Literature DB >> 29350182

The role of EEG in the diagnosis and classification of the epilepsy syndromes: a tool for clinical practice by the ILAE Neurophysiology Task Force (Part 2).

Michalis Koutroumanidis1, Alexis Arzimanoglou2, Roberto Caraballo3, Sushma Goyal4, Anna Kaminska5, Pramote Laoprasert6, Hirokazu Oguni7, Guido Rubboli8, William Tatum9, Pierre Thomas10, Eugen Trinka11, Luca Vignatelli12, Solomon L Moshé13.   

Abstract

The concept of epilepsy syndromes, introduced in 1989, was defined as "clusters of signs and symptoms customarily occurring together". Definition of epilepsy syndromes based on electro-clinical features facilitated clinical practice and, whenever possible, clinical research in homogeneous groups of patients with epilepsies. Progress in the fields of neuroimaging and genetics made it rapidly clear that, although crucial, the electro-clinical description of epilepsy syndromes was not sufficient to allow much needed development of targeted therapies and a better understanding of the underlying pathophysiological mechanisms of seizures. The 2017 ILAE position paper on Classification of the Epilepsies recognized that "as a critical tool for the practicing clinician, epilepsy classification must be relevant and dynamic to changes in thinking". The concept of "epilepsy syndromes" evolved, incorporating issues related to aetiologies and comorbidities. A comprehensive update (and revision where necessary) of the EEG diagnostic criteria in the light of the 2017 revised terminology and concepts was deemed necessary. Part 2 covers the neonatal and paediatric syndromes in accordance with the age of onset. [Published with educational EEG plates at www.epilepticdisorders.com].

Entities:  

Keywords:  EEG Atlas; EEG Telemetry; EEG and epilepsy diagnosis; EEG protocols; epilepsy syndromes

Mesh:

Year:  2017        PMID: 29350182     DOI: 10.1684/epd.2017.0952

Source DB:  PubMed          Journal:  Epileptic Disord        ISSN: 1294-9361            Impact factor:   1.819


  5 in total

1.  Scalp recorded spike ripples predict seizure risk in childhood epilepsy better than spikes.

Authors:  Mark A Kramer; Lauren M Ostrowski; Daniel Y Song; Emily L Thorn; Sally M Stoyell; McKenna Parnes; Dhinakaran Chinappen; Grace Xiao; Uri T Eden; Kevin J Staley; Steven M Stufflebeam; Catherine J Chu
Journal:  Brain       Date:  2019-05-01       Impact factor: 13.501

2.  An automated, machine learning-based detection algorithm for spike-wave discharges (SWDs) in a mouse model of absence epilepsy.

Authors:  Jesse A Pfammatter; Rama K Maganti; Mathew V Jones
Journal:  Epilepsia Open       Date:  2019-02-06

3.  Evaluating the Association of Calcified Neurocysticercosis and Mesial Temporal Lobe Epilepsy With Hippocampal Sclerosis in a Large Cohort of Patients With Epilepsy.

Authors:  Thaís Leite Secchi; Rosane Brondani; José Augusto Bragatti; Jorge Wladimir Junqueira Bizzi; Marino Muxfeldt Bianchin
Journal:  Front Neurol       Date:  2022-01-27       Impact factor: 4.003

Review 4.  When should we obtain a routine EEG while managing people with epilepsy?

Authors:  Tasneem F Hasan; William O Tatum
Journal:  Epilepsy Behav Rep       Date:  2021-05-03

Review 5.  Epilepsy Syndromes in the First Year of Life and Usefulness of Genetic Testing for Precision Therapy.

Authors:  Allan Bayat; Michael Bayat; Guido Rubboli; Rikke S Møller
Journal:  Genes (Basel)       Date:  2021-07-08       Impact factor: 4.096

  5 in total

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