Patient-elected low-dose intravenous naloxone for rapid buprenorphine induction: a case report
Bibliographic record
Abstract
BACKGROUND: Buprenorphine is a common partial opioid agonist treatment for opioid use disorder (OUD). Despite its efficacy, major challenges to induction include the significant time consumption and the difficult requirement for patients to be in moderate opioid withdrawal. CASE PRESENTATION: We present the case of a 31-year-old man with severe OUD and regular fentanyl use who was successfully initiated on buprenorphine-naloxone using low-dose intravenous naloxone in ten minutes and administered 300 mg of extended-release injectable buprenorphine within two hours. This involved the rapid administration of small doses of intravenous naloxone with an assessment of withdrawal symptoms after each dose. Buprenorphine-naloxone is immediately administered once moderate withdrawal is reached. CONCLUSIONS: Low-dose intravenous naloxone provides an alternative method of buprenorphine induction that limits the experience of withdrawal to a shorter time window compared to existing protocols.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".