Maternal opioid treatment after delivery and risk of adverse infant outcomes: population based cohort study
Bibliographic record
Abstract
OBJECTIVE: To examine whether maternal opioid treatment after delivery is associated with an increased risk of adverse infant outcomes. DESIGN: Population based cohort study. SETTING: Ontario, Canada. PARTICIPANTS: 865 691 mother-infant pairs discharged from hospital alive within seven days of delivery from 1 September 2012 to 31 March 2020. Each mother who filled an opioid prescription within seven days of discharge was propensity score matched to a mother who did not. MAIN OUTCOME MEASURES: The primary outcome was hospital readmission of infants for any reason within 30 days of their mother filling an opioid prescription (index date). Infant related secondary outcomes were any emergency department visit, hospital admission for all cause injury, admission to a neonatal intensive care unit, admission with resuscitation or assisted ventilation, and all cause death. RESULTS: 85 675 mothers (99.8% of the 85 852 mothers prescribed an opioid) who filled an opioid prescription within seven days of discharge after delivery were propensity score matched to 85 675 mothers who did not. Of the infants admitted to hospital within 30 days, 2962 (3.5%) were born to mothers who filled an opioid prescription compared with 3038 (3.5%) born to mothers who did not. Infants of mothers who were prescribed an opioid were no more likely to be admitted to hospital for any reason than infants of mothers who were not prescribed an opioid (hazard ratio 0.98, 95% confidence interval 0.93 to 1.03) and marginally more likely to be taken to an emergency department in the subsequent 30 days (1.04, 1.01 to 1.08), but no differences were found for any other adverse infant outcomes and there were no infant deaths. CONCLUSIONS: Findings from this study suggest no association between maternal opioid prescription after delivery and adverse infant outcomes, including death.
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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) | 0.000 | 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".