Clinical Investigations

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1 Clinical Investigations The Usage Patterns of Cardiac Bedside Markers Employing Point-of-Care Testing for Troponin in Non-ST-Segment Elevation Acute Coronary Syndrome: Results from CRUSADE Address for correspondence: Kevin M. Takakuwa, MD Thomas Jefferson University Hospital 1020 Sansom Street Suite 239, Thompson Building Philadelphia, PA Kevin M. Takakuwa, MD; Fang-Shu Ou, MS; Eric D. Peterson, MD, MPH; Charles V. Pollack, Jr., MD, MA; W. Frank Peacock, MD; James W. Hoekstra, MD; E. Magnus Ohman, MD; W. Brian Gibler, MD; Andra L. Blomkalns, MD; Matthew T. Roe, MD, MHS Thomas JeffersonUniversityHospital (Takakuwa), Philadelphia, Pennsylvania; Duke University Medical CenterandDukeClinicalResearchInstitute (Ou, Peterson, Ohman, Roe), Durham, North Carolina; Pennsylvania Hospital, University of Pennsylvania School of Medicine (Pollack), Philadelphia, Pennsylvania; Cleveland Clinic (Peacock), Cleveland, Ohio; Wake Forest University Health Sciences (Hoekstra), Winston-Salem, North Carolina; University of Cincinnati College of Medicine (Gibler, Blomkalns), Cincinnati, Ohio. Background: Point-of-care (POC) testing may expedite the care of emergency department (ED) patients suspected of having acute coronary syndromes (ACS). We evaluated the use patterns of cardiac bedside markers or POC testing for troponin in patients with non-st-segment elevation (NSTE) ACS. Methods: NSTE ACS data were collected from the Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes with Early Implementation of the American College of Cardiology/American Heart Association (ACC/AHA) Guidelines (CRUSADE) registry. We compared hospital and patient characteristics, in-hospital events, and process-of-care variables between hospitals to those that did not use POC testing in 50% of enrolled patients. We examined characteristics, in-hospital events, and process-of-care differences between patients with negative vs positive troponin POC testing results. Results: Of 568 hospitals, 74 (16,276 patients) had high POC usage compared with 197 hospitals ( patients) with no troponin POC usage. From the high POC usage hospitals, patients had recorded troponin POC test results. Hospitals with high POC usage had a shorter ED length of stay and were less likely to administer aspirin, β-blockers, and heparin during the first 24 hours of care. Patients with positive troponin POC results were more often older, minority, female, Medicare-insured, diabetic, and renally impaired. They had fewer electrocardiograms within 10 minutes but were more likely to get aspirin, β-blockers, glycoprotein IIb/IIIa inhibitors, and heparin within 24 hours of arrival. They also had longer ED lengths of stay, received fewer in-hospital and interventional procedures, and had more adverse clinical events. Conclusion: Differences existed in how hospitals used POC testing and the care given based on those results. Positive POC results are associated with expedited and higher use of anti-ischemic therapies. Introduction Emergency department (ED) care of patients with possible acute coronary syndrome (ACS) is complex. With issues such as ED crowding, cost containment, and capitated reimbursement, evaluating patients for ACS and rapidly admitting, observing, or discharging them without error CRUSADE is funded by the Schering-Plough Corporation. Bristol-Myers Squibb/Sanofi-Aventis Pharmaceuticals Partnership provides additional funding support. Millennium Pharmaceuticals, Inc., also funded this work. has become increasingly important. One technological advancement that has facilitated more rapid evaluation of patients with chest pain syndrome is point-of-care (POC) testing for biomarkers, which measures a combination of troponin, myoglobin, and MB fraction of creatine kinase. Cardiac POC testing can reduce length of stay in the ED, 1,2 cost of patient visits, 3 and time to anti-ischemic therapy. 4 Although there have been correlational studies between laboratory and POC tests, 5 relatively few studies have examined the ability of POC tests to predict clinical outcomes. Of these, POC testing appears to be sensitive for determining ACS. 6 8 However, the 2007 American College 498 Clin. Cardiol. 32, 9, (2009) Received: March 31, 2009 Accepted: April 30, 2009

