Third generation antiseizure medications exposure during pregnancy and neonatal adverse birth outcomes: A systematic review
Bibliographic record
Abstract
Background: Third generation antiseizure medications (ASMs) are currently used for seizure control as well as several other indications, including pain management and psychiatric disorders. As a result, maternal exposure to third generation ASMs during pregnancy has become increasingly prevalent. The current systematic review aimed to summarize the published evidence on third generation ASMs and their effect on preterm birth, cesarean section (c-section) and fetal loss. Methods: The following databases were searched: Medline, Embase, International Pharmaceutical Abstracts, Cochrane Library and Scopus until September 2022. Results: We screened 2987 studies, and identified 32 studies or case reports for inclusion, however only one study utilized a control group. Narrative systematic evidence synthesis was conducted for brivaracetam, eslicarbazepine, fosphenytoin, lacosamide and perampanel. Conclusion: Due to the scarcity and quality of published studies, drawing clear-cut conclusions regarding third generation ASMs and the outcomes of interest is challenging. More comparative safety studies focusing on neonatal safety of third generation ASMs in pregnancy are essential.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".