In this first study, we developed and validated the SeLECT score, an innovative prognostic tool for predicting the risk of late seizures after ischemic stroke. Using five easily obtainable clinical variables—stroke severity, large-artery atherosclerosis, early seizures, cortical involvement, and middle cerebral artery involvement—we demonstrated high predictive accuracy across multiple international cohorts.
Building on our initial development of the SeLECT score, we further investigated the role of thrombolysis and reperfusion therapies in the context of seizure risk after ischemic stroke. This subsequent study demonstrated that while reperfusion treatments such as intravenous thrombolysis and thrombectomy are essential for reducing stroke-related disability, they do not independently increase the risk of late seizures when accounting for stroke severity and cortical involvement.
In this study, we examined the impact of acute symptomatic seizures, particularly status epilepticus, on long-term outcomes after ischemic stroke. Our findings revealed that patients with status epilepticus face significantly higher risks of mortality and post-stroke epilepsy. Building on these insights, we adapted the SeLECT score to incorporate status epilepticus, enhancing its predictive accuracy for post-stroke seizure risk.
In this study, we investigated how the SeLECT2.0 score can guide safe driving decisions for stroke survivors at risk of seizures. By quantifying the conditional seizure risk (COSY) based on individual stroke characteristics and seizure-free intervals (SFI), we identified personalized thresholds for private and professional driving safety. Our findings revealed that COSY below 20% for private driving is achievable immediately in low-risk individuals (SeLECT2.0 scores 0–7), while higher-risk individuals may require SFIs of 5–20 months depending on their baseline score.
In this study, we examined how the timing and type of acute symptomatic seizures (ASyS) following ischemic stroke influence the risk of developing post-stroke epilepsy and mortality. By analyzing a large multicenter cohort of 4,552 stroke survivors, we demonstrated that ASyS occurring on the day of stroke onset (day 0) and seizures presenting as status epilepticus or focal to bilateral tonic-clonic seizures were associated with the highest risks. Using these insights, we developed and validated the novel SeLECT-ASyS model, which significantly outperformed the previous SeLECT2.0 model in predicting post-stroke epilepsy risk for patients with ASyS.
In this study, we explored the role of early electrographic biomarkers detected through EEG in predicting post-stroke epilepsy and developed a novel prognostic model, SeLECT-EEG, to improve risk estimation. By analyzing data from 1,105 stroke survivors who underwent EEG within seven days of acute ischemic stroke, we identified specific biomarkers, including epileptiform activity and regional slowing, as significant predictors of post-stroke epilepsy. The SeLECT-EEG model demonstrated superior predictive accuracy compared to the prior SeLECT2.0 model, particularly in patients without acute symptomatic seizures. Our findings revealed that patients with epileptiform activity had a 42% 5-year risk of post-stroke epilepsy, while those without showed a significantly lower risk (13%).
In this study, we quantified what continuous EEG (cEEG ≥12h) adds beyond a 60-minute EEG performed within 7 days after ischemic stroke in patients without acute symptomatic seizures. Over a median follow-up of 41 months, 14.5% developed post-stroke epilepsy. Compared with the first 60 minutes, cEEG substantially increased detection of prognostically relevant abnormalities—especially interictal epileptiform discharges (3%→11%) and electrographic seizures (0.7%→4.2%)—and improved long-term risk stratification (cEEG-derived SeLECT-EEG improved discrimination and reclassification). These findings support a shift from EEG as seizure “confirmation” toward EEG as a predictive biomarker guiding risk-based monitoring pathways and structured follow-up.
The purpose of this study was to identify risk factors for acute symptomatic seizures and post-stroke epilepsy after acute ischemic stroke and evaluate the effects of reperfusion treatment.
We assessed the risk factors for post-stroke seizures using logistic or Cox regression in a multicenter study, including adults from 8 European referral centers with neuroimaging-confirmed ischemic stroke. We compared the risk of post-stroke seizures between participants with or without reperfusion treatment following propensity score matching to reduce confounding due to treatment selection.
In the overall cohort of 4,229 participants (mean age 71 years, 57% men), a higher risk of acute symptomatic seizures was observed in those with more severe strokes, infarcts located in the posterior cerebral artery territory, and strokes caused by large-artery atherosclerosis. Strokes caused by small-vessel occlusion carried a small risk of acute symptomatic seizures. 6% developed post-stroke epilepsy. Risk factors for post-stroke epilepsy were acute symptomatic seizures, more severe strokes, infarcts involving the cerebral cortex, and strokes caused by large-artery atherosclerosis. Electroencephalography findings within 7 days of stroke onset were not independently associated with the risk of post-stroke epilepsy. There was no association between reperfusion treatments in general or only intravenous thrombolysis or mechanical thrombectomy with the time to post-stroke epilepsy or the risk of acute symptomatic seizures.
Post-stroke seizures are related to stroke severity, etiology, and location, whereas an early electroencephalogram was not predictive of epilepsy. We did not find an association of reperfusion treatment with risks of acute symptomatic seizures or post-stroke epilepsy.
