Application of Montreal cognitive assessment in evaluating alcoholism-induced cognitive impairment and analyses of associated clinical parameters
Bibliographic record
Abstract
Objective To assess the cognitive impairment induced by alcohol dependence with Montreal cognitive assessment(MoCA),and to analyze related clinical factors.Methods Montreal cognitive assessment(MoCA,Chinese version)was applied to evaluate the cognitive impairment of patients with alcohol dependence.Clinical parameters including electroencephalography(EEG),hippocampal volume and width of the temporal horns measured with CT scans were grouped for comparative analysis with cognitive evaluation.Result The positive rate of cognitive impairment,assessed with MoCA,of patients with alcohol dependence was 93%.Correlation study indicated that in alcohol dependence group,MoCA scores of patients were positively correlated with years of alcohol intake(r=0.368,P0.01),degree of abnormalities in EEG(r=0.215,P0.05)and hippocampal volume(r=0.403,P0.01),while negatively correlated with width of the temporal horns(r=-0.351,P0.01).Conclusion The scores of Montreal cognitive assessment of alcohol dependent patients with cognitive impairment apparently correlates with abnormal electrophysiological and radiographic changes observed.MoCA may have practical value for early assessment of cognitive function of patients with alcohol dependence.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".