5
,5.1
) 1.
3 (1
.0, 2
.8)
1.18
1.
29
1.06
1.
00
1.25
1.
77
2.14
1.
54
1.77
1.
21
3.16
1.
77
1.00
(0.9
9, 1
.41)
(1
.07,
1.5
6)
(0.8
7, 1
.28)
(0
.95,
1.6
4)
(1.3
5, 2
.34)
(1
.59,
2.8
8)
(1.1
5, 2
.07)
(1
.22,
2.5
7)
(0.8
1, 1
.81)
(2
.32,
4.3
0)
(1.2
7, 2
.47)
0.04
0.06
0.
009
0.56
<0
.001
0.11
<0.0
01
<0.0
01
0.00
4 0.
003
0.35
<0
.001
0.
001
110
7.5.2 Multivariable Analysis
Results of the multivariable linear regression analysis are presented in Table 23. Delay
times were 17% (95% CI, 4-28%) shorter if presenting with chest pain and 28% (95%
CI, 15-40%) shorter if presenting with diaphoresis. Delay times compared with being
<60 years, were 38% (95% CI, 16-64%) longer if ≥80 years, and 20% (95% CI, 1-43%)
longer if 70-79 years. Delay times compared with being at some other location, were
195% (95% CI, 119-299%) longer if with a primary HCP, and if the patient was at
home, delay times were 91% (95% CI, 42-156%) longer if a professional called the
ambulance, 54% (95% CI, 7-121%) longer if not sure who called, 51% (95% CI, 15-
99%) longer if the person who called was a family, friend, neighbour or work colleague,
and 42% (95% CI, 6-89%) longer if the patient called the ambulance.
Table 23: Multivariable Linear Regression Log Delay Time in Minutes
Variables Multivariable linear regression Exp(B) 95% CI p-value
Age (Years) ≥80 years 70 to 79 years 60 to 69 years <60 years
1.38 1.20 1.05 1.00
(1.16, 1.64) (1.01, 1.43) (0.88, 1.25)
0.001
<0.001 0.04 0.57
Presenting symptoms reported (No=0, Yes=1) Chest pain Right arm pain Diaphoresis
0.83 1.20 0.72
(0.72, 0.96) (1.00, 1.44) (0.60, 0.85)
0.01 0.05 <0.001
Location of patient ± who called the ambulance Home & spouse called Home & Family/friend/neighbor/work colleague called Home & a professional called Home & the patient called Home & not sure who called Family/friend/neighbor/or work place Primary HCP Nursing home Other location
1.20 1.51 1.91 1.42 1.54 1.22 2.95 1.38 1.00
(0.93, 1.57) (1.15, 1.99) (1.42, 2.56) (1.06, 1.89) (1.07, 2.21) (0.82, 1.79) (2.19, 3.99) (0.98, 1.93)
<0.001 0.17 0.003 <0.001 0.02 0.02 0.32 <0.001 0.06
Of patients with non-numeric prehospital delay times, most (n=65, 37%) delayed
between 1 to 3 days from symptom onset (see Table 24), and 110 (64%) had
documented statements of ‘intermittent’ (n=97) and/or ‘gradual onset’ (n=77) of
symptoms over a period of time. Descriptions of symptom onset-times included “pain
started after lunch”, “has had chest pain all day”, “3-day history of fatigue and malaise”,
“has had pain in jaw intermittently for a few days”, “complaining of left shoulder pain
111
and left arm pain for past 6-days”, and “experiencing chest pain 3 to 4 times per week
for the past 2 months.”
