Abstract:

Objective To establish and validate a risk prediction model for cognitive frailty in community elderly. Methods 526 elderly people taking physical examinations were recruited in a community health service center in Guangzhou by convenience sampling from August 2020 to July 2021. They were divided into a modeling group （368 cases） and a validation group（158 cases）. Data were collected by a general information questionnaire and cognitive frailty assessment tools. Logistic regression was used to determine the influencing factors,and R software was used to establish a nomogram model for predicting the risk of cognitive frailty. Bootstrap method was used for internal validation of the model,and the validation group was used for external validation. C statistic and calibration curve were used to evaluate the prediction performance of the model. Results The model variables included IADL,self-rated health,daytime mental state,the number of chronic diseases,age,nutritional status and physical exercise. The AUROC of the model was 0.920（95%CI：0.892~0.947）,the best cutoff value was 0.401;the sensitivity was 79.7%;the specificity was 89.1%;The C statistics of internal and external validation were 0.910 （95%CI：0.863~0.936） and 0.850（95%CI：0.785~0.915）,respectively;calibration curve and Brier score showed good fit. Conclusion The prediction model has a good degree of discrimination and calibration,which can intuitively and easily screen the elderly at high risk of cognitive frailty in the community,and provide references for early screening and intervention.

Key words: Aged, Cognitive Frailty, Risk Factors, Nomograms, Prediction Model, Community Health Nursing

摘要：

目的 构建并验证社区老年人认知衰弱风险预测模型。方法 2020年8月—2021年7月便利选取广州市某社区卫生服务中心526名体检老年人,分为建模集368名和验证集158名,采用一般状况调查表及认知衰弱评定工具收集资料。采用Logistic回归确定影响因素,应用R软件建立预测认知衰弱发生风险的列线图模型;采用加强Bootstrap法做模型内部验证,以验证集做外部验证,采用C统计量、校准曲线评价模型的预测性能。结果 模型变量包括工具性日常生活能力、自评健康状况、日间精神状态自评、慢性病数量、年龄、营养状况及体育锻炼,受试者操作特征曲线下面积为0.920（95%CI：0.892~0.947）,最佳临界值为0.401,灵敏度为79.7%,特异度为89.1%。内外部验证C统计量分别为0.910（95%CI：0.863~0.936）、0.850（95%CI：0.785~0.915）,校准曲线和Brier得分均显示拟合良好。结论 预测模型的区分度和校准度良好,可直观、简便地甄别社区认知衰弱高风险老年人,为早期筛查与干预提供参考。

关键词: 老年人, 认知衰弱, 危险因素, 列线图, 预测模型, 社区保健护理