2 of Cardiology/American Heart Association (ACC/AHA) guidelines for the management of non-st-segment elevation myocardial infarction (NSTEMI) state that to date, bedside testing has not succeeded in becoming widely accepted or applied. 9 This may be due to the qualitative or semiquantitative nature of many POC tests or perceptions that POC testing is less accurate than laboratory testing. Presently, we do not know the use patterns of bedside markers on a large scale or how they are being used in specific patient populations. We examine the utilization patterns of cardiac bedside markers between hospitals that frequently use and do not use POC testing and within-hospital differences based on a negative vs positive POC result using the Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes with Early Implementation of the ACC/AHA Guidelines (CRUSADE) database. We also explore the association between troponin bedside marker results and specific process-of-care variables: ED length of stay, use of ACS medications within the first 24 hours of care, and time to administration of platelet glycoprotein (GP) IIb/IIIa inhibitors. Methods Study Design This is a retrospective analysis of data collected for the CRU- SADE initiative. CRUSADE is a voluntary, observational data collection and quality improvement initiative focusing on clinical information regarding acute care and outcomes of high risk patients with non-st-segment elevation (NSTE) ACS (which includes unstable angina and NSTEMI). Initiated in November 2001, with retrospective data collection starting in January 2001, CRUSADE closed its registry on December 31, The CRUSADE initiative was designed to track guidelines adherence, provide feedback about performance, and develop quality improvement tools to improve adherence to the ACC/AHA guideline recommendations. 10 Each hospital received institutional review board approval prior to participation in CRUSADE. All information was collected anonymously during initial hospitalization without any patient identifiers; individual patient consent was not required. Study Setting and Population The CRUSADE registry included 568 hospitals in the United States. Patients were eligible for inclusion in CRUSADE if they presented to a participating hospital with acute ischemic symptoms lasting for 10 minutes while at rest within 24 hours of arrival. In addition, they had to have 1 of the following diagnostic features recommended in the ACC/AHA guidelines to distinguish patients with an increased risk of adverse outcomes: ST-segment depression 0.5 mm, transient ST-segment elevation 0.5 to 1.0 mm lasting for <10 minutes, or positive cardiac biomarkers defined as elevated troponin I or T or creatine kinase (CK)-MB greater than the upper limit of normal for the local laboratory assay used at each institution. Patients enrolled in the CRUSADE initiative from January 1, 2001 to December 31, 2006, who were not transferred into CRUSADE hospitals and who presented at an ED were eligible for this study. We excluded patients who died within 24 hours of arrival because they might not have had the opportunity to receive acute medications and a bedside assay. We also excluded patients from hospitals with <30 patients because we needed to have a stable estimate of the percentage of bedside troponin used in each hospital. Of the 503 CRUSADE hospitals with 30 patients after exclusions, we compared ED patients from hospitals with high bedside troponin use (defined as 50% usage, n = 74) to those with no use (n = 197). We therefore excluded hospitals that used bedside troponin markers between 0.1% to 49.99% of the time (n = 232), and we considered only troponin analysis because CK-MB POC results were infrequently used. Data Collection and Processing Process-of-care and in-hospital outcomes data were collected from participating CRUSADE hospitals through retrospective chart review. Data collected included the use of acute medications, use and timing of invasive cardiac procedures, laboratory results, physician and hospital characteristics, and discharge therapies and interventions. For GP IIb/IIIa inhibitors, the exact time at which the medication was started was recorded. For all other medications including aspirin, β-blockers, and heparin only whether the medication was administered within 24 hours of presentation was considered. Variables collected included age, race, sex, insurance status, comorbid illness, medical history, clinical presentation, medical therapies and associated major contraindications, use and timing