Neurodevelopmental disorders among term infants exposed to antenatal corticosteroids during pregnancy: a population-based study
Bibliographic record
Abstract
OBJECTIVE: An increasing proportion of fetuses are exposed to antenatal corticosteroids (ACS). Despite their immediate beneficial effects, the long-term safety of ACS has been an ongoing source of concern. In the current study, we assessed the likelihood of neurodevelopmental problems among term infants exposed to ACS earlier in pregnancy compared with non-exposed term infants. DESIGN: Retrospective cohort study (2006-2011). Median duration of follow-up was 7.8 (IQR 6.4-9.2) years. SETTING: Population-based study, Ontario, Canada. PARTICIPANTS: weeks gestation) (n=529 205). EXPOSURE: ACS during pregnancy. PRIMARY AND SECONDARY OUTCOME MEASURES: A composite of diagnostic or billing codes reflecting proven or suspected neurodevelopmental problems during childhood including audiometry testing, visual testing or physician service claim with a diagnosis code related to a suspected neurocognitive disorder. RESULTS: At 5 years of age, the cumulative rate for the primary outcome was higher among infants exposed to ACS compared with non-exposed infants: 61.7% (3346/5423) vs 57.8% (302 520/523 782), respectively (p<0.001; number needed to harm (NNH)=25, 95% CI 19 to 38; adjusted HR (aHR) 1.12, 95% CI 1.08 to 1.16). Similar findings were observed for each of the individual components of the primary outcome: 15.3% vs 12.7% for audiometry testing (p<0.001; NNH=39, 95% CI 29 to 63; aHR 1.18, 95% CI 1.11 to 1.25); 45.4% vs 43.5% for visual testing (p=0.006; NNH=54, 95% CI 31 to 200; aHR 1.08, 95% CI 1.04 to 1.12) and 25.8% vs 21.6% for suspected neurocognitive disorder (p<0.001; NNH=24, 95% CI 19 to 33; aHR 1.16, 95% CI 1.10 to 1.21). CONCLUSIONS: We found an association among term infants between exposure to ACS during pregnancy and healthcare utilisation during childhood related to suspected neurocognitive and neurosensory disorders.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".