Cognitive Function Deficits Associated With Type 2 Diabetes and Retinopathy: Volumetric Brain MR Imaging Study
Bibliographic record
Abstract
INTRODUCTION: Type 2 diabetes mellitus is a ubiquitous chronic inflammatory disease with deleterious effects on various tissues, including the kidney, retina, and peripheral nerves. Studies using histopathology and magnetic resonance imaging have revealed that diabetes-related chronic hyperglycemia may impact the brain's essential functioning by causing microvascular damage. The aim of this study was to examine the cognitive functioning of type 2 diabetic individuals with and without retinopathy by evaluating their morphological, structural, and biochemical differences. METHODS: Demographic characteristics, education level, type of diabetes mellitus (DM), disease duration, treatment received, other diabetic complications, such as nephropathy and neuropathy, and detailed medical histories were recorded. All participants underwent an extensive neuropsychological examination with Montreal Cognitive Assessment (MoCA) testing. Brain magnetic resonance imaging was performed to evaluate gray matter volume differences between the groups. RESULTS: Gray matter volume differences between the groups were observed. Differences were observed after multiple corrections (age, education, and total intracranial volume [TIV]). First, the diabetic retinopathy group exhibited a significantly smaller gray matter volume in the right inferior temporal gyrus than the diabetic group (p = 0.032). In addition, the diabetic retinopathy group exhibited a significantly smaller gray matter volume than the control group in the right insula (lateral and central part) (p = 0.011). In addition, MoCA scores exhibited significant correlation with the two regions emerging as statistically significant in our analyses (the right inferior temporal gyrus and right insula) (p = 0.003, p = 0.002, respectively). CONCLUSION: Our results suggest the presence of a neurodegenerative process associated with cognitive dysfunction that is particularly prominent in the retinopathy stage of DM.
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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 | 0.000 |
| 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".