The unborn smoker: association between smoking during pregnancy and adverse perinatal outcomes
Bibliographic record
Abstract
OBJECTIVE: To evaluate a possible dose-response relationship between active maternal smoking during pregnancy and adverse perinatal outcome. DESIGN: Retrospective cohort study. SETTING: Population-based in Montreal, Quebec, Canada. POPULATION: Women who gave birth to a liveborn or stillborn infant during the period of January 2001 to December 2007. METHODS: Active smokers of different daily cigarette consumption (n=1646) were identified through maternal self-reporting. The reference group comprised 19,292 non-smoking women who delivered during the same period. MAIN OUTCOME MEASURES: Birth weight, preterm delivery rate, fetal and neonatal mortality and morbidity, and congenital malformations. RESULTS: Preterm delivery rate was significantly higher in the smoking group compared with controls (22.2% vs. 12.4%, P<0.05), as was intrauterine fetal demise (1.4% vs. 0.3%, P<0.05). Newborns of active smokers were more likely to weigh less (3150±759 g vs. 3377±604 g, P<0.05), suffer from respiratory distress syndrome (2.5% vs. 1.3%, P<0.05), suffer from a cardiac malformation (1.5% vs. 0.8%, P<0.05), and die (neonatal death 1.2% vs. 0.6%, P<0.05). A dose-response relationship was demonstrated between levels of daily cigarette smoking and several adverse outcomes. Using multiple regression models, smoking was found to be an independent predictor of preterm delivery (odds ratios (OR) 1.9, 95% confidence intervals (95%CI) 1.6-2), and intrauterine fetal demise (OR 2.4, 95%CI 1.4-4.2). CONCLUSION: Any amount of daily smoking appears to harm the fetus and newborn. As pregnancy may be a "window of opportunity" for behavioural changes, efforts to promote smoking cessation should be encouraged.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".