Automated quantification of spike-wave activity may be used to predict the development of electrical status epilepticus in sleep (ESES) in children with perinatal stroke.
Automated quantification
CSWS
EEG
ESES
Perinatal stroke
Power Spectral Density
Spike-frequency
Journal
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
ISSN: 1872-8952
Titre abrégé: Clin Neurophysiol
Pays: Netherlands
ID NLM: 100883319
Informations de publication
Date de publication:
01 2021
01 2021
Historique:
received:
14
01
2020
revised:
30
10
2020
accepted:
06
11
2020
pubmed:
6
12
2020
medline:
17
7
2021
entrez:
5
12
2020
Statut:
ppublish
Résumé
Continuous spike and wave in slow-wave sleep (CSWS), an epileptic encephalopathy, occurs after perinatal stroke where it is associated with cognitive decline. CSWS features a distinct EEG pattern, electrical status epilepticus in sleep (ESES). Biomarkers for the prediction of ESES have not been identified but will facilitate earlier diagnosis and treatment. We hypothesized that spike-frequency and differences in power spectra would be predictive of subsequent ESES. A cross-sectional study comparing EEG spike-frequency and Power before the development of ESES in patients with perinatal stroke, patients with focal epilepsy, and appropriate controls. 43 patients met the inclusion criteria; 11 stroke-ESES, 10 stroke controls, 14 epilepsy-ESES, 8 epilepsy controls. ESES patients had higher pre-diagnosis mean spike-frequency (24.0 ± 24 versus 6.6 ± 9.1 SW/min, p = 0.002) than patients that did not develop ESES; these differences present ~ 3 years before ESES diagnosis. Pre-diagnosis, normalized delta power (1-4 Hz) was higher in the stroke-ESES group (105.7 ± 58 dB/Hz) compared to stroke controls (57.4 ± 45 dB/Hz, p = 0.036). Spike-frequency and delta power may represent EEG biomarkers of the risk of developing ESES in children with perinatal stroke. EEG biomarkers may be used by clinicians to assess which patients are more at-risk for ESES. Using spike-frequency, clinicians may be able to identify patients at risk of developing ESES.
Identifiants
pubmed: 33278667
pii: S1388-2457(20)30539-3
doi: 10.1016/j.clinph.2020.11.003
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
146-153Informations de copyright
Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.