Purpose: To evaluate EEG differences among syndromes in genetic generalized epilepsy based on quantified data.
Methods: Twenty-four-hour ambulatory EEGs were recorded in consecutive patients diagnosed with genetic generalized epilepsy. All epileptiform EEG abnormalities were quantified into density scores (total duration of epileptiform discharges per hour). One-way analysis of variance was conducted to find out differences in EEG density scores among the syndromes. Generalized linear mixed models were also fitted to explore the association between the proportion of “pure” generalized spike–wave paroxysms and fragments (without intervening polyspikes/polyspike–waves) and the syndromes.
Results: In total, 6,923 epileptiform discharges were analyzed from 105 abnormal EEGs. In the analysis of variance, six EEG variables were significantly different among syndromes: total spike density (P = 0.001), total polyspike and polyspike–wave density (P = 0.049), generalized spike–wave–only density (P < 0.001), generalized paroxysm density (P < 0.001), generalized paroxysm duration mean (P = 0.018), and generalized paroxysm duration maximum (P = 0.009). The density of epileptiform discharges and the paroxysm durations were the highest in juvenile absence epilepsy followed by juvenile myoclonic epilepsy, childhood absence epilepsy, and generalized epilepsy with tonic–clonic seizures only. Generalized linear mixed models revealed that “pure” generalized spike–wave discharges (without intervening polyspikes/polyspike waves) tended to be more frequent in absence epilepsies, although the difference was not statistically significant (P = 0.21).
Conclusions: The findings of this study suggest that the density and duration of epileptiform discharges can help differentiate among genetic generalized epilepsy syndromes.
*Department of Medicine, St. Vincent's Hospital, The University of Melbourne, Melbourne, Australia;
†Department of Neuroscience, Monash Medical Centre, Melbourne, Australia;
‡Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia; and
§Statistical Consulting Centre, The University of Melbourne, Melbourne, Australia.
Address correspondence and reprint requests to Udaya Seneviratne, FRACP, PhD, Department of Neuroscience, St. Vincent's Hospital, PO Box 2900, Fitzroy, Victoria 3065, Australia; e-mail: Udaya.Seneviratne@svhm.org.au.
U. Seneviratne has received travel and speaker honoraria from UCB Pharma. W. D'Souza has received grants and personal fees from UCB Pharma, grants and personal fees from Eisai Pharmaceuticals, and fees from SciGen Pharmaceuticals during the conduct of the study. M. Cook has received speaker honoraria from UCB Pharma and Sanofi Australia and travel honoraria from UCB Pharma and SciGen. He has received research grants from the National Health and Medical Research Council (Australia) and the Australian Research Council. He has also received a Science, Technology, and Innovation Grant from the State Government of Victoria, Australia. The remaining author has no funding or conflicts of interest to disclose.