Stroke patients who underwent continuous EEG (cEEG) monitoring within 7 days of presentation and developed post‐stroke epilepsy (PSE; cases, n = 36) were matched (1:2 ratio) by age and follow‐up duration with ones who did not (controls, n = 72). Variables significant on univariable analysis [hypertension, smoking, hemorrhagic conversion, pre‐cEEG convulsive seizures, and epileptiform abnormalities (EAs)] were included in the multivariable logistic model and only the presence of EAs on EEG remained significant PSE predictor [OR = 11.9 (1.75–491.6)]. With acute EAs independently predicting PSE development, accounting for their presence may help to tailor post‐acute symptomatic seizure management and aid anti‐epileptogenesis therapy trials.

Background: Post-traumatic epilepsy (PTE) is a severe complication of traumatic brain injury (TBI). Electroencephalography aids early post-traumatic seizure diagnosis, but its optimal utility for PTE prediction remains unknown. We aim to evaluate the contribution of quantitative electroencephalograms to predict first-year PTE (PTE₁).Methods: We performed a multicentre, retrospective case–control study of patients with TBI. 63 PTE₁patients were matched with 63 non-PTE₁patients by admission Glasgow Coma Scale score, age and sex. We evaluated the association of quantitative electroencephalography features with PTE₁using logistic regressions and examined their predictive value relative to TBI mechanism and CT abnormalities.Results: In the matched cohort (n=126), greater epileptiform burden, suppression burden and beta variability were associated with 4.6 times higher PTE₁risk based on multivariable logistic regression analysis (area under the receiver operating characteristic curve, AUC (95% CI) 0.69 (0.60 to 0.78)). Among 116 (92%) patients with available CT reports, adding quantitative electroencephalography features to a combined mechanism and CT model improved performance (AUC (95% CI), 0.71 (0.61 to 0.80) vs 0.61 (0.51 to 0.72)).Conclusions: Epileptiform and spectral characteristics enhance covariates identified on TBI admission and CT abnormalities in PTE₁prediction. Future trials should incorporate quantitative electroencephalography features to validate this enhancement of PTE risk stratification models.

To prospectively investigate the utility of seizure induction using systematic 1Hz stimulation by exploring its concordance with the spontaneous seizure onset zone (SOZ) and relation to surgical outcome; comparison with seizures induced by non-systematic 50 Hz stimulation was attempted as well. Prospective cohort study from 2018-2021 with ≥ 1y post-surgery follow up at Yale New Haven Hospital. With 1 Hz, all or most of the gray matter contacts were stimulated at 1, 5, and 10 mA for 30-60s. With 50 Hz, selected gray matter contacts outside of the medial temporal regions were stimulated at 1-5 mA for 0.5-3s. Stimulation was bipolar, biphasic with 0.3 ms pulse width. The Yale Brain Atlas was used for data visualization. Variables were analyzed using Fisher's exact, χ², or Mann-Whitney test. Forty-one consecutive patients with refractory epilepsy undergoing intracranial EEG for localization of SOZ were included. Fifty-six percent (23/41) of patients undergoing 1 Hz stimulation had seizures induced, 83% (19/23) habitual (clinically and electrographically). Eighty two percent (23/28) of patients undergoing 50 Hz stimulation had seizures, 65% (15/23) habitual. Stimulation of medial temporal or insular regions with 1 Hz was more likely to induce seizures compared to other regions [15/32 (47%) vs. 2/41 (5%), p < 0.001]. Sixteen patients underwent resection; 11/16 were seizure free at one year and all 11 had habitual seizures induced by 1 Hz; 5/16 were not seizure free at one year and none of those 5 had seizures with 1 Hz (11/11 vs 0/5, p < 0.0001). No patients had convulsions with 1 Hz stimulation, but four did with 50 Hz (0/41 vs. 4/28, p = 0.02). Induction of habitual seizures with 1 Hz stimulation can reliably identify the SOZ, correlates with excellent surgical outcome if that area is resected, and may be superior (and safer) than 50 Hz for this purpose. However, seizure induction with 1 Hz was infrequent outside of the medial temporal and insular regions in this study.

Objective: To investigate the factors associated with the long‐term continuation of anti‐seizure medications (ASMs) in acute stroke patients.Methods: We performed a retrospective cohort study of stroke patients with concern for acute symptomatic seizures (ASySs) during hospitalization who subsequently visited the poststroke clinic. All patients had continuous EEG (cEEG) monitoring. We generated a multivariable logistic regression model to analyze the factors associated with the primary outcome of continued ASM use after the first poststroke clinic visit.Results: A total of 507 patients (43.4% ischemic stroke, 35.7% intracerebral hemorrhage, and 20.9% aneurysmal subarachnoid hemorrhage) were included. Among them, 99 (19.5%) suffered from ASySs, 110 (21.7%) had epileptiform abnormalities (EAs) on cEEG, and 339 (66.9%) had neither. Of the 294 (58%) patients started on ASMs, 171 (33.7%) were discharged on them, and 156 (30.3% of the study population; 53.1% of patients started on ASMs) continued ASMs beyond the first poststroke clinic visit [49.7 (±31.7) days after cEEG]. After adjusting for demographical, stroke‐ and hospitalization‐related variables, the only independent factors associated with the primary outcome were admission to the NICU [Odds ratio (OR) 0.37 (95% CI 0.15–0.9)], the presence of ASySs [OR 20.31(95% CI 9.45–48.43)], and EAs on cEEG [OR 2.26 (95% CI 1.14–4.58)].Interpretation: Almost a third of patients with poststroke ASySs concerns may continue ASMs for the long term, including more than half started on them acutely. Admission to the NICU may lower the odds, and ASySs (convulsive or electrographic) and EAs on cEEG significantly increase the odds of long‐term ASM use.