The Internet Tracking Registry of Acute Coronary Syndromes (i*trACS): A Multicenter Registry of Patients With Suspicion of Acute Coronary Syndromes Reported Using the Standardized Reporting Guidelines for Emergency Department Chest Pain Studies

CARDIOLOGY AND VASCULAR/ORIGINAL RESEARCH

The Internet Tracking Registry of Acute Coronary Syndromes (i*trACS): A Multicenter Registry of Patients With Suspicion of Acute Coronary Syndromes Reported Using the Standardized Reporting Guidelines for Emergency Department Chest Pain Studies Christopher J. Lindsell, PhD Venkataraman Anantharaman, MD Deborah Diercks, MD Jin Ho Han, MD James W. Hoekstra, MD Judd E. Hollander, MD J. Douglas Kirk, MD Swee-Han Lim, MD W. Frank Peacock, MD Brian Tiffany, MD, PhD Eric K. Wilke, MD W. Brian Gibler, MD Charles V. Pollack, Jr, MA, MD For the EMCREG-International i*trACS Investigators

From the University of Cincinnati Medical Center, Cincinnati, OH (Lindsell, Han, Gibler); the Singapore General Hospital, Singapore (Anantharaman, Lim); the University of California, Davis Medical Center, Sacramento, CA (Diercks, Kirk); the University of Pennsylvania, Philadelphia, PA (Hollander, Pollack); the Wake Forest University, Winston Salem, NC (Hoekstra); The Cleveland Clinic Foundation, Cleveland, OH (Peacock); and the Maricopa Medical Center, Phoenix, AZ (Tiffany, Wilke).

Study objective: Observational studies of well-described patient populations presenting to emergency departments (EDs) with suspicion of acute coronary syndrome are necessary to understand the relationships between patients’ signs and symptoms, cardiac risk profile, test results, practice patterns, and outcomes. We describe the methods for data collection and the ED population enrolled in a multicenter registry of patients with chest pain. Methods: Patients older than 18 years, presenting to one of 8 EDs in the United States or 1 ED in Singapore, and with possible acute coronary syndrome were enrolled in the Internet Tracking Registry of Acute Coronary Syndromes between June 1999 and August 2001. Prospective data, including presenting signs and symptoms, ECG findings, and the ED physician’s initial impression of risk, were systematically collected. Medical record review or daily follow-up was used to obtain cardiac biomarker results, invasive and noninvasive testing, treatments, procedures, and inhospital outcomes. Thirty-day outcomes were determined by telephone follow-up and medical record review. Results: The registry includes 15,608 patients, with 17,713 visits. Chest pain was the chief complaint in 71% of visits. The ECG was diagnostic of ischemia or infarction in 10.1% and positive cardiac biomarkers were observed in 10% of visits. Forty-three percent of patients were sent home directly from the ED. Of admitted patients, 5% died by 30 days, and 3% had documented coronary artery disease or had undergone percutaneous coronary intervention or coronary artery bypass grafting within 30 days. For patients discharged directly from the ED, 0.4% died or had a documented myocardial infarction within 30 days. Coronary artery bypass graft surgery, percutaneous coronary intervention, or a diagnosis of coronary artery disease was found in 0.5% of discharged patients. Conclusion: A unique description of undifferentiated ED chest pain patients with suspected acute coronary syndrome is provided. The data set can be used to generate and explore hypotheses to improve understanding of the complex relationships between presentation, treatment, testing, intervention and outcomes. [Ann Emerg Med. 2006;48:666-677.] 0196-0644/$-see front matter Copyright © 2006 by the American College of Emergency Physicians. doi:10.1016/j.annemergmed.2006.08.005

666 Annals of Emergency Medicine

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Internet Tracking Registry of Acute Coronary Syndromes Editor’s Capsule Summary

What is already known on this topic Randomized controlled trials can demonstrate the effectiveness of therapies but do not focus on the complex clinical presentations of acute coronary syndrome. Observational data sets that contain systematically recorded information on every patient who could have an acute coronary syndrome can help examine interactions between patient characteristics, presentations, practice patterns, and outcomes. What question this study addressed The investigators established a 9-emergency department network that collected standardized information on a convenience sample of patients in whom acute coronary syndrome was considered. They present information on more than 17,000 patient encounters. What this study adds to our knowledge This study provides information about these patients’ demographics, cardiac enzyme patterns, and 30-day outcomes. How this might change clinical practice This study alone will not change clinical practice but provides a model for clinical networks whose data might eventually lead to better strategies for the risk stratification of patients to different diagnostic and therapeutic regimens.

INTRODUCTION More than 5.5 million patients present to a United States emergency department (ED) with chest pain and other symptoms related to acute coronary syndrome each year.1 Acute coronary syndrome is observed in people of all ages, races, and socioeconomic backgrounds. The clinical presentation of acute coronary syndrome is heterogeneous, varying from ST-segment elevation with positive cardiac biomarker results of myocardial necrosis to the very subtle cases of acute coronary syndrome with no observable ECG changes,2 negative cardiac biomarker results,3 atypical signs and symptoms,4 and a nonspecific medical history.4 This broad spectrum of disease has been extensively researched, yet appropriate evaluation and treatment can remain problematic for individual patients, and the impact of acute coronary syndrome remains enormous. Recently, improvements in medical management and invasive therapeutic options for these patients have resulted in the publication of numerous guidelines for appropriate evaluation and treatment of acute coronary syndrome.5-7 Despite these expert opinions, guidelines are poorly followed, disparities in outcomes persist, and emergency physicians miss up to 2% of acute myocardial infarctions in patients presenting to EDs.8,9 To reduce the burden of acute coronary syndrome on patients and providers, delineating the relationship between evaluation, treatment, and outcomes is fundamental. Volume , .  : December 

Randomized controlled trials can demonstrate the effectiveness of therapies or treatment pathways. They cannot help us to completely understand the complex presentations of acute coronary syndrome in the clinical setting. The only feasible method for unraveling the interaction between practice patterns, manners of presentation, patient characteristics, diagnostic testing, therapy, and outcomes in contemporary practice is through observational studies. To our knowledge, the only inclusive multicenter observational data sets compiled heretofore are those reported by Goldman et al10 and Selker et al,11 which were used to develop risk-stratification protocols for ED chest pain patients. Although inclusive, both data sets commenced more than 15 years ago, when many of today’s guidelines, as well as diagnostic and therapeutic options, did not exist. This limits generalizability to today’s practice of emergency medicine. Further, only limited descriptions of these patient populations are available, providing insufficient information for evaluating generalizability. Guidelines for reporting studies of chest pain patients have recently been developed to assist researchers in satisfying the minimum description of the sample necessary for understanding ED chest pain studies.12 These guidelines offer data definitions and indicate those variables that must be reported to interpret study results in an optimal and generalizable fashion. No multicenter observational cohort study has previously attempted to use these guidelines to describe a large patient population with suspected acute coronary syndrome. The dearth of more recent observational studies of welldescribed patient populations presenting to EDs with any suspicion of acute coronary syndrome represents a significant barrier to understanding the relationships between patients, signs and symptoms, practice patterns, and outcomes. There is a fundamental requirement for such a study. This need was recognized by EMCREG in 1999 when several of its member institutions began compiling i*trACS (the Internet Tracking Registry of Acute Coronary Syndromes). Since the registry was closed to enrollment in late 2001, subsets of the data have been used to assess health disparities, explore practice patterns, evaluate relationships between ECG results and cardiac biomarkers, and investigate the utility of diagnostic tests in subgroups such as diabetic patients and patients with heart failure.13-25 However, a comprehensive description of the institutions collecting the data, the data collection methods, and of the entire cohort enrolled in the registry has yet to be provided. To facilitate use of the i*trACS database for exploring the complex interactions involved in the ED evaluation and treatment of acute coronary syndrome, we describe the data collection procedures and present a description of the entire spectrum of patients with suspected acute coronary syndrome using the standardized reporting guidelines for chest pain studies.

MATERIALS AND METHODS Study Design This was a multicenter study using both direct observation and medical record review methods. Institutional review boards or ethics committees approved patient enrollment without informed consent at 8 of the 9 centers; at one center, verbal informed consent Annals of Emergency Medicine 667

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Table 1. Characteristics of participating institutions.

