Aim . To identify factors and develop a clinical risk model (nomogram) for in-hospital mortality in patients with acute myocardial infarction (AMI) after timely early invasive diagnosis and revascularization of infarct-related artery (IRA). Material and methods : We conducted a prospective, single-center observational study that included 712 consecutive patients with AMI [median age 65 (interquartile range 56-74 years), 61% were male, 47.8% with ST-elevation] who underwent coronary angiography <24 hours after symptom onset and successful endovascular revascularization of IRA. The primary endpoint was in-hospital mortality. Logistic regression analysis was used to identify independent prognostic risk factors for in-hospital mortality. Based on the multivariate analysis, a nomogram was developed to predict outcome. The discriminative ability of the nomogram was assessed by calculating the area under the receiver operating characteristic (ROC) curve. Results . The in-hospital mortality rate was 5.06%. The most common cause of in-hospital mortality was acute heart failure (AHF, 75%), followed by myocardial rupture with cardiac tamponade (11.1%). Multivariate analysis revealed that age (odds ratio (OR) 1.07, 95% confidence intervals (CI) 1.01-1.14, p=0.027), Killip class (OR 2.95, 95% CI 1.67-5.23, p<0.001), hemoglobin at admission (OR 0.97, 95% CI 0.95-0.99, p=0.006), and left ventricular ejection fraction (LVEF) ≤36% (OR 8.87, 95% CI 2.95-26.69, p<0.001), were independent predictors of adverse outcome. The identified predictors were included a nomogram, which demonstrated excellent discrimination in predicting in-hospital mortality (area under the ROC curve = 0.949, 95% CI: 0.925-0.972, p<0.001, sensitivity: 91.3%, specificity: 89.9%) and good calibration (Hosmer-Lemeshow test, p=0.93). Conclusions . Age, hemoglobin at admission, Killip class and left ventricular ejection fraction were independent predictors of in-hospital mortality in acute MI. The most common etiology of in-hospital mortality was AHF. The nomogram for prediction of in-hospital mortality demonstrated high prognostic potential, allowing for the identification of patients at high-risk of adverse outcome, and targeted therapeutic strategies may be needed to improve the survival of patients with acute MI.
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Hoang et al. (2024) studied this question.
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