Increased detection of mild cognitive impairment with type 2 diabetes mellitus using the Japanese version of the Montreal Cognitive Assessment: A pilot study
Bibliographic record
Abstract
Abstract Background Studies show that diabetes mellitus is the greatest lifestyle risk factor for dementia. Appropriate management and treatment of type 2 diabetes mellitus could prevent the onset and progression of mild cognitive impairment to dementia. Aim Detection of mild cognitive impairment in patients with type 2 diabetes mellitus. Methods Mild cognitive impairment was assessed using the Japanese version of the Montreal Cognitive Assessment. The study population was 33 non‐demented inpatients with type 2 diabetes mellitus receiving diabetes management training. The Japanese version of the Montreal Cognitive Assessment, the animal naming test and the digit‐symbol coding subtest of the Wechsler Adult Intelligence Scale were administrated in one‐to‐one interviews. Results The prevalence of mild cognitive impairment in diabetic patients was 72%. The background characteristics of mild cognitive impairment in diabetic patients included fewer schooling years and higher glycated hemoglobin levels in comparison to subjects without mild cognitive impairment. Neuropsychological testing showed that diabetic patients with mild cognitive impairment scored lower on the Japanese version of the Montreal Cognitive Assessment (total score, P < 0.0001), frontal lobe function (P < 0.001) and delayed recall (P < 0.05). The number of correct answers on the digit‐symbol coding subtest was also significantly lower in diabetic patients with mild cognitive impairment (P < 0.05). Conclusion Mild cognitive impairment with type 2 diabetes mellitus has a high prevalence. Our study suggests that mild cognitive impairment in diabetic patients can be classified into three groups: predominantly frontal lobe dysfunction, predominantly delayed recall impairment and a mixed‐type group.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".