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The Role of Electroencephalography in Predicting Post‐Stroke Seizures and an Updated Prognostic Model ( SeLECT ‐ EEG )

par Schubert, Kai Michael;Dasari, Vijaya;Oliveira, Ana Lúcia;Tatillo, Chiara ;Naeije, Gilles ;Strzelczyk, Adam;Merlino, Giovanni;Valente, Mariarosaria;Gaspard, Nicolas ;Punia, Vineet;Galovic, Marian;Bentes, Carla
Référence Annals of neurology
Publication Publié, 2025-06-01

Article révisé par les pairs

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Résumé :

Objective Seizures negatively impact stroke outcomes, highlighting the need for reliable predictors of post‐stroke epilepsy. Although acute symptomatic seizures are a known risk factor, most stroke survivors who develop epilepsy do not experience them. Early electroencephalography (EEG) findings may enhance risk prediction, particularly in patients without acute symptomatic seizures, aiding in patient management and counseling. Methods We conducted a multicenter cohort study using data from 1,105 stroke survivors (mean age 71 years, 54% male) with neuroimaging‐confirmed ischemic stroke who underwent EEG within 7 days post‐stroke. Electrographic biomarkers, including epileptiform activity and regional slowing, were analyzed for their association with post‐stroke epilepsy using Cox proportional hazards regression and Fine–Gray subdistribution hazard models, adjusted for differences in EEG timing and patient characteristics. Results Post‐stroke epilepsy developed in 119 patients (11%), whereas 233 (21%) had acute symptomatic seizures. The 5‐year epilepsy risk was 42% (95% confidence interval [CI]: 30–49%) in patients with epileptiform activity versus 13% (95% CI: 9–16%) in those without. Regional slowing doubled the 5‐year epilepsy risk (23%, 95% CI: 17–30% vs 11%, 95% CI: 7–16%). Epileptiform activity (subdistribution hazard ratio: 2.3, 95% CI: 1.5–3.4, p  < 0.001) and regional slowing (subdistribution hazard ratio: 1.7, 95% CI: 1.1–2.7, p  = 0.02) were independently associated with post‐stroke epilepsy. A novel prognostic model, SeLECT‐EEG (concordance statistic: 0.75, 95% CI: 0.71–0.80), outperformed the previous standard (SeLECT 2.0 ; 0.71, 95% CI: 0.65–0.76, p  < 0.001). Interpretation Electrographic biomarkers improve post‐stroke epilepsy prediction beyond clinical risk factors. The SeLECT‐EEG model enhances early risk stratification, particularly in patients without acute symptomatic seizures, informing management strategies and patient counseling. ANN NEUROL 2025