Site Site Site Site Site Site Site Site Site

1* 2 3 4 5 6 7‡ 8‡

Site 9‡

Geographic Region

Approximate Census During Study Period

Approximate Acute Coronary Syndrome Census During Study Period, %

Rocky Mountains Rocky Mountains Midwest Midwest Mid-Atlantic Midwest Midwest Pacific

9,000 120,000 160,000 50,000 100,000 50,000 45,000 60,000

70 1 4 8 5–10 6 10 10–15

475 (5.3) 634 (0.5) 3,868 (2.4) 1,848 (3.7) 3,686 (3.7) 1,327 (2.7) 283 (0.6) 2,064 (3.4)

94,000

4

3,528 (3.8)

Singapore

Number of Patients Enrolled (% of Census)

Enrollment Hours 24 h/Day, 365 days/y† 24 h/Day, 365 days/y† 8 AM To 12 AM, 365 days/y 8 AM To 12 AM, 365 days/y 8 AM To 12 AM, 365 days/y 24 h/Day, 365 days/y† 24 h/Day, 365 days/y 8 AM To 2 AM, 365 days/y except holidays 24 h/Day, 365 days/y

Teaching Hospital

Proportion of Patients With Medicaid or Without Insurance, %

No Yes Yes No Yes Yes Yes Yes

26 68 67 17 55 40 33 46

Yes

NA

NA, Not applicable, non-US institution. *This emergency department specialized in cardiovascular and neurovascular emergencies. † Enrollment was by physicians only. ‡ These sites enrolled patients only during the second year of data collection.

was required from the patients before data collection. At this site, no patients were known to have refused participation. Setting Eight sites participating in the registry were selected to represent a cross-section of providers in the United States; sites were selected from among the membership of EMCREG International. There were 6 academic and 2 community hospitals, with a census varying between 10,000 and 160,000 visits during the study period. Providers of health care to indigent and nonindigent populations were well represented, with the proportion of patients receiving Medicaid or without insurance ranging from 17% to 67%. One site in Singapore was included complementary to data collection in the United States, which provides opportunities for exploring how differences between patients, providers, and cultures can affect generalization of studies conducted in 1 country. The 9 sites are described in Table 1. Only data for United States institutions are included in the remainder of this report; comparable data for the site in Singapore are available online in Appendix E1(Tables E1-E9 at http://www.annemergmed.com). Selection of Participants Patients were prospectively enrolled between June 1999 and August 2001, although not all participating institutions collected data throughout the entire study period. Any patient aged 18 or older for whom an ECG was obtained for the evaluation of possible acute coronary syndrome was eligible. Patients were excluded if they were transferred from another hospital or if they received an ECG strictly for screening purposes preliminary to noncardiac-related procedures. Patients were identified while they were in the ED either by the treating physician or by trained research assistants. For any patient with chest pain, shortness of breath, weakness, upper 668 Annals of Emergency Medicine

abdominal pain, lightheadedness, or nausea and who received an ECG, the treating physician determined eligibility according to the possibility of acute coronary syndrome. Research assistants directly enrolled patients for whom an ECG and cardiac marker tests were ordered. Physician identification of study subjects occurred when the physician examined the patient and interpreted the ECG. Research assistant identification of subjects occurred by routine rounds of the ED and perusal of orders for an ECG. A convenience sample was enrolled at each center; efforts were made to capture the acute coronary syndrome populations as completely as possible. The proportion of chest pain patients estimated to have been captured at each site are provided in Table 1. Data Collection and Processing Standardized data collection forms were used at each participating site (Figure E1-E2, available online at http://www.annemergmed.com). The site in Singapore used the same English-language forms as sites in the United States. Once a patient was identified and enrolled, the treating physician completed data elements pertaining to initial diagnostic impression and ECG results. The ED physician’s interpretation of the ECG was recorded; standardized definitions were not provided for interpretation of the ECG. Initial ED impression was based on the ECG, medical history, and physical examination only and was determined and recorded before any other test or laboratory results were available. The initial impression was defined as the ED physician’s “gut feeling.” Low risk was defined as the patient likely to be sent home; high risk was defined as the patient for whom serial ECG or marker tests were likely to be ordered or for whom admission to a chest pain unit was likely. The ED and hospital course were followed by medical record review or daily follow-up of patients admitted to the inpatient setting. Times were obtained from the records. The arrival time Volume , .  : December 

Lindsell et al was defined as the earliest time documented in the record. Disposition time was the earliest recorded time at which the decision to discharge or admit was noted. This may have been the discharge time, which was defined as the time at which the patient left the ED. Timing of cardiac markers was documented by using the time results were available to the treating physician. The times of other tests were defined as the time at which the test was begun. Out-of-hospital treatments and medications taken by the patient the same day were included if they would otherwise have been given in the ED. The final ED diagnosis was obtained by medical record review and was defined as the discharge diagnosis for patients discharged home or the admitting diagnosis for patients admitted to an inpatient setting. Patients were contacted at 30 days for determination of outcomes. Primary follow-up was by telephone. Telephone follow-up was attempted for up to 90 days. Events occurring during the 30-day period after the ED presentation were captured. Medical record review and death registry review were used to follow up patients who could not be contacted by telephone. Once a data collection form was completed, the data were entered into a secure, Web-based database (Microsoft SQL server; Microsoft Corporation, Redmond, WA). A relational format was used for the database, which was designed and maintained by ClickFind Inc (Bryan, TX). Interim data sets were supplied to a central biostatistician to provide site performance updates biannually. On October 1, 2001, follow-up data collection was completed and a final database was provided to the central biostatistician. Data underwent a comprehensive cleaning process to ensure that duplicate entries were eliminated and inconsistencies were resolved; minimum specification for consistency was a progressive patient course and all data elements within acceptable range. Inconsistent data were recoded as missing; data collection procedures did not allow for linking the case report form to the medical record after data collection was complete. Data inconsistent with patient course would include, for example, results of a noninvasive test whose date and time was before arrival in the ED; it is unknown whether the test was conducted on an outpatient basis after a previous visit or if the date and time were entered incorrectly. Out-of-range data were predefined for continuous variables where possible. For example, patient age recorded as younger than 18 years or cardiac markers above the upper limit of detection for a site’s assay were removed. Primary Data Analysis The analysis reported in this paper is descriptive. Medians or means and interquartile ranges and ranges or SDs are used to describe continuous variables. Frequencies and percentages are used to describe categorical variables. Data are reported according to the specifications provided in the “Standardized Reporting Guidelines for Studies Evaluating Risk Stratification of Emergency Department Patients with Potential Acute Coronary Syndromes.”12 For the purposes of this report, each visit has been Volume , .  : December 

Internet Tracking Registry of Acute Coronary Syndromes Table 2. Demographics and medical history.* Characteristic Age, y (Mean, SD) Female Male Unknown sex Black White Hispanic Asian American Indian Unknown race Current or recent smoker Cocaine user Amphetamine user Hypertension Family history of CAD Dyslipidemia CAD Diabetes Angina CHF

All Visits

Index Visit Only

54 (16) 7,737 (54.5) 6,432 (45.3) 16 (0.1) 6,416 (45.2) 5,974 (42.1) 464 (3.3) 206 (1.5) 24 (0.2) 1,101 (7.8) 5,503 (38.8) 282 (2.0) 46 (0.3) 7,120 (50.2) 5,420 (38.2) 3,092 (21.8) 3,081 (21.7) 2,955 (20.8) 1,702 (12.0) 1,233 (8.7)

54 (16) 6,725 (54.3) 5,649 (45.6) 16 (0.1) 5,303 (42.8) 5,439 (43.9) 427 (3.4) 168 (1.4) 22 (0.2) 1,031 (8.3) 4,576 (36.9) 234 (1.9) 42 (0.3) 5,800 (46.8) 4,471 (36.1) 2,469 (19.9) 2,308 (18.6) 2,346 (18.9) 1,227 (9.9) 887 (7.2)

CAD, Coronary artery disease; CHF, congestive heart failure. *Frequencies and percentages are given unless otherwise indicated. Proportions of all visits are given. Data are also given for only the index visit.

considered independent, although some patients were enrolled in the registry multiple times. Although this multiple enrollment may result in some bias in demographic characteristics and medical history, it is unknown whether data were similarly reported at each point or whether the same providers treated the patient. Analyses were conducted using SAS version 8.1 (SAS Institute, Inc., Cary, NC), SPSS versions 10.0 to 13.0 (SPSS Inc., Chicago, IL), and Microsoft Excel (Microsoft Corporation).

