ArticleWorld journal of diabetes2022
Large-scale functional connectivity predicts cognitive impairment related to type 2 diabetes mellitus.
Article in World journal of diabetes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 5 citations in OpenAlex.
- Sequence of episodic memory-related behavioral and brain-imaging abnormalities in type 2 diabetes.Nutrition & diabetes · 2025Trial
- 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
- Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity.Scientific reports · 2023Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLarge-scale functional connectivity (LSFC) patterns in the brain have unique intrinsic characteristics. Abnormal LSFC patterns have been found in patients with dementia, as well as in those with mild cognitive impairment (MCI), and these patterns predicted their cognitive performance. It has been reported that patients with type 2 diabetes mellitus (T2DM) may develop MCI that could progress to dementia. We investigated whether we could adopt LSFC patterns as discriminative features to predict the cognitive function of patients with T2DM, using connectome-based predictive modeling (CPM) and a support vector machine.
aimTo investigate the utility of LSFC for predicting cognitive impairment related to T2DM more accurately and reliably.
methodsResting-state functional magnetic resonance images were derived from 42 patients with T2DM and 24 healthy controls. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Patients with T2DM were divided into two groups, according to the presence (T2DM-C;
resultsCPM could predict the MoCA scores in patients with T2DM (Pearson's correlation coefficient between predicted and actual MoCA scores,
conclusionLSFC provides neuroimaging-based information that may be useful in detecting MCI early and accurately in patients with T2DM.
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