Assessment of cognitive functions in patients with multiple sclerosis
Bibliographic record
Abstract
Abstract Background About 40–70% of patients with multiple sclerosis (MS) develop cognitive impairment (CI) throughout their life. We aim to study the influence of MS on cognitive changes. This is a case–control study of fifty patients with MS who met the revised 2017 Mc Donald Criteria and fifty age- and sex-matched healthy subjects. The Expanded Disability Status Scale (EDSS) was used to assess the degree of disability, and the Montreal Cognitive Assessment (MoCA) scoring system was used to assess cognitive function. Results MS patients show low total MoCA score than the controls. Total MoCA scores were lower in patients with CI versus those with intact cognition. CI was higher in those with a longer duration of illness and a high EDSS. MoCA was positively correlated with education level but negatively with EDSS and disease duration. Conclusion MoCA scale has optimal psychometric properties for routine clinical use in patients with MS, even in those with mild functional disability. The longer the disease duration and the higher the EDSS, the lower the MoCA score and the higher the education level, the higher the MoCA score. As for the profile of cognitive dysfunction in patients with MS, the domains most frequently failed by the patients were memory, attention, visuospatial learning, 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 | 0.000 |
| 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".