Clinical efficacy and predictive model development for levetiracetam in children with newly diagnosed epilepsy of unknown etiology

Levetiracetam (LEV) is one of the most widely used antiseizure medications (ASMs) in pediatric epilepsy owing to its broad-spectrum antiseizure efficacy, favorable safety profile, and good tolerability. However, considerable interindividual variability exists in treatment response to LEV. This study aimed to evaluate the efficacy and safety of LEV monotherapy in children with newly diagnosed epilepsy of unknown etiology, to identify clinical predictors associated with LEV treatment response, and to develop and validate a machine learning (ML)-assisted clinical risk assessment scale based on routinely available clinical information, thereby providing an objective and quantitative tool to support individualized treatment decision-making in pediatric epilepsy.