Electroencephalography abnormalities in generalized epilepsy and their predictors: A multicenter experience.

Background: In spite of the overwhelming significance of knowledge of basic elements of electroencephalography (EEG) in its application to the diagnostic workup and the management of patients with suspected or already established generalized epilepsy (GE), there is a dearth of data on the pattern and utility of clinical variables that can independently determine EEG abnormalities in GE. Objective: The study was designed to evaluate the frequency and pattern of EEG abnormality as well as assess the utility of clinical variables in predicting the likelihood of an abnormal EEG in GE. Methods: It was a cross-sectional study involving the analysis of EEGs of consecutive patients with clinical diagnosis of idiopathic GE from three centers over a 7-year period. Information on sociodemographic and seizure variables was obtained. The International Federation of Societies for Electroencephalography and Clinical Neurophysiology definition of interictal epileptiform discharges (interictal epileptiform activity [IEA]) was adopted in the study. Results: A total of 403 patients comprising 242 (60%) males and 161 (40%) females with clinical diagnosis of GE had EEG. Their age ranged between 2 weeks and 70 years, with a median age of 21 years and an interquartile age of 26 years. Two hundred and thirty-seven (58.8%) and 213 (52.9%) patients had abnormal EEG and IEA, respectively. Before adjustment for confounders, female gender (P = 0.0001), pediatric age group (P = 0.0388), duration of epilepsy of 1-4 years (P = 0.01387), uncontrolled seizure (P = 0.0060), and seizure frequency (P = 0.0001) were significantly associated with the presence of abnormal EEG. However, age, female gender, poor seizure control, and seizure frequencies were the independent predictors of EEG abnormality. Conclusion: The study showed that about 58% of patients with GE patients had abnormal EEG. Age, poor seizure control, and high frequency of seizure were independent predictors of the presence of EEG abnormality.