RESULTS Throughout the 3 years, 12,390 patients suspected of having acute coronary syndrome and who had an ECG ordered by the treating physician were enrolled at one of 8 EDs in the United States. An additional 3,008 patients were enrolled in Singapore; data for these patients are available in Appendix E1 (available online at http://www.annemergmed.com). In the United States, there were 14,185 patient visits. Six patients visited the ED 10 or more times, 53 patients visited between 5 and 10 times, 55 patients visited 4 times, 187 patients visited 3 times, 906 patients visited twice, and 11,183 visited only once. For 11,962 visits (84.3%), the patient was contacted for follow-up, or events were available in the medical record, subsequent visits were captured in the registry, or the patient was identified by the death registry review. It is unknown what proportion of events was captured by medical record review and what proportion was captured by telephone follow-up. In 1,576 cases (11.1%), sufficient information was obtained from the medical record to determine that the patient was alive at 30 days, but no events were recorded. There were 647 cases (4.6%) entirely lost to follow-up. Annals of Emergency Medicine 669

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Table 3. ECG findings.*

Table 4. Cardiac biomarker tested in the ED.* Known to Be Old

Findings Time to ECG, min (Median, interquartile range) Rate (Median, interquartile range) Rhythm Sinus rhythm Atrial fibrillation/flutter Supraventricular tachycardia VT/VF Second-degree or third-degree AV block Other/undetermined ST-segment elevation 1–2 mm ⬎2 mm ST-segment depression 0.5–1 mm 1–2 mm ⬎2 mm T–wave inversion Flattening 1–5 mm ⬎5 mm Left bundle-branch block Yes Right bundle-branch block Yes Diagnostic category†‡ AMI Acute ischemia Early repolarization Nondiagnostic Normal

All ECGs

No.

%

23 (10–58) 77 (66–90) 11,539 (92.1) 442 (3.5) 105 (0.8) 9 (0.1) 38 (0.3) 396 (3.2) 839 (6.7) 190 (1.5)

206

(20.0)

666 (5.3) 387 (3.1) 129 (1.0)

219

(18.5)

1,775 (14.2) 2,291 (18.3) 97 (0.8)

824

(19.8)

415 (3.3)

209

(50.4)

443 (3.5)

206

(46.5)

251 (2.0) 638 (5.1) 318 (2.5) 6,272 (50.1) 5,050 (40.3)

AMI, acute myocardial infarction; VT/VF, ventricular tachycardia/ventricular fibrillation. *Numbers are given as frequencies and percentages unless otherwise indicated. Proportions are based on the number of patients with all ECG findings (N⫽12,529). Diagnostic category is based on the emergency physicians’ interpretation, whereas interpretation is based on the final read in the medical record. † These categories are not the same as those recommended in the Standardized Reporting Guidelines. ‡ Diagnostic categories are based on the emergency physician’s impression and are not based on defined criteria.

Patient demographics and medical history are summarized in Table 2 and are additionally reported for each patient’s index visit only. The mean patient age was 54.1 years (SD 15.95 years). The age distribution is shown in Figure E3 (Appendix E2, available online at http://www.annemergmed.com). Age was not recorded for 127 (0.9%) patients. There were 7,737 (54.5%) visits for female patients and 6,432 (45.3%) visits for male patients; sex was not recorded for 16 patient visits. Race was recorded for 13,084 (92.2%) patient visits. Of these, 6,416 were black (45.2%), 5,974 were white (42.1%), 464 were Hispanic (3.3%), 206 were Asian (1.5%), and 24 were American Indian (0.2%). 670 Annals of Emergency Medicine

Marker TnT Patients with Patients with Patients with Patients with TnI Patients with Patients with Patients with Patients with Myoglobin Patients with Patients with Patients with Patients with CK-MB Patients with Patients with Patients with Patients with

No.

Positive†

Positive, %

a a a a

first marker second marker third marker fourth marker

4,715 722 179 17

302 49 6 1

6.4 6.8 3.4 5.9

a a a a

first marker second marker third marker fourth marker

5,800 1,431 272 56

466 166 38 9

8.0 11.6 14.0 16.1

a a a a

first marker second marker third marker fourth marker

2,198 853 112 22

392 175 14 3

17.8 20.5 12.5 13.6

a a a a

first marker second marker third marker fourth marker

7,864 1,293 343 90

788 148 26 5

10.0 11.4 7.6 5.6

*Up to 4 of each marker were tested; numbers are additive (ie, the 722 patients with a second TnT are included in the 4,715 with a first TnT). † For cardiac troponin T, the cutoff used was 0.1 ␮g/L; for cardiac troponin I, it was 0.6 ␮g/L at 7 sites and 0.06 ␮g/L at 1 site; for CK-MB, it was 6 ␮g/L at 7 sites and 3.5 ␮g/L at 1 site; and for myoglobin, it was 85 ␮g/L.

Insurance status was recorded for 12,306 patient visits (86.8%). There were 3,992 patient visits with private insurance (32.4%), 3,246 Medicare patient visits (26.4%), 1,267 Medicaid patient visits (10.3%), 1,674 (13.6%) self-pay patient visits, 23 patient visits (0.2%) covered by the Veterans Administration, 68 (0.6%) patient visits covered by correctional institutions, and 2,036 (16.5%) with some other form of insurance. There were 5,503 (38.8%) visits among current or recent smokers. Relatively few were for admitted cocaine users (2.0%) or amphetamine users (0.3%). More than 80% of all patient visits were for patients with at least 1 conventional cardiac risk factor. Hypertension was reported in 7,120 (50.2%) of visits, a family history of coronary artery disease in 5,420 (38.2%), dyslipidemia in 3,092 (21.8%), and coronary artery disease in 3,081 (31.7%) visits. A history of angina or congestive heart failure was reported in 12.0% and 8.7% of patient visits, respectively. There were 2,955 (20.8%) visits for patients with diabetes. At the majority of visits, patients reported dyspnea (57.3%), with a significant number of patients also reporting nausea (31.1%), diaphoresis (27.2%), dizziness (24.9%), and weakness (24.6%). Chest pain was the chief complaint in 67.8% of the sample. The chest pain was constant for 39.3% and reproducible by palpation in 8.1%. Midchest and left chest were the most common pain locations, occurring in 72.6% of all patient visits. The pain was most frequently reported as pressure (40.6%), but also as stabbing (21.5%), squeezing (10.3%), and aching (10.9%). Some other quality of pain was reported for 15.8%. Online supporting documentation provides a more Volume , .  : December 

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Table 5. Relationship between ECG findings, cardiac biomarkers, and final ED diagnosis for patients with an ECG diagnostic category and a final ED diagnosis recorded (N⫽13,179). Final ED Diagnosis ECG Diagnostic Category

Cardiac Biomarkers

ST-Elevation MI

Non–ST-Elevation MI/UA

Stable Angina

Other

MI (N⫽286)

⫺ (N⫽114) ⫹ (N⫽114) Not done (N⫽58) ⫺ (N⫽417) ⫹ (N⫽187) Not done (N⫽94) ⫺ (N⫽217) ⫹ (N⫽42) Not done (N⫽74) ⫺ (N⫽4,768) ⫹ (N⫽836) Not done (N⫽1,082) ⫺ (N⫽3,361) ⫹ (N⫽328) Not done (N⫽1,487)

64 78 44 8 17 6 3 1 0 10 27 6 6 9 1

12 12 5 124 80 32 11 3 1 500 161 100 188 37 35

0 0 0 9 3 1 3 2 2 75 13 27 43 6 8

38 24 9 276 87 55 200 36 71 4,183 635 949 3,124 276 1,443

Ischemia (N⫽698)

Early repolarization (N⫽333)

Nondiagnostic (N⫽6,686)

Normal (N⫽5,176)

detailed presentation of vital signs and symptoms (Table E10) and chest pain characteristics (Table E11; both in Appendix E2, available online at http://www.annemergmed.com). ECG data were captured for 13,952 patient visits (98.4%). The ECG findings required for reporting under the standardized guidelines are rate, rhythm, ST-segment elevation or depression, T-wave inversion, left bundle branch block, right bundle branch block, and overall categorization. All these data elements were completed for 12,529 visits, and these are reported in Table 3. Median time to ECG acquisition from ED arrival time was 23 minutes. ST-segment elevation was evident in 8.2% of visits, ST-segment depression in 9.4%, and T-wave inversion in 19.5%. Findings were known to be old for about 20% of each of these cases. Left bundle-branch block and right bundle-branch block occurred in 3.3% and 3.5% of visits, respectively. The emergency physician categorized the ECG as diagnostic for ischemia or infarction in 889 visits (7.1%). Different sites used different assays for measuring cardiac biomarkers; measures of central tendency and dispersion are not given, because they would not be meaningful. Data are reported as positive or negative. CK-MB level was used in the ED for 7,684 visits, TnI was used for 5,800 visits, TnT for 4,715 visits, and myoglobin for 2,198 visits. Overall, at least 1 cardiac biomarker was measured in the ED for 11,044 (77.9%) patient visits, of which 3,774 (34.2%) had serial markers measured. There were 1,601 patient visits (11.3%) with at least 1 positive cardiac biomarker. Table 4 describes results for the individual markers. Table 5 shows how cardiac biomarkers related to ECG findings. Data are stratified by the final ED diagnosis recorded by the emergency physician when the patient was dispositioned. Of the 14,185 visits, initial ED diagnostic impression and disposition are known for 13,782 (97.2%). For these patient visits, Table 6 describes the disposition, stratified by initial ED diagnostic impression, positivity of cardiac markers, and results of myocardial perfusion imaging obtained from the ED. Overall, patients were Volume , .  : December 

