Montreal cognitive assessment scales applied in screening for cognitive function in patients with hypertensive cerebral hemorrhage
Bibliographic record
Abstract
Objective To investigate the significance of Mo CA in the evaluation of the damage of cognitive function in patients with hypertension cerebral hemorrhage. Methods A total of 76 patients with hypertension cerebral hemorrhage who visited the doctor again after the onset of 6 months to 2 years were selected,and the cognitive function were detected by Mo CA and MMSE. First of all,used the MMSE to evaluate the cognitive function according to the patient education degree corresponding with the critical value of MMSE,selected the hypertension cerebral hemorrhage patients with normal value. For these hypertension cerebral hemorrhage patients,continue to test the cognitive function application of Mo CA,and with Mo CA rating scale,divided them into different groups and compared. Results There were 76 cases with normal value of MMSE,and the MMSE score was( 27. 5 ± 2. 3) points,Mo CA score( 23. 2 ± 4. 2) points,including 19 patients( 25%) with normal Mo CA( ≥26),57 cases( 75%) with anomaly Mo CA( 26),the anomaly Mo CA group had lower scales in visual space and executive ability,naming,note,language,abstract and delayed memory,directional force and cognitive domain score,the differences were statistically significant( P 0. 01). Conclusion Mo CA scale test can reflect the damage clinical characteristics of cognitive function in patients with hypertension cerebral hemorrhage. It can be used as a good screening tool for the damage of cognitive function in patients with hypertension cerebral hemorrhage,and its application value is better higher MMSE.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".