Prescribing Characteristics Associated with Return to Opioid use following Buprenorphine Treatment in Ontario
Bibliographic record
Abstract
Buprenorphine is a first-line treatment for opioid use disorder (OUD), however, many clients choose to discontinue therapy. We used Cox proportional hazards modelling to understand which prescribing characteristics were associated with return to opioids within 18 months following buprenorphine taper among persons 18 years or older with OUD in Ontario. Among 5,774 individuals, 65.8% experienced at least one opioid-overdose, treatment re-entry, or return to prescription opioid use. Time to taper initiation >1 year vs. ≤1 year (aHR:0.69, 95% CI:0.48-0.997) and a lower average rate of taper (≤ 2 mg/month and >2 to ≤4 mg/month compared with >4 mg/month) (aHR:0.65, 95% CI:0.46-0.91; aHR:0.69, 95% CI:0.51-0.93) were associated with lower risk of opioid-overdose. A more stepped taper, with doses decreasing in ≤1.75% of days compared with >3.5% of days, was also associated with reduced risk of opioid-overdose (aHR:0.64, 95% CI:0.43-0.93). Findings highlight the risks associated with tapering buprenorphine and underscore the importance of careful treatment planning.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".