Epileptic discharges in the acute phase of stroke using long-term EEG monitoring

Frontiers in Neuroscience(2019)

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Event Abstract Back to Event Epileptic discharges in the acute phase of stroke using long-term EEG monitoring Silke Proesmans1, 2, Veerle De Herdt1, 2*, Stephanie Hödl1, 2, Helena Janssen2, Dimitri Hemelsoet2 and Paul Boon1, 2 1 Ghent University, 4Brain lab, Belgium 2 Ghent University Hospital, Department of Neurology, Belgium Background Stroke is a common cause of seizures, especially in the elderly population. However, the incidence, associated factors and influence on outcome of interictal epileptic discharges and subclinical electrographic seizures in the acute phase of stroke are unknown. Methods In this prospective study, 35 patients underwent long-term video-EEG monitoring within 3 days after intracerebral haemorrhage or ischemic stroke. Epileptic activity on the EEG was analysed and correlated with clinical and neuroradiological patient characteristics, the occurrence of clinical seizures and outcome. Results Epileptic activity, a term comprising electrographic seizures, spikes and spike waves, was seen on the EEGs of 8/35 (23%) patients. 3/35 (9%) of patients had electrographic seizures and spikes or spike waves were seen in 6/35 (17%) of subjects. Ictal electrographic activity and early clinical seizures (<7 days post-stroke) were significantly correlated (p=0.018) in patients with ischemic stroke. No other significant associations were found between the occurrence of epileptic discharges and clinical or radiological features, nor with outcome. Conclusion In this study, epileptic discharges were frequently seen in the acute phase post-stroke. Ictal electrographic activity was associated with the occurrence of early clinical seizures. However, there was no association between electroencephalographic epileptic activity and outcome. Keywords: ischemic stroke, intracerebral hemorrhage, Stroke, Epilepsy, Epileptic discharges, human Conference: 13th National Congress of the Belgian Society for Neuroscience , Brussels, Belgium, 24 May - 24 May, 2019. Presentation Type: Poster presentation Topic: Behavioral/Systems Neuroscience Citation: Proesmans S, De Herdt V, Hödl S, Janssen H, Hemelsoet D and Boon P (2019). Epileptic discharges in the acute phase of stroke using long-term EEG monitoring. Front. Neurosci. Conference Abstract: 13th National Congress of the Belgian Society for Neuroscience . doi: 10.3389/conf.fnins.2019.96.00070 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Apr 2019; Published Online: 27 Sep 2019. * Correspondence: Prof. Veerle De Herdt, Ghent University, 4Brain lab, Ghent, Belgium, veerle.deherdt@uzgent.be Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Silke Proesmans Veerle De Herdt Stephanie Hödl Helena Janssen Dimitri Hemelsoet Paul Boon Google Silke Proesmans Veerle De Herdt Stephanie Hödl Helena Janssen Dimitri Hemelsoet Paul Boon Google Scholar Silke Proesmans Veerle De Herdt Stephanie Hödl Helena Janssen Dimitri Hemelsoet Paul Boon PubMed Silke Proesmans Veerle De Herdt Stephanie Hödl Helena Janssen Dimitri Hemelsoet Paul Boon Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.
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EEG Analysis,Epilepsy Detection,Deep Learning for EEG,Epilepsy
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