discharged directly from the ED for 5,846 (42.4%) visits, and at 210 visits (1.5%) patients left against medical advice. There were 7,614 (55.3%) admissions; 5,704 patients (41.4%) were admitted to a floor bed, 1,612 patients (11.7%) were admitted to an ICU bed, and 290 patients (2.1%) were transported to the cardiac catheterization laboratory. There were 9 deaths in the ED (0.1%), and at 8 visits, patients went directly to coronary artery bypass grafting surgery (0.1%). Transfer to another institution accounted for 0.7% of dispositions. No data pertaining to the use of a chest pain unit were collected. The final ED diagnoses are illustrated in the Figure for all visits. There were 128 additional patient visits resulting in admission that did not have a documented initial impression. Among all 7,742 known admissions, hospital course is shown in Table 7, stratified by the diagnosis recorded by the ED physician at the end of the ED course. Findings after hospital discharge are presented for visits with and without noninvasive testing and with cardiac catheterization or coronary artery bypass grafting. Between discharge and 30 days, 181 of the admitted patients (2.3%) had died, reported a repeated myocardial infarction, or had a repeated myocardial infarction documented in the medical record. There were 114 visits (1.5%) for patients who were diagnosed with coronary artery disease (according to noninvasive testing or coronary angiogram) or who underwent percutaneous coronary intervention or coronary artery bypass grafting surgery within 30 days of their initial ED visit. Noninvasive testing was conducted during 91 visits for patients discharged directly from the ED, with 3 patients testing positive for coronary artery disease. After discharge, there were 28 patients with death or myocardial infarction within 30 days (0.45%), whereas there was positive testing, coronary artery bypass grafting, or percutaneous coronary intervention in 17 additional patients (0.28%) (Table 8). Cause of death is Annals of Emergency Medicine 671

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Table 6. Patient ED course stratified by initial impression for the 13,782 patients with both initial impression and disposition available. Disposition From ED Initial Impression Acute MI (N⫽316)

Unstable angina/ non–Q-wave MI (N⫽1,024)

Cardiac Markers Neg (N⫽116) Pos (N⫽129) Not done (N⫽71) Neg (N⫽666)

Pos (N⫽220)

High-risk chest pain (N⫽3,861)

Not done (N⫽138) Neg (N⫽2,843)

Pos (N⫽596)

Not done (N⫽422)

Low-risk chest pain (N⫽5,487)

Neg (N⫽4,048)

Pos (N⫽502)

Not done (N⫽937)

Noncardiac chest pain (N⫽3,094)

Neg (N⫽1,566)

Pos (N⫽130)

Not done (N⫽1,398)

Sestamibi

Home

ICU

OR

Cath. Lab

Floor

Died in ED

Transferred

AMA

Not done (N⫽116) Pos (N⫽1) Not done (N⫽128) Not done (N⫽71) Neg (N⫽7) Pos (N⫽1) Not done (N⫽658) Neg (N⫽2) Pos (N⫽1) Indeterminate (N⫽1) Not done (N⫽216) Not done (N⫽138) Neg (N⫽72) Pos (N⫽15) Indeterminate (N⫽7) Not done (N⫽2,749) Neg (N⫽6) Pos (N⫽4) Indeterminate (N⫽2) Not done (N⫽584) Neg (N⫽4) Pos (N⫽2) Not done (N⫽416) Neg (N⫽291) Pos (N⫽26) Indeterminate (N⫽14) Not done (N⫽3,717) Neg (N⫽29) Pos (N⫽6) Indeterminate (N⫽2) Not done (N⫽465) Neg (N⫽16) Pos (N⫽1) Indeterminate (N⫽1) Not done (N⫽916) Neg (N⫽50) Pos (N⫽2) Indeterminate (N⫽2) Not done (N⫽1,512) Neg (N⫽3) Pos (N⫽1) Not done (N⫽126) Neg (N⫽10) Indeterminate (N⫽1) Not done (N⫽1,387)

3 0 2 1 3 1 27 1 0 0 5 16 61 1 3 456 4 0 2 63 3 0 89 266 9 9 1,787 26 0 2 143 15 0 1 579 50 1 1 972 2 1 48 10 1 1,182

41 1 45 26 0 0 199 0 1 1 111 50 1 10 1 470 0 1 0 166 0 2 76 6 7 2 207 1 2 0 58 0 0 0 40 0 1 1 56 0 0 15 0 0 14

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 2

47 0 56 33 0 0 27 0 0 0 16 8 0 0 0 46 0 0 0 15 0 0 8 0 0 0 21 0 0 0 9 0 0 0 1 0 0 0 1 0 0 2 0 0 0

24 0 25 7 4 0 383 1 0 0 81 58 9 4 2 1,692 2 3 0 331 1 0 224 15 8 3 1,619 1 4 0 248 1 1 0 264 0 0 0 470 1 0 55 0 0 163

0 0 0 3 0 0 0 0 0 0 2 0 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0

1 0 0 1 0 0 11 0 0 0 0 1 1 0 0 29 0 0 0 3 0 0 7 4 0 0 20 0 0 0 3 0 0 0 7 0 0 0 6 0 0 3 0 0 6

0 0 0 0 0 0 11 0 0 0 1 5 0 0 1 52 0 0 0 5 0 0 10 0 2 0 63 1 0 0 4 0 0 0 26 0 0 0 7 0 0 2 0 0 20

AMA, Against medical advice; MI, myocardial infarction.

unknown for mortality after discharge from the ED or the inpatient setting.

LIMITATIONS There are several limitations of this data set that must be accommodated by researchers using the registry. The primary limitation is the potential for bias arising from the sampling method. Although we attempted to sample as completely as 672 Annals of Emergency Medicine

possible, patients presenting overnight and on holidays were excluded at some sites. Complete capture during sampling hours is also unlikely; the practicality of obtaining a truly complete sample excluded its possibility. The most likely bias resulting from our sampling methods is the inclusion of verylow-risk patients. It is possible, for example, that some patients not truly suspected to have possible acute coronary syndrome were included; ECG or cardiac marker tests may Volume , .  : December 

Lindsell et al

Figure. Distribution of final ED diagnoses. Patients could have multiple diagnoses. NOS, Not otherwise specified.

have been unnecessarily ordered by protocol, resulting in inadvertent inclusion. However, these patients were, by some criteria, considered at possible risk for acute coronary syndrome during their ED stay, and the physician’s initial impression and subsequent patient course would be indicative of the low physician suspicion. Their inclusion is representative of the very-low-risk patient. The low ED mortality rate may also reflect the inclusion of a low-risk patient population, or it may represent appropriate and rapid treatment and admission of very-high-risk patients to receive necessary intervention. Alternative sampling methods that could have been implemented include identification by retrospective medical record review, consecutive sampling, and random sampling. Innovative sampling schemes that provide for consecutive enrollment during randomized times and days are also possible. Each of these approaches has costs and benefits. Identification by medical record review can often be less costly but would limit enrollment to those for whom a possibility of acute coronary syndrome was documented in the record; our sample is more inclusive of the low-risk patient. Consecutive sampling with aggressive prospective data collection would offer the leastbiased data set but is much more costly to achieve and was impractical for this project. Random sampling requires similarly aggressive identification of patients as consecutive sampling and again was impractical for this study. Within the data set itself, our methodology resulted in multiple missing data elements for many patients. Although patients were prospectively enrolled, many of the data were obtained by record review. The limitations of record-review data are well known. Bias has been mitigated somewhat by using a standardized data abstraction form. However, potential for bias because of non–randomly missing data points cannot be excluded in analyses. When medical record review data were not available to abstractors, were incorrectly entered into the hospital system, or were not documented, they were treated as missing in these analyses. Alternative reasons also exist for Volume , .  : December 

Internet Tracking Registry of Acute Coronary Syndromes missing data. Data that were inconsistent with patient course have been excluded, and out-of-range data values were excluded. Although this method results in some error, this is most likely random and due to data entry or data abstraction errors. Repeated visitors impose some bias on the data. Table 2 shows that the repeated visitors were of similar age, race, and sex to those who had only 1 visit, but they tended to have more risk factors, as demonstrated by the lower prevalence of risk factors among index visits than among all visits. For the data reported in this manuscript, each visit has been considered independent because only demographics and history are likely to be constant between visits. Analytic methods that take into account withinpatient clustering can be used for analyses including repeated visitors. Alternative strategies can also be considered, such as using only a patient’s first visit or using only their last visit and considering previous visits a positive history of chest pain. The particular strategy used should be appropriate to the hypothesis being explored or the patient group being studied. In addition to these distinct limitations of the data set, there are some general limitations of registry data. The first of these is generalizability. Although we have attempted to create a data set that is representative of chest pain patients from all demographic groups, socioeconomic groups, and those presenting to all provider types, there may remain some difficulties in generalizing the findings. The data are static and may not be reflective of future practice. They are not representative of chest pain patients internationally, with the exception of Singapore, and there may be some exclusion bias because of the convenience sampling methodology. Because of the enormous cost and effort required to obtain clinical and outcomes data on thousands of individuals, data monitoring is often not as robust for registry studies as for clinical trials and smaller observational cohort studies. The possibility for patient misclassification, double counting the same patient, and incorrect cross-matching with medical records and follow-up data cannot be ignored when results of analyses are interpreted using these data. However, it is assumed that any such error is random and the likelihood of drawing error-driven conclusions is minimal.

