Study on the decision tree model for risk factors of vascular cognitive impairment
10.3760/cma.j.issn.1674-6554.2017.06.011
- VernacularTitle:血管性认知功能障碍高危因素的决策树模型研究
- Author:
Xiao WANG
;
Zongjun GUO
;
Wenqing ZHANG
;
Qinjuan WU
;
Huanqing YU
;
Fengxiang ZHANG
;
Lin XIAO
- Keywords:
Vascular cognitive impairment(VCI);
Risk factors;
Decision tree;
The prediction model
- From:
Chinese Journal of Behavioral Medicine and Brain Science
2017;26(6):534-538
- CountryChina
- Language:Chinese
-
Abstract:
Objective To collect the demographic,lifestyle and clinical factors of patients with cerebrovascular disease,and analyze the vascular cognitive impairment(VCI) factors and set up high-risk factors model.methods 505 patients with cerebrovascular disease hospitalization in department of geriatrics and neurology in hospital from October 2014 to October 2016 were enrolled.According to the questionaire survey data of demographics,lifestyle and clinical factors,the patients were divided into training set (421 cases) and test set (84 cases),and training set were divided into the non-VCI set (225 cases) and VCI set (196 cases).Analyzed the influence factors of VCI in patients with cerebrovascular disease by decision tree algorithm,and compared it with the Logistic regression analysis and chi-square and established the decision tree model for risk factors of VCI.Result sAccording to the VCI decision tree model,cross validation model recognition accuracy was 73.63%,while test set prediction accuracy was 73.81%.Alcoholism,hobbies,education level,tea drinking,diabetes,hypertension,diet,age,sleep and physical exercise were classification of node variables,while drinking was the root.The probability of VCI had significant difference (P<0.05) in the crowds with different risk factors.According to Result s of Logistic regression analysis,education level,drinking,exercise and diabetes were independent risk factors for VCI,while the model prediction accuracy was 66.98%,and test set prediction accuracy was 53.57%.According to the ROC curve of the decision tree model and the Logistic regression model,the decision tree model AUC was 0.737 (95%CI 0.688 to 0.786),and the Logistic regression model AUC was 0.664 (95%CI 0.612 to 0.717).Conclusion It is suggested that the decision tree model might be superior to logistic regression model in the prediction accuracy for VCI of patients with cerebrovascular disease.The alcoholism,diabetes,high blood pressure,high fat diet and insomnia are risk factors of VCI,while hobbies,high level of education,physical exercise and drinking tea can be the protective factors of the VCI.
