Efficacy of Dexfenfluramine in the Treatment of Alcohol Dependence
Bibliographic record
Abstract
BACKGROUND: A substantial body of evidence supports a role for serotonin in modulating alcohol intake, which suggests that this neurotransmitter represents a promising target for pharmacotherapy development for alcohol use disorders. Dexfenfluramine. a serotonin releaser and reuptake inhibitor, decreases alcohol self-administration by rats. Its greater potency and several mechanisms of action suggest it should be more effective in treating alcohol dependence than drugs that only inhibit serotonin reuptake. METHODS: We conducted an 11 week, randomized, double-blind trial that compared oral placebo and dexfenfluramine 7.5, 15, 22.5, and 30 mg bid in 136 alcohol-dependent patients. A brief behavioral intervention was offered concurrently. RESULTS: The majority of subjects were male (72%), and the age of the group was 44 +/- 1 years (mean +/- SD). Both placebo- and drug-treated groups significantly reduced alcohol consumption compared with baseline (a 55% decrease in mean drinks per day; p < 0.01), but there were no significant differences between drug and placebo groups or dose effects for most outcome measures. CONCLUSIONS: Our results with dexfenfluramine are further evidence that serotonergic medications on their own do not significantly reduce alcohol consumption in alcohol-dependent individuals. Combination pharmacotherapy with agents that act on different receptors or neurotransmitter systems (e.g., naltrexone plus dexfenfluramine) may be one way to enhance serotonergic effects on drinking behavior and should be considered in future medication development clinical trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".