DISCUSSION Several large observational studies are reported in the contemporary literature. The Global Registry of Acute Coronary Events project26 has evaluated such diverse factors as the impact of diabetes and the effectiveness of percutaneous coronary intervention, thrombolytics, and glycoprotein IIb/IIIa receptor inhibitors, as well as describing variations in practice patterns and developing risk prediction models.27-31 Although providing valuable insights into acute coronary syndrome in the real-world setting, the data set excludes the low-risk patients, the “missed” patients, and patients successfully treated and discharged directly from the ED. Similarly, the Canadian Acute Coronary Syndrome Registry excluded discharged patients.32 The European Network for Acute Coronary Treatment study sampled only cardiologists,33 and the Prospective Registry of Acute Ischaemic Syndromes in the UK also excludes lower-risk Annals of Emergency Medicine 673

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Table 7. Hospital course for admitted patients, stratified by admitting diagnosis.* Findings at Follow-up Final ED Diagnosis ST-elevation MI (N⫽287)

Noninvasive Testing Neg (N⫽19)

Cath Lab Findings Neg (N⫽2) Pos (N⫽13)

Pos (N⫽32)

Not done (N⫽4) Pos (N⫽26)

Not done (N⫽242)

Not done (N⫽6) Neg (N⫽22) Pos (N⫽158)

Non–STelevation MI/unstable angina (N⫽1,327)

Neg (N⫽177)

Not done (N⫽56) Neg (N⫽17) Pos (N⫽29) Not done (N⫽131)

Pos (N⫽105)

Not done (N⫽1,045)

Neg (N⫽14) Pos (N⫽52) Not done (N⫽39) Neg (N⫽159) Pos (N⫽354) Not done (N⫽532)

Stable angina (N⫽128)

Neg (N⫽29)

Pos (N⫽10)

Other (N⫽6,066)

Neg (N⫽3) Pos (N⫽1) Not done (N⫽25) Neg (N⫽3) Pos (N⫽2)

Not done (N⫽89)

Not done (N⫽5) Neg (N⫽7) Pos (N⫽16)

Neg (N⫽1,061)

Not done (N⫽66) Neg (N⫽65) Pos (N⫽45) Not done (N⫽951)

Pos (N⫽385)

Neg (N⫽53) Pos (N⫽81) Not done (N⫽251)

Not done (N⫽4,554)

Neg (N⫽280) Pos (N⫽315) Not done (N⫽3,959)

CABG

No Death or MI

No (N⫽2) No (N⫽11) Yes (N⫽2) No (N⫽4) No (N⫽25) Yes (N⫽1) No (N⫽6) No (N⫽21) Yes (N⫽1) No (N⫽128) Yes (N⫽30) No (N⫽56) No (N⫽17) No (N⫽25) Yes (N⫽4) No (N⫽130) Yes (N⫽1) No (N⫽14) No (N⫽47) Yes (N⫽5) No (N⫽39) No (N⫽158) Yes (N⫽1) No (N⫽304) Yes (N⫽50) No (N⫽525) Yes (N⫽7) No (N⫽3) No (N⫽1) No (N⫽25) No (N⫽3) No (N⫽1) Yes (N⫽1) No (N⫽5) No (N⫽7) No (N⫽10) Yes (N⫽6) No (N⫽66) No (N⫽65) No (N⫽44) Yes (N⫽1) No (N⫽950) Yes (N⫽1) No (N⫽51) Yes (N⫽2) No (N⫽69) Yes (N⫽12) No (N⫽249) Yes (N⫽2) No (N⫽277) Yes (N⫽3) No (N⫽278) Yes (N⫽37) No (N⫽3,952) Yes (N⫽7)

2 10 2 4 23 1 6 16 1 124 27 46 16 25 4 129 1 14 46 5 37 157 1 300 50 512 7 3 1 25 3 1 1 5 7 10 6 65 65 44 1 939 1 51 2 64 11 238 2 275 3 268 36 3,861 7

Death or MI

No Procedures or Positive Tests

Procedure or Positive Test

0 1 0 0 2 0 0 5 0 4 3 10 1 0 0 1 0 0 1 0 2 1 0 4 0 13 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 11 0 0 0 5 1 11 0 2 0 10 1 91 0

2 11 2 4 25 1 6 21 1 127 27 56 16 24 4 130 1 14 45 4 37 157 1 292 44 517 6 3 1 24 3 1 1 5 6 10 5 66 65 42 1 948 1 51 1 63 11 243 2 274 3 269 32 3,916 6

0 0 0 0 0 0 0 0 0 1 3 0 1 1 0 0 0 0 2 1 2 1 0 12 6 8 1 0 0 1 0 0 0 0 1 0 1 0 0 2 0 2 0 0 1 6 1 6 0 3 0 9 5 36 1

CABG, Coronary artery bypass graft. *Data are given for the 7,742 patients known to have been admitted. Findings at follow-up are shown.

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Table 8. Findings for the 6,176 patients known to have been discharged from the ED, stratified by final ED diagnosis.* Findings at Follow-up

Final ED Diagnosis

Noninvasive Testing

No Death or MI

Death or MI

No Procedures or Positive Tests

ST-elevation MI (N⫽1) Non–ST-elevation MI/unstable angina (N⫽50) Stable angina (N⫽71)

Not done (N⫽1) Neg (N⫽2) Not done (N⫽48) Neg (N⫽2) Not done (N⫽69) Neg (N⫽84) Pos (N⫽3) Not done (N⫽5,967)

1 2 48 2 69 84 3 5,939

0 0 0 0 0 0 0 28

1 2 45 2 69 84 2 5,954

Other (N⫽6,054)

Procedure or Positive Test 0 0 3 0 0 0 1 13

*Results of any noninvasive testing in the ED are shown.

patients.34 The CRUSADE initiative (Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes with Early Implementation of ACC/AHA Guidelines) is much larger in scope, with over 100,000 records.35 However, generalizability is again limited because enrollment requires patients to manifest high-risk features of non–ST-segment elevation acute coronary syndrome and therefore excludes many ED patients who are just suspected of having acute coronary syndrome without high-risk features such as ST-segment changes or positive cardiac biomarker results. Although many data have been obtained to describe practice patterns and outcomes for acute coronary syndrome patients, these studies are not fully representative of the ED chest pain patient population, in which upwards of 40% are ultimately discharged home (Table 6). Clinical trial databases such as GUSTO (Global Utilization of Tissue-Plasminogen Activator for Occluded Coronary Arteries) and TIMI (Thrombolysis in Myocardial Infarction) are also limited because of standardization of patient care, the inclusion only of higher-risk patients, and the randomized nature of therapeutic options.26 The i*trACS registry reported here is the largest known data set to include ED patients with a clinical suspicion of having acute coronary syndrome across the entire spectrum of disease. Our results show the importance of including a broad crosssection of patients when contemporary ED practice is considered. For example, about 20% of patients initially considered to have possible acute coronary syndrome did not have cardiac biomarker tests. The majority of these (92%) patients had a normal or nondiagnostic ECG result; 86% had a normal or nondiagnostic ECG result and a final diagnosis other than acute coronary syndrome (Table 5). We also identified 142 patients who had a normal or nondiagnostic initial ECG result and no cardiac biomarker tests but who were subsequently diagnosed with acute myocardial infarction, non–ST-segment elevation myocardial infarction, or unstable angina by the emergency physician. Conversely, among patients with an ECG diagnostic for myocardial infarction, half had normal cardiac biomarker results and a quarter had a final ED diagnosis other Volume , .  : December 

