Résultats d’un programme de remédiation cognitive chez des malades alcooliques hospitalisés en SSR. Une étude observationnelle
Bibliographic record
Abstract
Background: the objective of our study was to evaluate the evolution of cognitive functions in patients with alcohol disorders who were hospitalized for six weeks in an addictology rehabilitation unit. Each patient received an on-site cognitive remediation programme. Methods: patients who were suspected of having cognitive disorders upon admission based on a MoCA (Montreal cognitive assessment) score < 26 were retrospectively included in this study. Another MoCA was performed at discharge. Patients remained abstinent throughout their stay. Cognitive remediation was performed by different professionals. The programme was based on mental and physical training. The evolution of cognitive disorders was assessed using the MoCA score variation from admission to discharge. Results: 491 patients were included, 402 men and 89 women (mean age: 50.2 ± 9.7 years). The MoCA score was severely (≤ 21) or moderately (22-25) diminished in respectively 44.6 % and 55.4 % of patients. MoCA scores were improved in 84 % of the patients. These improvements were more pronounced in patients with greater initial cognitive dysfunction. This corresponds with an overall improvement of all measured functions, with similar kinetics in all patients. Discussion: hospitalisation in an addictology rehabilitation unit, where abstinence is strict and patients benefit from a cognitive remediation program, enables cognitive functions to improve, even in the most affected patients. The results of this study lack a control group and thus do not enable us to define the relative impacts of abstinence and cognitive remediation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".