Birth defects after maternal exposure to corticosteroids: Prospective cohort study and meta-analysis of epidemiological studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Corticosteroids are first-line drugs for the treatment of a variety of conditions in women of childbearing age. Information regarding human pregnancy outcome with corticosteroids is limited. METHODS: We collected prospectively and followed up 184 women exposed to prednisone in pregnancy and 188 pregnant women who were counseled by Motherisk for nonteratogenic exposure. The primary outcome was the rate of major birth defects. A meta-analysis of all epidemiological studies was conducted. The Mantel-Haenszel summary odds ratio was calculated for the pooled studies with 95% confidence intervals. A cumulative summary odds ratio was also calculated by combining studies in chronological order. Chi-squared for homogeneity was determined to establish the comparability of the studies. RESULTS: In our prospective study, there was no statistical difference in the rate of major anomalies between the corticosteroid-exposed and control groups. In the meta-analysis, the Mantel-Haenszel summary odds ratio for major malformations with all cohort studies was 1.45 [95% CI 0.80, 2.60] and 3.03 [95% CI 1.08, 8. 54] when Heinonen et al. ('77) was removed. This suggests a marginally increased risk of major malformations after first-trimester exposure to corticosteroids. In addition, summary odds ratio for case-control studies examining oral clefts was significant (3.35 [95% CI 1.97, 5.69]). CONCLUSIONS: Although prednisone does not represent a major teratogenic risk in humans at therapeutic doses, it does increase by an order of 3.4-fold the risk of oral cleft, which is consistent with the existing animal studies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 it