Cognitive changes in topiramate‐treated patients with alcoholism: A 12‐week prospective study in patients recently detoxified
Bibliographic record
Abstract
AIMS: The aim of this study was to determine the 12-week cognitive changes in topiramate-treated patients recently detoxified from alcohol. METHODS: Participants were inpatients with DSM-IV alcohol dependence. All of them were discharged within 14 days after the initiation of topiramate treatment. The topiramate dose range was 50-300 mg/day. The Montreal Cognitive Assessment (MoCA) was used on day 0, day 29, day 57, and day 85. Differences of the MoCA total and seven subtest scores among four time-points were compared. RESULTS: Thirty-eight participants (36 men and two women) had a mean ± SD age of 43.1 ± 8.6 years old. At enrollment, they were abstinent for a mean ± SD of 11.5 ± 5.3 days. Five, one, and three patients dropped out of the study on day 29, day 57, and day 85, respectively. On day 85, the mean ± SD dose of topiramate was 253.1 ± 60.8 mg/day. Alcohol consumption decreased drastically during follow up. At each time-point, 75%-80% of the participants were continuous abstainers. The mean ± SD MoCA total, language subtest, and delayed recall subtest scores increased significantly from day 0 to day 85, from 22.0 ± 4.7 to 24.7 ± 3.4 (P < 0.01), from 1.1 ± 1.0 to 1.3 ± 1.0 (P = 0.03), and from 2.7 ± 1.7 to 4.1 ± 1.0 (P < 0.01), respectively. CONCLUSION: Topiramate-treated patients recently detoxified from alcohol usually have an improvement of their cognitive function, especially in the language and delayed recall domains. This phenomenon may be caused by the greater influence of cognitive recovery associated with decreased drinking as compared with topiramate-induced 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".