全科护理2025，Vol.23Issue(14)：2615-2620,6.DOI:10.12104/j.issn.1674-4748.2025.14.005
基于决策树算法构建间质性肺疾病病人发生肺部感染预测模型
The prediction model of pulmonary infection in patients with interstitial lung disease constructed based on decision tree algorithm
摘要
Abstract
Objective:To explore the influencing factors of pulmonary infection in patients with interstitial lung disease(ILD)and to construct a decision tree model.Methods:A total of 220 ILD patients admitted to the hospital from January 2023 to January 2024 were selected as the study subjects.They were divided into an infection group and a non-infection group based on the occurrence of pulmonary infection.Logistic regression analysis was used to identify the risk factors for pulmonary infection in ILD patients.SPSS Modeler software was employed to construct a decision tree model for predicting pulmonary infection in ILD patients,and the predictive performance of the decision tree model was analyzed.Results:This study included 220 ILD patients,of whom 56 had pulmonary infection,resulting in an incidence rate of 25.45%.A total of 71 strains of pathogens were isolated,with Gram-negative bacteria being the most prevalent(66.20%),followed by Gram-positive bacteria(26.76%)and fungi(7.04%).Univariate analysis showed statistically significant differences(P<0.05)between the infection and non-infection groups in terms of combined broad-spectrum antibiotic use,glucocorticoid dose,patchy CT imaging features,sputum production,hypoproteinemia,CRP levels,and ESR.Logistic regression analysis identified combined broad-spectrum antibiotic use,glucocorticoid dose≥30 mg/d,sputum production,hypoproteinemia,high CRP levels,high ESR,and patchy CT imaging features as risk factors for pulmonary infection in ILD patients(P<0.05).The decision tree model selected six explanatory variables,combined broad-spectrum antibiotic use,sputum production,hypoproteinemia,CRP level,ESR,and patchy CT imaging features,with CRP level being the most important predictor.The area under the curve(AUC)of the decision tree model for predicting pulmonary infection in ILD patients was 0.857[95%CI(0.803,0.900)],which was higher than the AUC of the Logistic regression model 0.801[95%CI(0.742,0.851)],and the difference was statistically significant(P<0.05).Conclusion:Combined broad-spectrum antibiotic use,glucocorticoid dose≥30 mg/d,sputum production,hypoproteinemia,high CRP levels,high ESR,and patchy CT imaging features are risk factors for pulmonary infection in ILD patients.The decision tree prediction model for pulmonary infection in ILD patients constructed in this study demonstrates good predictive performance.关键词
决策树算法/间质性肺疾病/肺部感染/预测模型/回归分析Key words
decision tree algorithm/interstitial lung disease/lung infection/prediction model/regression analysis引用本文复制引用
石凤,姜晓丽..基于决策树算法构建间质性肺疾病病人发生肺部感染预测模型[J].全科护理,2025,23(14):2615-2620,6.基金项目
徐州市重点研发计划(社会发展)项目,编号:KC22245. （社会发展）