than acute coronary syndrome. Of patients initially considered high risk, 16% had negative biomarker results and were discharged home. These groups of patients represent those for whom a change in the suspected risk of acute coronary syndrome occurred as a result of the evaluation performed by the ED physician. Their inclusion is fundamental to improving our understanding of ED decisionmaking in acute coronary syndrome. In summary, the i*trACS data set contains a wealth of information that can be used for understanding the complex of clinical care of the patients with undifferentiated chest pain. For example, the relationships between ECG findings, cardiac biomarkers, invasive and noninvasive testing, treatments, and both inhospital and 30-day outcomes can be evaluated with these data. We expect this description of the patient population and accompanying clinical data to raise many questions because this is the very purpose of the registry. Hypothesis generation and exploration using the available information can enhance patient care through improving our understanding of such things as risk stratification, health disparities, and treatment interactions, among others. Supervising editor: Michael L. Callaham, MD Author contributions: The i*trACS project was conceived and designed by CVP, JWH, JEH, JDK, WFP, BT, EKW, and WBG. CVP, VA, DD, JWH, JEH, JDK, S-HL, WFP, BT, EKW, and WBG were responsible for data collection. CJL prepared and analyzed the data, and CJL, CVP, JHH, and WBG drafted the manuscript. All authors provided critical revision of the manuscript for intellectual content. CJL had full access to the data and takes full responsibility for the integrity and analysis of the data. CJL takes responsibility for the paper as a whole. Funding and support: The i*trACS project was supported in part by Millenium Pharmaceuticals and Schering-Plough Pharmaceuticals. Annals of Emergency Medicine 675

Internet Tracking Registry of Acute Coronary Syndromes Publication dates: Received for publication November 2, 2005. Revisions received March 15, 2006, and April 4, 2006. Accepted for publication April 24, 2006. Available online October 2, 2006.

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13.

Reprints not available from the authors. Address for correspondence: Christopher J. Lindsell, PhD, Department of Emergency Medicine, University of Cincinnati Medical Center, PO Box 670769, Cincinnati, OH 45267-0769; 513-558-6937, fax 513-558-0943; E-mail [email protected].

14.

15.

16.

REFERENCES 1. McCaig LF, Burt CW. National Hospital Ambulatory Medical Care Survey: 2002 Emergency Department Summary: Advance Data from Vital and Health Statistics: No. 340. Hyattsville, MD: National Center for Health Statistics; 2004. 2. Gibler WB, Young GP, Hedges JR, et al. Acute myocardial infarction in chest pain patients with nondiagnostic ECGs: serial CK-MB sampling in the emergency department: the Emergency Medicine Cardiac Research Group. Ann Emerg Med. 1992;21: 504-512. 3. Balk EM, Ioannidis JP, Salem D, et al. Accuracy of biomarkers to diagnose acute cardiac ischemia in the emergency department: a meta-analysis. Ann Emerg Med. 2001;37:478-494. 4. Canto JG, Shlipak MG, Rogers WJ, et al. Prevalence, clinical characteristics, and mortality among patients with myocardial infarction presenting without chest pain. JAMA. 2000;283:32233229. 5. Braunwald E, Antman EM, Beasley JW, et al. ACC/AHA 2002 guideline update for the management of patients with unstable angina and non-ST-segment elevation myocardial infarction: summary article: a report of the American College of Cardiology/ American Heart Association Task Force on Practice Guidelines (Committee on the Management of Patients with Unstable Angina). J Am Coll Cardiol. 2002;40:1366-1374. 6. Antman EM, Anbe DT, Armstrong PW, et al. ACC/AHA guidelines for the management of patients with ST-elevation myocardial infarction: a report of the American College of Cardiology/ American Heart Association Task Force on Practice Guidelines (Committee to Revise the 1999 Guidelines for the Management of Patients with Acute Myocardial Infarction). J Am Coll Cardiol. 2004;44:e1-e211. 7. American College of Emergency Physicians. Clinical policy: critical issues in the evaluation and management of adult patients presenting with suspected acute myocardial infarction or unstable angina. Ann Emerg Med. 2000;35:521-544. 8. 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. 9. Miller CD, Lindsell CJ, Khandelwal S, et al. Is the initial diagnostic impression of “noncardiac chest pain” adequate to exclude cardiac disease? Ann Emerg Med. 2004;44:565-574. 10. Goldman L, Cook EF, Brand DA, et al. A computer protocol to predict myocardial infarction in emergency department patients with chest pain. N Engl J Med. 1988;318:797-803. 11. Selker HP, Griffith JL, D’Agostino RB. A time-insensitive predictive instrument for acute myocardial infarction mortality: a multicenter study. Med Care. 1991;29:1196-1211. 12. Hollander JE, Blomkalns AL, Brogan GX, et al, for the Multidisciplinary Standardized Reporting Criteria Task Force, Standardized Reporting Criteria Working Group of Emergency Medicine Cardiac Research and Education Group–International. Standardized reporting guidelines for studies evaluating risk

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stratification of emergency department patients with potential acute coronary syndromes. Ann Emerg Med. 2004;44:589-598. Miller CD, Lindsell CJ, Khandelwal S, et al. Is the initial diagnostic impression of “noncardiac chest pain” adequate to exclude cardiac disease? Ann Emerg Med. 2004;44: 565-574. Hiestand BC, Prall DM, Lindsell CJ, et al. Insurance status and the treatment of myocardial infarction at academic centers. Acad Emerg Med. 2004;11:343-348. Freda BJ, Peacock WF, Lindsell CJ, et al. Outcomes in HF patients with elevated cardiac markers of ischemia. [abstract]. J Card Fail. 2002;8:S54. Blomkalns AL, Lindsell CJ, Chandra A, et al. Can electrocardiographic criteria predict adverse cardiac events and positive cardiac markers? Acad Emerg Med. 2003;10: 205-210. Venkat A, Hoekstra J, Lindsell C, et al. The impact of race on the acute management of chest pain. Acad Emerg Med. 2003;10: 1199-1208. Miller CD, Lindsell CJ, Anantharaman V, et al. Performance of a cardiac risk stratification tool in Asian patients with chest pain. Acad Emerg Med. 2005;12:423-430. Messerley D, Heistand BC, Lindsell CJ, et al. A comparison of the clinical presentations of diabetic patients vs non-diabetic patients with MI and NSTE ACS [abstract]. Acad Emerg Med. 2002;9:372. Messerley D, Heistand BC, Lindsell CJ, et al. A comparison of the use of ACI/TIPI score to predict ACS in diabetics vs nondiabetics [abstract]. Acad Emerg Med. 2002;9:373. Peacock WF, Lindsell CJ, Gibler WB, et al. Small changes in serial troponins portend acute adverse outcomes [abstract]. Acad Emerg Med. 2002;9:370. Peacock WF, Lindsell CJ, Gibler WB, et al. The relation of ischemia markers to coronary artery occlusion in heart failure patients [abstract]. J Card Fail. 2002;8:S70. Diercks DB, Kirk JD, Lindsell CJ, et al. Compliance with guidelines for door-to-ECG time in patients with chest pain suspicious for myocardial infarction [abstract]. Acad Emerg Med. 2002;9:371-372. Diercks DB, Kirk JD, Lindsell CJ, et al. Relationship between time to ECG acquisition and adverse cardiac events in patients with unstable angina or non-ST elevation myocardial infarction [abstract]. Acad Emerg Med. 2003;10:516. Storrow AB, Lindsell CJ, Collins SP, et al. Relationship between time to emergency department cardiac marker results and adverse cardiac events [abstract]. Acad Emerg Med. 2004;11:570. GRACE Investigators. Rationale and design of the GRACE (Global Registry of Acute Coronary Events) project: a multinational registry of patients hospitalized with acute coronary syndromes. Am Heart J. 2001;141:190-199. Franklin K, Goldberg RJ, Spencer F, et al, for the GRACE Investigators. Implications of diabetes in patients with acute coronary syndromes: the Global Registry of Acute Coronary Events. Arch Intern Med. 2004;164:1457-1463. Eagle KA, Lim MJ, Dabbous OH, et al, for the GRACE Investigators. A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry. JAMA. 2004; 291:2727-2733. Mehta RH, Sadiq I, Goldberg RJ, et al, for the GRACE Investigators. Effectiveness of primary percutaneous coronary intervention compared with that of thrombolytic therapy in elderly patients with acute myocardial infarction. Am Heart J. 2004;147: 253-259. Budaj A, Brieger D, Steg PG, et al, for the GRACE Investigators. Global patterns of use of antithrombotic and antiplatelet therapies in patients with acute coronary syndromes: insights

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Lindsell et al from the Global Registry of Acute Coronary Events (GRACE). Am Heart J. 2003;146:999-1006. 31. Montalescot G, Van de Werf F, Gulba DC, et al, for the GRACE Investigators. Stenting and glycoprotein IIb/IIIa inhibition in patients with acute myocardial infarction undergoing percutaneous coronary intervention: findings from the Global Registry of Acute Coronary Events (GRACE). Catheter Cardiovasc Interv. 2003;60:360-367. 32. Yan AT, Tan M, Fitchett D, et al; Canadian Acute Coronary Syndromes Registry Investigators. One-year outcome of patients after acute coronary syndromes (from the Canadian Acute Coronary Syndromes Registry). Am J Cardiol. 2004;94: 25-29.

