Heart failure (HF) is a major chronic condition that significantly impacts humanl health. Coronary heart disease (CHD) is the leading cause of HF. Developing risk prediction models for HF in patients with CHD is crucial for enabling healthcare professionals to identify high-risk populations and implement timely interventions.

To systematically evaluate risk prediction models for HF with CHD in Chinese patients, serving as a reference for the development, selection, and dissemination of relevant predictive models.

CNKI, Wanfang Data, VIP, SinoMed, PubMed, Embase, Web of Science and the Cochrane Library were searched for relevant studies on risk prediction models for HF with CHD in Chinese patients up to October 2024. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias and applicability of the included studies using the Prediction Model Risk of Bias Assessment Tool (PROBAST).

A total of 27 studies were included, reporting 64 risk prediction models. The area under the receiver operating characteristic (ROC) curve (AUC) or these models ranged from 0.511 to 0.989, with 63 models achieving an AUC>0.7, indicating good predictive performance. However, PROBAST assessment revealed that all 27 studies had a high risk of bias and low applicability. Key predictive factors included age, left ventricular ejection fraction, history of diabetes, history of hypertension, N-terminal pro-B-type natriuretic peptide, and Gensini score.

The stability and external validity of existing risk prediction models for HF with CHD in Chinese patients require further validation through prospective, large-scale studies. Future model development should adhere strictly to PROBAST guidelines to ensure the design and implementation of high-quality, generalizable predictive models.

心力衰竭是严重危害人类健康的重大慢性疾病，冠心病是心力衰竭最常见的病因，针对冠心病并发心力衰竭的危险因素构建风险预测模型，有助于医务人员对心力衰竭高危人群进行早期识别和干预。

系统评价我国冠心病患者并发心力衰竭风险预测模型，为相关风险预测模型的构建、选择与推广提供参考。

检索中国知网、维普网、万方数据库知识服务平台、中国生物医学文献服务系统、PubMed、Cochrane Library、Web of Science、Embase数据库与我国冠心病患者并发心力衰竭风险预测模型相关的研究，检索时限为建库至2024年10月。由2名研究者独立筛选文献并提取信息，使用预测模型偏倚风险评价工具（PROBAST）评估纳入研究的偏倚风险及适用性。

共纳入27篇文献，报告了64个风险预测模型的开发情况，模型的受试者工作特征（ROC）曲线下面积（AUC）为0.511~0.989，其中63个模型AUC>0.7，提示模型整体预测性能较好；偏倚风险评估工具评估结果显示，纳入的27篇文献均为高偏倚风险，适用性偏低。年龄、左心室射血分数、糖尿病病史、高血压病史、N末端B型钠尿肽前体、Gensini评分是模型中纳入的重要预测因子。

当前我国冠心病患者并发心力衰竭风险预测模型的稳定性和外推性有待行前瞻性、大样本研究验证，后续建模应当严格遵循PROBAST指南设计实施研究，以开发可推广性强的高质量预测模型。