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Risk stratification of emergency department patients with chest pain
CARDIOLOGY/EDITORIAL
Risk Stratification of Emergency Department Patients With Chest Pain: The Need for Standardized Reporting Guidelines Judd E. Hollander, MD From the Department of Emergency Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA.
See related article, p. 59. [Ann Emerg Med. 2004;43:68-70.]
Annually, 14 million ECGs are obtained on patients in US emergency departments (EDs), up to 6 million patients are evaluated for potential acute coronary syndromes, and there are more than 3 million ED visits with a primary diagnosis of acute chest pain. As a result, a high percentage of emergency medicine research is focused on the risk stratification of patients with potential acute coronary syndromes. A MEDLINE search using the terms “myocardial infarction” or “unstable angina” and “risk stratification” identified more than 175 articles in the past 2 years alone. Despite all this research, researchers cannot identify a large group of ED chest pain patients with less than 1% risk for short-term adverse cardiovascular events. There are several possible explanations for the failure to identify a low-risk cohort safe for rapid release from the ED. First, it is theoretically possible that such a low-risk group does not exist. Second, it is possible that the optimal test or combination of tests to identify such patients has not yet been developed. Third, it is possible our research methods are fundamentally flawed. I would like to address this third possibility. Specifically, I propose that the lack of uniform reporting guidelines has impeded our progress in the area of cardiac risk stratification. Different investigators studying the same basic disease process enroll different
0196-0644/$30.00 Copyright © 2004 by the American College of Emergency Physicians. doi:10.1016/mem.2004.405
6 8
patient populations and analyze different outcomes. This makes it difficult to compare the results across studies. The lack of standardized reporting practices might explain why even the most widely accepted risk stratification algorithms have not been incorporated into clinical practice. It might also explain why investigators uninvolved in the original studies have found performance characteristics below those of the original studies. In the original studies, the Goldman risk score had a sensitivity for predicting acute myocardial infarction of 88% to 91% with a specificity of 78% to 92%.1,2 The Acute Cardiac Ischemia Time-Insensitive Predictive Instrument (ACI-TIPI) trial had a sensitivity of 86% to 95% and a specificity of 78% to 92% for prediction of acute coronary syndrome when combined with physician impression.2 When these algorithms were analyzed by different investigators, a Goldman risk score of 7% or greater had a sensitivity of 74% and specificity of 68%; an ACI-TIPI score of 25% or greater had a sensitivity of 62% and specificity of 73%.3,4 The difference in performance characteristics can be explained, in part, by different definitions of the outcome measures. This is illustrated by examining the definition and classification of unstable angina. There are several classification schemes for unstable angina. The Braunwald classification of unstable angina was designed for risk stratification on the basis of history, clinical circumstances, ECG findings, and intensity of treatment.5 The Canadian Cardiovascular Society divides angina into 4 classes.6 Class I represents those patients in whom ordinary physical activity does not cause angina, and Class IV is reserved for those patients who develop anginal symptoms at rest. The Agency for Health Care Policy and Research clinical practice guidelines differentiate unstable angina according to 3 clinical presentations: angina at rest, new-onset angina, or increasing angina.6 These guidelines are of little utility in the ED because they are based on the premise that the patient actually has myocardial ischemia. When patients present to the ED with acute chest pain syndromes, it is often not clear whether the pain is cardiac or noncardiac in origin. The most common definition of unstable angina in research studies is “clinical impression” (the definition
ANNALS OF EMERGENCY MEDICINE
43:1
JANUARY 2004
R I S K S T R A T I F I C A T I O N O F C H E S T P A I N P A T I E N T S Hollander
used in the derivation and validation of the ACI-TIPI trial). A clinical diagnosis of unstable angina can only be made on the basis of history, physical examination, or objective testing. However, only a minority of patients enrolled in chest pain studies receive provocative testing.7 Reliance on history and physical examination alone (in the absence of provocative testing) is contradictory to the available evidence. Studies analyzing the precision of clinical features in evaluating chest pain show them to be quite variable.8-11 Hickan et al12 found that certain features predictive of a low risk of acute myocardial infarction, such as pleuritic, positional, and sharp chest pain have poor interphysician reliability (g=0.27 to 0.44). Likewise, many physical examination findings are not reliable. For example, signs and symptoms of congestive