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Internet Tracking Registry of Acute Coronary Syndromes 33. Fox KA, Cokkinos DV, Deckers J, et al. The ENACT study: a pan-European survey of acute coronary syndromes: European Network for Acute Coronary Treatment. Eur Heart J. 2000;21: 1440-1449. 34. Collinson J, Flather MD, Fox KA, et al. Clinical outcomes, risk stratification and practice patterns of unstable angina and myocardial infarction without ST elevation: Prospective Registry of Acute Ischaemic Syndromes in the UK (PRAIS-UK). Eur Heart J. 2000;21:1450-1457. 35. Hoekstra JW, Pollack CV Jr, Roe MT, et al. Improving the care of patients with non-ST-elevation acute coronary syndromes in the emergency department: the CRUSADE initiative. Acad Emerg Med. 2002;9:1146-1155.

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APPENDIX E1. DATA FOR SINGAPORE.

Table E3. Chest pain descriptors.* Descriptor

Table E1. Demographics and medical history.* Characteristic Age, y (mean, SD) Female Male Black White Hispanic Asian American Indian Unknown race Current or recent smoker Cocaine user Amphetamine user Hypertension Family history of CAD Dyslipidemia CAD Diabetes Angina CHF

All Visits Nⴝ3,528

Index Visit Only Nⴝ3,218

56 (15) 1,349 (38.2) 2,179 (61.8) 1 (0.0) 4 (0.1) 4 (0.1) 3,502 (99.3) 6 (0.2) 11 (0.3) 700 (19.8) 0 (0) 2 (0.1) 1,659 (47.0) 324 (9.2) 1,117 (31.7) 1,052 (29.8) 877 (24.9) 11 (0.3) 112 (3.2)

55 (15) 1,243 (38.6) 1,975 (61.4) 1 (0.0) 4 (0.1) 3 (0.1) 3,197 (99.7) 2 (0.1) 11 (0.3) 637 (19.8) 0 (0) 2 (0.1) 1,440 (44.7) 258 (8.0) 943 (29.3) 825 (25.6) 753 (23.4) 10 (0.3) 78 (2.4)

CAD, Coronary artery disease; CHF, congestive heart failure. *Frequencies and percentages are given unless otherwise indicated. Proportions of all visits are given. Data are also given for only the index visit.

Table E2. Presenting vital signs and symptoms.* Percentiles Vital Sign Systolic BP (mm Hg) Diastolic BP (mm Hg) Respiratory rate Pulse rate O2 saturation

5

25

50

75

95

101 56 15 54 95

122 69 16 66 97

139 78 18 76 98

161 88 18 88 99

193 103 20 108 100

BP, Blood pressure. *Patients could have more than 1 symptom. The following symptoms are reported as No. (%): dyspnea, 1,378 (39.1); nausea, 324 (9.2); diaphoresis, 959 (27.2); dizziness, 420 (11.9); weakness, 130 (3.7); palpitations, 179 (5.1); other, 41 (1.2).

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Chest pain constant Chief complaint of chest pain Chest pain reproduced by palpation Chest pain worse than usual angina Primary location of pain Midchest Left chest No pain Diffuse chest Right chest Epigastrium Left arm Back Neck/jaw Right arm Leg Pain radiating to† Left arm Back Neck/jaw Left chest Right arm Other Diffuse chest Right chest Abdomen Leg Epigastrium Quality of chest pain Pressure Stabbing Other Aching Squeezing Burning Numbness Crushing Tearing

No.

%

2,189 3,037 152 279

62.0 86.1 4.3 7.9

1,872 1,072 73 267 167 38 11 16 10 1 1

53.1 30.4 2.1 7.6 4.7 1.1 0.3 0.5 0.3 0.0 0.0

351 172 255 38 96 47 28 23 7 4 30

41.7 20.5 30.3 4.5 11.4 5.6 3.3 2.7 0.8 0.5 3.6

748 119 1,518 327 466 126 36 197 6

21.2 3.4 43.0 9.3 13.2 3.6 1.0 5.6 0.2

*Proportions of all visits are given. Patients could report more than 1 pain quality and more than 1 location of pain radiation. Some patients did not report any radiation of pain. † Data reported for only 841 patients.

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Table E4. ECG findings.* Known to Be Old Finding Time to ECG (min) Rate Rhythm

ST-segment elevation ST-segment depression

T-wave inversion

Left bundle-branch block Right bundle-branch block Diagnostic category†

Finding

All ECGs

(Median, interquartile range) (Median, interquartile range) Sinus rhythm Atrial fibrillation/flutter Supraventricular tachycardia VT/VF Second-degree II or third-degree AV block Other/undetermined 1–2 mm ⬎2 mm 0.5–1 mm 1–2 mm ⬎2 mm Flattening 1–5 mm ⬎5 mm Yes Yes AMI Acute ischemia Early repolarization Nondiagnostic Normal

17 (12–26) 75 (64–86) 3134 (96.6) 63 (1.9) 2 (0.1) 4 (0.1) 10 (0.3) 30 (0.9) 382 (11.8) 242 (7.5) 278 (8.6) 212 (6.5) 116 (3.6) 587 (18.1) 682 (21.0) 67 (2.1) 41 (1.3) 93 (2.9) 300 (9.3) 410 (12.6) 156 (4.8) 945 (29.1) 1,432 (44.2)

No.

(%)

20

(3.2)

11

(1.8)

39

(2.9)

3 2

(7.3) (2.2)

AMI, Acute myocardial infarction; VT/VF, ventricular tachycardia/ventricular fibrillation. *Numbers are given as frequencies and percentages unless otherwise indicated. Proportions are based on the number of patients with all ECG findings (N⫽3,243). Diagnostic category is based on the emergency physicians’ interpretation, whereas interpretation is based on the final reading in the medical record. † These categories are not the same as those recommended in the Standardized Reporting Guidelines. Diagnostic categories are based on the emergency physician’s impression and are not based on defined criteria.

Table E5. Cardiac biomarkers tested in the ED.* Marker TnT Myoglobin CK-MB

No.

Positive†

Positive, %

639 771 3110

22 40 352

3.4 5.2 10.3

*Serial markers were not tested. † For cardiac troponin T, the cutoff used was 0.1 ␮g/L; for CK-MB, it was 6 ␮g/L; and for myoglobin, it was 85 ␮g/L.

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Table E6. Relationship between ECG findings, cardiac biomarkers, and final ED diagnosis for patients with an ECG diagnostic category and a final ED diagnosis recorded (N⫽3,356). Final ED Diagnosis Cardiac Biomarkers

ST-Elevation MI

Non–ST-Elevation MI/UA

Stable Angina

Other

⫺ (N⫽167) ⫹ (N⫽121) Not done (N⫽26) ⫺ (N⫽335) ⫹ (N⫽65) Not done (N⫽24) ⫺ (N⫽160) ⫹ (N⫽6) Not done (N⫽5) ⫺ (N⫽837) ⫹ (N⫽86) Not done (N⫽66) ⫺ (N⫽1,313) ⫹ (N⫽81) Not done (N⫽64)

63 52 8 5 9 0 0 0 0 11 6 2 6 6 1

56 41 13 168 35 9 10 2 1 187 42 18 137 22 13

15 4 2 53 11 4 3 0 0 99 11 5 107 7 1

33 24 3 109 10 11 147 4 4 540 27 41 1,063 46 49

ECG Diagnostic Category MI (N⫽314)

Ischemia (N⫽242)

Early repolarization (N⫽171)

Nondiagnostic (N⫽989)

Normal (N⫽1,458)

MI, Myocardial infarction; UA, unstable angina.

