Preliminary application of Montreal cognitive assessment in vascular cognitive impairment
Bibliographic record
Abstract
Objective To study the application of Montreal cognitive assessment (MoCA) in vascular cognitive impairment (VCI) ,and make a benchmark for a cutoff score.Methods 60 healthy elderly controls and 50 patients meeting the clinical criteria for VCI were tested by MoCA and mini-mental state examination(MMSE) .The validities of MoCA and MMSE were compared.The age,sex,education and nature of the work in the two groups were stratified and analyzed.Results Education and nature of the work had statistical differences between MoCA and MMSE.In persons whose educa-tion level was below junior high school,the cutoff score for MoCA was ≥22,and the sensitivity was 83.3% ,which was higher than that for MMSE sensitivity (46.7% ) ; in those whose education level was above junior high school,the cutoff score for MoCA was ≥25,the sensitivity was 85% ,which was higher than that for MMSE (50% ) .Conclusion MoCA has a higher screening sensitivity for VCI than MMSE do.Adjustment in the cutoff scores would improve the detection of VCI by reducing false negativity.MoCA scores should be used to identify current cognitive difficulties but not be used to make formal diagnosis.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".