Increased rate of major malformations in offspring exposed to valproate during pregnancy
Bibliographic record
Abstract
OBJECTIVE: To determine the rate of occurrence of major malformations in infants whose mothers had taken the drug valproic acid (VPA) as monotherapy during the first trimester of pregnancy and had enrolled in the North American Antiepileptic Drug Pregnancy Registry. METHODS: Data were collected from pregnant women throughout the United States and Canada through telephone-based interviews. Each woman was interviewed at enrollment, at 7 months' gestation, and postpartum. With her written permission, the medical records of each mother and her infant were obtained. The major malformations tabulated were those identified at or before 5 days of age. The prevalence of congenital malformations among offspring of monotherapy VPA-exposed women was compared with that among infants of women exposed to all other antiepileptic drugs (internal comparison group) and with that among newborns in the Active Malformations Surveillance Program at Brigham and Women's Hospital (external comparison group). RESULTS: Sixteen affected cases were identified among 149 VPA-exposed women (proportion: 10.7%; 95% CI: 6.3 to 16.9%). The prevalence in the internal comparison group was 2.9% (95% CI: 2.0 to 4.1%; odds ratio: 4.0, 95% CI: 2.1 to 7.4; p < 0.001). Assuming a 1.62% prevalence in the external comparison group, the relative risk of having an affected offspring for VPA-exposed women was 7.3 (95% CI: 4.4 to 12.2; p < 0.001). CONCLUSION: Maternal exposure to valproic acid during the first trimester of pregnancy significantly increased the risk of major malformations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".