Differential long-term outcomes for voluntary and involuntary transition from injection to oral opioid maintenance treatment
Bibliographic record
Abstract
BACKGROUND: The most widely used maintenance treatment for opioid dependency is substitution with long-acting oral opioids. Treatment with injectable diacetylmorphine provides an opportunity for patients to stabilize and possibly transition to oral treatment, if clinically indicated. The aim of this study was to explore outcomes of individuals that received injectable diacetylmorphine and voluntarily transitioned to oral methadone. DESIGN AND METHODS: The North American Opiate Medication Initiative was a randomized controlled trial that compared the effectiveness of injectable diacetylmorphine (or hydromorphone) to oral methadone for long-term opioid-dependency. Treatment was provided for 12-months with an additional 3 months for transition and weaning. Participants were followed until 24-months from randomization. Among the participants randomized to injectable treatments, a sub-group voluntarily chose to transition to oral methadone (n = 16) during the treatment period. Illicit heroin use and treatment retention were assessed at 24-months for those voluntarily and involuntarily transitioning (n = 95) to oral methadone. RESULTS: At 24-months, the group that voluntarily transitioned to oral methadone had higher odds of treatment retention (adjusted odds ratio = 5.55; 95% confidence interval [CI] = 1.11, 27.81; Chi-square = 4.33, df = 1, p-value = 0.037) than the involuntary transition group. At 24-months, the adjusted mean difference in prior 30 days of illicit heroin use for the voluntary, compared to the involuntary group was -5.58 (95% CI = -11.62, 0.47; t-value = -1.83, df = 97.4, p-value = 0.070). CONCLUSIONS: Although the results of this study were based on small groups of self-selected (i.e., non-randomized) participants, our data underlines the critical importance of voluntary and patient-centered decision making. If we had continued offering treatment with diacetylmorphine, those retained to injectable medication may have sustained the achieved improvements in the first 12 months. Diversified opioid treatment should be available so patients and physicians can flexibly choose the best treatment at the time. CLINICAL TRIAL REGISTRATION: NCT00175357.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".