heart failure have poor interrater reliability (S3 gallop, g=0.14 to 0.37; rales, g=0.12 to 0.31; neck vein distention, g=0.31 to 0.51; hepatomegaly, g=0.00 to 0.16; dependent edema, g=0.27 to 0.64).13 Thus, these individual signs and symptoms cannot be used to assign a final diagnosis in a rigorous research study. The variability in clinical assessment and minimal use of objective testing in studies of ED patients with chest pain can easily explain the differing results when risk stratification schemes are evaluated by different investigators in different patient populations with different physicians deciding the final diagnosis. Another area where research methodology can be improved is through better description of the population studied. Some risk stratification studies have reported an incidence of acute myocardial infarction of 15% to 20%, whereas others have found that only 5% of patients were diagnosed with acute myocardial infarction and only 10% had non–acute myocardial infarction acute coronary syndrome. Thus, 85% of patients may have non–acute coronary syndrome causes for their symptoms. It is hard to compare results of different risk stratification schemes in patient populations that differ in the rate of acute myocardial infarction by threefold to fourfold. More complete reporting on the patient population would allow the reader to better define exactly who comprised the study population. A recent examination of 2 years of studies that evaluated ED patients with chest pain using cardiac troponin I found that the majority of important features were reported less than 50% of the time.14 Cardiac risk factor criteria were reported only 32% of the time, chief complaint criteria 18% of the time, and the duration of the follow-up period was only noted 77% of the time. The
JANUARY 2004
43:1
ANNALS OF EMERGENCY MEDICINE
follow-up periods ranged from 3 days to 3 years. Although most studies (86%) used a standardized definition of acute myocardial infarction, few (32%) defined what they considered an acute coronary syndrome or unstable angina. More complete reporting is needed to assess the validity, importance, and applicability of published studies.15 The lack of standardized reporting in these studies makes it difficult to compare patient populations, risk stratification algorithms, and outcomes. As I review the excellent study by Prina et al16 in this issue of Annals, these problems again are evident. I am not sure how I can apply their results to my daily clinical practice. In the study by Prina et al, only 230 (12%) of 1,973 admitted chest pain patients were given a diagnosis of chest pain of undetermined origin. Thus, at least 88% of their study population received an evaluation for cardiac and/or noncardiac causes of chest pain. According to Table 1, only 359 (18%) patients in their cohort had a noncardiac origin of chest pain. In my institution, less than 18% of patients have a cardiac origin of chest pain, fewer than one third receive a stress test or cardiac catheterization, and few receive objective evaluations for noncardiac conditions. To extrapolate the results of their study to my clinical practice, I would need more detailed information. I am not sure which of my patients are analogous to their study population. Prina et al16 used a clinical definition of unstable angina that assumes that the cardiologists can distinguish ischemic chest pain from nonischemic chest pain. Of the study patients with chest pain of undetermined origin, 10 had adverse events, many of whom had underlying coronary artery disease and an abnormal ECG result. Only 3 had nuclear testing for ischemia during hospitalization; 1 had a positive result. Thus, I am not sure that their clinical impression of chest pain of undetermined origin would be the same as mine. I may have considered these patients to have a cardiac etiology of chest pain. These methodologic issues obviously affect the outcome of the study. Until rigid reporting criteria and clearly defined outcomes are developed, results will be subjected to the biases of individual practitioners and investigators at the study institution. Until we agree on standardized definitions of outcomes, we are unlikely to define the optimal treatment or evaluation pathway for these patients. Rather than continuing to identify, study, and evaluate new technologies for risk stratification, we should pause and better refine our research methodology and reporting guidelines. Once rigid outcomes are defined and report-
6 9
R I S K S T R A T I F I C A T I O N O F C H E S T P A I N P A T I E N T S Hollander
ing strategies are agreed on, we can move forward defining optimal methods of treating and evaluating these patients. If we do not develop methodologic and reporting standards, we will continue to be unable to develop successful clinical strategies. The author reports this study did not receive any outside funding or support. Reprints not available from the authors. Address for correspondence: Judd E. Hollander, MD, Department of Emergency Medicine, Hospital of the University of Pennsylvania, Ground Floor, Ravdin Building, 3400 Spruce Street, Philadelphia, PA 19104-4283; 215-662-2767, fax 215-662-3953; E-mail jholland@mail. med.upenn.edu.
