Extended-release injectable buprenorphine for the treatment of opioid use disorder among individuals at high risk of overdose: The FASTER-BUP udy
Bibliographic record
Abstract
BACKGROUND: Extended-release injectable buprenorphine (XR-BUP) has emerged as a promising alternative to address some of the adherence challenges of oral opioid use disorder (OUD) medications. However, real-world evaluations of XR-BUP in settings outside the United States and high-risk populations are limited. Our aim was to evaluate the feasibility and clinical utility of XR-BUP among people with OUD at risk of recurrent overdose in a low-barrier outpatient addiction treatment setting. METHODS: 24-week observational prospective cohort study of 25 adults with OUD and high risk of recurrent overdose (i.e., lifetime history of overdose, urine drug test positive for fentanyl) starting XR-BUP in a low-barrier outpatient addiction clinic in Vancouver, BC, Canada, between September 15, 2022 and July 2, 2024. The primary outcome was 6-month retention in XR-BUP treatment. Secondary outcomes included use of illicit opioids and safety. RESULTS: Participants were mostly men (64 %) and White (80 %), with a median age of 44 years old. Almost all participants had a lifetime history of prior overdose (92.0 %) and 76 % were using fentanyl at baseline. Only 8 (32.0 %) participants received the six scheduled XR-BUP injections (median number of injections 2). Of the 17 participants who discontinued the study, 7 switched to an alternative medication. The average percentage of opioid-free visits during the active treatment period was 28.5 %. Of the 72 injections administered, only 10 (13.9 %) were associated with mild injection site reactions. No other adverse events, including overdoses, were reported. CONCLUSIONS: While XR-BUP was well tolerated in this sample of people with OUD at high risk of overdose, six-month retention rates were low and most continued to use illicit opioids while on treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".