Effects of Type 2 Diabetes on the Neuropsychological Profile in Mild Cognitive Impairment
Bibliographic record
Abstract
Background: Diabetes is one of the main risk factors for developing mild cognitive impairment (MCI) and Alzheimer's disease. Most studies have demonstrated a worse performance in executive function, verbal fluency, and information processing speed in patients with diabetes. Objective: To assess the cognitive functioning of persons with type 2 diabetes and amnesic mild cognitive impairment (aMCI-T2DM) compared to persons with aMCI without diabetes and persons without diabetes or aMCI as controls, to understand the role of diabetes in the neuropsychological profile. Methods: Cross-sectional study involving a sample of 83 patients, ranging in age from 61 to 85 years and divided into three groups: aMCI-T2DM (27 patients), aMCI (29 patients), Controls (27 individuals). All the participants undertook an exhaustive neuropsychological assessment (auditory-verbal and visual memory, attention, information processing speed, language, executive function, and depression). Results: Both groups of aMCI patients performed significantly worse than the controls in all the neuropsychological tests. A significant linear tendency (p trend < 0.05) was found between groups, with the aMCI-T2DM group presenting worse results in global cognition assessed by the Mini-Mental State Examination and Montreal Cognitive Assessment; Rey-Osterrieth Complex Figure Test; Auditory Verbal Learning Test; Trail Making Test A and B, Verbal Fluency Test, and Hamilton Depression Rating Scale. Conclusions: aMCI patients with or without diabetes showed worse cognitive function compared to persons without diabetes or aMCI. Additionally, aMCI patients without T2DM presented a different cognitive profile than aMCI patients with T2DM, which tended towards presenting worse cognitive functions such as global cognition, memory, attention, executive function, and language.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".