Sodium Oxybate for Alcohol Dependence: A Network Meta-Regression Analysis Considering Population Severity at Baseline and Treatment Duration
Bibliographic record
Abstract
AIMS: The estimated effect of sodium oxybate (SMO) in the treatment of alcohol dependence is heterogeneous. Population severity and treatment duration have been identified as potential effect modifiers. Population severity distinguishes heavy drinking patients with <14 days of abstinence before treatment initiation (high-severity population) from other patients (mild-severity population). Treatment duration reflects the planned treatment duration. This study aimed to systematically investigate the effect of these potential effect moderators on SMO efficacy in alcohol-dependent patients. METHODS: Network meta-regression allows for testing potential effect modifiers. It was selected to investigate the effect of the above factors on SMO efficacy defined as continuous abstinence (abstinence rate) and the percentage of days abstinent (PDA). Randomized controlled trials for alcohol dependence with at least one SMO group conducted in high-severity and mild-severity populations were assigned to a high-severity and mild-severity group of studies, respectively. RESULTS: Eight studies (1082 patients) were retained: four in the high-severity group and four in the mild-severity group. The high-severity group was associated with larger SMO effect sizes than the mild-severity group: abstinence rate risk ratio (RR) 3.16, P = 0.004; PDA +26.9%, P < 0.001. For PDA, longer treatment duration was associated with larger SMO effect size: +11.3% per extra month, P < 0.001. In the high-severity group, SMO showed benefit: abstinence rate RR 2.91, P = 0.03; PDA +16.9%, P < 0.001. In the mild-severity group, SMO showed benefit only in PDA for longer treatment duration: +23.9%, P < 0.001. CONCLUSIONS: In the retained studies with alcohol-dependent patients, high-severity population and longer treatment duration were associated with larger SMO effect sizes.
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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 | 0.019 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.049 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".