White Matter Atrophy in Type 2 Diabetes Mellitus Patients With Mild Cognitive Impairment
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) patients are highly susceptible to developing dementia, especially for those with mild cognitive impairment (MCI), but its underlying cause is still unclear. In this study, we performed a battery of neuropsychological tests and high-resolution sagittal T1-weighted structural imaging to explore how T2DM affects white matter volume (WMV) and cognition in 30 T2DM-MCI patients, 30 T2DM with normal cognition (T2DM-NC) patients, and 30 age-, sex-, and education-matched healthy control (HC) individuals. The WMV of the whole brain was obtained with automated segmentation methods. Correlations between the WMV of each brain region and neuropsychological tests were analyzed in the T2DM patients. The T2DM-NC patients and HC individuals did not reveal any significant differences in WMV. Compared with the T2DM-NC group, the T2DM-MCI group showed statistically significant reduction in the WMV of seven brain regions, mainly located in the frontotemporal lobe and limbic system, five of which significantly correlated with Montreal Cognitive Assessment (MoCA) scores. Subsequently, we evaluated the discriminative ability of these five regions for MCI in T2DM patients. The WMV of four regions, including left posterior cingulate, precuneus, insula, and right rostral middle frontal gyrus had high diagnostic value for MCI detection in T2DM patients (AUC > 0.7). Among these four regions, left precuneus WMV presented the best diagnostic value (AUC: 0.736; sensitivity: 70.00%; specificity: 73.33%; Youden index: 0.4333), but with no significant difference relative to the minimum AUC. In conclusion, T2DM could give rise to the white matter atrophy of several brain regions. Each WMV of left posterior cingulate, precuneus, insula, and right rostral middle frontal gyrus could be an independent imaging biomarker to detect cognitive impairment at the early stage in T2DM patients and play an important role in its pathophysiological mechanism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".