Table 24: Categorised Time Intervals from Non-Numeric Symptom Onset-Times and
Relationship with Intermittent or Gradual Onset of Symptoms (yes/no)
7.6 Discussion
Prehospital time is the most important component of total delay for MI patients, and
delay to definitive treatment is associated with increased mortality and morbidity.11,12
Median prehospital delay in our study was 2.2 hours which is comparable to other
international studies.107,188 Only 11.7% (n=97) of patients arrived in the ED within the
accepted window of 1 hour needed for the greatest benefit to be gained from reperfusion
therapy.11
Our findings were similar to other studies in that older age107,169 was associated with
increased prehospital delay. Patients ≥80 years delayed a median of 1.2 hours longer
than patients <60 years. Several studies have suggested this may be because older
patients report atypical symptoms compared with younger patients.107 Symptom
presentation was also important. Similar to other studies, decreased delay was
associated with patients presenting with diaphoresis80,187,200 and chest pain.169,199-201
Twenty per cent of patients did not have a documented numeric onset-time and had
words describing their onset-time. Of these patients, almost two thirds had documented
‘intermittent’ and/or ‘gradual onset’ of symptoms. Two other studies198,202 have reported
the intermittent and gradual nature of symptom onset as an important factor associated
with delay. This is a key finding as the pain from myocardial ischaemia can come and
go, and can be temporarily relieved by rest and vasodilators. These data reinforce the
importance of symptom presentation in relation to delay in seeking medical treatment.
Category Intermittent or gradual onset
of symptoms n (%) Total Yes No
≤1 hour 0 (0.0) 5 (100.0) 5 >1 hour to 6 hours 3 (33.3) 6 (66.7) 9 >6 hours to 1 day 30 (52.6) 26 (45.6) 57 >1 day to 3 days 48 (73.8) 17 (26.2) 65 >3 days to 1 week 15 (75.0) 5 (25.0) 20 >1 week to 2 months 14 (87.5) 2 (12.5) 16 Missing 2 Total 174
112
Symptom identification alone may not be sufficient to motivate a patient to seek
medical attention. We found the role of family members, friends, and co-workers in
assisting the patient to make the decision to call the ambulance important. In this study,
if the patient was at home and if the person who called was anyone other than the
spouse, there was an increased delay. We also found that if a ‘professional’ initiated the
phone call from the patient’s home there was an increased delay. A ‘professional’ in this
study included a health monitoring company, a locum doctor, security personnel at a
low care facility, or Health Direct. Health Direct is a government funded, free 24 hour,
7 day a week, health advice line answered by registered nurses. All of these
‘professionals’ relied on the patient to contact them in the first instance. We cannot
assume the patients were alone at symptom onset, however, many studies107,199 have
found that patients who were alone at time of symptom onset were more likely to delay
seeking medical treatment. Also similar to previous studies, consulting a primary
HCP80,198 was associated with increased delay. The median delay for these patients was
5.1 hours.
It is of concern that only 63.1% (n=2100) of patients arrived by ambulance in this study.
The risk of sudden cardiac death within the first hour of symptoms is much increased.197
Paramedics are trained and equipped to recognise and treat life-threatening cardiac
arrhythmias should they occur and the ambulance is usually the quickest mode of
transport to hospital.
7.7 Strengths and Limitations
This study has several strengths, including its population-based design that captured all
public ED MI discharge diagnoses in Perth’s metropolitan area over a 22-month period.
However, several limitations need to be considered. Information about prehospital delay
was abstracted from the paramedic’s PCR or the emergency telephone call transcript.
We do not know if the delay time was the same for patients who did not arrive by
ambulance, but calling the ambulance is known to be associated with a shorter delay
time.169,192 Over a third of patients had missing data on delay time. Although rates of
missing delay time in this study did not differ from another study,107 the rates differed
by age, sex, and whether or not the patient presented with chest pain; therefore our
findings should be interpreted with caution. Nonetheless there were 1003 patients for
whom we had onset-time in this study. One of the challenges in conducting a
113
retrospective cohort study is the reliance on the accuracy of reported symptom presence
and onset-time. Paramedic and medical record documentation of symptom presence and
onset-time has been reported in a prior study.3 In brief, agreement between the two
records for symptom presence was excellent, and symptom onset-time agreed exactly
for 60% of the records and times were within 30 minutes for over 80% of the records.
While we adjusted for a number of demographics, symptom presentation, location, and
time factors, we did not have information on other factors that may have influenced
delay, such as patient comorbidity, psychosocial, cognitive, and situational factors.
7.8 Recommendations for Future Study
Although rapid treatment after symptom onset of MI is associated with better outcomes,
most patients did not reach the hospital within the optimal time frame. Future research
needs to incorporate patient interviews into research designs that will assist in
understanding how individuals interpret their symptoms, and how they make the
decision to seek medical attention.
