Naltrexone in the treatment of alcohol dependence: a Canadian trial.
Bibliographic record
Abstract
OBJECTIVES: Alcohol dependence is a prevalent psychiatric disorder affecting approximately 12% of the adult population at some point in their lifetime. Psychosocial treatments are associated with only modest success rates. The first Canadian clinical trial with naltrexone, an opiate antagonist, was conducted to evaluate its safety and usefulness as an adjunctive treatment in the management of alcohol dependence. METHODS: One hundred twenty alcohol-dependent individuals were assessed to receive treatment with 50 mg of naltrexone orally for 12 weeks in an open-label trial. Patients were seen biweekly and received a concurrent psychosocial intervention. Treatment was conducted at multiple sites in Canada. RESULTS: Fifty-four per cent of subjects completed the entire 12 weeks of treatment. During the study, 39% of patients abstained, while of the individuals reporting drinking at baseline, 86% were consuming less alcohol by their final visit. These reductions were accompanied by a significant decrease in craving for alcohol at week 12, as measured by the Obsessive Compulsive Drinking Scale (P<0.01). Naltrexone was well tolerated and no serious adverse events were experienced. CONCLUSIONS: The data lend support to the hypothesis that endogenous opioid activity is involved in the regulation of alcohol intake, and that antagonists of endogenous opioids decrease craving and drinking. Opiate antagonists such as naltrexone are a new strategy in the treatment of alcohol dependence. Naltrexone can be safely given to female and male alcoholics, is acceptable to patients, and plays a role in reducing alcohol consumption and preventing relapse to heavy drinking.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".