Risk Factors and Prediction Nomogram of Cognitive Frailty with Diabetes in the Elderly

Yinhui Deng,1 Na Li,2 Yaru Wang,2 Chen Xiong,2 Xiaofang Zou1 1Department of Nursing, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, People’s Republic of China; 2School of Nursing, Guangzhou Medical University, Guangzhou, Guangdong, People’s Republic of ChinaCorrespondence: Xiaofang Zou, Department of Nursing, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, People’s Republic of China, Tel +8618998321627, Fax +86-20-81292949, Email 1037189214@qq.comPurpose: Diabetes is a well-recognized risk factor for cognitive frailty. This study aimed to investigate the influencing factors of cognitive frailty in elderly patients with diabetes and develop a nomogram for its assessment.Methods: We collected the clinical data of diabetic patients aged 60 years or older and the patients were divided into training and validation cohorts at a ratio of 7:3. In the training cohort, logistic regression was used to screen out the influencing factors of cognitive frailty in elderly diabetic patients, and a risk prediction model and nomogram were constructed and verified in the validation cohort. The performance of the model was evaluated using various measures, including the area under the receiver operating characteristic curve, calibration curve, Hosmer-Lemeshow test and decision curve analysis.Results: A total of 315 elderly diabetic patients were included, of which 87 (27.6%) patients had cognitive frailty. Age, albumin levels, calf circumference, duration of diabetes, intellectual activity, and depressive state were identified as independent risk factors for cognitive frailty in older patients with diabetes (P < 0.05). The training cohort and validation cohort demonstrated area under curve (AUC) values of 0.866 and 0.821, respectively.Conclusion: Older patients with diabetes have a higher prevalence of cognitive frailty. The nomogram model exhibited satisfactory calibration and identification, providing a reliable tool for assessing the risk of cognitive frailty in individuals with diabetes.Keywords: cognitive frailty, diabetes, nomogram, prediction, risk factors