REFERENCES 1. Lee TH, Juarez G, Cook EF, et al. Ruling out myocardial infarction. A prospective multicenter validation of a 12-hour strategy for patients at low risk. N Engl J Med. 1991;324:1239-1246. 2. Lau J, Ioannidis JPA, Balk EM, et al. Diagnosing acute cardiac ischemia in the emergency department: a systematic review of the accuracy and clinical effect of current technologies. Ann Emerg Med. 2001;37:453-460. 3. Baxt WG, Shofer FS, Sites FD, et al. A neural computational aid to the diagnosis of acute myocardial infarction. Ann Emerg Med. 2002;39:366-373. 4. Baxt WG. Neural computational aid to the diagnosis of acute myocardial infarction. Presented at: Society of Academic Emergency Medicine annual meeting; May 2001; Atlanta, GA. 5. Braunwald E. Unstable angina. A classification. Circulation. 1989;80:410-4. 6. Braunwald E, Mark DB, Jones RH, et al. Unstable angina: diagnosis and management. Clinical Practice Guideline Number 10 (amended) AHCPR Publication No. 94-0602. Rockville, MD: Agency for Health Care Policy and Research and the National Health, Lung and Blood Institute, Public Health Service, Department of Health and Human Services; 1994. 7. Chan GW, Sites FD, Shofer FS, et al. Impact of stress testing on 30-day cardiovascular outcomes for low-risk chest pain patients admitted to floor telemetry beds. Am J Emerg Med. 2003;21:282-287. 8. Zucker DR, Griffith JL, Beshansky JR, et al. Presentations of acute myocardial infarction in men and women. J Gen Intern Med. 1997;12:79-87. 9. Jayes RL, Beshansky JR, D’Agostino RB, et al. Do patients’ coronary risk factor reports predict acute cardiac ischemia in the emergency department? A multicenter study. J Clin Epidemiol. 1992;45:621-626. 10. Rouan GW, Lee TH, Cook EF, et al. Clinical characteristics and outcome of acute myocardial infarction in patients with initially normal or nonspecific electrocardiograms. Am J Cardiol. 1989;64:1087-1092. 11. Pope JH, Aufderheide TP, Ruthazer R, et al. Missed diagnosis of acute cardiac ischemia in the emergency department. N Engl J Med. 2000;342:1163-1170. 12. Hickan DH, Sox HC, Sox CH. Systematic bias in recording history in patients with chest pain. J Chronic Dis. 1985;38:91-100. 13. Gadsboll N, Hoiland-Carlsen PF, Nielsen GG, et al. Symptoms and signs of heart failure in patients with myocardial infarction: reproducibility and relationship to chest x-ray, radionuclide ventriculography and right heart catheterization. Eur Heart J. 1989;10:1017-1028. 14. Glavan B, Shewakramani S, Hollander JE. Incomplete data reporting in studies of ED patients with potential acute coronary syndromes utilizing troponins. Acad Emerg Med. 2003;10:943-948. 15. Harden RD. Critical appraisal of papers describing triage systems. Acad Emerg Med. 1999;6:1166-1171. 16. Prina LD, Decker WW, Weaver AL, et al. Outcome of patients with a final diagnosis of chest pain of undetermined origin admitted under the suspicion of acute coronary syndrome: a report from the Rochester Epidemiology Project. Ann Emerg Med. 2003;43:59-67.
