Use of Antiseizure Medications Early in Pregnancy and the Risk of Major Malformations in the Newborn
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Maternal use of first-generation antiseizure medications (ASMs), such as valproate and phenobarbital, increases the risk of congenital malformations in offspring. Second-generation ASMs, such as lamotrigine and levetiracetam, pose less risk to fetal development, although topiramate seems to increase the risk of oral clefts. Less is known about the safety of newer second-generation ASMs during pregnancy including oxcarbazepine, zonisamide, and lacosamide. The aim of this study was to quantify the relative risk of major malformations in offspring after maternal use of specific ASMs early in pregnancy, with special interest in second-generation ASMs. METHODS: The study population included pregnant women who enrolled in the North American Antiepileptic Drug Pregnancy Registry between 1997 and 2023. Data on ASM use and maternal characteristics were collected through phone interviews at enrollment, at 7 months of gestation, and within 3 months after delivery. Malformations were confirmed by medical records and adjudicated by a dysmorphologist. The risk of major malformations was estimated among infants exposed to specific ASMs in monotherapy during the first trimester of pregnancy. Risk ratios (RRs) and 95% CIs were estimated with logistic regression models. RESULTS: A total of 7,311 participants taking an ASM as monotherapy during the first trimester were eligible for analysis. The mean age was 30 years. The risk of major malformations was 2.1% (52/2,461) for lamotrigine, 2.0% (26/1,283) for levetiracetam, 2.8% (32/1,132) for carbamazepine, 5.1% (26/510) for topiramate, 2.8% (12/423) for phenytoin, 9.2% (31/337) for valproate, 1.5% (5/327) for oxcarbazepine, 1.5% (4/270) for gabapentin, 1.3% (3/228) for zonisamide, 6.0% (12/200) for phenobarbital, 3.2% (2/62) for pregabalin, and 0% (0/88) for lacosamide. Compared with lamotrigine, the RR was 5.1 (95% CI 3.0-8.5) for valproate, 2.9 (1.4-5.8) for phenobarbital, and 2.2 (1.2-4.0) for topiramate. Topiramate was specifically associated with a higher risk of cleft lip. DISCUSSION: Results confirm the association between maternal use of valproate, phenobarbital, and topiramate early in pregnancy and a higher risk of major malformations in the infant compared with lamotrigine. However, they do not support meaningful risk elevation for levetiracetam, oxcarbazepine, gabapentin, or zonisamide. Relative risk estimates for lacosamide and pregabalin are still imprecise.
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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 | 0.000 |
| 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) | 0.001 | 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".