Risk Prediction Models and Risk Factors for Early Heart Failure after Acute Myocardial Infarction

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Objective This article collects and measures relevant clinical indicators of patients with acute myocardial infarction, studies and analyzes potential predictors of heart failure in the early (30 days) after acute myocardial infarction, explores the value of possible factors for early heart failure, and establish a simple risk assessment model has a certain predictive value for the occurrence of early heart failure after acute myocardial infarction. Methods A total of 318 patients who were admitted to the Second Hospital of Lanzhou University for acute myocardial infarction from March 2018 to June 2019 were included in this study. The data collected includes general demographic data, clinical data, laboratory data, and 14 possible predictors. All patients included in the study were followed up for 30 days on an outpatient or telephone basis. The patients were divided into heart failure group (89 cases) and non-heart failure group (229 cases) according to the follow-up results. We used univariate Logistic regression analysis for the screening of various data to analyze the potential predictors related to early heart failure after acute myocardial infarction. We use the Lasso-logistic regression model to further filter the variables to obtain the variables with the best predictive characteristics and incorporate them into the multi-factor logistic regression model. A nomogram of early heart failure after acute myocardial infarction was constructed based on the Logistic multivariate regression model. The prediction model was evaluated by calculating the consistency index (C-index),the area under the receiver's working characteristic curve (AUC), and drawing the calibration curve of the prediction model. Results Comparison of data between the heart failure group and the non-heart failure group: There were statistically significant differences between the two groups in terms of male, age, smoking history, lung rale within 24 hours of admission,time from symptoms appear to arriving at the hospital, BNP, LVEF, atrial fibrillation, multi-vessel stenosis,preoperative disease, TIMI classification levels before treatment, Galectin-3, IMA, IL-10, sST2(P Conclusions The independent risk factors related to early heart failure after acute myocardial infarction include:gender, age, lung rale within 24 hours of admission, time from symptoms appear to arriving at the hospital, BNP, LVEF, atrial fibrillation, multi-vessel stenosis, Galectin-3, sST2.We established a simple risk prediction model to predict the occurrence of heart failure in the early (30 days) after acute myocardial infarction. Keywords acute myocardial infarction, heart failure, risk factors, risk prediction model