Comparison of nicotine exposure during pregnancy when smoking and abstinent with nicotine replacement therapy: systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Smoking during pregnancy is strongly associated with negative pregnancy and perinatal outcomes. Some guidelines recommend nicotine replacement therapy (NRT) for smoking cessation during pregnancy, but adherence with NRT is generally poor and could be partially explained by nicotine-related safety concerns. We compared pregnant women's cotinine and nicotine exposures from smoking with those when they were abstinent from smoking and using NRT. DESIGN: Systematic review with meta-analysis and narrative reporting. Twelve studies were included: in most, only one type of NRT was used. Seven were quality-assessed and judge of variable quality. SETTING: Studies from any setting that reported nicotine or cotinine levels when smoking and later when abstinent and using NRT. PARTICIPANTS: Pregnant women who smoked and became abstinent but used NRT either in a cessation study or in a study investigating other impacts of NRT. MEASUREMENTS: We quality-assessed longitudinal cohort studies using a modified version of the Newcastle-Ottawa scale. For meta-analysis, we used mean within-person differences in cotinine or nicotine levels when smoking and at later follow-up when abstinent and using NRT. Where such data were not available, we calculated differences in group mean levels and reported these narratively, indicating where data were not completely longitudinal. FINDINGS: = 42.1%, P = 0.11). Of eight narratively-described studies, six reported lower cotinine and/or nicotine levels when abstinent and using NRT; two had mixed findings, with higher levels when abstinent but using NRT reported from at least one assay time-point. CONCLUSIONS: Pregnant women who use nicotine replacement therapy instead of smoking reduce their nicotine exposure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".