SCREENING FOR POSTSTROKE COGNITIVE IMPAIRMENT VIA MINI MENTAL STATE EXAMINATION AND MONTREAL COGNITIVE ASSESSMENT SCALE
Bibliographic record
Abstract
Objective: The aim of our study is to examine cognitive performance after mild stroke via Mini Mental State Examination (MMSE) and Montreal cognitive assessment scale (MoCA) and to compare the results.Material and methods: We examined 54 patients with mild stroke (aged 52 to 72 (mean 63.17, SD 5.96); 34 males and 20 females) and 54 controls, adjusted by age, sex and education level.All subjects were tested via MMSE (Bulgarian version) and MoCa (Bulgarian version).Data was collected in the single step model at the 90 th day after stroke incident for patients and at the day of obtaining informed consent for controls.Results: Patients have poorer performance on both MMSE and MoCa than controls.MoCa has comparatively good discriminative validity and sensitivity.Conclusions: Although MMSE is one of the classical screening tools for cognitive impairment widely used in Bulgaria, other screening tools should not be ignored.On the basis of our results, MoCa is also a good screening instrument, especially for poststroke cognitive impairment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".