1. Development and validation of dynamic models to predict postdischarge mortality risk in patients with acute myocardial infarction: results from China Acute Myocardial Infarction Registry
- Author
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Yang Wang, Xuan Zhang, Rui Fu, Jingang Yang, Haiyan Xu, Xiaojin Gao, Yuejin Yang, Hui Sun, Yunqing Ye, Junxing Lv, Chuangshi Wang, Qiuting Dong, Xinxin Yan, and Yanyan Zhao
- Subjects
Medicine - Abstract
Objectives The risk of adverse events and prognostic factors are changing in different time phases after acute myocardial infarction (AMI). The incidence of adverse events is considerable in the early period after AMI hospitalisation. Therefore, dynamic risk prediction is needed to guide postdischarge management of AMI. This study aimed to develop a dynamic risk prediction instrument for patients following AMI.Design A retrospective analysis of a prospective cohort.Setting 108 hospitals in China.Participants A total of 23 887 patients after AMI in the China Acute Myocardial Infarction Registry were included in this analysis.Primary outcome measures All-cause mortality.Results In multivariable analyses, age, prior stroke, heart rate, Killip class, left ventricular ejection fraction (LVEF), in-hospital percutaneous coronary intervention (PCI), recurrent myocardial ischaemia, recurrent myocardial infarction, heart failure (HF) during hospitalisation, antiplatelet therapy and statins at discharge were independently associated with 30-day mortality. Variables related to mortality between 30 days and 2 years included age, prior renal dysfunction, history of HF, AMI classification, heart rate, Killip class, haemoglobin, LVEF, in-hospital PCI, HF during hospitalisation, HF worsening within 30 days after discharge, antiplatelet therapy, β blocker and statin use within 30 days after discharge. The inclusion of adverse events and medications significantly improved the predictive performance of models without these indexes (likelihood ratio test p
- Published
- 2023
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