Our findings suggest that future interventions should not only target education in high-
risk populations, but also older adults, and patients who present without chest pain.
Many of the patients were with someone at symptom onset; therefore, including family
members, friends and co-workers in education programmes is crucial. Education must
include not only common symptoms of MI, but the atypical, intermittent, and
progressive nature of some symptoms, and it is essential to emphasize the urgency of
immediate emergency transport by ambulance. Information should be disseminated
face-to-face at patients’ bedsides, as written information on ward corridor walls, and on
electronic screens in outpatient areas. Public education media campaigns in the
community should include articles in the newspaper, on the radio, and television
programmes.
Another aspect that requires further investigation is the role of the primary HCP. The
primary HCP called the ambulance for 10% (n=166) of the patients in our cohort.
Further research is required to investigate how the primary HCP establishes their office
routines to care for patients with suspected MI. It would be valuable to know the
incidence of calls to primary HCPs involving symptoms suggestive of MI, and the
114
patient characteristics of those who did not require ED evaluation and treatment and
were successfully managed by their primary HCP.
7.9 Conclusions
This population-based study found the delay to hospital after symptom onset exceeded
the recommended one hour.11 Shorter delay was associated with presenting with the
symptoms of chest pain and diaphoresis, and longer delay was associated with older
age, calling a primary HCP, and the patient’s relationship with the person who called
the ambulance. Given that delay times continue to be prolonged, public awareness of
MI symptoms and the need to seek help early should be enhanced, in order to decrease
prehospital delay and improve MI survival.
115
Chapter 8: Discussion
8.1 Introduction
This doctoral research comprised a systematic review and meta-analysis, and analyses
that used linked data, to answer research questions pertaining to symptom presentation
in MI, ambulance times, survival, and prehospital delay. In this chapter the major results
are summarised and compared with the results of other studies published after the
manuscripts in Chapters 2, 4, 5, 6 and 7 were published. This chapter also describes the
strengths and limitations of the research, with reference to its implications and
recommendations for policy, practice, and future research.
Since the manuscripts in this thesis were accepted for publication there have been
further studies published on sex differences in symptom presentation of MI, and
ambulance times. No recent studies were found that related to the paramedic patient
care record (PCR) and the hospital medical record concordance of symptoms of MI,
survival differences between patients presenting with and without chest pain; or studies
that report the patient characteristics and presenting symptoms which contribute to
prehospital delay.
8.2 Overview of Major Findings
The research questions posed in Chapter 1, Section 1.4 are repeated here with the
answers suggested by the statistical analyses of the data available for this PhD research
and the published literature to date.
1. Do men and women equally present with chest pain as a symptom of
MI and are there sex differences in other presenting symptoms of MI?
The study described in “Sex differences in symptom presentation in acute myocardial
infarction: a systematic review and meta-analysis” (Chapter 2) found that women with
MI had lower odds and a lower rate of presenting with chest pain than men. Women
were significantly more likely to present with fatigue, neck pain, syncope, nausea, right
arm pain, dizziness, and jaw pain.
116
Three studies203-205 that investigated sex differences in symptom presentation of MI and
one meta-analysis206 have been published after completion of the literature search (in
October 2009) for the manuscript in Chapter 2. Two of these studies203,204 found that
women were less likely than men to present with chest pain, supporting the results of
this thesis. The other study205 which found no sex differences for the symptom of chest
pain only included patients aged 25 to 74 years. But as reported in “Myocardial
infarction: sex differences in symptoms reported to emergency dispatch” (Chapter 4)2
the mean age of women who had a MI was 77.6 years compared with 69.1 years for
men, so the upper limit of 74 years in the Kirchberger205 study may have excluded some
women who had a MI.
With regard to other symptoms of MI, one study205 had similar findings in that women
were more likely than men to experience nausea, jaw pain, and dizziness; and the other
study203 found women were more likely to experience neck pain. In addition to these
symptoms, the “Sex differences in symptom presentation in acute myocardial infarction:
a systematic review and meta-analysis” (Chapter 2) found women were more likely than
men to experience left arm pain, vomiting, dyspnoea, and back pain. However, the
manuscript in Chapter 2 reported moderate to substantial heterogeneity for these
additional symptoms and suggested it may be misleading to report a combined summary
measure. One study205 had similar findings in that women were more likely than men to
experience left arm pain, vomiting, dyspnoea, and two studies203,205 found women were
more likely than men to experience back pain.
