Successful Buprenorphine/Naloxone Low-dose Induction in Pregnancy: A Case Report
Bibliographic record
Abstract
BACKGROUND: Medication for opioid use disorder (OUD) with methadone or buprenorphine/naloxone is recommended for pregnant women with OUD. Traditional buprenorphine/naloxone induction requires patients to be in moderate withdrawal before the first dose of medication to minimize the chances of precipitated withdrawal. The low-dose buprenorphine "microinduction" (Bernese) method was described in 2016 and involves giving small doses of buprenorphine to patients for whom opioid withdrawal was not desirable. This method is being used widely in Vancouver in the context of high rates of overdose due to fentanyl poisoning. CASE PRESENTATION: A 24-year-old woman, in her first pregnancy, with severe opioid and stimulant use disorder successfully started on buprenorphine/naloxone through a low-dose-induction protocol. The dose was started at 0.5 mg sublingual daily and slowly increased to 18 mg over 17 days. She continued to use fentanyl/heroin during the induction. She did not experience precipitated withdrawal and was able to stop using nonprescribed opioids once at a therapeutic dose of buprenorphine/naloxone. DISCUSSION: This represents the first documented case of successful buprenorphine/naloxone low-dose induction in pregnancy. First-line recommendations still remain to use traditional buprenorphine/naloxone induction when patients present in withdrawal. Obtaining informed consent regarding the lack of research on low-dose induction in pregnancy as well as discussion of risks and benefits is essential. CONCLUSION: Low-dose induction with buprenorphine/naloxone was successfully done in an outpatient setting. This represents a novel way of initiation of medication for OUD, which may enhance choice and collaboration between health care providers and women impacted by substance use in pregnancy.
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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) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 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".