Estimated Dose Exposure of the Neonate to Buprenorphine and Its Metabolite Norbuprenorphine via Breastmilk During Maternal Buprenorphine Substitution Treatment
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to estimate the dose of buprenorphine and its primary metabolite norbuprenorphine that a breastfed infant would receive during maternal maintenance treatment with buprenorphine. STUDY DESIGN: Seven pregnant opioid-dependent women taking buprenorphine (median, 7 mg/day; range, 2.4-24 mg) and who intended to breastfeed were recruited. After lactation was established, several milk samples were collected from each subject over a 24-hour dose interval, and buprenorphine and norbuprenorphine concentrations were measured by liquid chromatography-tandem mass spectrometry. The average concentration (C(avg)) across the dose interval was estimated as for both buprenorphine and norbuprenorphine (as buprenorphine equivalents). Absolute infant dose (AID), defined as C(avg) × daily milk intake, and relative infant dose (RID), defined as 100×AID/weight-adjusted maternal daily dose, via milk were calculated, assuming a milk intake of 0.15 L/kg/day. The infant's health and progress were assessed directly and by questionnaire on the study day. RESULTS: Mean (95% confidence interval) norbuprenorphine concentration in milk and AID values (1.94 [0.79-3.08] μg/L and 0.29 [0.12-0.46] μg/kg/day, respectively) were approximately half those for buprenorphine (3.65[1.61-5.7] μg/L and 0.55 [0.24-0.85] μg/kg/day, respectively). Similarly, the mean RID values were 0.18% (0.11-0.25%) for norbuprenorphine and 0.38% (0.23-0.53%) for buprenorphine. The breastfed infants showed no adverse effects, were all in good health, and were progressing as expected. CONCLUSION: Thus the dose of buprenorphine and norbuprenorphine received via milk is unlikely to cause any acute adverse effects in the breastfed infant.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".