AI Article Synopsis

  • This study aimed to improve the detection of major adverse cardiac events (MACE) in patients suspected of having an acute myocardial infarction (AMI) by combining clinical judgment and ECG findings with a specific troponin testing algorithm.
  • Involving over 3,123 patients, it found that the European Society of Cardiology (ESC) hs-cTnT 0/1 h algorithm was more effective at ruling out AMI without increasing the rate of missed MACE cases compared to an extended algorithm.
  • While the hs-cTnT algorithm contributed to fewer false positives (rule-in), it outperformed in high predictive values for identifying true positives, indicating it could be a valuable tool in emergency settings for evaluating heart attack risks

Article Abstract

Background: Early and accurate detection of short-term major adverse cardiac events (MACE) in patients with suspected acute myocardial infarction (AMI) is an unmet clinical need.

Objectives: The goal of this study was to test the hypothesis that adding clinical judgment and electrocardiogram findings to the European Society of Cardiology (ESC) high-sensitivity cardiac troponin (hs-cTn) measurement at presentation and after 1 h (ESC hs-cTn 0/1 h algorithm) would further improve its performance to predict MACE.

Methods: Patients presenting to an emergency department with suspected AMI were enrolled in a prospective, multicenter diagnostic study. The primary endpoint was MACE, including all-cause death, cardiac arrest, AMI, cardiogenic shock, sustained ventricular arrhythmia, and high-grade atrioventricular block within 30 days including index events. The secondary endpoint was MACE + unstable angina (UA) receiving early (≤24 h) revascularization.

Results: Among 3,123 patients, the ESC hs-cTnT 0/1 h algorithm triaged significantly more patients toward rule-out compared with the extended algorithm (60%; 95% CI: 59% to 62% vs. 45%; 95% CI: 43% to 46%; p < 0.001), while maintaining similar 30-day MACE rates (0.6%; 95% CI: 0.3% to 1.1% vs. 0.4%; 95% CI: 0.1% to 0.9%; p = 0.429), resulting in a similar negative predictive value (99.4%; 95% CI: 98.9% to 99.6% vs. 99.6%; 95% CI: 99.2% to 99.8%; p = 0.097). The ESC hs-cTnT 0/1 h algorithm ruled-in fewer patients (16%; 95% CI: 14.9% to 17.5% vs. 26%; 95% CI: 24.2% to 27.2%; p < 0.001) compared with the extended algorithm, albeit with a higher positive predictive value (76.6%; 95% CI: 72.8% to 80.1% vs. 59%; 95% CI: 55.5% to 62.3%; p < 0.001). For 30-day MACE + UA, the ESC hs-cTnT 0/1 h algorithm had a higher positive predictive value for rule-in, whereas the extended algorithm had a higher negative predictive value for the rule-out. Similar findings emerged when using hs-cTnI.

Conclusions: The ESC hs-cTn 0/1 h algorithm better balanced efficacy and safety in the prediction of MACE, whereas the extended algorithm is the preferred option for the rule-out of 30-day MACE + UA. (Advantageous Predictors of Acute Coronary Syndromes Evaluation [APACE]; NCT00470587).

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Source
http://dx.doi.org/10.1016/j.jacc.2019.06.025DOI Listing

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