The meta-analysis206 had similar findings to those reported in Chapter 2, but reported
effect sizes (standardised risk differences) rather than odds and rate ratios. Although
men were more likely than women to report chest pain and diaphoresis; the effect size
for each symptom was small. In order of decreasing effect size, women were
significantly more likely than men to report loss of appetite, back pain, palpitations,
nausea and vomiting, neck pain, jaw pain, fatigue, dyspnoea, dizziness, and right arm
pain.
2. Are the symptoms, in particular chest pain, reported during the
emergency telephone call to SJA-WA, and ambulance response times,
the same for men and women with MI?
117
The study described in “Myocardial infarction: sex differences in symptoms reported to
emergency dispatch” (Chapter 4) found that women were less likely than men to report
chest pain and were more likely to present with vomiting. It also found that ambulance
response times did not differ between men and women with chest pain. However,
women with chest pain were less likely than men with chest pain to be allocated a
priority 1 (lights and sirens) ambulance response.
Two studies that examined symptom presentation to emergency dispatch207 and
ambulance times207,208 have been published recently. One study207 found men and
women were similar with regard to presenting symptoms when they called emergency
dispatch. A possible reason for this differing from the results in “Myocardial infarction:
sex differences in symptoms reported to emergency dispatch” (Chapter 4) is that this
study only included patients with a STEMI, and patients who have a STEMI are more
likely to present with chest pain.
Irrespective of presenting with similar symptoms, Melberg 207 also found women with
STEMI were given a lower priority ambulance response. They concluded emergency
dispatch may have difficulty in reaching action decisions with women and, as men and
women presented similarly, there was a possibility of gender-specific bias in ambulance
priority response. Another study208 reviewed ambulance times in a cohort of patients
who had a prehospital electrocardiogram and presented with chest pain. They found a
significant difference of 2 to 4 minutes between men and women with regard to
ambulance scene time and total scene to hospital time. Additionally, they stated that in
the case of women with STEMI this could translate into a possible increase of 0.25% to
1.6% in mortality.
3. Are paramedic records a reliable source of information about
presenting symptoms of MI and onset-time of symptoms compared
with the documentation in the hospital medical record?
The study described in “Symptoms of myocardial infarction: concordance between
paramedic and hospital records” (Chapter 5) demonstrated that documentation of the
common symptoms of MI and symptom-onset time were similar between the paramedic
and hospital records. This phase of the study was important as it validated the accuracy
of the paramedic documentation which was used to answer the final research questions.
This study justified the use of paramedic PCRs as a source of data for research in
118
prehospital MI and patient delay. No further studies have been found post acceptance of
the Chapter 5 manuscript.
4. Are patient characteristics and patient outcomes (survival and
hospital discharge diagnosis) of patients presenting with and without
chest pain the same?
The study described in “Characteristics and outcomes of MI patients with and without
chest pain: a cohort study” (Chapter 6) found that characteristics differed between
patients with and without chest pain. The odds of presenting without chest pain were
increased for patients who were over 70 years of age and for women. However,
presenting with the symptom of chest pain was not associated with survival. Since this
manuscript has been published no further studies of MI patient characteristics and
outcomes of patients presenting with and without chest pain have been found.
5. What is the prehospital delay time for MI patients transported by
ambulance, and what are the patient characteristics and presenting
symptoms which contribute to prehospital delay?
The study described in “The effect of presenting symptoms and patient characteristics
on prehospital delay in MI patients presenting to emergency department by ambulance:
a cohort study” (Chapter 7) found that median delay was 2.2 hours and decreased delay
was associated with age <70 years, presenting with chest pain, and diaphoresis.
Increased delay was associated with being with a primary health care provider, if the
patient was at home, and if the person who called the ambulance was anyone other than
their spouse. Many patients described their symptoms as intermittent and/or of gradual
onset. Since this manuscript has been published no further studies of MI patient
characteristics and presenting symptoms which contribute to prehospital delay have
been found.