of cardiac procedures, laboratory results, in-hospital outcomes, and discharge therapies and interventions. Participating institutions were instructed to submit consecutive eligible patients to the CRUSADE database. Outcome Measurements The primary outcome measures were between-hospital differences, patient baseline, and process-of-care differences in high vs no POC usage, and patient and process-of-care differences stratified by positive vs negative POC results. Primary Data Analyses Hospital characteristics were compared across 2 hospital groups: either no POC troponin used or high percentage of POC testing used. Baseline characteristics, treatment Clin. Cardiol. 32, 9, (2009) 499

3 Clinical Investigations continued profiles, procedure use, and clinical outcomes were compared across the 2 hospital groups and separately across 2 patient groups defined by the POC troponin results among patients who received POC testing. Continuous variables are presented as medians with interquartile percentiles, and categorical variables are expressed as percentages. To test for independent patient baseline characteristics, in-hospital care patterns, and outcomes with respect to different hospital groups as well as different patient groups, Wilcoxon rank-sum testing was used for continuous variables and a Pearson χ 2 test was used for categorical variables. Results A total of patients initially evaluated in the ED of 271 participating CRUSADE sites met the inclusion/exclusion criteria. Of these, 50,782 patients from 197 hospitals were from hospitals that had 0% usage of bedside markers and served as our reference group. Of the remaining 16,276 patients from 74 hospitals, 13,154 patients had a bedside marker test administered (6.7% of the total CRUSADE population), and 12,604 had recorded results (Figure 1). There were no significant differences in characteristics between hospitals with high bedside marker usage compared with those that had none. Specifically, there were no differences by geographic region (West, Northeast, Midwest, or South), ability to provide cardiac catheterization or cardiothoracic surgical services, academic hospital status, or hospital bed size. In comparing patients in hospitals with no cardiac POC usage to those in hospitals with high POC usage, we found patients who were older, female, and white with private/health maintenance organization (HMO) insurance to be more likely to come from hospitals with no POC usage. We also found higher POC usage associated with patients who had the classic cardiac risk factors of diabetes, hypertension, and smoking, and in sites with higher rates of in-hospital procedures and adverse clinical events (Table 1). As for process-of-care variables, hospitals with high vs no POC usage more frequently met the 10-minute window to obtain an electrocardiogram (ECG), were more likely to administer clopidogrel and GP IIb/IIIa inhibitor within the first 24 hours of care, and had decreased ED length of stay. They were less likely to provide ACC/AHA-recommended medications within 24 hours, including aspirin, β-blocker, and heparin (Table 2). Comparing POC results within hospitals that had high percentages of POC testing use, we found that those patients who had positive POC results were older, female, minority, Medicare-insured, diabetic, and renally impaired. They had fewer percutaneous coronary interventions (PCI) and higher in-hospital adverse clinical event rates (Table 3). Those with negative POC results had more prior cardiac disease (prior myocardial infarction [MI], PCI, coronary artery bypass grafting [CABG]) and significant ECG findings. Regarding process-of-care variables, patients with positive POC test results had fewer ECGs within 10 minutes of arrival,were more often administered aspirin,β-blocker, and heparin within 24 hours of arrival, and longer ED lengths of stay (Table 4). We were also able to determine that GP IIb/IIIa inhibitors were administered not only more frequently with positive POC test results but more quickly when any POC test was performed, regardless of test results. When no POC test was performed, it took a median of 330 minutes (interquartile range [IQR]: minutes) to receive GP IIb/IIIa inhibitor. In contrast, when the POC test was administered and the result was negative, it took a median of 323 minutes (IQR: min). However, when the POC test was positive, GP IIb/IIIa inhibitors were given significantly