Rule-In and Rule-Out of Myocardial Infarction Using Cardiac Troponin and Glycemic Biomarkers in Patients with Symptoms Suggestive of Acute Coronary Syndrome
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BACKGROUND: Early rule-in/rule-out of myocardial infarction (MI) in patients presenting to the emergency department (ED) is important for patient care and resource allocation. Given that dysglycemia is a strong risk factor for MI, we sought to explore and compare different combinations of cardiac troponin (cTn) cutoffs with glycemic markers for the early rule-in/rule-out of MI. METHODS: We included ED patients (n = 1137) with symptoms suggestive of acute coronary syndrome (ACS) who had cTnI, high-sensitivity cTnI (hs-cTnI), hs-cTnT, glucose, and hemoglobin A1c (Hb A1c) measurements. We derived rule-in/rule-out algorithms using different combinations of ROC-derived and literature cutoffs for rule-in and rule-out of MI within 7 days after presentation. These algorithms were then tested for MI/cardiovascular death and ACS/cardiovascular death at 7 days. ROC curves, sensitivity, specificity, likelihood ratios, positive and negative predictive values (PPV and NPV), and CIs were determined for various biomarker combinations. RESULTS: MI was diagnosed in 133 patients (11.7%; 95% CI, 9.8-13.8). The algorithms that included cTn and glucose produced the greatest number of patients ruled out/ruled in for MI and yielded sensitivity ≥99%, NPV ≥99.5%, specificity ≥99%, and PPV ≥80%. This diagnostic performance was maintained for MI/cardiovascular death but not for ACS/cardiovascular death. The addition of hemoglobin A1c (Hb A1c) (≥6.5%) to these algorithms did not change these estimates; however, 50 patients with previously unknown diabetes may have been identified if Hb A1c was measured. CONCLUSIONS: Algorithms incorporating glucose with cTn may lead to an earlier MI diagnosis and rule-out for MI/cardiovascular death. Addition of Hb A1c into these algorithms allows for identification of diabetes. Future studies extending these findings are needed for ACS/cardiovascular death. ClinicalTrials.gov identifier: NCT01994577.
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