7 0
ANNALS OF EMERGENCY MEDICINE
43:1
JANUARY 2004
Risk Stratification of Emergency Department Patients With Chest Pain: The Need for Standardized Reporting Guidelines Judd E. Hollander, MD From the Department of Emergency Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA.
See related article, p. 59. [Ann Emerg Med. 2004;43:68-70.]
Annually, 14 million ECGs are obtained on patients in US emergency departments (EDs), up to 6 million patients are evaluated for potential acute coronary syndromes, and there are more than 3 million ED visits with a primary diagnosis of acute chest pain. As a result, a high percentage of emergency medicine research is focused on the risk stratification of patients with potential acute coronary syndromes. A MEDLINE search using the terms “myocardial infarction” or “unstable angina” and “risk stratification” identified more than 175 articles in the past 2 years alone. Despite all this research, researchers cannot identify a large group of ED chest pain patients with less than 1% risk for short-term adverse cardiovascular events. There are several possible explanations for the failure to identify a low-risk cohort safe for rapid release from the ED. First, it is theoretically possible that such a low-risk group does not exist. Second, it is possible that the optimal test or combination of tests to identify such patients has not yet been developed. Third, it is possible our research methods are fundamentally flawed. I would like to address this third possibility. Specifically, I propose that the lack of uniform reporting guidelines has impeded our progress in the area of cardiac risk stratification. Different investigators studying the same basic disease process enroll different
0196-0644/$30.00 Copyright © 2004 by the American College of Emergency Physicians. doi:10.1016/mem.2004.405
6 8
patient populations and analyze different outcomes. This makes it difficult to compare the results across studies. The lack of standardized reporting practices might explain why even the most widely accepted risk stratification algorithms have not been incorporated into clinical practice. It might also explain why investigators uninvolved in the original studies have found performance characteristics below those of the original studies. In the original studies, the Goldman risk score had a sensitivity for predicting acute myocardial infarction of 88% to 91% with a specificity of 78% to 92%.1,2 The Acute Cardiac Ischemia Time-Insensitive Predictive Instrument (ACI-TIPI) trial had a sensitivity of 86% to 95% and a specificity of 78% to 92% for prediction of acute coronary syndrome when combined with physician impression.2 When these algorithms were analyzed by different investigators, a Goldman risk score of 7% or greater had a sensitivity of 74% and specificity of 68%; an ACI-TIPI score of 25% or greater had a sensitivity of 62% and specificity of 73%.3,4 The difference in performance characteristics can be explained, in part, by different definitions of the outcome measures. This is illustrated by examining the definition and classification of unstable angina. There are several classification schemes for unstable angina. The Braunwald classification of unstable angina was designed for risk stratification on the basis of history, clinical circumstances, ECG findings, and intensity of treatment.5 The Canadian Cardiovascular Society divides angina into 4 classes.6 Class I represents those patients in whom ordinary physical activity does not cause angina, and Class IV is reserved for those patients who develop anginal symptoms at rest. The Agency for Health Care Policy and Research clinical practice guidelines differentiate unstable angina according to 3 clinical presentations: angina at rest, new-onset angina, or increasing angina.6 These guidelines are of little utility in the ED because they are based on the premise that the patient actually has myocardial ischemia. When patients present to the ED with acute chest pain syndromes, it is often not clear whether the pain is cardiac or noncardiac in origin. The most common definition of unstable angina in research studies is “clinical impression” (the definition
ANNALS OF EMERGENCY MEDICINE
43:1
JANUARY 2004
R I S K S T R A T I F I C A T I O N O F C H E S T P A I N P A T I E N T S Hollander
used in the derivation and validation of the ACI-TIPI trial). A clinical diagnosis of unstable angina can only be made on the basis of history, physical examination, or objective testing. However, only a minority of patients enrolled in chest pain studies receive provocative testing.7 Reliance on history and physical examination alone (in the absence of provocative testing) is contradictory to the available evidence. Studies analyzing the precision of clinical features in evaluating chest pain show them to be quite variable.8-11 Hickan et al12 found that certain features predictive of a low risk of acute myocardial infarction, such as pleuritic, positional, and sharp chest pain have poor interphysician reliability (g=0.27 to 0.44). Likewise, many physical examination findings are not reliable. For example, signs and symptoms of congestive heart failure have poor interrater reliability (S3 gallop, g=0.14 to 0.37; rales, g=0.12 to 0.31; neck vein distention, g=0.31 to 0.51; hepatomegaly, g=0.00 to 0.16; dependent edema, g=0.27 to 0.64).13 Thus, these individual signs and symptoms cannot be used to assign a final diagnosis in a rigorous research study. The variability in clinical assessment and minimal use of objective testing in studies of ED patients with chest pain can easily explain the differing results when risk stratification schemes are evaluated by different investigators in different patient populations with different physicians deciding the final diagnosis. Another area where research methodology can be improved is through better description of the population studied. Some risk stratification studies have reported an incidence of acute myocardial infarction of 15% to 20%, whereas others have found that only 5% of patients were diagnosed with acute myocardial infarction and only 10% had non–acute myocardial infarction acute coronary syndrome. Thus, 85% of patients may have non–acute coronary syndrome causes for their symptoms. It is hard to compare results of different risk stratification schemes in patient populations that differ in the rate of acute myocardial infarction by threefold to fourfold. More complete reporting on the patient population would allow the reader to better define exactly who comprised the study population. A recent examination of 2 years of studies that evaluated ED patients with chest pain using cardiac troponin I found that the majority of important features were reported less than 50% of the time.14 Cardiac risk factor criteria were reported only 32% of the time, chief complaint criteria 18% of the time, and the duration of the follow-up period was only noted 77% of the time. The
JANUARY 2004
43:1
ANNALS OF EMERGENCY MEDICINE
follow-up periods ranged from 3 days to 3 years. Although most studies (86%) used a standardized definition of acute myocardial infarction, few (32%) defined what they considered an acute coronary syndrome or unstable angina. More complete reporting is needed to assess the validity, importance, and applicability of published studies.15 The lack of standardized reporting in these studies makes it difficult to compare patient populations, risk stratification algorithms, and outcomes. As I review the excellent study by Prina et al16 in this issue of Annals, these problems again are evident. I am not sure how I can apply their results to my daily clinical practice. In the study by Prina et al, only 230 (12%) of 1,973 admitted chest pain patients were given a diagnosis of chest pain of undetermined origin. Thus, at least 88% of their study population received an evaluation for cardiac and/or noncardiac causes of chest pain. According to Table 1, only 359 (18%) patients in their cohort had a noncardiac origin of chest pain. In my institution, less than 18% of patients have a cardiac origin of chest pain, fewer than one third receive a stress test or cardiac catheterization, and few receive objective evaluations for noncardiac conditions. To extrapolate the results of their study to my clinical practice, I would need more detailed information. I am not sure which of my patients are analogous to their study population. Prina et al16 used a clinical definition of unstable angina that assumes that the cardiologists can distinguish ischemic chest pain from nonischemic chest pain. Of the study patients with chest pain of undetermined origin, 10 had adverse events, many of whom had underlying coronary artery disease and an abnormal ECG result. Only 3 had nuclear testing for ischemia during hospitalization; 1 had a positive result. Thus, I am not sure that their clinical impression of chest pain of undetermined origin would be the same as mine. I may have considered these patients to have a cardiac etiology of chest pain. These methodologic issues obviously affect the outcome of the study. Until rigid reporting criteria and clearly defined outcomes are developed, results will be subjected to the biases of individual practitioners and investigators at the study institution. Until we agree on standardized definitions of outcomes, we are unlikely to define the optimal treatment or evaluation pathway for these patients. Rather than continuing to identify, study, and evaluate new technologies for risk stratification, we should pause and better refine our research methodology and reporting guidelines. Once rigid outcomes are defined and report-
6 9
R I S K S T R A T I F I C A T I O N O F C H E S T P A I N P A T I E N T S Hollander
ing strategies are agreed on, we can move forward defining optimal methods of treating and evaluating these patients. If we do not develop methodologic and reporting standards, we will continue to be unable to develop successful clinical strategies. The author reports this study did not receive any outside funding or support. Reprints not available from the authors. Address for correspondence: Judd E. Hollander, MD, Department of Emergency Medicine, Hospital of the University of Pennsylvania, Ground Floor, Ravdin Building, 3400 Spruce Street, Philadelphia, PA 19104-4283; 215-662-2767, fax 215-662-3953; E-mail jholland@mail. med.upenn.edu.
