Direct Induction of Buprenorphine Extended-Release: A Case Report
Bibliographic record
Abstract
Buprenorphine has superior safety in opioid use disorder compared with alternatives due to its action as a partial opioid agonist, which limits its ability to cause respiratory depression. There is a risk of precipitated opioid withdrawal after buprenorphine exposure in someone using full opioid agonists. Buprenorphine induction strategies that avoid precipitated withdrawal remain a crucial component for starting buprenorphine in individuals actively using opioids. These strategies start with low doses of buprenorphine increasing over time, which may avoid precipitated withdrawal at the cost of an extended initiation period, potentially discouraging patients and increasing healthcare costs. A 55-year-old male with severe opioid use disorder and unregulated fentanyl use presented after an overdose, was admitted due to a cerebral venous sinus thrombosis and anemia (hemoglobin of 4.4 g/dL), and was given 300 mg of buprenorphine injection depot subcutaneously without any prior buprenorphine stabilization. Prior to injection, he was taking 30 mg of methadone and 96 mg of oral hydromorphone equivalents daily. Over the 6 hours after injection, he received another 272 mg oral hydromorphone equivalents and experienced a maximum Clinical Opiate Withdrawal Scale score of 7. Over the next 18 hours, he received no additional hydromorphone, and his Clinical Opiate Withdrawal Scale was a maximum of 1. This case illustrates a buprenorphine induction method without precipitated withdrawal by relying on the elution of buprenorphine from the subcutaneous depot alongside full agonist opioids that are given as needed. If these results are readily replicable, this approach may have significant implications for the accessibility and acceptability of buprenorphine for patients and providers.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".