急性心力衰竭再入院及死亡风险预测模型研究进展

心力衰竭是各种心脏疾病的严重和终末期表现，具有高住院率、高病死率等特点，已成为重要的公共卫生问题。急性心力衰竭患者出院后再入院率及死亡率是评价心力衰竭医疗质量的重要指标，基于此开展急性心力衰竭患者疾病预后风险预测研究，对量化疾病风险、落实分层管理、优化临床决策、提高生存质量、改善患者预后、全面提升我国急性心力衰竭医疗质量至关重要。近20年来，国外学者已开发出数十个急性心力衰竭再入院及死亡风险预测模型，我国学者也开发出了近十个基于中国人群的预测模型，但目前国内指南中尚无推荐使用的急性心力衰竭预后风险预测模型。本文旨在通过介绍国内外主要急性心力衰竭再入院和死亡风险预测模型，重点概述现有模型局限性及今后发展方向，包括整合多源数据、挖掘新兴生物标志物、构建多基因风险评分、优化机器学习方法、推进模型适用性调整及拓宽应用渠道等，以期为国内急性心力衰竭再入院和死亡风险预测模型相关研究提供思路。

Progress in research of models for predicting the risk of readmission and mortality among patients with acute heart failure

Heart failure is a serious and end-stage status of various heart diseases, characterized by comparatively high rate of readmission and mortality, and has become an important public health issue. The risk of readmission and mortality following discharge of an index hospitalization are key indicators to evaluate the quality of medical care among patients with acute heart failure. Therefore, it is important to carry out risk prediction research for patients with acute heart failure, quantify the disease risk, perform risk stratification, optimize clinical decision-making, elevate patients'' quality of life and prognosis, and comprehensively improve the medical quality of acute heart failure. During the past 20 years, foreign researchers have developed dozens of models to predict the risk of acute heart failure readmission and mortality, and Chinese researchers have also developed up to 10 models applicable to the Chinese population. However, there is no recommended risk prediction model for acute heart failure in current clinical guidelines across China. In this report, we aim to introduce the major models for predicting the risk of acute heart failure readmission and mortality from home and abroad, focus on putting forward limitations of established models, and initiating potential directions for future studies from the following aspects: integrate multi-source data, mine emerging biomarkers, establish polygenic risk scores, optimize machine learning methods, promote flexible adjustment, and broaden approaches that applicable for various scenarios. Accordingly, this study will help facilitate domestic research in predicting the risk of readmission and mortality among patients hospitalized for acute heart failure.