REFERENCES 1. Lee TH, Juarez G, Cook EF, et al. Ruling out myocardial infarction. A prospective multicenter validation of a 12-hour strategy for patients at low risk. N Engl J Med. 1991;324:1239-1246. 2. Lau J, Ioannidis JPA, Balk EM, et al. Diagnosing acute cardiac ischemia in the emergency department: a systematic review of the accuracy and clinical effect of current technologies. Ann Emerg Med. 2001;37:453-460. 3. Baxt WG, Shofer FS, Sites FD, et al. A neural computational aid to the diagnosis of acute myocardial infarction. Ann Emerg Med. 2002;39:366-373. 4. Baxt WG. Neural computational aid to the diagnosis of acute myocardial infarction. Presented at: Society of Academic Emergency Medicine annual meeting; May 2001; Atlanta, GA. 5. Braunwald E. Unstable angina. A classification. Circulation. 1989;80:410-4. 6. Braunwald E, Mark DB, Jones RH, et al. Unstable angina: diagnosis and management. Clinical Practice Guideline Number 10 (amended) AHCPR Publication No. 94-0602. Rockville, MD: Agency for Health Care Policy and Research and the National Health, Lung and Blood Institute, Public Health Service, Department of Health and Human Services; 1994. 7. Chan GW, Sites FD, Shofer FS, et al. Impact of stress testing on 30-day cardiovascular outcomes for low-risk chest pain patients admitted to floor telemetry beds. Am J Emerg Med. 2003;21:282-287. 8. Zucker DR, Griffith JL, Beshansky JR, et al. Presentations of acute myocardial infarction in men and women. J Gen Intern Med. 1997;12:79-87. 9. Jayes RL, Beshansky JR, D’Agostino RB, et al. Do patients’ coronary risk factor reports predict acute cardiac ischemia in the emergency department? A multicenter study. J Clin Epidemiol. 1992;45:621-626. 10. Rouan GW, Lee TH, Cook EF, et al. Clinical characteristics and outcome of acute myocardial infarction in patients with initially normal or nonspecific electrocardiograms. Am J Cardiol. 1989;64:1087-1092. 11. Pope JH, Aufderheide TP, Ruthazer R, et al. Missed diagnosis of acute cardiac ischemia in the emergency department. N Engl J Med. 2000;342:1163-1170. 12. Hickan DH, Sox HC, Sox CH. Systematic bias in recording history in patients with chest pain. J Chronic Dis. 1985;38:91-100. 13. Gadsboll N, Hoiland-Carlsen PF, Nielsen GG, et al. Symptoms and signs of heart failure in patients with myocardial infarction: reproducibility and relationship to chest x-ray, radionuclide ventriculography and right heart catheterization. Eur Heart J. 1989;10:1017-1028. 14. Glavan B, Shewakramani S, Hollander JE. Incomplete data reporting in studies of ED patients with potential acute coronary syndromes utilizing troponins. Acad Emerg Med. 2003;10:943-948. 15. Harden RD. Critical appraisal of papers describing triage systems. Acad Emerg Med. 1999;6:1166-1171. 16. Prina LD, Decker WW, Weaver AL, et al. Outcome of patients with a final diagnosis of chest pain of undetermined origin admitted under the suspicion of acute coronary syndrome: a report from the Rochester Epidemiology Project. Ann Emerg Med. 2003;43:59-67.
7 0
ANNALS OF EMERGENCY MEDICINE
43:1
JANUARY 2004