COGNITIVE AND BEHAVIORAL EFFECTS OF LONG TERM ANTIEPILEPTIC DRUG USE IN ADOLESCENTS WITH GENERALIZED EPILEPSY
Bibliographic record
Abstract
Background: Adolescents with generalized epilepsy often require long-term antiepileptic drug (AED) therapy during a critical phase of cognitive and emotional development. While AEDs are essential for seizure control, increasing evidence suggests they may adversely affect cognition and behavior, raising concerns about their broader impact on quality of life and neurodevelopment. Objective: This narrative review aims to explore and synthesize current evidence on the cognitive and behavioral consequences of prolonged AED use in adolescents with generalized epilepsy, highlighting differences among commonly prescribed medications and identifying areas in need of further investigation. Main Discussion Points: The review discusses cognitive impairments associated with older AEDs such as valproate and carbamazepine, which are more pronounced compared to newer agents like levetiracetam and oxcarbazepine. Behavioral issues, including emotional instability and attention deficits, are also prevalent. Themes such as treatment duration, monotherapy versus polytherapy, variability in neuropsychological assessments, and methodological gaps in the literature are critically analyzed. Emerging therapies and the need for routine cognitive monitoring are highlighted. Conclusion: The existing literature supports a cautious, individualized approach to AED therapy in adolescents, with attention to neurocognitive outcomes alongside seizure control. Further pediatric-focused, long-term research is essential to guide safer clinical practices and informed policy development.
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 | 0.000 |
| 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".