Comparative Evaluation of 2-Hour Rapid Diagnostic Algorithms for Acute Myocardial Infarction Using High-Sensitivity Cardiac Troponin T
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BACKGROUND: Symptoms of acute coronary syndrome account for a large proportion of emergency department (ED) visits and hospitalizations. High-sensitivity troponin can rapidly rule out or rule in acute myocardial infarction (AMI) within a short time of ED arrival. We sought to validate test characteristics and classification performance of 2-hour high-sensitivity troponin T (hsTnT) algorithms for the rapid diagnosis of AMI. METHODS: We included consecutive patients from 4 academic EDs with suspected cardiac chest pain who had hsTnT assays performed 2 hours apart (± 30 minutes) as part of routine care. The primary outcome was AMI at 7 days. Secondary outcomes included major adverse cardiac events (mortality, AMI, and revascularization). Test characteristics and classification performance for multiple 2-hour algorithms were quantified. RESULTS: Seven hundred twenty-two patients met inclusion criteria. Seven-day AMI incidence was 10.9% and major adverse cardiac event incidence was 13.7%. A 2-hour rule-out algorithm proposed by Reichlin and colleagues ruled out AMI in 59.4% of patients with 98.7% sensitivity and 99.8% negative predictive value (NPV). The 2-hour rule-out algorithm proposed by the United Kingdom National Institute for Health and Care Excellence ruled out AMI in 50.3% of patients with similar sensitivity and NPV. Other exploratory algorithms had similar sensitivity but marginally better classification performance. According to Reichlin et al., the 2-hour rule-in algorithm ruled in AMI in 16.5% of patients with 92.4% specificity and 58.5% positive predictive value. CONCLUSIONS: Two-hour hsTnT algorithms can rule out AMI with very high sensitivity and NPV. The algorithm developed by Reichlin et al. had superior classification performance. Reichlin and colleagues' 2-hour rule-in algorithm had poor positive predictive value and might not be suitable for early rule-in decision-making.
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