Predicting Major Adverse Events in Patients With Acute Myocardial Infarction.

Area of Science:

• Cardiology
• Diagnostic Accuracy
• Biomarker Analysis

Background:

• Early and accurate detection of short-term major adverse cardiac events (MACE) in patients with suspected acute myocardial infarction (AMI) remains a critical unmet clinical need.
• Current diagnostic strategies require optimization to improve patient outcomes and healthcare efficiency.

Purpose of the Study:

• To evaluate if incorporating clinical judgment and electrocardiogram (ECG) findings with the European Society of Cardiology (ESC) high-sensitivity cardiac troponin (hs-cTn) 0/1 hour algorithm enhances MACE prediction.
• To compare the diagnostic performance of the ESC hs-cTn 0/1 hour algorithm against an extended algorithm for MACE and MACE + unstable angina (UA) prediction.

Main Methods:

• A prospective, multicenter diagnostic study enrolled 3,123 patients presenting to emergency departments with suspected AMI.
• The primary endpoint was 30-day MACE (all-cause death, cardiac arrest, AMI, cardiogenic shock, sustained ventricular arrhythmia, high-grade AV block).
• The secondary endpoint was 30-day MACE + UA requiring early revascularization.

Main Results:

• The ESC hs-cTn 0/1 hour algorithm successfully triaged more patients for rule-out (60%) compared to the extended algorithm (45%), maintaining similar 30-day MACE rates (0.6% vs. 0.4%) and negative predictive values (99.4% vs. 99.6%).
• Fewer patients were ruled-in using the ESC hs-cTn 0/1 hour algorithm (16%) versus the extended algorithm (26%), but with a higher positive predictive value (76.6% vs. 59%).
• Similar performance trends were observed using both hs-cTnT and hs-cTnI assays.

Conclusions:

• The ESC hs-cTn 0/1 hour algorithm demonstrates a superior balance between efficacy and safety for predicting 30-day MACE.
• The extended algorithm may be preferable for ruling out MACE + UA, highlighting a nuanced approach based on clinical endpoints.
• The study, Advantageous Predictors of Acute Coronary Syndromes Evaluation (APACE), provides valuable insights into optimizing AMI diagnosis.