8.3 Strengths of the Study
The strengths of the systematic review (Chapter 2) are that the application of an updated
search strategy enabled all additional studies up to September 2009 to be considered for
inclusion, study inclusion criteria were precise, and a quality assessment of each study
119
was conducted. This review was the first to conduct meta-analyses of sex differences in
chest pain and other symptoms of MI and quantify the differences in MI presentation
between men and women.
The strength of the retrospective cohort studies, presented in Chapters 4, 5, 6 and 7, are
that they analysed data from a population-based cohort of patients with ED-confirmed
MI, drawn from all public hospitals EDs in the Perth metropolitan area over a 22-month
period. Furthermore, SJA-WA covers the largest area of any single ambulance service
in the world and is the single provider of emergency road ambulance for WA. SJA-WA
data are ideal for epidemiological research for a number of reasons: almost three
quarters of WA’s population resides in Perth; the state’s population is relatively stable;
and there is an absence of border drift with adjoining state ambulance services due to
the natural barrier afforded by inland Australia.
To our knowledge, Chapter 4 is the first study to analyse symptoms of MI reported
during the emergency phone call for ED confirmed MI patients, and Chapter 5 is the
first study to analyse the concordance between documentation of symptoms of MI
between the paramedic and hospital records.
A further strength of this thesis present the use of three different data sources for the
same patient cohort. These independent sources are the transcribed emergency
telephone call (Chapter 4), the documentation from the paramedic PCR (Chapter 5 & 7),
and the documentation from the hospital medical record (Chapter 5 & 6). As the three
sources all showed women and older age were associated with presenting without chest
pain, we are confident that the findings are sound.
8.4 Limitations of the Study
Several limitations need to be acknowledged when considering the results presented in
this thesis. The systematic review and meta-analyses (Chapter 2) were conducted by one
investigator (the candidate, LC), who reviewed the literature, and extracted and
analysed the data. However, the search strategy, inclusion / exclusion criteria, data to be
extracted, and analyses were based on consensus among all three authors, and any
uncertainties were resolved through discussion. Other potential limitations of the
systematic review include reporting bias,209 in that the data were abstracted from the
120
medical records, which may have led to under-reporting of patients’ presenting
symptoms; and recall bias209 in data from the studies that used questionnaires and
interviews to collect symptoms of MI.
A limitation of the retrospective cohort studies (Chapters 4 to 7) is that they only
included patients with an ED-confirmed diagnosis of MI and the patient may not have
had a hospital discharge diagnosis of MI. In the study that compared characteristics and
outcomes for patients who presented with and without chest pain (Chapter 6), 27% of
the patients with an ED discharge diagnosis of MI did not have a hospital discharge
diagnosis of MI. Although, this discrepancy could not be ascertained for the cohorts in
Chapter 4, 5, and 7, we would assume similar results. In addition, the cohorts only
included patients who arrived by ambulance, and comprised 63% of the patients with an
ED-confirmed diagnosis of MI. When reviewing the results of this study, it must be
considered that patients who did not arrive by ambulance may present with a different
symptom profile.
One of the challenges of conducting a retrospective cohort study of MI symptoms
(Chapters 5, 6, and 7) is the reliance on the accuracy of the documented symptoms.
Some of the patient’s presenting symptoms of MI may not have been considered
relevant and, consequently, they were not documented by paramedics or medical staff.
It is also important to highlight that ambulance dispatch officers do not attempt to elicit
the full range of symptoms experienced by the patient. Once chest pain is mentioned,
the need for a priority 1 response is established, and any further questioning about
symptoms is unlikely.
The data for the manuscripts in Chapter 5 and 6 were collected at a single hospital,
which may limit the generalizability of the results. However, there is no reason to
suspect that hospital medical documentation of symptoms of MI would differ in other
similar tertiary-level metropolitan hospitals. The sample size for the manuscript in
Chapter 5 was small, thus the lack of significant differences in some patient
characteristics (e.g. diabetes and hypertension) may have been due to insufficient
statistical power.
