Quick screening of cognitive function in Indian multiple sclerosis patients using Montreal cognitive assessment test-short version
Bibliographic record
Abstract
BACKGROUND: Cognitive impairments in multiple sclerosis (MS) are now well recognized worldwide, but unfortunately this domain has been less explored in India due to many undermining factors. The aim of this study was to evaluate cognitive impairments in Indian MS patients with visual or upper limb motor problems with the help of short version of Montreal cognitive assessment test (MoCA). SUBJECTS AND METHODS: Thirty MS patients and 50 matched controls were recruited for the 12 points MoCA task. Receiver operating characteristic curve (ROC) analysis was performed to determine optimal sensitivity and specificity of the 12 points MoCA in differentiating cognitively impaired patients and controls. RESULTS: The mean 12 points MoCA scores of the controls and MS patients were 11.56 ± 0.67 and 8.06 ± 1.99, respectively. In our study, the optimal cut-off value for 12 points MoCA to be able to differentiate patients with cognitive impairments from controls is 10/12. Accordingly, 73.3% patients fell below the cut off value. Both the groups did not have significant statistical differences with regard to age and educational years. CONCLUSION: The 12 points, short version of MoCA, is a useful brief screening tool for quick and early detection of mild cognitive impairments in subjects with MS. It can be administered to patients having visual and motor problems. It is of potential use by primary care physicians, nurses, and other allied health professionals who need a quick screening test. No formal training for administration is required. Financial and time constraints should not limit the use of the proposed instrument.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".