Associations of maternal asthma severity and control with pregnancy complications
Bibliographic record
Abstract
OBJECTIVES: To assess the associations of maternal asthma severity and control with pregnancy-induced hypertension (PIH), gestational diabetes and cesarean delivery. METHODS: A cohort of 41 660 pregnancies from women with and without asthma who delivered between 1990 and 2002 was constructed by linking Québec's administrative databases. Maternal asthma was defined by at least one asthma diagnosis and one dispensed prescription for an asthma medication in the 2 years before or during pregnancy. Asthma severity and control were assessed using validated indexes during the entire pregnancy to study cesarean delivery and 1-year prior to week 20 of gestation to study PIH and gestational diabetes. Generalized Estimation Equation models were used to obtain odds ratios (OR) for PIH, gestational diabetes and cesarean in association with maternal asthma severity and control. RESULTS: Almost one-third of the women had uncontrolled asthma and up to 5% had severe asthma. Severe asthma increased the risk of cesarean delivery (OR = 1.35; 95% CI: 1.11-1.63) compared with mild asthma, but no association was found between asthma severity and the other outcomes. The level of asthma control was not associated with any of the outcomes, except for a near-significant increased risk of PIH among uncontrolled women (OR = 1.18; 95% CI: 0.97-1.42). CONCLUSIONS: The risk of gestational diabetes was not associated with asthma severity or control, and the risk of PIH was not associated with asthma severity. However, further studies are needed to clarify the association between asthma control and PIH. The increased risk of cesarean among women with severe asthma may be explained by the physician's and patient's concerns over the safety of normal delivery.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 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".