ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2023
Risk Factors and Prediction Nomogram of Cognitive Frailty with Diabetes in the Elderly.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.
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Who cites it
15 citing papers in PubMed, 3 syntheses or guidelines pooled it, 17 citations in OpenAlex.
- Characterization of Models for Identifying Physical and Cognitive Frailty in Older Adults With Diabetes: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Risk prediction model for cognitive frailty in older adults with diabetes: a systematic review and meta-analysis.Frontiers in endocrinology · 2026Pooled it
- The risk prediction models for cognitive frailty in the older people in China: a systematic review and meta-analysis.BMC geriatrics · 2025Pooled it
- Article
- Cognitive frailty and associated factors in older adults with type 2 diabetes in rural Vietnam.BMC geriatrics · 2026Article
- Prevalence and predictive factors of cognitive impairment among hospitalized older adults in iran: a cross-sectional study, 2024.Aging clinical and experimental research · 2026Article
- Development and Internal Validation of a Machine Learning-Based Classification Model for Identifying Cognitive Frailty in Older Inpatients with Type 2 Diabetes Mellitus.Clinical interventions in aging · 2026Article
- Development and validation of a nomogram for predicting cognitive frailty in patients on cancer.BMC geriatrics · 2025Article
- Association between depression symptoms and cognitive frailty in chronic kidney disease patients: a cross-sectional study.Frontiers in psychiatry · 2025Article
- Establishment and validation of a risk prediction model for urinary tract infection in elderly patients with type 2 diabetes mellitus.Frontiers in endocrinology · 2025Article
- The value of nomogram based on MRI functional imaging in differentiating cerebral alveolar echinococcosis from brain metastases.European journal of medical research · 2024Article
- Synergistic effects of cognitive frailty and comorbidities on disability: a community-based longitudinal study.BMC geriatrics · 2024Article
- Frailty and Parkinson's disease: the role of diabetes mellitus.Frontiers in medicine · 2024Review
- Risk factors analysis of cognitive frailty among geriatric adults in nursing homes based on logistic regression and decision tree modeling.Frontiers in aging neuroscience · 2024Article
- Risk Factors and Prediction Nomogram of Cognitive Frailty with Diabetes in the Elderly [Letter].Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: 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.
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