Effect of maternal asthma on the risk of specific congenital malformations: A population‐based cohort study
Bibliographic record
Abstract
BACKGROUND: There is a lack of consensus in the literature about the effect of maternal asthma on the development of congenital malformations. OBJECTIVE: To further examine the association between maternal asthma and the risk of congenital malformations. METHODS: A cohort of 41,637 pregnancies from women with and without asthma who delivered between 1990 and 2002 was reconstructed by linking three Quebec (Canada) administrative databases. All cases of malformations were identified using either the medical services or the hospital databases. The main exposure was maternal asthma, defined by the presence of at least one asthma diagnosis and at least one prescription for an asthma medication at any time in the two years before or during pregnancy. Generalized Estimation Equation models were performed to estimate the adjusted odds ratio (OR) of congenital malformations as a function of maternal asthma. RESULTS: The crude prevalences of any congenital malformation were 9.5% and 7.5% for women with and without asthma, respectively. Maternal asthma was significantly associated with an increased risk of any malformation (OR=1.30; 95% CI: 1.20-1.40) and three specific groups (at the 0.0028 level): nervous system (excluding spina bifida: OR=1.83; 1.37-2.83); respiratory system (OR=1.75; 1.21-2.53); and digestive system (OR=1.48; 1.19-1.85). CONCLUSIONS: Maternal asthma increases the risk of specific groups of congenital malformations. The disease itself, through fetal oxygen impairment, is likely to play a role in this increased risk, but more research is needed to disentangle the relative effect of asthma and medications used to treat this disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.005 | 0.005 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".