Asthma exacerbations during the first trimester of pregnancy and congenital malformations: revisiting the association in a large representative cohort
Bibliographic record
Abstract
BACKGROUND: We previously reported an increased prevalence of any congenital malformation among women experiencing moderate-to-severe asthma exacerbations during the first trimester of pregnancy, based on a study in which 90.1% of the cohort of women were social welfare recipients. This study re-examined the association between asthma exacerbations and congenital malformations in a new large representative cohort of asthmatic pregnant women. METHODS: A cohort of 36 587 pregnancies in asthmatic women was reconstructed from Québec Province administrative databases (1998-2009). Occurrences of asthma exacerbations during the first trimester of pregnancy were assessed and categorised into severe, moderate and no such exacerbations. For comparison, we also considered moderate and severe asthma exacerbations combined. Congenital malformations were identified using diagnoses recorded in the hospitalisation database. Generalised estimation equations were used to estimate adjusted ORs of congenital malformations. RESULTS: The prevalence of any congenital malformation was 19.1%, 11.7% and 12.0% among women with severe, moderate and no such exacerbations during the first trimester, respectively. The adjusted OR for all malformations was 1.64 (95% CI 1.02 to 2.64) when women with severe exacerbations were compared with those in the reference group, while no association was seen for moderate exacerbations. Also, no association was observed between cases of moderate and severe asthma exacerbations combined and any congenital malformation. CONCLUSIONS: Only severe asthma exacerbations were found to significantly increase the risk of congenital malformations in this representative study. Previous studies possibly overestimated the risk because they were based mainly on women at a lower socioeconomic status.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".