Hypnotic benzodiazepine receptor agonist exposure during pregnancy and the risk of congenital malformations and other adverse pregnancy outcomes: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: To determine if there is an association between antenatal hypnotic benzodiazepine receptor agonist exposure and congenital malformations or other adverse pregnancy outcomes in the offspring. METHODS: Databases were searched to January 31, 2021. Cohort studies published in English on congenital malformations or other adverse pregnancy outcomes in infants following exposure compared with those unexposed, were summarized and meta-analyzed where possible. RESULTS: Following screening, 25 studies were assessed for eligibility and seven included in the meta-analyses. Five studies were pooled for congenital malformations following first trimester exposure and not statistically significant (OR 0.87, 95% CI 0.56-1.36). The five studies that assessed for preterm birth following anytime exposure did pool to a statistically significant effect (OR 1.49, 95% CI 1.19-1.86); study quality, control for other psychotropic drugs and psychiatric diagnosis did not appear to be moderators. There were two missing studies when examining for publication bias in both of the main analyses above but the revised estimates were similar to the original. Low birth weight (LBW) was significant (three studies, any time exposure, OR 1.51, 1.27-1.78) as was small for gestational age (SGA) (three studies with anytime exposure, OR 1.34, 1.22-1.48). There were too few studies to summarize birth weight, gestational age, respiratory difficulties, APGAR score at 5 min and NICU admission. CONCLUSIONS: Pregnancy exposure to hypnotics was not associated with a higher risk for congenital malformations but was associated with an increased risk for preterm birth, LBW and SGA compared with those infants who were not exposed. These findings are consistent with the antidepressant and benzodiazepine literature.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.036 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".