Objective To establish a decision tree model of deep vein thrombosis associated with peripheral inserted central catheters(PICC)in elderly patients.Methods A total of 400 elderly cancer patients receiving PICC in a hospital from March 2017 to May 2021 were selected as the model group,and 120 elderly cancer patients receiving PICC in a hospital from June 2021 to February 2023 were selected as the validation group.Logistic regression was used to screen the risk factors of PICC-related deep vein thrombosis in elderly cancer patients.SPSS Modeler software was used to build a decision tree model of PICC-related deep vein thrombosis in elderly cancer patients,and the prediction efficiency of the decision tree model was analyzed.Re-sults Among 400 elderly tumor patients,74 cases developed PICC-associated DVT,and the incidence of DVT was 18.50％.Logistic regression analysis showed that body mass index,puncture times,catheter retention time,diabetes and chronic renal in-sufficiency were the risk factors for PICC-related deep vein thrombosis in elderly tumor patients(P＜0.05).The classification nodes of the decision tree model of PICC-related deep vein thrombosis in elderly tumor patients were diabetes,catheter retention time,chronic renal insufficiency,puncture times and body mass index,among which diabetes was the most important predictor.The AUC of the decision tree model(AUC=0.749,95％CI:0.688-0.811)was higher than that of the logistic regression model(AUC=0.701,95％CI:0.633-0.770)(P＜0.05),and that of the verification group was 0.812(95％CI:0.783-0.841).Conclusion Body mass index,puncture times,catheter retention time,diabetes and chronic renal insufficiency are risk factors for PICC-related DVT in elderly cancer patients.The decision tree model of PICC-related DVT in elderly cancer patients estab-lished in this study has high accuracy.
old agetumor patientPICCdeep vein thrombosislogistic regressiondecision tree
NETL
NSTL
维普
万方数据
