ArticleScientific reports2023
Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 28 citations in OpenAlex.
- Domain-Specific and Domain-General Functional Brain Alterations in Type 2 Diabetes Mellitus: A Task-Based and Functional Connectivity Meta-Analysis.Brain and behavior · 2025Pooled it
- Research trend of functional magnetic resonance imaging in diabetes mellitus research: a visualization and bibliometric analysis.Frontiers in neurologyPooled it
- Comparative evaluation of dulaglutide alone vs. dulaglutide combined with probiotics on cardiovascular risk factors in T2DM.Hormones (Athens, Greece) · 2025Trial
- Simultaneous PET/fMRI distinguishes the separate and synergistic effects of T2DM and MCI on cerebral glucose metabolism and fALFF.Scientific reports · 2026Article
- Integrated cortical-cognitive signatures identified by machine learning enable early detection of MCI in type 2 diabetes.Scientific reports · 2026Article
- In newly diagnosed diabetes, hyperglycemia is associated with increased brain iron deposition, measured by MRI-based Quantitative Susceptibility Mapping (QSM).Journal of advanced research · 2026Article
- A neuroimaging functional connectivity signature of emotional conflict monitoring predicting cognitive decline in type 2 diabetes.Scientific reports · 2026Article
- Protective effects of Parabacteroides distasonis against high-fat diet-induced brain injury in mice.NPJ science of food · 2025Article
- Article
- Functional MRI Analysis of Brain Activity in Rats With Diabetic Bladder Dysfunction.CNS neuroscience & therapeutics · 2025Article
- Overview of Metformin and Neurodegeneration: A Comprehensive Review.Pharmaceuticals (Basel, Switzerland) · 2025Review
- A Narrative Review on Cognitive Impairment in Type 2 Diabetes: Global Trends and Diagnostic Approaches.Biomedicines · 2025Review
- Network pharmacology-based prediction and "gut microbiota-inflammation-brain axis" validation of the active ingredients and potential mechanisms ofFrontiers in pharmacology · 2025Article
- Support Vector Machine for Stratification of Cognitive Impairment Using 3D T1WI in Patients with Type 2 Diabetes Mellitus.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- Machine learning-based predictive model for high- grade cytokine release syndrome in chimeric antigen receptor T-cell therapy.Frontiers in immunology · 2025Observational
- Vitamin K2 Ameliorates Diabetes-Associated Cognitive Decline by Reducing Oxidative Stress and Neuroinflammation.Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology · 2024Article
- Harmful Effects on the Hippocampal Morpho-Histology and on Learning and Memory in the Offspring of Rats with Streptozotocin-Induced Diabetes.International journal of molecular sciences · 2024Article
- 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
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Type 2 diabetes mellitus (T2DM) is closely linked to cognitive decline and alterations in brain structure and function. Resting-state functional magnetic resonance imaging (rs-fMRI) is used to diagnose neurodegenerative diseases, such as cognitive impairment (CI), Alzheimer's disease (AD), and vascular dementia (VaD). However, whether the functional connectivity (FC) of patients with T2DM and mild cognitive impairment (T2DM-MCI) is conducive to early diagnosis remains unclear. To answer this question, we analyzed the rs-fMRI data of 37 patients with T2DM and mild cognitive impairment (T2DM-MCI), 93 patients with T2DM but no cognitive impairment (T2DM-NCI), and 69 normal controls (NC). We achieved an accuracy of 87.91% in T2DM-MCI versus T2DM-NCI classification and 80% in T2DM-NCI versus NC classification using the XGBoost model. The thalamus, angular, caudate nucleus, and paracentral lobule contributed most to the classification outcome. Our findings provide valuable knowledge to classify and predict T2DM-related CI, can help with early clinical diagnosis of T2DM-MCI, and provide a basis for future studies.
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Registered trials
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.