Predicting outcome in coronary disease statistical models versus expert clinicians

Lee, Kerry L.; Pryor, David B.; Harrell, Frank E.; Califf, Robert M.; Behar, Victor S.; Floyd, Robert W.; Morris, James J.; Waugh, Robert; Whalen, Robert E.; Rosati, Robert A.

doi:10.1016/0002-9343(86)90807-7

Cited by 129 publications

(45 citation statements)

References 32 publications

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“…11,13,14,31,56,57 One possible reason for the more supportive results of this analysis is that physicians were allowed to label patients across a spectrum of risk, which is more consistent with the pathophysiology of disease. With the advent of observation units, rapid MI rule-out protocols, and CT coronary angiography, the array of ACS risk-stratification options has increased.…”

Section: Discussionmentioning

confidence: 99%

Emergency Physician High Pretest Probability for Acute Coronary Syndrome Correlates with Adverse Cardiovascular Outcomes

Chandra

Lindsell

Diercks

et al. 2009

Academic Emergency Medicine

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Objectives: The value of unstructured physician estimate of risk for disease processes, other than acute coronary syndrome (ACS), has been demonstrated. The authors sought to evaluate the predictive value of unstructured physician estimate of risk for ACS in emergency department (ED) patients without obvious initial evidence of a cardiac event.Methods: This was a post hoc secondary analysis of the Internet Tracking Registry for Acute Coronary Syndromes (i*trACS), a prospectively collected multicenter data registry of patients over the age of 18 years presenting to the ED with symptoms of ACS between 1999 and 2001. In this registry, following patient history, physical exam, and electrocardiogram (ECG), the unstructured treating physician estimate of risk was recorded. A 30-day follow-up and a medical record review were used to determine rates of adverse cardiac events, death, myocardial infarction (MI), or revascularization procedure. The analysis included all patients with nondiagnostic ECG changes, normal initial biomarkers, and a non-MI initial impression from the registry and excluded those without complete data or who were lost to follow-up. Data were stratified by unstructured physician risk estimate: noncardiac, low risk, high risk, or unstable angina.Results: Of 15,608 unique patients in the registry, 10,145 met inclusion ⁄ exclusion criteria. Patients were defined as having unstable angina in 6.0% of cases; high risk, 23.5% of cases; low risk, 44.2%; and noncardiac, 26.3% of cases. Adverse cardiac event rates had an inverse relationship, decreasing from 22.0% (95% confidence interval [CI] = 18.8% to 25.6%) for unstable angina, 10.2% (95% CI = 9.0% to 11.5%) for those stratified as high risk, 2.2% (95% CI = 1.8% to 2.6%) for low risk, and to 1.8% (95% CI = 1.4% to 2.4%) for noncardiac. The relative risk (RR) of an adverse cardiac event for those with an initial label of unstable angina compared to those with a low-risk designation was 10.2 (95% CI = 8.0 to 13.0). The RR of an event for those with a high-risk initial impression compared to those with a low-risk initial impression was 4.7 (95% CI = 3.8 to 5.9). The risk of an event among those with a low-risk initial impression was the same as for those with a noncardiac initial impression (RR = 0.83, 95% CI = 0.6 to 1.2). Conclusions:In ED patients without obvious initial evidence of a cardiac event, unstructured emergency physician (EP) estimate of risk correlates with adverse cardiac outcomes.ACADEMIC EMERGENCY MEDICINE 2009; 16:740-748 ª

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Section: Discussionmentioning

confidence: 99%

Emergency Physician High Pretest Probability for Acute Coronary Syndrome Correlates with Adverse Cardiovascular Outcomes

Chandra

Lindsell

Diercks

et al. 2009

Academic Emergency Medicine

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“…Initial evaluation, including a history and physical examination and 12-lead ECG, is conclusive in only a minority of patients. 1,2 The use of cardiac markers has become standard to further risk-stratify such patients. Often this is done in a chest pain unit (CPU), following protocols for marker testing over 6 to 12 hours.…”

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confidence: 99%

Bedside Multimarker Testing for Risk Stratification in Chest Pain Units

2001

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Background-Earlier, rapid evaluation in chest pain units may make patient care more efficient. A multimarker strategy (MMS) testing for several markers of myocardial necrosis with different time-to-positivity profiles also may offer clinical advantages. Methods and Results-We prospectively compared bedside quantitative multimarker testing versus local laboratory results (LL) in 1005 patients in 6 chest pain units. Myoglobin, creatine kinase-MB, and troponin I were measured at 0, 3, 6, 9 to 12, and 16 to 24 hours after admission. Two MMS were defined: MMS-1 (all 3 markers) and MMS-2 (creatine kinase-MB and troponin I only).

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“…Table 1 demonstrates the survival times with medical and surgical therapy estimated from past experience with our patients at Duke. These estimated probabilities of survival at 1, 3, and 5 years are based on statistical models developed from our entire population of patients.17 18 The difference in survival with medical therapy is dramatic and the predicted benefit from surgery is quite different between the two patients. Because the randomized controlled trials have reported benefits only for the "average" patient, the clinician relying on this information alone is often ill-equipped to estimate the benefit of therapy for an individual patient.…”

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confidence: 99%

Beyond randomized clinical trials: applying clinical experience in the treatment of patients with coronary artery disease.

Califf¹,

Pryor²,

Greenfield³

1986

Circulation

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Predicting outcome in coronary disease statistical models versus expert clinicians

Cited by 129 publications

References 32 publications

Emergency Physician High Pretest Probability for Acute Coronary Syndrome Correlates with Adverse Cardiovascular Outcomes

Emergency Physician High Pretest Probability for Acute Coronary Syndrome Correlates with Adverse Cardiovascular Outcomes

Bedside Multimarker Testing for Risk Stratification in Chest Pain Units

Beyond randomized clinical trials: applying clinical experience in the treatment of patients with coronary artery disease.

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