Construction and evaluation of nomogram model for individualized prediction of risk of major adverse cardiovascular events during hospitalization after percutaneous coronary intervention in patients with acute ST-segment elevation myocardial infarction

作者：Caoyang Fang, Zhenfei Chen, Jinig Zhang, Xiaoqin Jin, Mengsi Yang · 发表于：Frontiers in Cardiovascular Medicine · 年份：2022 · DOI：10.3389/fcvm.2022.1050785 · 被引用次数：35 · 研究领域：Acute Myocardial Infarction Research、Statistical Methods in Epidemiology、Sepsis Diagnosis and Treatment

Background Emergency percutaneous coronary intervention (PCI) in patients with acute ST-segment elevation myocardial infarction (STEMI) helps to reduce the occurrence of major adverse cardiovascular events (MACEs) such as death, cardiogenic shock, and malignant arrhythmia, but in-hospital MACEs may still occur after emergency PCI, and their mortality is significantly increased once they occur. The aim of this study was to investigate the risk factors associated with MACE during hospitalization after PCI in STEMI patients, construct a nomogram prediction model and evaluate its effectiveness. Methods A retrospective analysis of 466 STEMI patients admitted to our hospital from January 2018 to June 2022. According to the occurrence of MACE during hospitalization, they were divided into MACE group ( n = 127) and non-MACE group ( n = 339), and the clinical data of the two groups were compared; least absolute shrinkage and selection operator (LASSO) regression was used to screen out the predictors with non-zero coefficients, and multivariate Logistic regression was used to analyze STEMI Independent risk factors for in-hospital MACE in patients after emergency PCI; a nomogram model for predicting the risk of in-hospital MACE in STEMI patients after PCI was constructed based on predictive factors, and the C-index was used to evaluate the predictive performance of the prediction model; the Bootstrap method was used to repeat sampling 1,000 Internal validation was carried out for the se...