Study objective: We compare the diagnostic accuracy of 3 methods--attribute matching, physician's written unstructured estimate, and a logistic regression formula (Acute Coronary Insufficiency-Time Insensitive Predictive Instrument, ACI-TIPI)--of estimating a very low pretest probability (< or = 2%) for acute coronary syndromes in emergency department (ED) patients evaluated in chest pain units.
Methods: We prospectively studied 1,114 consecutive patients from 3 academic EDs, evaluated for acute coronary syndrome. Physicians collected data required for pretest probability assessment before protocol-driven chest pain unit testing. A pretest probability greater than 2% was considered "test positive." The criterion standard was the outcome of acute coronary syndrome (death, myocardial infarction, revascularization, or > 60% stenosis prompting new treatment) within 45 days, adjudicated by 3 independent reviewers.
Results: Fifty-one of 1,114 enrolled patients (4.5%; 95% confidence interval [CI] 3.4% to 6.0%) developed acute coronary syndrome within 45 days, including 4 of 991 (0.4%; 95% CI 0.1% to 1.0%) patients, discharged after a negative chest pain unit evaluation result, who developed acute coronary syndrome. Unstructured estimate identified 293 patients with pretest probability less than or equal to 2%, 2 had acute coronary syndrome, yielding sensitivity of 96.1% (95% CI 86.5% to 99.5%) and specificity of 27.4% (95% CI 24.7% to 30.2%). Attribute matching identified 304 patients with pretest probability less than or equal to 2%; 1 had acute coronary syndrome, yielding a sensitivity of 98.0% (95% CI 89.6% to 99.9%) and a specificity of 26.1% (95% CI 23.6% to 28.7%). ACI-TIPI identified 56 patients; none had acute coronary syndrome, yielding sensitivity of 100% (95% CI 93.0% to 100%) and specificity of 6.1% (95% CI 4.7% to 7.9%).
Conclusion: In a low-risk ED population with symptoms suggestive of acute coronary syndrome, patients with a quantitative pretest probability less than or equal to 2%, determined by attribute matching, unstructured estimate, or logistic regression, may not require additional diagnostic testing.