Antiseizure medication use during pregnancy and the risk of autism spectrum disorder in children
Bibliographic record
Abstract
The etiology of autism spectrum disorder (ASD) is not fully understood. There is concern about the potential association between prenatal antiseizure medication (ASM) exposure and the development of ASD. This study examined the risk of ASD in children exposed to ASMs during pregnancy. We conducted a retrospective population-based cohort study using data from the Manitoba Center for Health Policy (MCHP), which included data from pregnancies in Manitoba from January 1, 1998, to March 31, 2021. We included all live singleton births and excluded multiple births and stillbirths. We reported crude and adjusted hazard ratios (aHRs) and 95% CIs using Cox regression hazard model. To account for familial confounding, we created a sub-cohort of randomly selected one child per mother. We examined associations in pregnant women with epilepsy to address confounding by indication. Among the 289,794 pregnancies included, 2,474 (0.9%) were exposed to ASMs during the second and third trimesters of the pregnancy, with 99 (4%) diagnosed with ASD. Among 1,853 children of pregnant women with epilepsy, 755 (40.7%) were exposed to ASMs, with 30 (4%) diagnosed with ASD. The mean follow-up periods were 11.1 and 11.3 years, respectively. Primary analysis showed ASM exposure was associated with an increased risk of ASD (aHR, 1.27; 95% CI, 1.03–1.56), with lamotrigine showing a twofold increase (aHR, 2.16; 95% CI, 1.16-4.02). In the epilepsy cohort, ASM exposure doubled the risk of ASD (aHR, 2.12; 95% CI, 1.09–4.11), with phenytoin showing a nearly threefold increase (aHR, 2.68; 95% CI, 1.05–6.73). Sensitivity analysis adjusting for familial confounding showed adjusted hazard ratios of 1.13 (95% CI, 0.85–1.51) for all pregnant women and 1.50 (95% CI, 0.61-3.67) for those with epilepsy. We observed an increased risk in the overall analysis of antiseizure medication use during pregnancy and the risk of ASD in newborns. This association was also observed within the epilepsy cohort. This observed risk could either be a true effect of these medications, attributed to the correlation between siblings, confounding by severity, or an effect of residual confounding. Additional studies are warranted to identify the true risk of these medications on ASD.
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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 | 0.002 |
| 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 | 0.001 |
| 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".