Paternal exposure to antiepileptic drugs and offspring outcomes: a nationwide population-based cohort study in Sweden
Bibliographic record
Abstract
OBJECTIVES: To investigate the association between paternal use of antiepileptic drugs (AEDs) and adverse neurodevelopmental outcomes and major congenital malformations (MCM) in the offspring. METHODS: Using nationwide Swedish registries, we included 1 144 795 births to 741 726 fathers without epilepsy and 4544 births to 2955 fathers with epilepsy. Of these, 2087 (45.9%) were born to fathers with epilepsy who had dispensed an AED during the conception period. Children who had both parents with epilepsy were excluded. The incidence rate of MCM, autism spectrum disorder, attention deficit hyperactivity disorder (ADHD) and intellectual disability in offspring was analysed. RESULTS: Offspring of fathers exposed to AEDs did not show an increased risk of MCM (adjusted OR 0.9, 95% CI 0.7 to 1.2), autism (adjusted HR (aHR) 0.9, 95% CI 0.5 to 1.7), ADHD (aHR 1.1, 95% CI 0.7 to 1.9) or intellectual disability (aHR 1.3, 95% CI 0.6 to 2.8) compared with offspring of fathers with epilepsy not exposed to AEDs. Among offspring of fathers with epilepsy who used valproate in monotherapy during conception, rates of autism (2.9/1000 child-years) and intellectual disability (1.4/1000 child-years) were slightly higher compared with the offspring of fathers with epilepsy who did not use AEDs during conception (2.1/1000 child-years autism, 0.9/1000 child-years intellectual disability), but in the propensity-score adjusted analyses, no statistically significant increased risk of adverse outcomes was found. CONCLUSIONS: Paternal AED use during conception is not associated with adverse outcomes in the offspring.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".