OPIUM TRIAL: A MULTICENTRE RANDOMIZED CLINICAL TRIAL COMPARING OPIUM TINCTURE WITH METHADONE FOR MEDICATION-ASSISTED TREATMENT OF OPIOID USE DISORDER
Bibliographic record
Abstract
Objective: To characterize the patterns of substance use and risky-behavior profiles among the participants and compare rural and urban areas. Methods: Data were obtained from 204 participants in opium trial, a phase 3 multi-center, parallel-group, double-blind, non-inferiority randomized clinical trial in Iran. Participants with opioid use disorder were randomized to receive either methadone or opium tincture. Baseline assessments were Addiction Severity Index u2013 5, blood tests, urine toxicology, and sociodemographic questionnaire. Recruitment centers were four private outpatient medication-assisted treatment clinics located in three major cities and one rural center in Iran. Results: The three most commonly used substance during lifetime were opium (80%), methadone (67%), and Shireh/Sukhteh (58%). Polysubstance use was reported by 96 (47%) participants. Lifetime history of overdose and injection were positive in 9% and 7% of the sample, respectively. Rural participants had lower frequencies of unemployment (18% vs. 45%, p <0.01) and lifetime incarceration (14% vs. 30%, p=0.02), and were more satisfied with their family situation (85% vs. 70%, p=0.04) compared to urban centers. Urban centers reported significantly higher heroin and methamphetamine use and a significantly lower prevalence of opium than rural centers. Moreover, participants in urban areas demonstrated a higher risk profile with a higher number of overdoses in the past (12% vs. 0, p=0.01). Conclusions: Types of substances used by individuals in urban and rural areas in Iran are different. Furthermore, participants in urban centers exhibit higher risky behaviors, such as higher number of reported overdoses, than rural participants.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".