Idiopathic generalized epilepsies in the epilepsy monitoring unit: Systematic quantification of focal EEG and semiological signs

Johannes Koren, Clemens Lang, Gerhard Gritsch, Lisa Mayer, Manfred Hartmann, Sebastian Hafner, Tilmann Kluge, Christoph Baumgartner

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

Abstract

Objective: Focal seizure symptoms (FSS) and focal interictal epileptiform discharges (IEDs) are common in patients with idiopathic generalized epilepsies (IGEs), but dedicated studies systematically quantifying them both are lacking. We used automatic IED detection and localization algorithms and correlated these EEG findings with clinical FSS for the first time in IGE patients. Methods: 32 patients with IGEs undergoing long-term video EEG monitoring were systematically analyzed regarding focal vs. generalized IEDs using automatic IED detection and localization algorithms. Quantitative EEG findings were correlated with FSS. Results: We observed FSS in 75% of patients, without significant differences between IGE subgroups. Mostly varying/shifting lateralizations of FSS across successive recorded seizures were seen. We detected a total of 81,949 IEDs, whereof 19,513 IEDs were focal (23.8%). Focal IEDs occurred in all patients (median 13% focal IEDs per patient, range 1.1 - 51.1%). Focal IED lateralization and localization predominance had no significant effect on FSS. Conclusions: All included patients with IGE showed focal IEDs and three-quarter had focal seizure symptoms irrespective of the specific IGE subgroup. Focal IED localization had no significant effect on lateralization and localization of FSS. Significance: Our findings may facilitate diagnostic and treatment decisions in patients with suspected IGE and focal signs. (c) 2024 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
OriginalspracheEnglisch
Seiten (von - bis)82-90
Seitenumfang9
FachzeitschriftClinical Neurophysiology
Volume162
DOIs
PublikationsstatusVeröffentlicht - 1 Juni 2024

Research Field

  • Medical Signal Analysis

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