Abstract:

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.

Key words: heart failure, lung infection, influencing factors, decision tree