Montreal Cognitive Assessment in cryptogenic epilepsy patients with normal Mini‐Mental State Examination scores
Bibliographic record
Abstract
This cross-sectional study examined the Montreal Cognitive Assessment (MoCA) performance in cryptogenic epileptic patients aged more than 15 years with normal global cognition according to the Mini-Mental State Examination (MMSE) score. We tested our hypothesis that the prevalence of mild cognitive impairment and associated patient correlation factors might be increased (score < 26) according to the MoCA, in spite of a normal MMSE score, and that cognitive impairment might occur in a range of domains of the MoCA. Eighty-five patients participated in this study. The mean MoCA score was 22.44 (± 4.32). In spite of a normal MMSE score, which was an inclusion criterion, cognitive impairment was detected in 60% patients based on the MoCA score. The variable that correlated with a higher risk of cognitive impairment was the number of antiepileptic drugs (polytherapy: OR 2.71; CI 1.03-7.15). The mean scores of visuospatial and executive function, naming ability, attention, language, abstraction, delayed recall and orientation among patients with mild cognitive impairment were significantly lower than those of patients with normal cognitive function. These findings suggest that mild cognitive impairment in cryptogenic epileptic patients is common. We suggest using MoCA as a screening test for patients with epilepsy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".