ArticleJournal of diabetes2023
The use of nomogram for detecting mild cognitive impairment in patients with type 2 diabetes mellitus.
Article in Journal of diabetes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 17 citations in OpenAlex.
- The relationships between diabetic male infertility, diabetic cognitive impairment, and the neuroendocrine-immune network: A review.Medicine · 2026Review
- Research Progress on Pathology, Molecular Mechanisms, and Intervention Strategies of Cognitive Dysfunction Associated with Type 2 Diabetes.International journal of general medicine · 2026Review
- Development and multi-center validation of a high-performance predictive model for early detection of cognitive impairment in older adults: data-based on communities in Northern China.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Article
- Predicting Mild Cognitive Impairment in Type 2 Diabetes: A Machine Learning Approach.Journal of diabetes research · 2025Article
- Observational
- Prediction model for mild cognitive impairment in patients with type 2 diabetes using the autonomic function test.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Article
- Article
- Prevalence of cognitive impairment and its associated factors in type 2 diabetes mellitus patients with hypertension in Hunan, China: a cross-sectional study.Frontiers in psychiatry · 2024Article
- Development and Validation of a Risk Score for Mild Cognitive Impairment in Individuals with Type 2 Diabetes in China: A Practical Cognitive Prescreening Tool.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
- A Nomogram Including Total Cerebral Small Vessel Disease Burden Score for Predicting Mild Vascular Cognitive Impairment in Patients with Type 2 Diabetes Mellitus.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
- Changes of brain structure and structural covariance networks in Parkinson's disease associated cognitive impairment.Frontiers in aging neuroscience · 2024Article
- Risk Prediction Models for Mild Cognitive Impairment in Patients with Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Review
- The use of nomogram for detecting mild cognitive impairment in patients with type 2 diabetes mellitus.Journal of diabetes · 2023Article
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Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundType 2 diabetes mellitus (T2DM) is highly prevalent worldwide and may lead to a higher rate of cognitive dysfunction. This study aimed to develop and validate a nomogram-based model to detect mild cognitive impairment (MCI) in T2DM patients.
methodsInpatients with T2DM in the endocrinology department of Xiangya Hospital were consecutively enrolled between March and December 2021. Well-qualified investigators conducted face-to-face interviews with participants to retrospectively collect sociodemographic characteristics, lifestyle factors, T2DM-related information, and history of depression and anxiety. Cognitive function was assessed using the Mini-Mental State Examination scale. A nomogram was developed to detect MCI based on the results of the multivariable logistic regression analysis. Calibration, discrimination, and clinical utility of the nomogram were subsequently evaluated by calibration plot, receiver operating characteristic curve, and decision curve analysis, respectively.
resultsA total of 496 patients were included in this study. The prevalence of MCI in T2DM patients was 34.1% (95% confidence interval [CI]: 29.9%-38.3%). Age, marital status, household income, diabetes duration, diabetic retinopathy, anxiety, and depression were independently associated with MCI. Nomogram based on these factors had an area under the curve of 0.849 (95% CI: 0.815-0.883), and the threshold probability ranged from 35.0% to 85.0%.
conclusionsAlmost one in three T2DM patients suffered from MCI. The nomogram, based on age, marital status, household income, duration of diabetes, diabetic retinopathy, anxiety, and depression, achieved an optimal diagnosis of MCI. Therefore, it could provide a clinical basis for detecting MCI in T2DM patients.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.