Table E7. Patient ED course stratified by initial impression for the 3,528 patients with both initial impression and disposition available. Disposition From ED Initial Impression

Cardiac Markers

Sestamibi

Home

ICU

OR

Cath. Lab

Floor

Died in ED

Transferred

AMA

Acute MI (N⫽254)

Neg (N⫽132) Pos (N⫽91) Not done (N⫽31)

Unstable angina/non– Q-wave MI (N⫽492)

Neg (N⫽398) Pos (N⫽65)

Not done (N⫽132) Not done (N⫽91) Not done (N⫽28) Neg (N⫽3) Not done (N⫽398) Pos (N⫽1) Not done (N⫽64) Not done (N⫽29) Neg (N⫽72) Pos (N⫽13) Not done (N⫽596) Neg (N⫽1) Pos (N⫽2) Not done (N⫽83) Not done (N⫽28) Neg (N⫽248) Pos (N⫽16) Not done (N⫽1,001) Neg (N⫽11) Pos (N⫽1) Not done (N⫽79) Not done (N⫽56) Neg (N⫽34) Pos (N⫽1) Not done (N⫽439) Not done (N⫽48) Not done (N⫽53)

0 0 0 3 17 0 1 0 68 2 160 1 2 3 4 244 4 660 8 0 16 25 33 1 298 10 34

83 67 16 0 41 0 20 3 0 0 19 0 0 18 2 0 0 14 0 0 15 3 0 0 10 12 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

46 24 6 0 311 1 39 22 2 11 319 0 0 48 13 2 12 153 2 1 39 11 0 0 63 18 6

0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

2 0 0 0 24 0 2 1 1 0 88 0 0 12 6 2 0 130 1 0 7 8 0 0 52 5 5

1 0 1 0 5 0 2 3 1 0 10 0 0 2 3 0 0 44 0 0 2 9 1 0 16 3 7

High-risk chest pain (N⫽795)

Not done (N⫽29) Neg (N⫽681)

Pos (N⫽86)

Low-risk chest pain (N⫽1,412)

Not done (N⫽28) Neg (N⫽1,265)

Pos (N⫽91)

Noncardiac chest pain (N⫽575)

Not done (N⫽56) Neg (N⫽474)

Pos (N⫽48) Not done (N⫽53)

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Table E8. Hospital course for admitted patients, stratified by admitting diagnosis.* Findings at Follow-up Final ED Diagnosis ST-elevation MI (N⫽168)

Noninvasive Testing Neg (N⫽11)

Cath Lab Findings

Pos (N⫽12)

Pos (N⫽9) Not done (N⫽2) Neg (N⫽1) Pos (N⫽5) Not done (N⫽6)

Not done (N⫽154)

Neg (N⫽22) Pos (N⫽82) Not done (N⫽50)

Non–ST-elevation MI/UA (N⫽739)

Neg (N⫽47)

Pos (N⫽38)

Not done (N⫽654)

Neg (N⫽1) Pos (N⫽9) Not done (N⫽37) Neg (N⫽3) Pos (N⫽7) Not done (N⫽28) Neg (N⫽52) Pos (N⫽232) Not done (N⫽17)

Stable angina (N⫽259)

Neg (N⫽13)

Pos (N⫽7) Not done (N⫽239)

Neg (N⫽1) Pos (N⫽1) Not done (N⫽11) Pos (N⫽3) Not done (N⫽4) Neg (N⫽22) Pos (N⫽59) Not done (N⫽158)

Other (N⫽297)

Neg (N⫽13)

Pos (N⫽18)

Not done (N⫽266)

Neg (N⫽2) Pos (N⫽2) Not done (N⫽9) Neg (N⫽2) Pos (N⫽3) Not done (N⫽13) Neg (N⫽15) Pos (N⫽84) Not done (N⫽167)

CABG

No Death or MI

Death or MI

No Procedures or Positive Tests

Procedure or Positive Test

No (N⫽9) No (N⫽2) No (N⫽1) No (N⫽5) No (N⫽5) Yes (N⫽1) No (N⫽20) Yes (N⫽2) No (N⫽80) Yes (N⫽2) No (N⫽47) Yes (N⫽3) No (N⫽1) No (N⫽7) Yes (N⫽2) No (N⫽37) No (N⫽3) No (N⫽6) Yes (N⫽1) No (N⫽28) No (N⫽50) Yes (N⫽2) No (N⫽211) Yes (N⫽21) No (N⫽353) Yes (N⫽17) No (N⫽1) No (N⫽1) No (N⫽11) No (N⫽3) No (N⫽4) No (N⫽21) Yes (N⫽1) No (N⫽49) Yes (N⫽10) No (N⫽150) Yes (N⫽8) No (N⫽2) No (N⫽2) No (N⫽9) No (N⫽2) No (N⫽3) No (N⫽12) Yes (N⫽1) No (N⫽15) No (N⫽78) Yes (N⫽6) No (N⫽160) Yes (N⫽7)

5 1 1 1 3 1 15 2 41 2 24 3 1 4 1 37 3 3 0 23 45 2 151 21 316 16 1 1 10 3 4 20 1 46 10 142 8 2 1 8 2 2 10 1 13 59 5 140 7

4 1 0 4 2 0 5 0 39 0 23 0 0 3 1 0 0 3 1 5 5 0 60 0 37 1 0 0 1 0 0 1 0 3 0 8 0 0 1 1 0 1 2 0 2 19 1 20 0

8 2 1 5 5 0 19 0 77 1 47 1 1 6 0 37 3 6 0 28 49 1 198 3 329 1 1 1 11 3 4 20 0 49 1 142 1 2 2 9 2 3 12 0 15 74 2 152 0

1 0 0 0 0 1 1 2 3 1 0 2 0 1 2 0 0 0 1 0 1 1 13 18 24 16 0 0 0 0 0 1 1 0 9 8 7 0 0 0 0 0 0 1 0 4 4 8 7

*Data are given for the 1,472 patients known to have been admitted. Findings at follow-up are shown.

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Table E9. Findings for the 1,704 patients known to have been discharged from the ED, stratified by final ED diagnosis. No noninvasive testing was done in the ED. Findings at Follow-up Final ED Diagnosis ST-elevation MI (N⫽2) Non–ST-elevation MI/unstable angina (N⫽23) Stable angina (N⫽54) Other (N⫽1,625)

677.e5 Annals of Emergency Medicine

No Death or MI

Death or MI

No Procedures or Positive Tests

Procedure or Positive Test

2 22 54 1,620

0 1 0 5

2 20 53 1,607

0 3 1 18

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APPENDIX E2. Table E10. Presenting vital signs and symptoms.* Percentiles Vital Sign Systolic BP (mm Hg) Diastolic BP (mm Hg) Respiratory rate Pulse rate O2 saturation Temperature (°F)

5

25

50

75

95

103 55 16 59 92 96.0 (35.6°C)

125 70 16 73 96 97.0 (36.1°C)

142 80 18 84 98 98.0 (36.7°C)

159 91 20 97 99 98.6 (37.0°C)

194 110 28 120 100 99.6 (37.6°C)

BP, Blood pressure. *Patients could have more than 1 symptom. The following symptoms are reported as No. (%): dyspnea, 8,131 (57.3); nausea, 4,410 (31.1); diaphoresis, 3,854 (27.2); dizziness, 3,534 (24.9); weakness, 3,492 (24.6); palpitations, 2,004 (14.1); other, 990 (7.0).

Table E11. Chest pain descriptors.* Descriptor Chest pain constant Chief complaint of chest pain Chest pain reproduced by palpation Chest pain worse than usual angina Primary location of pain Midchest Left chest No pain Diffuse chest Right chest Epigastrium Left arm Back Neck/jaw Right arm Leg Pain radiating to Left arm Back Neck/jaw Left chest Right arm Other Diffuse chest Right chest Abdomen Leg Epigastrium Quality of chest pain Pressure Stabbing Other Aching Squeezing Burning Numbness Crushing Tearing

No.

%

5,572 9,618 1,143 561

39.3 67.8 8.1 4.0

5,295 4,997 1,028 979 727 545 264 186 84 49 25

37.3 35.2 7.3 6.9 5.1 3.8 1.9 1.3 0.6 0.3 0.2

3,608 1,836 1,811 1,229 981 673 566 404 359 323 260

25.4 12.9 12.8 8.7 6.9 4.7 4.0 2.8 2.5 2.3 1.8

5,765 3,051 2,236 1,551 1,456 977 533 436 115

40.6 21.5 15.8 10.9 10.3 6.9 3.8 3.1 0.8

*Proportions of all visits are given. Patients could report more than 1 pain quality and more than 1 location of pain radiation. Some patients did not report any radiation of pain.

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Figure E1. Data collection form used for this study. Multiple forms were used for patients with repeated tests and findings available.

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Figure E2. Data collection form used for this study. Multiple forms were used for patients with repeated tests and findings available. Volume 48, .  : December 

Annals of Emergency Medicine 677.e8

Figure E3. Age distribution for US patients enrolled in the registry

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