Is drug insurance status an effect modifier in epidemiologic database studies? The case of maternal asthma and major congenital malformations
Bibliographic record
Abstract
BACKGROUND: Our previous work on the association between maternal asthma and congenital malformations was based on cohorts formed by women with public drug insurance, i.e., over-represented by women with lower socioeconomic status, questioning the generalizability of our findings. This study aimed to evaluate whether or not drug insurance status, as a proxy of socioeconomic status, is an effect modifier for the association between maternal asthma and major congenital malformations. METHODS: A cohort of 36,587 pregnancies from asthmatic women and 198,935 pregnancies from nonasthmatic women selected independently of their drug insurance status was reconstructed with Québec administrative databases (1998-2009). Asthmatic women were identified using a validated case definition of asthma. Cases of major congenital malformations were identified using diagnostic codes recorded in the hospitalization database. Drug insurance status at the beginning of pregnancy was classified into three groups: publicly insured with social welfare, publicly insured without social welfare, and privately insured. Adjusted odds ratios were estimated with generalized estimation equations, including an interaction term between maternal asthma and drug insurance status. RESULTS: The prevalence of congenital malformations was 6.8% among asthmatic women and 5.8% among nonasthmatics. The impact of asthma on the prevalence of congenital malformations was significantly greater in women publicly insured with social welfare (odds ratio = 1.42; 95% confidence interval, 1.25-1.61) than in the other two groups ([odds ratio = 1.10; 1.00-1.21] in the publicly insured without social welfare and [odds ratio = 1.13; 1.07-1.20] in the privately insured group). CONCLUSION: The increased risk of major congenital malformation associated with asthma was significantly higher among pregnant women publicly insured with social welfare than among those privately insured. As a result of this effect modification by drug insurance status, findings from Québec observational studies using databases mainly formed of patients publicly insured with social welfare may not be generalized to the entire population.
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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 | 0.039 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".