Maternal smoking and preeclampsia.
Bibliographic record
Abstract
OBJECTIVE: To study the relationship between maternal smoking and preeclampsia and whether this association differs between primiparous and multiparous women. STUDY DESIGN: We conducted a population-based, retrospective, cohort study of 58,216 singleton pregnancies from northern and central Alberta, Canada, between 1995 and 1997. Multivariate logistic regression was used to control for maternal alcohol consumption, drug dependence, maternal age, maternal weight, prior intrauterine growth restriction and other confounders. RESULTS: Maternal smoking was associated with a significantly reduced overall risk of preeclampsia (adjusted odds ratio [aOR]: .61; 95% confidence interval [CI]: .50-.75; P < .01). Stratified analyses showed that in primiparous pregnancies, maternal smoking was associated with a significantly decreased risk (aOR: .63; 95% CI: .50-.80; P < .01); in multiparous women, maternal smoking was not associated with a statistically significant decreased risk of preeclampsia (aOR: 0.72; 95% CI: .51-1.02; P > .05). CONCLUSION: Maternal smoking is protective against preeclampsia. Understanding the underlying biologic mechanisms of this protective effect may advance our knowledge of the pathogenesis of preeclampsia.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".