Objective To quantify short-term antiseizure medication (ASM) effects on interictal epileptiform discharge (IED) rates during long-term video-EEG monitoring (LT-VEM) in idiopathic generalized epilepsy (IGE) using pharmacokinetic modeling and automated IED detection. Methods In a retrospective cohort of 38 IGE patients undergoing LT-VEM with ASM tapering (January 2010–December 2024), we applied AI-based hybrid IED detection and first-order pharmacokinetic modeling to calculate hourly normalized IED rates and cumulative DDD-normalized ASM drug-load profiles. We compared each patient’s IED rate between their lowest- and highest-load 24-hour windows using paired t-tests in the full cohort and in a benzodiazepine-naïve subgroup. Results IED rate was reduced by a median 63.6% (IQR 17.8–92.3%) between each patient’s lowest- and highest-load 24-hour windows ( p < 0.001; Cohen’s d = − 0.81, 95% CI − 1.24 to − 0.37). The effect was preserved in the benzodiazepine-naïve subgroup (n = 18; p = 0.007; Cohen’s d = − 0.84, 95% CI − 1.48 to − 0.19), ruling out acute benzodiazepine-induced effects as the driver. Conclusions Pharmacokinetic modeling combined with automated IED quantification demonstrates a large, robust short-term ASM effect on IED rates in IGE across a multi-day monitoring scale. Significance These findings support IED quantification as a candidate neurophysiological biomarker for individualized treatment response assessment.
Lang et al. (Mon,) studied this question.