Antenatal corticosteroids and newborn respiratory outcomes in twins: A regression discontinuity study
Bibliographic record
Abstract
Abstract Objective To estimate the effect of antenatal corticosteroids on newborn respiratory morbidity in twins. Design Regression discontinuity applied to population‐based birth registry data. Setting British Columbia, Canada, 2008–2018. Population Twin pregnancies admitted for birth between 31+0 and 36+6 weeks of gestation. Methods During our study period, Canadian clinical practice guidelines recommended antenatal corticosteroid administration for imminent preterm birth up to 33+6 weeks. We used a logistic model to compare the predicted risks of our outcomes among pregnancies admitted for birth immediately before this clinical cut‐point (higher probability of exposure to antenatal corticosteroids) versus immediately after it (lower probability). Main outcome measures Our primary outcome was a composite of newborn respiratory distress or in‐hospital death. Our secondary outcome was a composite of newborn respiratory intervention or in‐hospital death. Results Among 2524 pregnancies (5035 liveborn twins), 47% of admissions before 34+0 weeks of gestation were exposed to antenatal corticosteroids but only 4.2% of admissions after this cut‐point were exposed. The risk of newborn respiratory distress or in‐hospital mortality increased abruptly at 34+0 weeks, corresponding to a protective effect of treatment (risk ratio [RR] 0.69, 95% CI 0.53–0.90; risk difference [RD] −12 cases per 100 births, 95% CI −20 to −4.1). There was no clear evidence for or against an effect on newborn respiratory intervention or in‐hospital death (RR 0.89, 95% CI 0.70–1.13; RD −4.2 per 100, 95% CI −13 to +4.2). Conclusions Our findings provide evidence for the effectiveness of antenatal corticosteroids in preventing adverse newborn respiratory outcomes in twins.
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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 | 0.010 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".