121
8.5 Implications of Thesis Findings
8.5.1 Implications for Public Health
Overall duration of prehospital delay has remained relatively unchanged over the last
two decades,107,169,188,210 and public educational campaigns185,197 and targeted education
and counselling141,197 have had little success in reducing prehospital delay. This doctoral
thesis supports both men and women, and older patients may present atypically or
without chest pain. Implications for policy include health campaigns that educate the
public that the spectrum of symptoms of MI is wide. A snippet of some of the findings
from this thesis will be reported in the Edith Cowan University magazine Cohesion (see
Appendix P). This story discusses some of the major findings: the key message for the
public is that both men and women, and older patients may not experience chest pain as
a symptom of a heart attack. If they do experience symptoms of heart attack they should
call an ambulance immediately.
To educate the public a multi-media approach should be adopted that includes
advertising in magazines, newspapers, and in radio and television programmes.
Information should be disseminated face-to-face at patients’ bedsides, as written
information on ward corridor walls, and on electronic screens in outpatient areas. Social
media and social network sites are evolving and should be utilised to educate the public
about the symptoms of MI. An example of a web page is Her Heart211 produced by
Professor Linda Worral-Carter and this web page discusses heart disease in women,
including, signs and symptoms of heart attack, know your risk, and how to change your
lifestyle. Web pages, health campaigns and education are particularly important as our
population continues to age, and with women living longer than men, it is likely that
patients without chest pain will make up an increasing proportion of those having a MI.
8.5.2 Implications for Professional Practice
The systematic review and meta-analyses challenge the stereotypical Hollywood
depiction of a MI as a dramatic onset of chest pain and collapse. In addition, the
retrospective cohort studies show that women and older persons are less likely to
experience chest pain as a symptom of their MI (Chapters 2, 4, and 6). Prehospital and
emergency department clinicians need to understand that just because a patient does not
have central sternal crushing chest pain, this does not exclude the possibility of an MI.
122
The education of professionals; including paramedics, General Practitioners, nursing
and medical personnel and those who give health advice and answer emergency
telephone lines; needs to emphasise that MI can occur without chest pain and that there
are other atypical symptoms that should be considered. Education should include the
intermittent and progressive nature of symptoms, and it is essential to emphasize the
urgency of immediate emergency transport to hospital by ambulance.
Another snippet of some of the findings from this thesis has been reported in the
Australian Doctor magazine (see Appendix Q). This story discusses that patients with
MI who initially visit their GP too an average of five hours to reach ED. The also story
also reiterates the importance of going to hospital immediately.
8.6 Areas for Future Research
This thesis has contributed to our knowledge about the symptoms of MI, the emergency
telephone call and ambulance times, characteristics associated with MI with and without
chest pain, and characteristics associated with prehospital delay; however, further
research questions remain. Future research into symptoms of MI presentation should be
prospective to increase reporting accuracy, and it should use a standardised symptom
checklist, as recently recommended by Canto and colleagues.212 A standard symptom
checklist would allow for comparative analyses between published studies and
adjustment for differences in age, sex, race, comorbidity, and type of MI (STEMI /
NSTEMI).
This research found a persistent underuse of the emergency ambulance with only 63%
of patients with an ED discharge diagnosis of MI calling an ambulance. The reasons
why 37% of patients in Perth chose not to call an ambulance warrant further
exploration. Current Australian guidelines213 recommend that if you experience the
warning signs of a heart attack for 10 minutes, if they are severe or get progressively
worse, make an emergency telephone call by dialing triple zero (000) immediately and
ask for an ambulance.
It was found that 80% of patients with an ED discharge diagnosis of MI who called an
ambulance were allocated a priority 1 ambulance response (Chapter 4). Those patients
123
who were allocated a priority 2 or 3 response had longer median time from emergency
call to hospital arrival. The other symptoms of MI (e.g. shortness of breath, collapse,
confusion, nausea etc.) are not specific and can reflect a wide spectrum of conditions
and thus pose challenges to ambulance dispatch officers and triage in the ED. Further
research is required to investigate strategies that better identify patients who do not
present with classic MI symptoms; otherwise, they are unlikely to be allocated to a
high-priority response or ED triage category and will consequently have increased delay
to definitive treatment.
Although rapid treatment after symptom onset of MI is associated with better outcomes,
most patients did not reach the hospital within the optimal time frame of 60 minutes.
Future research needs to incorporate patient interviews into research designs that will
assist in understanding how individuals interpret their symptoms, and how they make
the decision to seek medical attention. Research should not only target high-risk
populations, but also older adults, and patients who present without chest pain.
