Opioid Medical Detoxification Compared to Opioid Agonist Treatment during Pregnancy: A Scoping Review
Bibliographic record
Abstract
Opioid use disorder (OUD) is highly prevalent, affecting up to 1% of pregnancies. The current standard of care for the management of OUD during pregnancy has been maintained with opioid agonist treatment (OAT), using either methadone or buprenorphine. OAT use has been associated with a risk of neonatal abstinence syndrome (NAS), which requires a longer neonatal length of stay for monitoring and possible pharmacological treatment. As a result, opioid medical detoxification (OMD) was proposed as an alternative strategy to reduce the stigma associated with OAT and to eliminate the risk of NAS by detoxifying or tapering pregnant persons during their pregnancy before delivery; however, the safety and effectiveness of OMD during pregnancy have not been established. This scoping review aims to summarize recent evidence related to maternal, obstetrical, and neonatal outcomes of OMD in comparison to OAT maintenance. This review also provides recommendations for future research initiatives to fill gaps in managing this patient population.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".