Risk of perinatal mortality associated with asthma during pregnancy
Bibliographic record
Abstract
BACKGROUND: Thirteen studies investigating the association between asthma during pregnancy and perinatal mortality reported generally no increased risk. Most of these studies should be interpreted with caution because they were limited in terms of statistical power. A study was therefore undertaken to evaluate whether maternal asthma during pregnancy increases the risk of perinatal mortality. METHODS: Through three administrative databases from Québec (Canada), a cohort of women with and without asthma who had at least one pregnancy between 1990 and 2002 was formed. Perinatal mortality was identified by diagnostic codes. The adjusted odds ratio (OR) of perinatal mortality in women with and without asthma was compared using Generalised Estimation Equation (GEE) models. The first model included all potential confounders (except small for gestational age, SGA), the second model excluded birth weight, gestational age at birth and SGA and the third model excluded birth weight, gestational age at birth but included only SGA. This analysis was also stratified for birth weight and gestational age at birth. RESULTS: The cohort was formed of 13 100 and 28 042 single pregnancies in women with and without asthma. The crude OR of perinatal mortality was 1.35 (95% CI 1.08 to 1.67), which decreased to 0.93 (95% CI 0.75 to 1.17) after adjustment for birth weight and gestational age at birth. Women with asthma had a higher rate of low birthweight babies and preterm delivery than those without asthma. CONCLUSION: The increased risk of low birthweight babies and premature delivery in women with asthma may partly explain the association between maternal asthma and the increased risk of perinatal mortality.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".