目的 分析老年左室射血分数降低型心力衰竭患者并发肺部感染的危险因素，并通过决策树CART算法建立老年左室射血分数降低型心力衰竭患者并发肺部感染的风险预警模型。 方法 回顾性选取2020年1月至2022年12月济南人民医院收治的320例老年左室射血分数降低型心力衰竭患者为研究对象，根据患者是否并发肺部感染将其分为感染组各非感染组，通过logistic回归模型和决策树CART模型构建预测老年左室射血分数降低型心力衰竭并发肺部感染的预测模型，采用5折交叉验证法进行内部验证，并对比模型的预测效能。 结果 320例老年左室射血分数降低型心力衰竭患者中，肺部感染发生率为30.94%。感染组和非感染组患者年龄、抽烟史、合并糖尿病、心功能分级、合并慢阻肺、侵入性操作、住院时间等资料对比差异有统计学意义（P < 0.05）。logistic回归分析结果显示，年龄≥75岁、抽烟史、合并糖尿病、心功能分级Ⅲ/Ⅳ级、合并慢阻肺、侵入性操作、住院时间≥ 14 d均是老年左室射血分数降低型心力衰竭患者并发肺部感染的独立危险因素（P < 0.05）。概率预测模型P = 1/［1+e-^{（-3.368+0.763*X1+0.814*X2+0.652*X3+1.085*X4+0.865*X5+1.027*X6+0.652*X7）}］，模型预测总体正确性为80.9%。Omnibus检验的结果显示P < 0.001。经过5折交叉验证，预测正确率为73.6%。决策树模型显示，有侵入性操作是老年左室射血分数降低型心力衰竭患者并发肺部感染最为重要的影响因素，信息增益为0.280。ROC结果显示，logistic回归模型的AUC值稍高于决策树（Z = 2.850，P = 0.004），两种模型的预测效能均为中等。 结论 年龄、抽烟史、合并糖尿病、心功能分级、合并慢阻肺、侵入性操作、住院时间均是老年左室射血分数降低型心力衰竭患者并发肺部感染的影响因素，本研究构建的决策树模型具有较好的风险预测效能，可为临床早期甄别及干预老年左室射血分数降低型心力衰竭患者临床治疗提供参考。

Objective To analyze the risk factors of pulmonary infection in elderly patients with heart failure with reduced left ventricular ejection fraction heart failure， and establish a risk predicting model of pulmonary infection in those patients by decision tree CART algorithm. Methods 320 elderly patients with heart failure with reduced left ventricular ejection fraction admitted from January 2020 to December 2022 were retrospectively selected as study objects， and were divided into an infection group and a non-infection group according to whether the patients were complicated with pulmonary infection. Logistic regression model and decision tree CART model were used to construct a prediction model of heart failure with reduced left ventricular ejection fraction complicated with pulmonary infection， and 5-fold cross-validation method was used for internal verification. The prediction efficiency of the models was compared. Results In the 320 patients， the incidence of pulmonary infection was 30.94%. The data on age， smoking history， diabetes mellitus， cardiac function grades， COPD， invasive procedures， length of hospital stay were compared between the infection and non-infection groups （P < 0.05）. logistic regression analysis showed that age of ≥ 75 years smoking history， complications with diabetes or/and COPD， cardiac function grade Ⅲ/Ⅳ， invasive procedures， and hospital stay of ≥14 days were independent risk factors for pulmonary infection in the patients （P < 0.05）. Probability forecasting model P = 1/［1 + e^{（-3.368+0.763*X1+0.814*X2+0.652*X3+1.085*X4+0.865*X5+1.027*X6+0.652*X7）}］， with an overall accurate rate of prediction of 80.9%. The Omnibus test showed P < 0.001. The accuracy of prediction was 73.6% after the cross-validation of 5 fold. The decision tree model showed that invasive procedures were the most important influencing factors for pulmonary infection in elderly patients with heart failure with reduced left ventricular ejection fraction， with an information gain of 0.280. The ROC showed that the AUC value of logistic regression model was slightly higher than that of the decision tree （Z = 2.850， P = 0.004）， and the prediction efficiency of both models was medium. Conclusions Age， smoking history， complications with diabetes mellitus or/and COPD， cardiac function grades， invasive procedures， and length of hospital stay are all influencing factors for pulmonary infection in elderly patients with heart failure with reduced left ventricular ejection fraction. The decision tree model constructed in this study has a better efficiency for risk prediction， and it can provide reference for early clinical screening and intervention of heart failure with reduced left ventricular ejection fraction.