Montreal cognitive assessment for detection of patients with vascular cognitive impairment,no dementia
Bibliographic record
Abstract
Objective: To evaluate Montreal cognitive assessment( Mo CA) and mini-mental state examination( MMSE) in early detection of patients with vascular cognitive impairment,no dementia( VCIND). Methods: One hundred and twenty patients with VCIND and 50 cases with no cognitive impairment( NCI) after stroke were performed laboratory examinations and neuropsychological assessments. All the subjects were divided into NCI group 50 cases,mild VCIND group 44 cases and severe VCIND group 76 cases according to the results of MMSE and Mo CA; the scores were compared among the three groups. Results: The Mo CA domain subtest scores( visuospatial / executive,attention,language,abstraction,delayed recall and orientation) and the MMSE domain subtest scores( delayed recall and orientation) in the mild VCIND group were significantly lower than those in the NCI group( P 0. 05 to P 0. 01); all the Mo CA domain subtest scores and the MMSE domain subtest score( executive,computation,delayed recall and orientation) in the severe VCIND group were lower than those in the NCI group( P 0. 01); the Mo CA domain subtest scores( visuospatial/executive,attention,language,delayed recall and orientation) and the MMSE domain subtest score( executive,delayed recall and orientation) in the severe VCIND group were lower than those in the mild VCIND group( P 0. 05 to P 0. 01).Conclusions: Mo CA is superior to MMSE in early detection of VCIND and may help to predict the prognosis.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".