摘要目的 收集脑血管病患者人口学、生活模式和临床疾病因素,分析导致血管性认知功能障碍(VCI)的高危因素,建立VCI高危因素的决策树模型.方法 选取2014年10月至2016年10月于老年医学科和神经内科住院治疗脑血管病患者505例,进行人口学、生活模式和临床疾病因素问卷调查和数据采集,分为训练集组(421例)与测试集组(84例),其中训练集组患者分为非VCI患者组(225例)和VCI患者组(196例).采用决策树算法分析脑血管病患者发生VCI的影响因素,并与Logistic回归分析和卡方检验比较,建立VCI高危因素的决策树模型.结果 训练集组构建的决策树模型交叉验证模型识别准确度为73.63%,对测试集的预测准确度为73.81%.饮酒、业余爱好、饮茶、受教育程度、高血压、睡眠、年龄、饮食、糖尿病、体育锻炼是决策树模型的分类节点变量,饮酒作为根节点变量.卡方检验分析根据分类节点分类的患者,其VCI发病率差异有统计学意义(P<0.05).多因素Logistic回归分析显示,文化水平、饮酒、体育锻炼、糖尿病4个因素为VCI发生的影响因素,该模型预测准确度为66.98%,对测试集的预测准确度为53.57%.决策树模型与Logistic回归模型的ROC曲线显示,决策树模型AUC为0.737(95%CI: 0.688~0.786),Logistic回归模型AUC为0.664(95%CI:0.612~0.717).结论 在对脑血管病患者发生VCI预测准确度方面,决策树模型优于Logistic回归模型.过量饮酒、糖尿病、高血压、高脂饮食、失眠是VCI发生的危险因素;业余爱好、高受教育程度、体育锻炼、饮茶是VCI的保护因素.

abstractsObjective 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.