The safety of ondansetron for nausea and vomiting of pregnancy: a prospective comparative study
Bibliographic record
Abstract
OBJECTIVE: Ondansetron (Zofran) is a drug used for the treatment of nausea and vomiting caused by cancer chemotherapy. Despite the fact that it is not indicated, women are being prescribed this drug for the treatment of nausea and vomiting of pregnancy (NVP). There is a paucity of information on fetal safety for this indication. The objective of this study is to determine whether this drug increases the baseline rate of major malformations. DESIGN: A prospective comparative observational study. SETTING: Teratogen Information Services (TIS). POPULATION: Pregnant women. METHODS: Our three groups included women who were exposed to ondansetron and women exposed to (1) other anti-emetics and (2) non-teratogen exposures. All of the women called either our NVP Helpline or TIS at The Motherisk Program in Toronto, Canada, or The Mothersafe Program in Sydney, Australia. MAIN OUTCOME MEASURE: Rates of major malformation. RESULTS: We have completed 176 pregnancy outcomes in each group. In the ondansetron cohort, there were 169 live births, 5 miscarriages, 2 therapeutic abortions, 6 (3.6%) major malformations and the mean birthweight was 3362 g [SD 525]. There were no statistical differences in any of the study endpoints between the ondansetron and the comparison groups. CONCLUSIONS: This drug does not appear (although the sample size is limited) to be associated with an increased risk for major malformations above baseline.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".