Heart failure (HF) is the most common complication of acute myocardial infarction (AMI), which seriously affects the prognosis and quality of life of patients. After successful revascularization, the risk of heart failure in patients with acute myocardial infarction is closely related to the state of coronary microcirculation, and the risk of heart failure also changes dynamically with the prognosis of patients. However, current heart failure prediction models only include routine baseline variables to assess short-and long-term risk and lack newly explored new risk factors for heart failure-coronary microcirculation function, there are static, single defects. Therefore, this study is intended to be based on patients with acute ST-segment elevation myocardial infarction who had an infarct artery in the anterior descending artery and underwent emergency percutaneous coronary intervention to open the culprit lesion within 12 hours, according to the multi-dimensional data of clinical epidemiology, serology, radiology, and microcirculation resistance index based on coronary angiography during hospitalization and 6 and 12 months after discharge, respectively, to construct a multimodal dynamic predictive model for heart failure risk at 0-24 months, 6-24 months, and 12-24 months after acute myocardial infarction, to explore the heart failure risk model based on the dynamic data of different outcome nodes of patients after myocardial infarction, and to achieve the goal of timely correction of heart failure risk of patients, which is multi-linear, dynamic and practical, to provide a stage-by-stage reference for follow-up.
This study aims to explore the heart failure risk model based on the dynamic data of patients with different outcome nodes after myocardial infarction to correct the heart failure risk of patients timely.