John Libbey Eurotext

Epileptic Disorders

The Educational Journal of the

Quantitative EEG analysis in Encephalopathy related to Status Epilepticus during slow Sleep Volume 21, supplément 1, June 2019

Illustrations

  • Figure 1
  • Figure 2
  • Figure 3
  • Figure 4
  • Figure 5
  • Figure 6
  • Figure 7
Auteurs
1 Child Neuropsychiatry Unit, University of Verona, Verona, Italy
2 Child Neuropsychiatry Unit, Neuroscience Department, University of Parma, Parma, Italy
3 Department of Clinical Neurophysiology, Danish Epilepsy Centre, Dianalund, Denmark
4 University of Aarhus, Aarhus, Denmark
5 Neuroscience Department, University of Parma, Parma, Italy
6 Institute for Regional Health Services, University of Southern Denmark, Odense, Denmark
7 Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
* Correspondence: Gaetano Cantalupo Child Neuropsychiatry, Department of Surgical Sciences, Dentistry, Gynecology and Pediatrics, University of Verona, P.le L.A. Scuro, 10 - 37134 - Verona, Italy
  • Mots-clés : encephalopathy related to status epilepticus during slow sleep, ESES, quantitative analysis, EEG, spike index, CSWS, LKS, HFOs, independent component analysis, sleep downscaling
  • DOI : 10.1684/epd.2019.1055
  • Page(s) : 31-40
  • Année de parution : 2019

Since its first description, quantifying the burden of epileptiform abnormalities in sleep EEG has played a fundamental role in the diagnosis of Encephalopathy related to Status Epilepticus during slow Sleep (ESES). In fact, in the 1971 seminal paper by Tassinari's group and in the following studies on this syndrome, the amount of epileptiform discharges (EDs) was calculated as the percentage of slow sleep occupied by spike-and-waves and referred to as “spike and wave index” (SWI). However, nowadays it is becoming increasingly clear that the SWI alone does not explain the whole clinical course of patients affected by ESES. In this paper, we aim to provide a state-of-the-art summary of the quantitative EEG methods currently used in the ESES/CSWS literature, highlighting the possible pitfalls and discrepancies explaining the unsatisfactory correlation between SWI and clinical course. Furthermore; we illustrate a number of methodological refinements - taking into account inter-individual, intra-individual, and temporal variability of EDs - alongside “new” quantitative variables -including ED-related and sleep-related features - potentially useful to reach a reliable electro-clinical correlation in patients with ESES.