Romanian Journal of Neurology (Dec 2021)
The frequency of abnormal electroencephalography for detecting acute ischemic stroke
Abstract
Introduction. Cerebrovascular accident is defined as rapidly developing symptoms or signs of focal and global loss of cerebral function lasting for 24 hours or more with no apparent cause other than that of vascular origin. Stroke is the fifth leading cause of death in the United States and it is one of the most disabling cause of neurological disorders. The attack of cerebrovascular accident begins abruptly, the focal neurologic deficit either fully evolved at the onset or it progress over minutes to hours or within days. Electroencephalogram (EEG) is used to detect electrical activity in the brain for various neurologic disorders like epilepsy, encephalopathy, prion diseases (CJD), Alzheimer disease and also stroke. Objective. To determine the frequency of abnormal EEG for detecting acute ischemic stroke. Methods. This was a cross sectional study conducted at Department of Medicine, Dow University of Health Sciences Karachi OJHA Campus, Dow International Medical College (DIMC), and Duration of study was 06 month from 1st October 2020 to 30th March 2021. Non-probability consecutive sampling technique was used. A total of 460 patients of acute ischemic stroke were included in this study. Patients were diagnosed on the basis of CT scan brain or diffusion weighted imaging. Within 24 hours the EEG was done in all admitted patients. The potentials recorded by EEG were cumulated excitatory and inhibitory postsynaptic potentials in neuronal dendrites, usually in most superficial regions of cerebral cortex. All data was entered and analyzed using SPSS v25.0. Data were stratified for age, gender, BMI and duration of stroke to address the effect modifiers. Post-stratification, Chi-square test was used by taking p-value ≤0.05 as significant. Results. 460 patients were selected for this study. Mean age was 40.04±9.1 years. Among cases, there were 276 (60%) males and 184 (40%) females. 235 patients (51.08%) had abnormal EEG. By stratification of abnormal EEG, it was found that duration of acute stroke had significant effect having abnormal EEG (p = 0.000001). Conclusions. The role of complexity of abnormal Electro Encephalogram is useful following acute ischemic stroke. The various parameters of EEG help to evaluate the large ischemic stroke.
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