Can EEG differentiate among syndromes in genetic generalized epilepsy?

PURPOSE:: To evaluate electroencephalographic (EEG) differences among syndromes in genetic generalized epilepsy (GGE) based on quantified data. METHODS:: 24-hour ambulatory EEGs were recorded in consecutive patients diagnosed with GGE. All epileptiform EEG abnormalities were quantified into density scores (total duration of epileptiform discharges per hour). We conducted one-way analysis of variance (ANOVA) to find out differences in EEG density scores among the syndromes. We also fitted generalized linear mixed models to explore the association between the proportion of “pure” generalized spike-wave paroxysms and fragments (without intervening polyspikes/ polyspike-waves) and the syndromes. RESULTS:: We analyzed 6923 epileptiform discharges from 105 abnormal EEGs. In the ANOVA, 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, though the difference was not statistically significant (p = 0.21). CONCLUSIONS:: Our findings suggest that the density and duration of epileptiform discharges can help differentiate among GGE syndromes.