Observational study of the safety of buprenorphine+naloxone in pregnancy in a rural and remote population
Bibliographic record
Abstract
OBJECTIVES: To describe the effect of in utero exposure to the buprenorphine+naloxone combination product in a rural and remote population. SETTING: A district hospital that services rural and remote, fly-in communities in Northwestern Ontario, Canada. PARTICIPANTS: A retrospective cohort study was conducted of 855 mother infant dyads between 1 July 2013 and 30 June 2015. Cases included all women who had exposure to buprenorphine+naloxone during pregnancy (n=62). 2 control groups were identified; the first included women with no opioid exposure in pregnancy (n=618) and the second included women with opioid exposure other than buprenorphine+naloxone (n=159). Women were excluded if they had multiple pregnancy or if they were part of a methadone programme (n=16). The majority of women came from Indigenous communities. OUTCOMES: The primary outcomes were birth weight, preterm delivery, congenital anomalies and stillbirth. Secondary neonatal outcomes included gestational age at delivery, Apgar scores at 1 and 5 min, NAS Score >7 and treatment for neonatal abstinence syndrome (NAS). Secondary maternal outcomes included the number of caesarean sections, postpartum haemorrhages, out of hospital deliveries and transfer of care to tertiary centres. RESULTS: No difference was found in the primary outcomes or in the Apgar score and caesarean section rate between in utero buprenorphine+naloxone exposure versus no opioid exposure in pregnancy. Compared to women taking other opioids, women taking buprenorphine+naloxone had higher birthweight babies (p=0.001) and less exposure to marijuana (p<0.001) during pregnancy. CONCLUSIONS: Retrospective data suggest that there likely is no harm from taking buprenorphine+naloxone opioid agonist treatment in pregnancy. Larger, prospective studies are needed to further assess safety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".