The FASTER-BUP Study, Extended-Release Injectable Buprenorphine for the Treatment of Opioid Use Disorder Among Individuals at High Risk of Overdose: Protocol for an Observational Prospective Study
Bibliographic record
Abstract
North America is facing an unprecedented public health emergency of opioid-related morbidity and mortality. The mortality benefits of oral medication treatment for opioid use disorder (MOUD), such as methadone or buprenorphine, are well documented. However, barriers to access and long-term engagement have prevented maximizing their benefits. Long-acting injectable buprenorphine formulations were developed to address some of the challenges associated with oral MOUD. The "Pilot study to assess the feasibility, efficacy, and safety of extended-release injectable buprenorphine for the treatment of opioid use disorder among individuals at high risk of overdose" (FASTER-BUP) was developed to explore this treatment option in populations at high risk of overdose in a real-world Canadian setting. FASTER-BUP is a 24-week observational prospective study evaluating the feasibility and clinical utility of extended-release injectable buprenorphine (XR-BUP) for the treatment of opioid use disorder (OUD) among 40 adults at high risk of overdose (ie, lifetime history of overdose or a positive urine drug test (UDT) for fentanyl within 30 days prior to screening) in Vancouver, BC. The primary outcome is retention in treatment and secondary outcomes include: use of unregulated opioids, safety, overdose events, treatment satisfaction, changes in drug-related problems, changes in quality of life, opioid cravings, health service utilization, and criminal activity. FASTER-BUP is the first study to explore XR-BUP among individuals at high risk of overdose in a real-world Canadian setting. This commentary provides a brief narrative about the study thus far and presents insights on key adaptations to the study protocol, including those adopted to mitigate recruitment challenges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.013 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.033 | 0.009 |
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".