Comparing opium tincture and methadone for medication‐assisted treatment of patients with opioid use disorder: Protocol for a multicenter parallel group noninferiority double‐blind randomized controlled trial
Bibliographic record
Abstract
OBJECTIVES: This is the first study to compare the safety and efficacy of opium tincture (OT) with methadone for treatment of opioid use disorder. METHODS: In this multicenter, double-blind, noninferiority controlled trial, a stratified sample of 204 participants with opioid use disorder were recruited from community outreach, drop-in centers, and triangular clinics. Participants were excluded in case of active participation in another treatment program for opioid use disorder, hypersensitivity to trial medications, pregnancy, and certain serious medical conditions. They were randomized to receive either OT or methadone with an allocation ratio of 1:1 using a patient-centered flexible dosing strategy. Eligible participants were followed for a period of 12 weeks. Primary outcome is the difference in percentage of patients retained in the treatment. Secondary outcomes are craving, withdrawal symptoms, physical health, mental health, quality of life, and severity of substance use problems, cognitive function, safety profile, cost-effectiveness, and participants' satisfaction. Both intention-to-treat and per-protocol analyses will be conducted. The Ethics Board of the University of British Columbia and Tehran University of Medical Sciences approved the study. (clinicaltrials.gov; NCT02502175). RESULTS: To be reported after final analysis. CONCLUSIONS: If shown to be effective, OT will diversify the options for medication-assisted treatment of opioid use disorder.
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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 | 0.037 | 0.030 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.057 | 0.013 |
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".