Risk of malformation after ondansetron in pregnancy: An updated systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Ondansetron is increasingly used off label to treat nausea and vomiting during pregnancy. The main objective of this study was to evaluate the risk of major congenital malformations (MCM), cardiac defects and orofacial clefts associated with first trimester exposure to ondansetron using a meta‐analytic approach. MEDLINE, ClinicalTrials.gov and Scopus were searched until November 2019. All comparative cohort and case–control studies on MCM, cardiac or orofacial defects and use of ondansetron during pregnancy were included. A team of paired reviewers independently extracted data using a proprietary collaborative WEB‐based meta‐analysis platform ( metaPreg.org ). Pooled odd ratios with corresponding 95% CIs were calculated using random effects models. From 214 records initially retrieved, 12 studies were included. Using all available information to date, first trimester exposure to ondansetron was found to be associated with an increased risk of (a) ventricular septal defects (VSD) (OR 1.11, 95% CI 1.00–1.23; p < .05; n = 6 studies; I 2 = 0%) and (b) oral clefts (OR 1.22, 95% CI 1.00–1.49; p < .05; n = 4 studies; I 2 = 0%). No significant association was observed for the risk of cleft palate but, when excluding the study that contributed to the study heterogeneity, we found an OR of 1.48 (95% CI 1.19–1.84; p < .01; n = 5 studies; I 2 = 0%). No statistically significant association was found for MCM, overall cardiac malformations, atrial septal defects and cleft lip with or without cleft palate. Exploratory investigations of other malformations showed an increased risk of diaphragmatic hernia, hypoplastic left heart and “respiratory system anomalies.”
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.037 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 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".