A 1-h Combination Algorithm Allows Fast Rule-Out and Rule-In of Major Adverse Cardiac Events.

Background: A 1-h algorithm based on high-sensitivity cardiac troponin T (hs-cTnT) testing at presentation and again 1 h thereafter has been shown to accurately rule out acute myocardial infarction.
Objectives: The goal of the study was to evaluate the diagnostic accuracy of the 1-h algorithm when supplemented with patient history and an electrocardiogram (ECG) (the extended algorithm) for predicting 30-day major adverse cardiac events (MACE) and to compare it with the algorithm using hs-cTnT alone (the troponin algorithm).
Methods: This prospective observational study enrolled consecutive patients presenting to the emergency department (ED) with chest pain, for whom hs-cTnT testing was ordered at presentation. Hs-cTnT results at 1 h and the ED physician's assessments of patient history and ECG were collected. The primary outcome was an adjudicated diagnosis of 30-day MACE defined as acute myocardial infarction, unstable angina, cardiogenic shock, ventricular arrhythmia, atrioventricular block, cardiac arrest, or death of a cardiac or unknown cause.
Results: In the final analysis, 1,038 patients were included. The extended algorithm identified 60% of all patients for rule-out and had a higher sensitivity than the troponin algorithm (97.5% vs. 87.6%; p < 0.001). The negative predictive value was 99.5% and the likelihood ratio was 0.04 with the extended algorithm versus 97.8% and 0.17, respectively, with the troponin algorithm. The extended algorithm ruled-in 14% of patients with a higher sensitivity (75.2% vs. 56.2%; p < 0.001) but a slightly lower specificity (94.0% vs. 96.4%; p < 0.001) than the troponin algorithm. The rule-in arms of both algorithms had a likelihood ratio >10.
Conclusions: A 1-h combination algorithm allowed fast rule-out and rule-in of 30-day MACE in a majority of ED patients with chest pain and performed better than the troponin-alone algorithm.
(Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)