Quantitative EEG and functional outcome following acute ischemic stroke.

Area of Science:

• Neuroscience
• Clinical Neurology
• Biomedical Engineering

Background:

• Ischemic stroke is a leading cause of long-term disability.
• Accurate prediction of stroke outcome is crucial for patient management and rehabilitation planning.
• Existing prognostic markers (demographic, clinical, imaging) have limitations in predicting long-term outcomes.

Purpose of the Study:

• To identify the most accurate quantitative electroencephalography (qEEG) predictors of unfavorable post-ischemic stroke outcome.
• To compare the discriminative capacity of qEEG indices against established prognostic markers.
• To determine if qEEG indices improve outcome prediction models.

Main Methods:

• Prospective cohort study of 151 anterior circulation ischemic stroke patients.
• Electroencephalography (EEG) recorded within 72 hours and at 7 days post-stroke.
• Calculation and analysis of qEEG indices (band power, symmetry, ratios) as predictors of unfavorable outcome (mRS ≥ 3) at discharge and 12 months, adjusted for clinical and imaging factors.

Main Results:

• Higher delta and lower alpha/beta relative powers predicted unfavorable outcomes.
• Delta-theta to alpha-beta ratio (DTABR) and alpha relative power demonstrated superior discriminative capacity.
• Outcome prediction models incorporating qEEG indices were superior to those without.
• Infarct size was not a significant predictor when qEEG indices were included.

Conclusions:

• DTABR and alpha relative power are the most effective qEEG predictors of stroke outcome.
• These qEEG indices outperform ASPECTS in predicting post-stroke outcomes.
• qEEG indices enhance the predictive accuracy of existing clinical and imaging markers at both short-term and long-term follow-up.
• qEEG indices serve as independent predictors of stroke outcome.