The Role of Preterm Birth in the Association Between Opioid Maintenance Therapy and Neonatal Abstinence Syndrome
Bibliographic record
Abstract
BACKGROUND: Pregnant women treated with methadone as opioid maintenance therapy are more likely than women treated with buprenorphine to deliver preterm. Preterm birth is associated with less risk of neonatal abstinence syndrome (NAS). We sought to assess the role of preterm birth as a mediator of the relationship between in utero exposure to methadone and NAS compared with buprenorphine. METHODS: We studied 716 women receiving methadone or buprenorphine and delivering liveborn infants at Magee-Womens Hospital, Pittsburgh, Pennsylvania (2013-15). We implemented inverse probability weighted marginal structural models to isolate the role of preterm birth (<37 weeks' gestation). Weights accounted for confounding by maternal age, race, insurance, parity, delivery year, marital, employment, hepatitis C, and smoking status. RESULTS: Approximately 57% of the cohort were treated with methadone. Preterm birth was more common in methadone-exposed pregnancies (25% versus 14%). The incidence of NAS treatment was higher in methadone compared with buprenorphine-exposed infants (65% vs 49%), and term compared with preterm births (64% vs 36%). For every 100 infants liveborn to mothers treated for opioid dependence, there were 13 excess cases of NAS among infants exposed to methadone compared with buprenorphine (adjusted risk difference [RD] 13.3, 95% confidence interval [CI] 5.7, 20.9). Among term births, this increased to 17 excess cases of NAS in methadone- compared with buprenorphine-exposed (RD 16.7, 95% CI 9.3, 24.0). CONCLUSION: The further increased risk of NAS associated with methadone use vs buprenorphine in term deliveries emphasises the utility of buprenorphine in clinical settings aimed at decreasing NAS.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".