faster at 243 minutes (IQR: min). This represents a faster time to administration by 87 minutes compared with when no POC test was performed a substantial time savings. Discussion Our results show that while there were no differences in the types of hospitals that used or did not use POC testing, there were differences in the types of patients receiving POC testing that likely reflect differences in hospital demographics. It would be interesting to know what factors played into a hospital s decision regarding whether to make cardiac POC testing available, how it was used, and, for those hospitals with discretionary use of the test, how the decision of whether to administer a POC test was made. Unfortunately, this information cannot be ascertained from a large database study. We do know that hospitals that had high usage of POC testing also had decreased ED lengths of stay. This is intuitive because waits for cardiac marker results are presumably shorter, and a disposition on whether to admit or discharge is made more quickly. Our results are consistent with a study that showed cardiac POC testing use decreased length of ED stay. 1 We found that hospitals with high POC testing had increased usage of newer treatments like clopidogrel and GP IIb/IIIa inhibitors while having decreased usage of older, standard treatments like aspirin and β-blockers. Perhaps these hospitals were lulled into a false sense of a non- ACS diagnosis by an initial POC test result rather than appreciating the features of an ACS patient s history. Clearly, a single negative troponin does not rule out ACS but could be detrimental if the clinician emphasizes test results over clinical history. An alternative explanation could be that hospitals that adopted POC testing were also the early adopters of newer, state-of-the-art approaches to cardiac care that may have overlooked standard therapies. 500 Clin. Cardiol. 32, 9, (2009)

4 568 CRUSADE hospitals 147,610 patients arrived to ED Excluded: Death within 24 hours (646 patients) Hospitals <30 patients (990 pts, 65 hosp) Hospitals with % POC usage (78,916 patients, 232 hospitals) 271 hospitals 67,058 patients 74 high POC usage hospitals 16,276 patients 197 no POC usage hospitals 50,782 patients Excluded 3122 patients without POC test performed 13,154 POC tests performed Excluded 550 patients without POC recorded results 12,604 POC test results 6419 patients negative POC result 6185 patients positive POC result Figure 1. Flow chart of patients. Abbreviations: ACC, American College of Cardiology; AHA, American Heart Assocation; CRUSADE, Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes with Early Implementation of the ACC/AHA Guidelines registry; ED, emergency department; POC, point-of-care. When looking at patient characteristics and hospital events by negative vs positive POC test results, we found some expected results: older, diabetic, and renally impaired patients were more likely to have positive POC results. Patients with positive POC results unexpectedly received fewer PCIs. Patients with positive POC results also had longer ED lengths of stay, which might reflect the time to provide more medical care to patients who were sicker (or Clin. Cardiol. 32, 9, (2009) 501

5 Clinical Investigations continued Table 1. Patient Characteristics, Presenting Features, In-Hospital Procedures, and Clinical Events in Hospitals with No POC Usage Compared with High POC Usage Demographics No POC Testing Used (n = a ) High Percentage of POC Testing Used (n = b ) P Value Age c 69 (57, 79) 68 (56, 79) < Female sex White < Insurance status HMO/private < Medicare Military/VAMC Medicaid Self/none BMI c 27.6 (24.2, 31.9) 27.5 (24.2, 31.7) 0.07 Medical history Diabetes mellitus Hypertension < Current/recent smoker < Dyslipidemia < Peripheral arterial disease Prior MI < Prior PCI Prior CABG Prior CHF Prior stroke Renal insufficiency Presenting signs and symptoms Heart rate on admission c 84 (71, 100) 84 (71, 100) Systolic BP on admission c 146 (126, 168) 145 (124, 167) < who were perceived to be sicker) and higher in-hospital adverse events such as shock, death, or MI. We do not know why patients with negative POC results would more often receive in-hospital and interventional procedures (such as percutaneous interventions) than would those patients with positive results. One explanation Table 1. (Continued) ECG findings No POC Testing Used (n = a ) High Percentage of