脑卒中后认知障碍预测模型的构建与验证  

Development and validation of predictive model for cognitive impairment after stroke

作　　者：黄莉[1] 区腾飞[2] 杨洁[1] 庄红花[1] 刘天妮 杨华才 HUANG Li;OU Tengfei;YANG Jie;ZHUANG Honghua;LIU Tianni;YANG Huacai(Department of Neurology,The Second Affiliated Hospital of Guangzhou Medical University,Guangzhou 510260;Department of Neurology,No.2 People’s Hospital,Foshan 528000;Department of Neurology,The First Affiliated Hospital of Guangzhou Medical University,Guangzhou 510120,China)

机构地区：[1]广州医科大学附属第二医院神经内科,广东广州510260 [2]佛山市第二人民医院神经内科,广东佛山528000 [3]广州医科大学附属第一医院神经内科,广东广州510120

出　　处：《西安交通大学学报（医学版）》2023年第2期214-220,共7页Journal of Xi’an Jiaotong University（Medical Sciences）

基　　金：国家自然科学基金资助项目(No.81801304);广东省自然基金项目(No.粤科规财字[2017]105号);广州市卫生健康科技项目(No.20211A011081)。

摘　　要：目的构建和验证基于人口学特征、临床特征及影像学指标的脑卒中后的认知功能障碍风险预测模型。方法通过电子病历系统及患者随访完善资料收集,发病后3个月进行认知功能检测,以简易智能状态检查量表评分≤26分定义为认知功能障碍。采用最优子集回归分析筛选变量,Logistic回归分析进行认知障碍预测模型的构建,使用C-指数、校准图和临床决策曲线分析评价模型的区分度、一致性和临床可用性,并绘制列线图。结果筛选出脑卒中前认知功能、年龄、受教育年限、入院时的美国国立卫生院卒中量表评分、缺血性心脏病史、陈旧性腔隙性梗死病灶个数、内侧颞叶萎缩7个变量,构建出预测模型,该预测模型的C-指数为0.845(95%CI:0.805~0.885),校准图显示良好的一致性,临床决策曲线得出在阈概率为9.0%~90.0%时,模型具有正的净效益。结论脑卒中患者认知障碍预测模型具有良好的预测效能,为在各种亚型的脑卒中患者中筛查认知障碍的高危病例提供了有效的评估工具。Objective To construct and validate a risk prediction model for cognitive impairment after stroke based on demographic,clinical,and neuroimaging characteristics.Methods Through the medical record system,we collected all data of the patients.We finished cognitive function testing three months after the indexed stroke.The Mini-Mental State Examination Scale score≤26 was defined as cognitive dysfunction.Optimal subset regression analysis was used to screen variables,Logistic regression analysis was used to construct a predictive model for cognitive impairment,and C-index,calibration chart and clinical decision curve analyses were used to evaluate the discrimination,consistency,and clinical availability of the model.And nomograms were used to express the performance of the model.Results Seven variables were selected:cognitive function before stroke,age,years of education,National Institutes of Health Stroke Scale score at admission,history of ischemic heart disease,the number of old lacunar infarct lesions,and medial temporal lobe atrophy scale.The prediction model had a C-index of 0.845(95%CI:0.805-0.885).The clinical decision curve showed that the model had a positive net benefit when the threshold probability was 9.0%-90.0%.Conclusion The predictive model of cognitive impairment in stroke patients has good predictive efficiency and provides an effective assessment tool for screening high-risk cases of cognitive impairment in patients with stroke of various subtypes.

关 键 词：脑卒中 认知障碍 预测模型 列线图 

分 类 号：R749.13[医药卫生—神经病学与精神病学]