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老年共病患者认知衰弱风险预测模型的构建及验证

Construction and validation of a risk screening model for cognitive frailty in elderly patients with comorbidities
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摘要 目的调查老年共病患者认知衰弱的现状,分析相关影响因素并构建风险筛查模型。方法选取2021-06-01-10-31上海市第五人民医院收治的老年共病患者738例,分为建模组590例和验证组148例,采用一般资料问卷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SPSS 19.0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;采用C统计量、校准曲线评价模型的预测性能。结果建模组认知衰弱发生率为33.6%,验证组为35.1%。logistic回归分析结果显示,年龄(70~<80岁:OR=2.861,95%CI为1.567~5.224,P=0.001;≥80岁:OR=13.333,95%CI为5.744~30.951,P<0.001)、日常生活能力(OR=6.301,95%CI为3.344~11.871,P<0.001)、营养状况(OR=0.370,95%CI为0.179~0.763,P=0.007)、抑郁(OR=2.689,95%CI为1.414~5.114,P=0.003)、睡眠障碍(OR=3.218,95%CI为1.833~5.647,P<0.001)、共病数量≥4(OR=2.126,95%CI为1.075~4.203,P=0.030)、糖尿病(OR=3.054,95%CI为1.766~5.280,P<0.001)及慢性心力衰竭(OR=16.657,95%CI为5.821~42.112,P<0.001)是老年共病患者认知衰弱独立危险因素。模型变量包括上述8个独立预测因素,受试者工作特征曲线下面积为0.928(95%CI为0.905~0.951,P<0.001),Hosmer-Leme-showχ^(2)=4.863,P=0.772,最佳临界值为0.731,灵敏度为0.894,特异度为0.837。内外部验证C统计量分别为0.901和0.934,校准曲线显示拟合良好,Brier得分分别为0.113和0.093。结论老年共病患者认知衰弱发生率较高,年龄≥70岁、日常生活能力受损、糖尿病、慢性心力衰竭、共病数量≥4种、营养不良、睡眠障碍、抑郁的老年共病患者更易发生认知衰弱。构建的风险预测模型有着良好的区分度和校准度,可为临床医务人员评估老年共病患者认知衰弱的发生风险,为早期筛查和制订护理对策提供参考。 Objective To investigate the status and risk factors of cognitive frailty in elderly patients with comorbidities,and to develop a risk screening model.Methods Totally 738 elderly patients with comorbidities were recruited in Shanghai Fifth People's Hospital from June 1,to October 31,2021 were selected and divided into a modeling group of 590 patients and a validation group of 148 patients.Data were collected by a general questionnaire and cognitive frailty assessment tools.Logistic regression was used to determine the influencing factors,and SPSS 19.0 software was used to establish a nomogram model to predict the risk of cognitive frailty.Bootstrap method was used for internal verification of the model.C statistic and calibration curve were used to evaluate the prediction performance of the model.Results The incidence of cognitive frailty in modeling group and a validation group were 33.6%and 35.1%,respectively.Logistic regression analysis showed that age(70-<80 years:OR=2.861,95%CI was 1.567—5.224,P=0.001);≥80 years:(OR=13.333,95%CI was 5.744—30.951,P<0.001),activities of daily living(OR=6.301,95%CI was 3.344—11.871,P<0.001),nutritional status(OR=0.370,95%CI was 0.179—0.763,P=0.007),depression(OR=2.689,95%CI was 1.414—5.114,P=0.003),sleep disorders(OR=3.218,95%CI was 1.833—5.647,P<0.001),number of comorbidity≥4(OR=2.126,95%CI was 1.075—4.203,P=0.030),diabetes(OR=3.054,95%CI was 1.766—5.280,P<0.001),and chronic heart failure(OR=16.657,95%CI was 5.821—42.112,P<0.001)were independent risk factors for cognitive frailty among patients with comorbidities.The model included these eight independent predictors.The area under the curve of receiver operating characteristic of the model was 0.928(95%CI was 0.905—0.951,P<0.001),the Hosmer-Lemeshow test was 4.863,P=0.772,the best cutoff value was 0.731,the sensitivity was 0.894,and the specificity was 0.837;The C statistics of internal and external validation were 0.901 and 0.934,respectively;calibration curve showed a good fit,and Brier scores were 0.113 and 0.093.Conclusions The incidence of cognitive frailty is high among elderly patients with comorbidities.Elderly patients with age≥70,impaired ability of daily living,diabetes,chronic heart failure,≥4 comorbid conditions,malnutrition,sleep disorders,and depression are more susceptible to cognitive frailty.The risk prediction model has good discrimination and calibration,which can be used by clinical medical personnel to evaluate the risk of cognitive frailty among elderly patients with comorbidities,and provide reference for early screening and formulating nursing strategies.
作者 汪亚男 朱月兰 盛英 樊丽芳 周会 WANG Yanan;ZHU Yuelan;SHENG Ying;FAN Lifang;ZHOU Hui(The First People's Hospital of Kunshan,Kunshan,Jiangsu 215312,China;Department of Science and Research,Shanghai Fifth People's Hospital,Fudan University,Shanghai 200240,China)
出处 《社区医学杂志》 CAS 2024年第13期441-448,共8页 Journal Of Community Medicine
基金 昆山市重点研发(社会发展)计划(KS2210) 闵行区自然科学研究课题(2020MHZ045) 复旦大学附属上海市第五人民医院曙光青年人才培养计划(2020WYRCSG08)
关键词 老年人 共病 认知衰弱 影响因素分析 列线图 预测模型 aged comorbidities cognitive frailty influencing factors nomograms prediction model
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