Abstracts

The Role of EEG in the Prediction of Post-stroke Seizures

Abstract number : 2.273
Submission category : 4. Clinical Epilepsy / 4D. Prognosis
Year : 2024
Submission ID : 796
Source : www.aesnet.org
Presentation date : 12/8/2024 12:00:00 AM
Published date :

Authors :
Kai Michael Schubert, MD PhD – Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Zurich, Switzerland
Vijaya Dasari, MD – Epilepsy Center, Cleveland Clinic, Cleveland, OH, United States.
Ana Lúcia Oliveira, MD – Department of Neurosciences and Mental Health (Neurology), Hospital de Santa Maria-CHULN. Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
Chiara Tatillo, MD – Department of Neurology, Hôpital Universitaire de Bruxelles – Hôpital Erasme, Brussels, Belgium
Gilles Naeije, MD – Department of Neurology, Hôpital Universitaire de Bruxelles – Hôpital Erasme, Brussels, Belgium
Nicolas Gaspard, MD, PhD – Hôpital Universitaire de Bruxelles
Adam Strzelczyk, MD, MHBA, FEAN – Goethe-University Frankfurt
Presenting Author: Marian Galovic, MD PhD – Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Zurich, Switzerland

Vineet Punia, MD – Cleveland Clinic
Carla Bentes, MD PhD – Department of Neurosciences and Mental Health (Neurology), Hospital de Santa Maria-CHULN. Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal

Rationale: Seizures significantly impact outcomes after stroke, highlighting the need for accurate predictors of post-stroke epilepsy (PSE). We aimed to evaluate whether electrographic biomarkers detected early after acute ischemic stroke improve the prediction of PSE.

Methods: We analyzed data from six international cohorts who had neuroimaging-confirmed acute ischemic stroke (mean age 71, 54% male) and underwent EEG within the first few days post-stroke. Cox proportional hazards regression, adjusted through inverse probability weighting, was used to assess the impact of electrographic biomarkers on the risk of PSE.

Results: Among 1064 stroke survivors who received early EEG, post-stroke seizures occurred in 135 (11.36%). In addition to known clinical risk factors, epileptiform activity (lateralized periodic discharges (LPD), interictal epileptiform discharges (IED), and electrographic seizures (ES); odds ratio [OR] 2.1, 95% confidence interval [CI]: 1.2-3.0, p=0.004) and regional slowing (OR 1.6, 95% CI: 1.1-2.4, p=0.02) were independently associated with developing PSE. We implemented this findings into a novel prognostic model (SeLECT-EEG; concordance statistic (95%-CI 0.66-0.76)) which outperformed a previous gold-standard model (SeLECT2.0; concordance statistic 0.71 (95%-CI 0.70-0.79)); p < 0.001; Table 1).

Conclusions: Electrographic biomarkers enhance post-stroke epilepsy risk prediction beyond previously known clinical risk factors. This information improves the prediction of PSE and may inform counselling and management strategies for stroke survivors at risk of seizures.

Funding: -

Clinical Epilepsy