Ondansetron use in the first trimester of pregnancy and the risk of neonatal ventricular septal defect
Bibliographic record
Abstract
BACKGROUND: Literature is divided regarding the risk of neonatal ventricular septal defect (VSD) associated with first trimester ondansetron use in pregnancy. METHODS: We evaluated the risk of VSD associated with first trimester exposure to intravenous or oral ondansetron in 33 677 deliveries at Magee-Womens Hospital in Pittsburgh, PA (2006-2014). Using log-binomial regression, we evaluated the risk: (1) in the full cohort, (2) using propensity score designs with both matching and inverse probability weighting and (3) utilizing clustered trajectory analysis evaluating the role of dose. Sensitivity analyses assessed the association between ondansetron and all recorded birth defects in aggregate. RESULTS: A total of 3733 (11%) pregnancies were exposed to ondansetron in the first trimester (dose range: 2.4-1008 mg). Ondansetron was associated with increased risk of VSD with risk ratios ranging from 1.7 [95% confidence interval (CI) 1.0-2.9] to 2.1 (95% CI 1.1-4.0) across methods. Risks correspond to one additional VSD for approximately every 330 pregnancies exposed in the first trimester. The association was dose-dependent with increased risk in women receiving highest cumulative doses compared with lowest doses [adjusted risk ratio: 3.2 (95% CI 1.0-9.9)]. The association between ondansetron and congenital malformations was diluted as the outcome included additional birth defects. CONCLUSIONS: First trimester ondansetron use is associated with an increased risk of neonatal VSD potentially driven by higher doses. This risk should be viewed in the context of risks attributable to severe untreated nausea and vomiting of pregnancy.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".