老年2型糖尿病患者认知衰弱风险预测模型的构建与验证

Construction and validation of a cognitive frailty risk prediction model in elderly patients with type 2 diabetes

目的构建并验证老年2型糖尿病患者认知衰弱风险预测模型。方法采用方便抽样法,选取2022年6—12月在天津市第一中心医院就诊的483例老年2型糖尿病患者为研究对象。通过随机分组法将患者分为建模组(n=338)和验证组(n=145)。采用一般资料调查表、微型营养评定法简表、简版老年抑郁量表、衰弱表型量表、蒙特利尔认知评估量表和临床痴呆评定量表对患者进行调查。采用Logistic回归分析老年2型糖尿病患者发生认知衰弱的影响因素。基于回归结果构建认知衰弱风险列线图预测模型并在验证集中进行验证;通过受试者工作特征曲线下面积(AUC)、校准曲线、临床决策曲线评价模型的预测性能和临床有效性。本研究共发放问卷483份,回收有效问卷483份,问卷有效回收率为100.0%。结果483例老年2型糖尿病患者认知衰弱发生率为20.3%(98/483);年龄、规律运动、糖尿病病程、糖化血红蛋白水平、抑郁及营养状况为模型预测因子;模型的AUC为0.886,H-L拟合度检验χ^(2)=8.004(P=0.433),最佳截断值为0.335,准确度为89.0%。结论预测模型具有良好的拟合度和预测效果,可直观、简便地甄别老年2型糖尿病认知衰弱高危人群,为早期筛查与干预提供参考。

ObjectiveTo develop and validate a risk prediction model for cognitive frailty in elderly patients with type 2 diabetes.MethodsA total of 483 elderly patients with type 2 diabetes who visited Tianjin First Central Hospital from June to December 2022 were selected using convenience sampling.They were randomly divided into a modeling group(n=338)and a validation group(n=145).Data were collected using a self-designed general information questionnaire,the Short-Form Mini Nutritional Assessment(MNA-SF),the Geriatric Depression Scale-15(GDS-15),the Frailty Phenotype(FP),the Montreal Cognitive Assessment(MoCA),and the Clinical Dementia Rating(CDR).Logistic regression analysis was performed to identify the influencing factors.A cognitive frailty risk prediction nomogram model was constructed based on the results.The model was validated in the validation group,and its predictive performance and clinical applicability were evaluated using the area under the receiver operating characteristic curve(AUC),calibration curve,and clinical decision curve analysis.A total of 483 questionnaires were distributed and all were returned as valid,resulting in a 100.0%response rate.ResultsThe prevalence of cognitive frailty in the 483 elderly patients with type 2 diabetes was 20.3%(98/483).Age,regular exercise,duration of diabetes,HbA1c levels,depression and nutritional status were identified as predictive factors in the model.The AUC of the model was 0.886,and the Hosmer-Lemeshow test showed aχ^(2) value of 8.004(P=0.433).The optimal cutoff value was 0.335,and the accuracy was 89.0%.ConclusionsThe prediction model demonstrates good fit and strong predictive performance,and can intuitively and easily identify elderly patients with type 2 diabetes who are at high risk of cognitive frailty,providing a reference for early screening and intervention.