Associations between epileptic seizures in pregnancy and adverse pregnancy outcomes: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Epileptic seizures during pregnancy may increase the risk of adverse pregnancy outcomes. Socioeconomic disparities in epilepsy incidence may extend to seizure control. We conducted a systematic review and meta-analysis to assess the association between epileptic seizures during pregnancy and adverse pregnancy outcomes. We also evaluated the association between socioeconomic and individual-level factors and seizure occurrence. METHODS AND FINDINGS: We searched MEDLINE, Embase, CINAHL, and PsycINFO databases from inception to May 2025 for observational studies on pregnant women with epileptic seizures. We compared maternal and foetal outcomes in pregnant women with and without seizures and assessed the association between seizure occurrence and socioeconomic or individual-level factors. We used the Newcastle-Ottawa Scale to assess the risk of bias of included studies. Meta-analyses using random effects model were performed to estimate pooled odds ratios (ORs) with 95% confidence intervals (CIs). From 13,381 identified publications, 25 studies (24,596 pregnancies) are included in this analysis. In pregnant women with epilepsy, women with seizures compared to those without had increased odds of caesarean birth (OR 1.62, 95% CI 1.14 to 2.30, p = 0.007), peripartum depression (OR 2.20, 95% CI 1.04 to 4.65, p = 0.04), and small for gestational age baby (OR 1.32, 95% CI 1.03 to 1.69, p = 0.03). The odds of preterm birth (OR 1.66, 95% CI 1.29 to 2.15, p < 0.001), low birthweight (OR 1.47, 95% CI 1.12 to 1.93, p = 0.006), and small for gestational age baby (OR 1.44, 95% CI 1.19 to 1.74, p < 0.001) were higher in women with seizures compared to women without epilepsy. The risk of seizures was greater in pregnant women with epilepsy with low income compared to those with higher income (OR 1.57, 95% CI 1.22 to 2.02, p < 0.001), and in women with focal epilepsy compared to those with generalised epilepsy (OR 1.84, 95% CI 1.54 to 2.20, p < 0.001). The number of studies for some outcomes was small, limiting subgroup analyses and detection of heterogeneity. CONCLUSION: Epileptic seizures are associated with increased risks of adverse maternal and foetal outcomes. Risk assessment to identify women with epilepsy at highest risk of seizures is needed to optimise care.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.037 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".