石家庄市老年人轻度认知障碍的危险因素分析及风险预测模型的构建  

Risk factor analysis of mild cognitive impairment and construction of the risk prediction model in the elderly in Shijiazhuang City

作　　者：张圆圆 李秀莉[2] 孟宇晗 孙克娟[2] 崔慧先[4] 李妍[3] ZHANG Yuan-yuan;LI Xiu-li;MENG Yu-han;SUN Ke-juan;CUI Hui-xian;LI Yan(Department of Cardiovascular Medicine,the First Hospital of Hebei Medical University,Shijiazhuang 050031,China;Department of Nursing,the First Hospital of Hebei Medical University,Shijiazhuang 050031,China;School of Nursing,Hebei Medical University,Shijiazhuang 050017,China;Department of Anatomy,the School of Basi Medicine,Hebei Medical University,Shijiazhuang 050017,China)

机构地区：[1]河北医科大学第一医院心血管内科,河北石家庄050031 [2]河北医科大学第一医院护理部,河北石家庄050031 [3]河北医科大学护理学院,河北石家庄050017 [4]河北医科大学基础医学院解剖学教研室,河北石家庄050017

出　　处：《河北医科大学学报》2025年第1期66-71,共6页Journal of Hebei Medical University

基　　金：国家自然科学基金项目(91849134);河北省医学适用技术跟踪项目(GZ2022055)。

摘　　要：目的 识别老年人轻度认知障碍(mild cognitive impairment, MCI)的相关危险因素并建立MCI风险的列线图,为临床早期识别和干预提供参考。方法 选取2021年9月-2022年7月于石家庄市社区体检的322例老年人作为研究对象,采集一般资料、临床检测指标以及日常休闲活动现状,采用单因素分析和多因素Logistic回归分析确定老年人患MCI风险的独立危险因素,建立列线图预测模型,并用受试者工作曲线(receiver operating characteristic, ROC)曲线、拟合优度Hosmer-Lemeshow(H-L)检验以及校准曲线评价列线图模型的区分度和校准度。结果 多因素Logistic回归分析显示,高龄、低教育程度、低认知活动参与以及携带载脂蛋白E(apolipoprotein E,ApoE)ε4风险基因是MCI的独立危险因素。建立列线图预测模型,预测MCI的ROC曲线下面积=0.887(95%CI:0.834~0.939,P<0.001),H-L检验P=0.675。校准曲线Brier值为0.078,绝对误差为0.013,校准曲线极其接近理想参考线。结论 基于年龄、教育程度、认知活动指数、ApoE ε4风险基因四项风险因素的列线图模型能够有效预测石家庄市老年人MCI风险,可进一步开展外部验证研究。Objective To identify the relevant risk factors of mild cognitive impairment(MCI)in the elderly and to establish a nomogram of MCI risk,so as to provide references for early clinical identification and intervention.Methods A total of 322 elderly people who underwent physical examination in the community of Shijiazhuang City from September 2021 to July 2022 were selected as the research subjects,and the general information,clinical detection indicators,and status of daily leisure activities were collected.Univariate analysis and multivariate Logistic regression analysis were used to determine the independent risk factors of MCI risk in the elderly.The nomogram prediction model was established and the discrimination and calibration of the nomogram model were evaluated by the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow(H-L)test,and calibration curve.Results Multivariate Logistic regression analysis showed that advanced age,low education level,low cognitive activity participation,and Apolipoprotein E(ApoE)ε4 risk gene were independent risk factors for MCI.A nomogram predictive model was established and the area under the ROC curve(AUC)was 0.887(95%CI:0.834-0.939,P<0.001),and the P value of the H-L test was 0.675.The Brier value of the calibration curve was 0.078,the absolute error was 0.013,and the calibration curve was very close to the ideal reference line.Conclusion The nomogram model based on the four risk factors,including age,education level,cognitive activity index,and ApoEε4 risk gene,can effectively predict the risk of MCI in the elderly in Shijiazhuang City,and further external verification research can be carried out.

关 键 词：认知功能障碍 比例危险度模型 危险因素 

分 类 号：R741[医药卫生—神经病学与精神病学]