Antenatal Corticosteroids and Risk of Cerebral Palsy: A Regression Discontinuity Study
Bibliographic record
Abstract
OBJECTIVE: To use a natural experiment to investigate the effect of antenatal corticosteroids on the risk of cerebral palsy. STUDY DESIGN: We included singleton livebirths with a maternal admission for delivery from 31 + 0 through 36 + 6 weeks of gestation, in British Columbia, Canada, between 2000 and 2015. Guidelines recommended antenatal corticosteroids through 33 + 6 weeks, and we estimated the effect of the corresponding sharp drop in the proportion treated at 34 + 0 weeks on the risk of a composite of death before age 2 or cerebral palsy. We defined cerebral palsy using diagnostic codes in hospital and physician-billing records before age 5 years and corrected for misclassification using external estimates of the sensitivity and specificity. We used logistic regression to estimate marginal effects at 34 + 0 weeks. RESULTS: There were 20 009 children in our study sample. The crude and misclassification-corrected risks of cerebral palsy were 6.2 and 5.6 per 1000, respectively. The risk of death before age 2 or cerebral palsy declined with increasing gestational age at maternal admission for delivery, but we found no convincing evidence of an abrupt change just before vs just after 34 + 0 weeks (risk ratio: 0.98, 95% confidence interval: 0.50 to 1.98). Results were similar using a composite outcome of in-hospital newborn death or cerebral palsy, and using cerebral palsy alone. CONCLUSIONS: We did not find evidence that the lower likelihood of being treated with antenatal corticosteroid at 34 + 0 weeks affected the risk of cerebral palsy, but the estimates were imprecise and compatible with benefits or harms.
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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 | 0.037 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".