POC Testing Used (n = b ) P Value Transient ST-elevation < ST-depression Both Neither Signs of CHF < ACS type NSTEMI < UA In-hospital procedures Diagnostic cath < Cath <48h ofarrival < PCI < CABG In-hospital clinical events Cardiogenic shock CHF Death < Death or MI < Data are presented as percentages unless otherwise indicated. a From 197 hospitals. b From 74 hospitals. c Presented as median (25th, 75th percentile). Abbreviations: ACS, acute coronary syndromes; BMI, body mass index; BP, blood pressure; CABG, coronary artery bypass grafting; cath, cardiac catheterization; CHF, congestive heartfailure;ecg, electrocardiograph; HMO, health maintenance organization; MI, myocardial infarction; NSTEMI, non-st-elevation MI; PCI, percutaneous coronary intervention; POC, point-of-care; UA, unstable angina; VAMC, Veterans Administration medical center. is that the positive POC group may have had more contraindications to PCI, possibly due to advanced age or renal insufficiency. Another explanation is that the positive POC group, comprising more women, may have refused these advanced procedures. This is consistent with 2 studies that showed women were more likely to refuse a theoretical PCI and CABG even with a physicianrecommended test. 11,12 Another possibility is that the decision for PCI was based more on patients overall clinical status rather than their POC results. We would hope that greater frequency of PCI in the negative POC results group is not the result of insurance status or ability to pay for 502 Clin. Cardiol. 32, 9, (2009)

6 Table 2. Process-of-Care Variables in Hospitals with no POC Usage Compared with High POC Usage Time to ECG No POC Testing Used (n = a ) High Percentage of POC Testing Used (n = b ) P Value Within 10 min of arrival < Medications within 24 h Aspirin < Any heparin β-blocker < Clopidogrel < GP IIb/IIIa < Time of care ED length of stay (hours) c 4.2 (2.9, 6.5) 3.9 (2.6, 6.0) < Data are presented as percentages unless otherwise indicated. a From 197 hospitals. b From 74 hospitals. c Presented as median (25th, 75th percentile) Abbreviations: ED, emergencydepartment; GP, glycoprotein; POC, pointof-care. Table 3. Characteristics, Presenting Features, In-Hospital Procedures, and Clinical Events of Patients with Negative vs Positive POC Results Demographics Negative POC (n = 6419 a ) Positive POC (n = 6185 a ) P Value Age b 67 (56, 77) 69 (57, 80) < Female sex White < Insurance status HMO/private < Medicare Military/VAMC Medicaid Self/none BMI b 27.9 (24.5, 32.0) 27.3 (23.9, 31.4) < Medical history Diabetes mellitus Hypertension Current/recent smoker Table 3. (Continued) Negative POC (n = 6419 a ) Positive POC (n = 6185 a ) P Value Dyslipidemia < Peripheral arterial disease Prior MI Prior PCI < Prior CABG < Prior CHF Prior stroke < Renal insufficiency < Presenting signs and symptoms Heart rate on admission b 83 (70, 98) 85 (72, 101) < Systolic BP on admission b 149 (127, 170) 142 (121, 162) < ECG findings Transient ST-elevation < ST-depression Both Neither Signs of CHF < ACS type NSTEMI < UA In-hospital procedures Diagnosis cath < Cath <48h ofarrival < PCI < CABG In-hospital clinical events Cardiogenic shock < CHF < Death < Death or MI < Data are presented as percentages unless otherwise indicated. a From 74 hospitals. b Presented as median (25th, 75th percentile). Abbreviations: ACS, acute coronary syndromes; BMI, body mass index; BP, blood pressure; CABG, coronary artery bypass grafting; cath, cardiac catheterization; CHF, congestive heartfailure;ecg, electrocardiograph; HMO, health maintenance organization; MI, myocardial infarction; NSTEMI, non-st-elevation MI; PCI, percutaneous coronary intervention; POC, point-of-care; UA, unstable angina; VAMC, Veterans Administration medical center. Clin. Cardiol. 32, 9, (2009) 503