Risk Factors:
Reperfusion Treatments:
Role of EEG:
Acute symptomatic seizures occurring within 7 days after ischemic stroke may be associated with an increased mortality and risk of epilepsy. It is unknown whether the type of acute symptomatic seizure influences this risk.
To compare mortality and risk of epilepsy following different types of acute symptomatic seizures.
This cohort study analyzed data acquired from 2002 to 2019 from 9 tertiary referral centers. The derivation cohort included adults from 7 cohorts and 2 case-control studies with neuroimaging-confirmed ischemic stroke and without a history of seizures. Replication in 3 separate cohorts included adults with acute symptomatic status epilepticus after neuroimaging-confirmed ischemic stroke. The final data analysis was performed in July 2022.
Type of acute symptomatic seizure.
All-cause mortality and epilepsy (at least 1 unprovoked seizure presenting >7 days after stroke).
A total of 4552 adults were included in the derivation cohort (2547 male participants [56%]; 2005 female [44%]; median age, 73 years [IQR, 62-81]). Acute symptomatic seizures occurred in 226 individuals (5%), of whom 8 (0.2%) presented with status epilepticus. In patients with acute symptomatic status epilepticus, 10-year mortality was 79% compared with 30% in those with short acute symptomatic seizures and 11% in those without seizures. The 10-year risk of epilepsy in stroke survivors with acute symptomatic status epilepticus was 81%, compared with 40% in survivors with short acute symptomatic seizures and 13% in survivors without seizures. In a replication cohort of 39 individuals with acute symptomatic status epilepticus after ischemic stroke (24 female; median age, 78 years), the 10-year risk of mortality and epilepsy was 76% and 88%, respectively. We updated a previously described prognostic model (SeLECT 2.0) with the type of acute symptomatic seizures as a covariate. SeLECT 2.0 successfully captured cases at high risk of poststroke epilepsy.
In this study, individuals with stroke and acute symptomatic seizures presenting as status epilepticus had a higher mortality and risk of epilepsy compared with those with short acute symptomatic seizures or no seizures. The SeLECT 2.0 prognostic model adequately reflected the risk of epilepsy in high-risk cases and may inform decisions on the continuation of antiseizure medication treatment and the methods and frequency of follow-up.
Incidence of ASS and Status Epilepticus (SE):
Mortality Rates:
Risk of Developing PSE:
Prognostic Significance of SE:
Updated SeLECT 2.0 Score:
The study emphasizes the critical impact of ASS, particularly when presenting as SE, on long-term outcomes after ischemic stroke. The updated SeLECT 2.0 model serves as a valuable tool for predicting PSE risk, facilitating informed clinical decisions regarding patient management and follow-up.
In addition to other stroke-related deficits, the risk of seizures may impact driving ability after stroke.
We analysed data from a multicentre international cohort, including 4452 adults with acute ischaemic stroke and no prior seizures. We calculated the Chance of Occurrence of Seizure in the next Year (COSY) according to the SeLECT2.0 prognostic model. We considered COSY<20% safe for private and <2% for professional driving, aligning with commonly used cut-offs.
Seizure risks in the next year were mainly influenced by the baseline risk-stratified according to the SeLECT2.0 score and, to a lesser extent, by the poststroke seizure-free interval (SFI). Those without acute symptomatic seizures (SeLECT2.0 0–6 points) had low COSY (0.7%–11%) immediately after stroke, not requiring an SFI. In stroke survivors with acute symptomatic seizures (SeLECT2.0 3–13 points), COSY after a 3-month SFI ranged from 2% to 92%, showing substantial interindividual variability. Stroke survivors with acute symptomatic status epilepticus (SeLECT2.0 7–13 points) had the highest risk (14%–92%).
Personalised prognostic models, such as SeLECT2.0, may offer better guidance for poststroke driving decisions than generic SFIs. Our findings provide practical tools, including a smartphone-based or web-based application, to assess seizure risks and determine appropriate SFIs for safe driving.
To assess seizure risk after ischemic stroke using the SeLECT2.0 model, focusing on its implications for driving safety based on seizure-free intervals (SFI) and personalized risk estimates.
Risk Quantification:
Driving Implications:
Impact of Acute Symptomatic Seizures:
Model Accuracy:
Acute symptomatic seizures (ASyS) increase the risk of epilepsy and mortality after a stroke. The impact of the timing and type of ASyS remains unclear.
This multicenter cohort study included data from 9 centers between 2002 and 2018, with a final analysis in February 2024. The study included 4552 adults (2005 female; median age, 73 years) with ischemic stroke and no seizure history. Seizures were classified using International League Against Epilepsy definitions. We examined ASyS occurring within seven days after stroke. The main outcomes were all-cause mortality and epilepsy. Validation of the updated SeLECT score (SeLECT-ASyS) was performed in 3 independent cohorts (Switzerland, Argentina, and Japan) collected between 2012 and 2024, including 74 adults with ASyS.
