Challenges with buprenorphine inductions in the context of the fentanyl overdose crisis: A case series
Bibliographic record
Abstract
INTRODUCTION AND AIMS: North America is currently experiencing an epidemic of opioid overdose deaths, driven by the proliferation of fentanyl in the street drug market. Although buprenorphine/naloxone (BUP/NX) is an evidence-based, first-line opioid agonist for the management of opioid use disorder, a key challenge in its prescribing lies in the fact that it can precipitate opioid withdrawal during its initial induction process. At this time, there is minimal literature on the BUP/NX induction process in individuals who use illicit fentanyl regularly. DESIGN, METHODS AND RESULTS: A case series from a Vancouver, Canada addiction medicine clinic of three fentanyl-exposed patients who experienced unexpected, precipitated withdrawal when initiating BUP/NX. DISCUSSION AND CONCLUSION: These cases describe incidents of precipitated opioid withdrawal occurring after unusually long periods of fentanyl abstention. Although fentanyl is experienced as a short-acting opioid, the drug persists much longer in the body's peripheral tissues. Here, we highlight the new challenges fentanyl may pose to current BUP/NX induction strategies, and explore the possibility of a long-acting pharmacokinetic effect of fentanyl in the setting of repeated illicit use.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".