7 Clinical Investigations continued Table 4. Process-of-Care Variables in Patients with Negative Compared with Positive POC Results Time to ECG Negative POC (n = 6419 a ) Positive POC (n = 6185 a ) P Value Within 10 min of arrival < Medications within 24 h Aspirin < Any heparin < β-blocker < Clopidogrel < GP IIb/IIIa < Time of care ED length of stay (h) b 3.7 (2.4, 5.8) 4.0 (2.7, 6.1) < Data are presented as percentages unless otherwise indicated. a From 74 hospitals. b Presented as median (25th, 75th percentile). Abbreviations: ED, emergencydepartment; GP, glycoprotein; POC, pointof-care. the procedure because patients had more HMO/private insurance. Furthermore, we would hope that this is not the result of racial bias because the group that received more PCI included more white patients, and blacks are known to receive less PCI than whites. 13,14 We were not surprised that the presence of some classic cardiac risk factors had no correlation with positive POC tests because they have limited value for diagnosing ACS in an ED setting. 15 In contrast, we were surprised that prior cardiac disease and ECG findings did not correspond with positive POC results because ST-segment depression is associated with adverse outcomes. 16,17 Our results showed that patients with positive POC results were given ACC/AHA-recommended treatments more frequently: aspirin, β-blockers, heparin, and GP IIb/IIIa inhibitors. We believe this may be due to an early positive POC result prompting rapid ED treatment. It is possible that patients who had negative initial POC testing may have had a delay to treatment or were not treated with acute medications because they were not considered acutely ill. In a busy ED, the treating physician may have simply neglected acute medications as he or she moved on to care for other patients. We are uncertain of the significance of increased usage of GP IIb/IIIa inhibitors in the positive POC results group because they received fewer PCIs, and the benefits of GP IIb/IIIa inhibitors are greatest for NSTEMI patients undergoing PCI. 9,18 The rate of use in the positive group was higher than in a previous study showing patients treated with GP IIb/IIIa inhibitors had lower unadjusted in-hospital mortality. 19 Because having any POC test performed was associated with more rapid treatment with GP IIb/IIIa inhibitors, it is possible that the POC test may have prompted that action, particularly when the test was positive. Limitations Cardiac POC testing was not widely used in this study. Hence, even though we had the largest sampling of NSTE ACS patients with POC testing, the sample size was relatively limited. There are many types of commercially available POC tests, and this study did not record the type of bedside marker test performed. Also, there is no standardization for what determines a positive vs negative POC result, and there are no quality control measures in place to determine if the POC test was administered and interpreted correctly. Because this is a volunteer registry study, participation was self-selecting; thus, this is a nonrandom sampling of hospitals and patients. There was wide hospital variation not only in the use of POC testing but in within-hospital usage as reflected in the percentage of patients in which these tests were performed. We excluded patients who died within 24 hours, which may have resulted in selection bias of the results. Finally, this study is subject to all of the limitations inherent to observational database studies; in particular, the inability to determine cause-and-effect relationships between variables. Conclusion There was a high variability of POC testing usage between hospitals and characteristics of patients. As POC technology improves and increasing patient volumes force earlier risk stratification of ED chest pain patients, we suspect there will be a greater role for these types of assays. References 1. Singer AJ, Ardise J, Gulla J, et al. Point-of-care testing reduces length of stay in emergency department chest pain centers. Ann Emerg Med. 2005;45: Ryan RJ, Lindsell CJ, Hollander JE, et al. A multicenter randomized controlled trial comparing central laboratory and point-of-care cardiac marker testing strategies: the disposition impacted by serial point of care markers in Acute Coronary Syndromes (DISPO-ACS) Trial. Ann Emerg Med. 2009;53: Apple FS, Chung AY, Kogut ME, et al. Decreased patient charges following implementation of point-of-care cardiac troponin monitoring in acute coronary syndrome patients in a community hospital cardiology unit. Clinica Chimica Acta. 2006;370: Renaud B, Maison P, Ngako A, et al. Impact of point-of-care testing in the emergency department evaluation and treatment of patients with suspected acute coronary syndromes. Acad Emerg Med. 2008;15: Bock JL, Singer AJ, Thode HC Jr. Comparison of emergency department patient classification by point-of-care and central laboratory methods for cardiac troponin I. Am J Clin Pathol. 2008;130: Clin. Cardiol. 32, 9, (2009)

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