The AED (Antiepileptic Drug) Pregnancy Registry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Pregnancy registries are a new method for assessing the fetal risks from exposures in pregnancy. We present the findings of the North American AED (antiepileptic drug) Pregnancy Registry for phenobarbital sodium-exposed pregnancies. OBJECTIVE: To determine whether exposure during pregnancy to anticonvulsant drugs as monotherapy, and phenobarbital in particular, is associated with an increased risk of major malformations in comparison with unexposed controls. DESIGN: Evaluation of registry data. SETTING: The North American AED Pregnancy Registry. PATIENTS: Pregnant women throughout the United States and Canada who were taking an anticonvulsant drug and who called a toll-free telephone number to enroll. INTERVENTIONS: Each woman was interviewed by telephone at enrollment, at 7 months' gestation, and post partum. With the mother's written permission, her medical records and those of her infant were obtained. MAIN OUTCOME MEASURES: Major malformations identified by 5 days of age. Criteria for the release of findings were established by the independent Scientific Advisory Committee on the basis of malformations identified in infants of women who had enrolled prospectively before having had any prenatal screening ("pure" enrollees). RESULTS: Five (6.5%) of 77 pure pregnancies with exposure to phenobarbital monotherapy were associated with major malformations (95% confidence interval of proportion, 2.1%-14.5%). When compared with the background rate (1.62%), there was a significantly increased risk (relative risk, 4.2; 95% confidence interval, 1.5-9.4). CONCLUSIONS: A hospital-based pregnancy registry can establish the fetal risk of major malformations for a commonly used drug. Prenatal exposure to phenobarbital is associated with a significantly increased risk of fetal abnormalities.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it