Electroencephalography in Seizure Diagnosis and the Prediction of Functional Outcomes of Stroke Patients at Korle Bu Teaching Hospital

Abstract

Background: As compared to developed economies, stroke is a rising epidemic affecting mostly the younger workforce in Sub-Saharan Africa (SSA), exerting a severe toll on the physical, psychoemotional, cognitive and social lives of its victims with a 3-year mortality rate of 84%. The occurrence of seizures lead to poor prognosis and increased mortality in stroke patients. Early screening for seizures and effective prognostication of the functional outcome of stroke may improve the outcomes of patients. General aim: This study aimed to determine the incidence of seizures in 30 stroke patients and how quantitative electroencephalography (QEEG) indices prognosticate their one-month functional outcome. Methodology: Electroencephalography (EEG) is a non-invasive analysis of brain function available at Korle Bu Teaching Hospital. Stroke outcome was measured using the modified National Institute of Health Stroke Scale (mNIHSS), modified Rankin Scale (MRS) and Barthel Index (BI). In this study, routine EEG of thirty (30) consenting acute stroke patients was recorded using the 10/20 standardized format within ten days of stroke onset. The EEG patterns were characterized by a neurologist and then delta/alpha ratio (DAR), relative alpha power (RAP) and the pairwise derived brain symmetry index (pdBSI) were calculated using the EEGLAB software. On the day of recording EEG, the mNIHSS, MRS and Barthel Index scores of the patients were measured and again a month later. Clinical and EEG findings were displayed on bar charts and statistical tables while Spearman’s rank correlation and linear regression was used to determine predictors of one-month outcome using the Statistical Product for Service Solution (SPSS) version 20. Results: The 30 participants of this study consisted 60% aged 60years or below, 66.7% male and 33.3% haemorrhagic stroke. Clinical seizures occurred in 13.3% of study participants, electrographic seizure occurred in 46.7% (with 92.9% being generalized seizures) and cerebral dysfunction was diagnosed in 56.7% of the participants. The MRS, mNIHSS and BI measured at recruitment significantly correlated to their measures at one-month (p < 0.01); the least being between MRS and mNIHSS scores at recruitment (rho = 0.753) and the highest was between MRS and BI scores at recruitment (rho = -0.932). The only correlation for QEEG indices was between RAP and DAR (rho = -0.988, p < 0.001), the highest in the entire analysis. Overall, mNIHSS score at recruitment was the best predictor of all three functional outcome measures at one-month- MRS1 (beta = 0.471, p = 0.001), mNIHSS1 (beta= 0.753, p = 0.001) and BI1 (beta= -0.556, p = 0.001). Conclusion: There was a high incidence of electrographic seizure in stroke patients of Korle Bu Teaching Hospital than what could be clinically diagnosed. The QEEG indices- DAR, RAP and pdBSI did not significantly predict post-stroke functional outcomes measures (MRS, mNIHSS or BI) at one-month across all stroke types. Relative alpha power (RAP) measured at recruitment was the only QEEG index useful in the prediction of neurological deficit (mNIHSS) in ischaemic stroke at one-month post stroke. The mNIHSS measured at recruitment was the most significant predictor of all functional outcome measures (MRS, mNIHSS and BI) assessed at one-month post stroke.