Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2026
Investigating short-term antiseizure medication effects on interictal epileptiform discharges in idiopathic generalized epilepsy.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Lang Clemens, Lisy Tamara, Gritsch Gerhard, Koren Johannes, Kluge Tilmann, Pirker Susanne, Baumgartner Christoph
Аннотация
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.
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.