Systematic Review and Meta-Analysis to Assess the Safety of Bupropion and Varenicline in Pregnancy
Bibliographic record
Abstract
INTRODUCTION: Smoking in pregnancy is a substantial public health issue, but, apart from nicotine replacement therapy (NRT), pharmacological therapies are not generally used to promote cessation. Bupropion and varenicline are effective cessation methods in nonpregnant smokers and this systematic review investigates their safety in pregnancy. METHODS: We searched MEDLINE, EMBASE, CINAHL, and PsychINFO databases for studies of any design reporting pregnancy outcomes after bupropion or varenicline exposure. We included studies of bupropion used for smoking cessation, depression, or where the indication was unspecified. Depending on study design, quality was assessed using the Newcastle-Ottawa Scale or Cochrane Risk of Bias Tool. Most findings are reported narratively but meta-analyses were used to produce pooled estimates for the proportion of live births with congenital malformations and of the mean birthweight and gestational age at delivery following bupropion exposure. RESULTS: In total, 18 studies were included: 2 randomized controlled trials, 11 cohorts, 2 case- control studies, and 3 case reports. Study quality was variable. Gestational safety outcomes were reported in 14 bupropion and 4 varenicline studies. Meaningful meta-analysis was only possible for bupropion exposure, for which the pooled estimated proportion of congenital malformations amongst live-born infants was 1.0% (95% CI = 0.0%-3.0%, I2 = 80.9%, 4 studies) and the mean birthweight and mean gestational age at delivery was 3305.9 g (95% CI = 3173.2-3438.7 g, I2 = 77.6%, 5 studies) and 39.2 weeks (95% CI = 38.8-39.6 weeks, I2 = 69.9%, 5 studies), respectively. CONCLUSIONS: There was no strong evidence that either major positive or negative outcomes were associated with gestational use of bupropion or varenicline. PROSPERO registration number CRD42017067064. IMPLICATIONS: We believe this to be the first systematic review investigating the safety of bupropion and varenicline in pregnancy. Meta-analysis of outcomes following bupropion exposure in pregnancy suggests that there are no major positive or negative impacts on the rate of congenital abnormalities, birthweight, or premature birth. Overall, we found no evidence that either of these treatments might be harmful in pregnancy, and no strong evidence to suggest safety, but available evidence is of poor quality.
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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 | 0.027 | 0.079 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.050 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".