Acute epileptiform abnormalities are the primary predictors of post-stroke epilepsy: a matched, case-control study

Area of Science:

• Neurology
• Epileptology
• Neurophysiology

Background:

• Post-stroke epilepsy (PSE) is a common complication following stroke.
• Predicting PSE risk is crucial for timely intervention and management.
• Continuous EEG (cEEG) monitoring is increasingly used in stroke patients.

Purpose of the Study:

• To identify predictors of post-stroke epilepsy (PSE) in patients undergoing continuous EEG (cEEG) monitoring.
• To determine the significance of acute EEG findings in predicting PSE development.

Main Methods:

• A case-control study matching 36 PSE cases with 72 controls (1:2 ratio) based on age and follow-up duration.
• Univariable analysis identified potential predictors: hypertension, smoking, hemorrhagic conversion, pre-cEEG seizures, and epileptiform abnormalities (EAs).
• Multivariable logistic regression was used to identify independent predictors of PSE.

Main Results:

• The presence of epileptiform abnormalities (EAs) on cEEG was the sole significant predictor of PSE (OR = 11.9).
• Other factors significant in univariable analysis did not independently predict PSE in the multivariable model.
• Acute EAs on EEG strongly indicated a higher risk of developing PSE.

Conclusions:

• Acute epileptiform abnormalities detected on continuous EEG monitoring are a significant independent predictor of post-stroke epilepsy.
• Identifying these acute EEG findings can inform targeted post-acute symptomatic seizure management.
• This finding may aid in the design and stratification of anti-epileptogenesis therapy trials.