Additionally, many patients were with someone at symptom onset, therefore including
family members, friends and co-workers in future interventional studies may assist in
decreasing delay times.
Another aspect that requires further investigation is the role of the primary health care
provider. The primary health care provider called the ambulance for 10% (n=166) of the
patients in our cohort. It would be valuable to know the incidence of visits to primary
health care providers that involved patients with symptoms suggestive of MI, and the
patient characteristics of those who did not require ED evaluation and treatment and
were successfully managed by their primary health care provider.
8.7 Conclusion
This doctoral thesis contributes to the evidence about sex differences and symptoms of
MI presentation. The meta-analysis demonstrated women were less likely than men to
present with chest pain as a symptom of MI and women were more likely to present
with fatigue, neck pain, syncope, right arm pain, dizziness, and jaw pain. This is the first
study to quantify the differences in MI presentation between men and women by meta-
analyses. The retrospective cohort studies demonstrated women were also less likely to
present with chest pain in their emergency telephone call to the ambulance service, as
124
were older patients.
This research demonstrated good to excellent concordance in the reporting of the
symptoms of MI between the paramedic and the hospital medical record. These findings
support the use of prehospital paramedic documentation as an acceptable means of
obtaining data for research purposes.
It was also found that the delay to hospital after symptom onset for WA patients
exceeded recommended time frames. Shorter delay was associated with the symptoms
of chest pain and diaphoresis, and longer delay was associated with older age, calling a
primary health care provider, and the patient’s relationship with the person who called
the ambulance.
Given that for MI, the symptom of chest pain differs with age, as well as between men
and women, and prehospital delay times remain longer than recommended, public
awareness of symptoms and health professionals’ education about symptoms should be
enhanced to reduce time from symptom onset to definitive care.
125
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“Every reasonable effort has been made to acknowledge the owners of copyright material. I would be pleased to hear from any copyright owner who has been omitted or incorrectly acknowledged.
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Appendices
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Appendix A: Sex Differences in Symptom Presentation in Acute
Myocardial Infarction: A Systematic Review and Meta-analysis
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Appendices B & C removed due to copyright restrictions.
Coventry, L. L., Bremner, A., Jacobs, I., & Finn, J. (2013). Myocardial infarction: Sex differences in symptoms reported to emergency dispatch. Prehospital Emergency Care, 17(2), 193-202. 10.3109/10903127.2012.722175
Coventry, L. L., Bremner, A., Williams, T., Jacobs, I., & Finn, J. (2014). Symptoms of Myocardial Infarction: Concordance Between Paramedic and Hospital Records. Prehospital Emergency Care, 18(3), 393-401. 10.3109/10903127.2014.891064
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Appendix D: Characteristics and Outcomes of MI Patients with and
without Chest Pain: A Cohort Study
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Appendix E: The Effect of Presenting Symptoms and Patient
Characteristics on Prehospital Delay in MI Patients Presenting
to ED by Ambulance: A Cohort Study
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Appendix F: Abstract for Cardiac Society of Australia and New
Zealand conference titled - Sex Differences in Symptom
Presentation in Acute Myocardial Infarction: A Systematic
Review and Meta-analysis
Abstract 1
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Appendix G: Poster for American Heart Association conference titled -
Sex Differences in Symptoms Reported to Emergency Medical
Dispatch in Acute Myocardial Infarction Patients - Impact on
Pre-hospital Delay
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Appendix H: Abstract for American Heart Association conference
titled - Sex Differences in Symptoms Reported to Emergency
Medical Dispatch in Acute Myocardial Infarction - Impact on
Prehospital Delay
Abstract 2
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Appendix I: Poster for Paramedics Australasia conference titled -
Gender Differences in Emergency ‘000’ Calls and Ambulance
Response for Acute Myocardial Infarction (AMI) Patients
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Appendix J: Abstract for Paramedics Australasia Conference titled –
Gender differences in Emergency ‘000’ Calls and Ambulance
Response for Acute Myocardial Infarction (AMI) Patients
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Appendix K: The University of Western Australia Human Research
Ethics Committee – Ethics Approval
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Appendix L: Sir Charles Gairdner Hospital Human Research Ethics
Committee – Ethics Approval
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Appendix M: Reciprocal The University of Western Australia Ethics
for Sir Charles Gairdner Hospital Study
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Appendix N: Government of Western Australia Department of Health
Human Research Ethics Committee Conditional Approval
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Appendix O: Government of Western Australia Department of Health
Human Research Ethics Committee Final Approval
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Appendix P: Cohesion – Mysteries of the Heart Continue to Confound
our Response
MYSTERIES OF THE HEART CONTINUE TO CONFOUND OUR RESPONSE
The standard Hollywood representation of a heart attack, like many dramatisations of
life-threatening events, over-simplifies what is in reality a complex and variable medical
emergency that is only slowly yielding its secrets to medical researchers.
