Predictive factors of cognitive impairment in alcohol use disorder inpatients
Bibliographic record
Abstract
BACKGROUND: Cognitive impairments are common in patients with AUD and worsen the prognosis of addiction management. There are no clear guidelines for screening cognitive impairments in hospitalized patients with AUD. METHODS: Fifty-seven patients with an AUD history who were admitted to an acute hospital and assessed by the addiction care team were included. Those patients were screened for cognitive impairments using the Montreal Cognitive Assessment (MoCA) test. We collected clinical information regarding addiction history, comorbidities, and current treatments. Chi-square tests, t-tests, and Mann-Whitney tests were performed to determine factors associated with a pathological MoCA score (<26). RESULTS: A pathological MoCA score was positively associated with spatial-temporal disorientation, difficulty in recalling addiction history, patient underreporting of AUD and a date of last alcohol consumption lower than 11 days ago, and negatively associated with a reason for hospitalization due to alcohol-related health issues. No medication was associated with cognitive impairments. CONCLUSIONS: Clinical elements from assessment by the addiction care team allow for relevant indication for screening cognitive impairments.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".