Use of inhaled corticosteroids during the first trimester of pregnancy and the risk of congenital malformations among women with asthma
Why this work is in the frame
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Bibliographic record
Abstract
AIM: To investigate whether the maternal use of different doses of inhaled corticosteroids (ICSs) during the first trimester of pregnancy for the treatment of asthma increases the risk of congenital malformations in the offspring. METHODS: From the linkage of three administrative Canadian databases, a cohort of 4561 pregnancies from women with asthma who delivered between 1990 and 2000 was reconstructed. A two-stage sampling cohort design was used to acquire additional data from the woman's medical chart. Cases of congenital malformation were identified from the medical services database or the hospital database. Using refill patterns of medications, the average daily dose of ICSs used during the first trimester was calculated and categorised as follows: 0, 1-500, 500-1000 and >1000 microg/day in beclomethasone-chlorofluorocarbon equivalent. A Generalized Estimation Equation model was used to estimate the adjusted odds ratio of congenital malformation as a function of ICS daily dose. All analyses were performed for all malformations and major malformations separately. RESULTS: Within the cohort 418 babies were identified with a congenital malformation (9.2%), 278 of which had a major malformation. About 40% of women used ICSs during the first trimester, but only 5.3% of women used >500 microg/day. The adjusted odds ratio (95% CI) for all malformations associated with the use of ICSs during the first trimester was: 0.77 (0.53 to 1.13) for 1-500, 0.41 (0.19 to 0.92) for 501-1000 and 1.00 (0.42 to 2.36) for >1000 microg/day. The corresponding figures for major malformations were 0.90 (0.64 to 1.24), 0.56 (0.22 to 1.43) and 1.67 (0.56 to 5.03). CONCLUSION: This study adds evidence to the safety of ICSs for the treatment of asthma during pregnancy, with regard to the likelihood of congenital malformation.
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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 | 0.000 | 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 | 0.001 |
| 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 it