ECU Research Fellow Linda Coventry, in a series of investigative papers that together
make up her PhD thesis, has explored the events that precede presentation by men and
women at major public hospitals who are subsequently diagnosed as having suffered a
myocardial infarction (MI), or heart attack.
“Some of the research findings in this area are really quite surprising,” she says. “For
example, about a third of the women and a quarter of the men who are diagnosed with
MI, having arrived at hospital in an ambulance, have not experienced any chest pain.
“Typically, the absence of this diagnostic signal is more prevalent among people in the
70 and 80-year age groups, and as the population ages we need to be aware that the
incidence of easily-recognised warning signals may decrease.
“Health and para-medical professionals will be on the lookout for other symptoms, such
as shortness of breath, sweating, or collapse, but education about when an ambulance
needs to be called should be brought to the entire adult population.”
The firm rule about a suspected heart attack is that an ambulance should be called
immediately to take the patient to hospital. This is time-critical: the patient should
arrive at hospital less than 60 minutes after first symptoms of a heart attack, so that he
or she can be admitted, and taken to the catheterisation laboratory for a coronary
angiography within 90 minutes.
“The cohort that I studied had an average delay time of 2.2 hours, and these were
patients who arrived by ambulance,” Linda says. “Many people who feel unwell, but
who don’t have chest pain or the period of chest pain has stopped, may make an
appointment with their GP.
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“Once they get a consultation they are likely to be sent for a blood test, and when the
results show that a heart attack has occurred the doctor will ring them and tell them to
call an ambulance. About 10% of my cohort first went to their GP, and their median
time delay in hospital presentation was 5½ hours.”
Unlike some other studies, Linda’s research did not show any difference in the mortality
rates of those presenting with chest pain, compared with those who did not. “Most of
the big studies show that if you present without chest pain, you are less likely to
survive,” she says.
“The difference in my results was possibly because I had a smaller cohort, or there
could have been other factors at play. I started with 3,030 patients diagnosed with MI,
but my study only investigated the ones who arrived at hospital by ambulance.
“This was 63% of the total group, and that in itself is cause for concern. The remainder
were driven to hospital, took public transport or in some cases took the very dangerous
option of driving themselves.
“Some of the case notes for those who delayed going to hospital make quite worrying
reading. Patients have reported symptoms such as ‘had pain in jaw intermittently for a
few days’, and ‘left shoulder pain and left arm pain for the past six days’, and ‘chest
pain three to four time per week for the past two months’.
“This poses challenges for health care professionals,” Linda says. “We need further
research to investigate strategies to better identify the high risk patients who present
without chest pain.
“We should take account of the fact that as our population ages, a greater proportion of
those who have had an MI may present without chest pain. In an older population you
have more co-morbid diseases, such as diabetes, that may mask the pain associated with
heart attack.
“We should also be aware that if there isn’t a spouse or partner present in the household,
and the decision to call an ambulance is made by someone else such as a neighbour or
non-resident relative, there may be greater delay. This most likely is because the person
delays informing someone of their symptoms.
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“In terms of policy, education campaigns should also take account of the fact that older
people, and particularly older women, are less likely to have chest pain and that there
are other symptoms to look for,” Linda says.
[Do you know the symptoms of a heart attack? The Heart Foundation provides valuable
information at www.heartattackfacts.org.au ]
Written by Brian Wills-Johnson
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Appendix Q: Australian Doctor - GP Visits Delay Heart Attack
Treatment
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