The 10-year risk of poststroke epilepsy ranged from 41% to 94%, and mortality from 36% to 100%, depending on ASyS type and timing. ASyS on stroke onset day had a higher epilepsy risk (adjusted hazard ratio [aHR], 2.3 [95% CI, 1.3–4.0]; P=0.003) compared with later ASyS. Status epilepticus had the highest epilepsy risk (aHR, 9.6 [95% CI, 3.5–26.7]; P<0.001), followed by focal to bilateral tonic-clonic seizures (aHR, 3.4 [95% CI, 1.9–6.3]; P<0.001). Mortality was higher in those with ASyS presenting as focal to bilateral tonic-clonic seizures on day 0 (aHR, 2.8 [95% CI, 1.4–5.6]; P=0.004) and status epilepticus (aHR, 14.2 [95% CI, 3.5–58.8]; P<0.001). The updated SeLECT-ASyS model, available as an application, outperformed a previous model in the derivation cohort (concordance statistics, 0.68 versus 0.58; P=0.02) and in the validation cohort (0.70 versus 0.50; P=0.18).
ASyS timing and type significantly affect epilepsy and mortality risk after stroke, improving epilepsy prediction and guiding patient counseling.
To evaluate how the timing and type of acute symptomatic seizures (ASyS) after ischemic stroke affect the risk of developing poststroke epilepsy (PSE) and mortality, and to create an updated, more accurate prognostic model (SeLECT-ASyS) for stroke survivors with ASyS.
Risk Quantification:
The 10-year risk of developing PSE ranged from 41% to 94%, depending on the type and timing of ASyS.
Seizures occurring on the day of stroke onset (day 0) were associated with higher PSE risk (aHR 2.3).
Status epilepticus carried the highest risk of PSE (aHR 9.6), followed by focal to bilateral tonic-clonic seizures (FBTCS) (aHR 3.4).
Mortality over 10 years ranged from 36% to 100%, with status epilepticus presenting the highest mortality risk (aHR 14.2).
Impact of Acute Symptomatic Seizures:
Timing (day 0 vs later) and type (SE or FBTCS) of ASyS were critical determinants of long-term outcomes.
ASyS on day 0 and severe seizure types (SE, FBTCS) indicated more severe underlying stroke damage and a greater tendency toward epileptogenesis.
Model Accuracy:
The existing SeLECT2.0 model underestimated PSE risk in patients with ASyS (C statistic 0.58).
The newly developed SeLECT-ASyS model, incorporating ASyS characteristics, improved risk prediction (C statistic 0.68 in derivation cohort, 0.70 in validation cohort).
SeLECT-ASyS provides individualized risk estimates for epilepsy after stroke in patients with ASyS.
Patients with ASyS occurring as status epilepticus or FBTCS on day 0 had ≥60% risk of developing epilepsy over 10 years.
Accurate prediction of epilepsy risk can guide more tailored clinical counseling, management strategies, and potentially early interventions.
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.
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.
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 (SeLECT2.0; 0.71, 95% CI: 0.65–0.76, p < 0.001).
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.
To evaluate how early EEG findings (epileptiform activity and regional slowing) after ischemic stroke affect the risk of developing post–stroke epilepsy (PSE), and to develop an updated, more accurate prognostic model (SeLECT–EEG) for stroke survivors without acute symptomatic seizures (ASyS).
Risk Quantification:
Epileptiform activity: 42% risk of PSE within 5 years vs 13% in patients without such findings (aHR 2.0).
Regional slowing: 24% risk vs 11% risk for those without this finding (aHR 1.9).
Impact of EEG Findings:
Epileptiform activity and regional slowing early after stroke are independent markers of long–term seizure risk.
These EEG abnormalities reveal a “hidden” risk in patients without clinical ASyS, identifying a group prone to post–stroke epilepsy despite the absence of early clinical seizures.
Model Accuracy:
The new SeLECT–EEG model (points range 0–8) outperformed the clinical SeLECT2.0 model in patients without ASyS (C-statistic: 0.75 vs 0.71).
Validation confirmed its robust discrimination and calibration across external cohorts.
Enables early, individualized risk estimates for post–stroke epilepsy based on EEG findings and clinical data.
Identifies high–risk patients (SeLECT–EEG ≥7) with a >60% risk of epilepsy over 10 years, supporting closer monitoring, patient counseling, and consideration for early intervention trials.
Refines long–term planning, including driving recommendations and antiseizure therapy decisions.
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 poststroke epilepsy (PSE) in patients without acute symptomatic seizures.
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).
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).
The cEEG identifies additional epileptiform abnormalities with prognostic value beyond routineduration EEG, supporting extension of monitoring in selected cases based on baseline risk and early EEG findings.
To quantify what continuous EEG (cEEG ≥12 hours) adds beyond a 60-minute EEG (the first 60 minutes of the same recording) for detecting EEG abnormalities and improving prediction of post-stroke epilepsy (PSE) after ischemic stroke in patients without acute symptomatic seizures.
Diagnostic yield (cEEG vs 60-min EEG):
Regional slowing: 24% risk vs 11% risk for those without this finding (aHR 1.9).
Strongest EEG predictors of later PSE:
Prognostic improvement with longer monitoring:
Timing matters: