Continuous Versus Short EEG After Ischemic Stroke: What cEEG Adds for Detecting Abnormalities and Predicting Post-Stroke Epilepsy.
Overview
- Department of Neurology, Clinical Neuroscience Center University Hospital and University of Zurich Zurich Switzerland
- Epilepsy Center, Cleveland Clinic Cleveland OH
- Department of Neurology Hôpital Universitaire de Bruxelles – Hôpital Erasme Brussels Belgium
- Department of Clinical Neurophysiology Aarhus University Hospital, Aarhus and Danish Epilepsy Centre Dianalund Denmark
- Department of Neurosciences and Mental Health (Neurology), Hospital de Santa Maria – ULSSM, Centro de Estudos Egas Moniz, Faculdade de Medicina Universidade de Lisboa Lisbon Portugal
- Laboratory of Experimental Neurology Université Libre de Bruxelles Brussels Belgium
- Department of Neurology Yale University School of Medicine New Haven CT
Abstract
Objective: The objective of this study was to quantify incremental diagnostic yield and prognostic value of continuous electroencephalography (cEEG; ≥12 hours) versus a 60‐minute short electroencephalography (sEEG) in predicting post‐stroke epilepsy (PSE) in patients without acute symptomatic seizures.
Methods: We retrospectively included 283 adults who underwent cEEG within 7 days; sEEG comprised the first 60 minutes of the same recording. EEGs were interpreted using American Clinical Neurophysiology Society (ACNS) terminology by neurophysiologists blinded to outcomes. Within‐patient yield was quantified using odds ratios (ORs) with 95% confidence intervals (CIs). PSE were modeled using Fine–Gray competing‐risks regression (death as competing event) and reported as subdistribution hazard ratios (sHR). SeLECT‐EEG derived from sEEG and cEEG was compared using C‐index and net reclassification improvement (NRI).
Results: Over a median follow‐up of 41 months (interquartile range [IQR] = 22–64), 41 of 283 patients (14.5%) developed PSE. Compared to sEEG, cEEG increased detection of interictal epileptiform discharges (11 vs 3%, OR = 3.75, 95% CI = 1.75–8.02, p < 0.001) and electrographic seizures (4 vs 0.7%, OR = 6.22, 95% CI = 1.38–28.06, p = 0.01). Lateralized periodic discharges (sHR = 4.50, 95% CI = 2.13–9.51) and electrographic seizures (sHR = 3.63, 95% CI = 1.52–8.63) were the strongest predictors of PSE. The cEEG‐derived SeLECT‐EEG improved discrimination versus sEEG‐derived scoring (ΔC‐index 0.055, 95% CI = 0.012–0.101, p = 0.014) and reclassification (NRI = 0.25, 95% CI = 0.07–0.42). Epileptiform activity emerging after the first hour conferred higher 5‐year PSE risk than never detected (28 vs 11%, Gray p = 0.006).
Interpretation: The cEEG identifies additional epileptiform abnormalities with prognostic value beyond routine‐duration EEG, supporting extension of monitoring in selected cases based on baseline risk and early EEG findings. ANN NEUROL 2026;100:400–415
Reproduced under the paper's license (CC BY), from the paper cited above.
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Data Availability
De‐identified participant data and supporting documentation, including statistical and analytic code, will be made available upon reasonable request following publication. Access will be granted to qualified investigators, contingent upon approval by the lead investigator and the respective local cohort contributors, as well as evidence of appropriate ethical approvals. Requests should be directed to . Data may be used for any purpose deemed scientifically sound and ethically approved.
Reproduced under the paper's license (CC BY), from the paper cited above.
Versions
The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.
Version 2, 28 September 2026
- Publisher: — → Wiley
Version 1, 28 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 13 MeSH terms, 48 references.
Cite
This paper
Schubert, K. M., Dasari, V., Tatillo, C., Naeije, G., Beniczky, S., Bentes, C., Galovic, M., Gaspard, N., & Punia, V. (2026). Continuous Versus Short EEG After Ischemic Stroke: What cEEG Adds for Detecting Abnormalities and Predicting Post-Stroke Epilepsy. Annals of neurology, 100(2), 400-415. https://
BibTeX
@article{schubert2026con
author = {Schubert, Kai Michael and Dasari, Vijaya and Tatillo, Chiara and Naeije, Gilles and Beniczky, Sándor and Bentes, Carla and Galovic, Marian and Gaspard, Nicolas and Punia, Vineet},
title = {{Continuous Versus Short EEG After Ischemic Stroke: What cEEG Adds for Detecting Abnormalities and Predicting Post-Stroke Epilepsy}},
journal = {Annals of neurology},
year = {2026},
month = may,
volume = {100},
number = {2},
pages = {400--415},
publisher = {Wiley},
issn = {0364-5134},
doi = {10.1002/
url = {https://
pmid = {42144833},
pmcid = {PMC13387982}
}
RIS
TY - JOUR
AU - Schubert, Kai Michael
AU - Dasari, Vijaya
AU - Tatillo, Chiara
AU - Naeije, Gilles
AU - Beniczky, Sándor
AU - Bentes, Carla
AU - Galovic, Marian
AU - Gaspard, Nicolas
AU - Punia, Vineet
TI - Continuous Versus Short EEG After Ischemic Stroke: What cEEG Adds for Detecting Abnormalities and Predicting Post-Stroke Epilepsy
T2 - Annals of neurology
J2 - Ann Neurol
PY - 2026
DA - 2026/
VL - 100
IS - 2
SP - 400
EP - 415
SN - 0364-5134
PB - Wiley
DO - 10.1002/
UR - https://
LA - en
ER -
CSL-JSON
{
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"title": "Continuous Versus Short EEG After Ischemic Stroke: What cEEG Adds for Detecting Abnormalities and Predicting Post-Stroke Epilepsy",
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"author": [
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