Effect of Acetaminophen use during pregnancy on adverse pregnancy outcomes: a systematic review and meta-analysis
Bibliographic record
Abstract
A high number of women are exposed to acetaminophen during pregnancy worldwide. This drug safety during pregnancy regarding preterm birth, birth weight, and fetal development has not been well described. This study investigated the effect of acetaminophen use during pregnancy on selected adverse pregnancy outcomes. Databases were searched to identify studies reporting the effects of acetaminophen use during pregnancy on preterm birth, low birth weight, and small for gestational age. The studies’ quality was assessed by the Newcastle-Ottawa Scale and the Methodological Index for Non-Randomized Studies. Risk ratios with 95% confidence intervals were estimated using a fixed or random‐effects model. Six studies were included for final review, four cohort and two case‐control studies. We found no increased risk of preterm birth (RR 0.97; 95% CI 0.59–1.58), and decreased risks of low birth weight (RR 0.65; 95% CI 0.59–0.72) and small for gestational age (RR 0.69; 95% CI 0.50–0.97). Acetaminophen exposure during the third trimester revealed non-significantly in the outcomes. Exposure to acetaminophen during pregnancy appears to not increase the risk of the outcomes analyzed. However, there is a lack of information regarding the exposure dose and frequency of acetaminophen use.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".