Abstract

Objective: Post-stroke epilepsy (PSE) is associated with increased morbidity and mortality. Stroke-associated acute symptomatic seizures are an important risk factor: 20.8–34.3% of these patients will go on to develop PSE. Identifying these “high risk” individuals may result in earlier PSE diagnosis, treatment, and avoidance of seizure-related morbidity. This study was to identify predictors of PSE development in patients with stroke-associated acute symptomatic seizures.Participants and Methods: This was a retrospective cohort study of 167 patients with stroke-associated acute symptomatic seizures admitted to the Neurology Department of a tertiary Hospital of China, from 1 May 2006 to 30 January 2020. Both those with primary ischemic stroke and intracerebral hemorrhage were included in the study. Patient demographics, medical history, stroke-associated, and seizure-related variables were evaluated with univariable analysis and multivariable Cox regression analysis. PSE was defined as unprovoked seizures occurring > 7 days post-stroke. Data points were extracted from medical records and supplemented by tele-interview.Results: Of the 167 patients with stroke-associated acute symptomatic seizures, 49 (29.3%) developed PSE. NIHSS score > 14 [hazard ratio (HR) 2.98, 95% CI 1.57–5.67], longer interval from stroke to acute symptomatic seizures (days 4–7 post-stroke) (HR 2.51, 95% CI 1.37–4.59) and multiple acute symptomatic seizures (HR 5.08, 95% CI 2.58–9.99) were independently associated with PSE development. This association remained in the sub-analysis within the ischemic stroke cohort. In the sub-analysis of the hemorrhagic stroke cohort, multilobar involvement (HR 4.80, 95% CI 1.49–15.39) was also independently associated with development of PSE. Further, we developed a nomogram to predict individual risk of developing PSE following stroke-associated acute symptomatic seizures. The nomogram showed a C-index of 0.73.Conclusion: More severe neurofunctional deficits (NIHSS score > 14), longer interval from stroke to acute symptomatic seizures (days 4–7 post-stroke), and multiple acute symptomatic seizures were independently associated with development of PSE in patients with stroke-associated acute symptomatic seizures. This knowledge may increase clinical vigilance for development of PSE, facilitating rapid diagnosis and treatment initiation, and subsequently reduce seizure-related morbidity.

Highlights

  • Stroke is the leading cause of epilepsy in the elderly, accounting for 30–50% of all-cause epilepsy in this group (Ruggles et al, 2001; Verellen and Cavazos, 2011; Zhao et al, 2018)

  • We aimed to identify the factors associated with post-stroke epilepsy (PSE) development in patients who have experienced acute symptomatic seizures following ischemic or hemorrhagic stroke, and to incorporate this into a nomogram for use at the bedside or outpatient clinic to predict PSE

  • Exclusion criteria included: (1) patients without available computed tomography (CT) and/or magnetic resonance imaging (MRI); (2) patients with a prior diagnosis of epilepsy; (3) patients with secondary intracranial hemorrhage or venous infarction; (4) patients whose seizure might be attributed to other potential causes; and (5) patients who were lost to follow-up or died within 3 months of the stroke incident; (6) patients who reported ambiguous event occurring > 7 days post-stroke

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Summary

Introduction

Stroke is the leading cause of epilepsy in the elderly, accounting for 30–50% of all-cause epilepsy in this group (Ruggles et al, 2001; Verellen and Cavazos, 2011; Zhao et al, 2018). Seizures occurring more than 7 days after strokes are defined as post-stroke epilepsy (PSE) since the risk of recurrent unprovoked seizures over the subsequent 10-year period is 71.5% (Hesdorffer et al, 2009) and fulfills ILAE criteria for epilepsy, i.e., post-stroke epilepsy (PSE) (Fisher et al, 2014). They are thought to be the long-term sequela of progressive structural changes secondary to the stroke, including neuronal loss, subsequent gliosis, and reorganization of neuronal networks (Sun et al, 2001, 2002; Camilo and Goldstein, 2004)

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