Educational outcomes associated with prenatal exposure to antiseizure medications: A systematic literature review and meta-Analysis
Bibliographic record
Abstract
Objective To systematically review and meta-analyse evidence of the associations between prenatal exposure to antiseizure medications (ASMs) and educational outcomes in childhood, including educational difficulties, learning difficulties and academic performance. Methods We conducted a systematic review following the PICOS framework and PRISMA guidelines. MEDLINE (Ovid), CINAHL, PubMED, ERIC, and PsycINFO databases, along with Google Scholar, were searched from inception to 28 June 2024. Study quality was assessed using the Newcastle-Ottawa Scale and ROBINS-E. Relevant outcomes included record of special education needs, school-related behavioural problems, learning difficulties, and examination scores in core academic subjects. Pooled estimates were derived where appropriate and bias and heterogeneity assessed using funnel plots, Egger's tests, and I 2 tests. Results Seventeen studies (12 cohort, 5 case-control) were included, encompassing 854,142 participants. Pooled estimates indicated that prenatal exposure to ASMs was associated with increased educational difficulties (RR 1.3, 95 % CI 1.01–1.69, p = 0.04), with sodium valproate showing the strongest association (RR 2.38, 95 % CI 1.25–4.53, p = 0.01). Carbamazepine and other first-generation ASMs showed no significant associations. Narrative findings suggested associations between newer-generation ASMs and educational difficulties, but limited data precluded quantitative synthesis. Studies assessing academic outcomes suggested lower academic performance among children exposed to sodium valproate or ASM polytherapy but could not undergo meta-analysis due to methodological heterogeneity. Conclusions Prenatal exposure to first-generation ASMs, especially sodium valproate, was associated with increased educational support needs. Newer-generation ASMs appear to have a more favourable risk profile, though evidence remains limited, underscoring the need for further high-quality research to inform clinical practice.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".