[Electroencephalography in acute stroke].

Area of Science:

• Neuroscience
• Clinical Neurology
• Medical Imaging

Background:

• Acute stroke frequently leads to neurological complications.
• Electroencephalography (EEG) is crucial for monitoring brain activity in critically ill patients.
• Understanding EEG patterns in stroke can aid in prognosis prediction.

Purpose of the Study:

• To determine the incidence of non-convulsive status epilepticus, epileptiform activity, and rhythmic/periodic patterns in acute stroke patients.
• To assess the diagnostic value of EEG for predicting survival and recovery post-stroke.
• To identify reliable EEG biomarkers for unfavorable outcomes.

Main Methods:

• Analysis of electroencephalography (EEG) data from 86 neurointensive care unit stroke patients.
• EEG recordings were initiated based on seizure occurrence or suspicion of status epilepticus.
• Evaluation of ictal-interictal continuum biomarkers and EEG's predictive value for survival and recovery.

Main Results:

• Pathological EEG changes were observed in 84% of patients.
• Common findings included absence of dominant occipital rhythm (66%), hemispheric slowing (42%), and diffuse slowing (41%).
• EEG reactivity was absent in 20%; epileptiform discharges occurred in 36%, and rhythmic/periodic patterns in 26%.

Conclusions:

• EEG amplitude, dominant frequency, and reactivity are the most useful biomarkers for predicting survival.
• Sporadic epileptiform discharges, rhythmic, and periodic patterns are not definitively linked to negative prognoses in stroke patients.
• Absence of dominant occipital rhythm, lack of reactivity, and low background EEG amplitude reliably predict unfavorable outcomes.