Temporal patterns of epileptiform discharges in genetic generalized epilepsies

- Epileptiform discharge (ED) distribution in genetic generalized epilepsy demonstrates a nonrandom pattern.
- This pattern across the 24-hour time scale is heavily influenced by the state of arousal.
- The maximum activity of EDs is seen from 23:00 through 07:00 h.
- Brief EDs (fragments) are more frequent in sleep, whereas longer paroxysms are more frequent in wakefulness.
- Overall, two-thirds of EDs occur in sleep.

ObjectiveWe sought to investigate the temporal patterns and sleep-wake cycle-related epileptiform discharges (EDs) in genetic generalized epilepsies (GGEs).MethodsWe studied 24-hour ambulatory electroencephalography (EEG) recordings of patients with GGE, diagnosed and classified according to the International League against Epilepsy criteria. We manually coded the type of discharge, time of occurrence, duration, and arousal state of each ED. We employed mixed effects Poisson regression modeling to study the temporal distribution of epileptiform discharges. Additionally, we used multinomial regression analysis to explore the significance of the relationship between different states of arousal and types of epileptiform discharges.ResultsWe analyzed 6923 EDs from 105 abnormal 24-hour EEGs. Mixed effects Poisson regression analysis demonstrated significant changes in ED counts across time blocks. This distribution was largely influenced by the state of arousal. Generalized fragments (duration < 2 s) and focal discharges were more frequent during non-REM sleep while paroxysms (duration ≥ 2 s) were more frequent in wakefulness. Overall, 67% of epileptiform discharges occurred in non-REM sleep and only 33% occurred in wakefulness. Twenty-four patients (23%) had ED exclusively in sleep. Epileptiform discharges peaked from 23:00 through 07:00 h.SignificanceThere is a time-of-day dependency of ED with a significant influence exerted by the state of arousal. Our observations suggest that the generation of epileptiform discharges is not a random process but is the result of complex interactions among biological rhythms such as the sleep-wake cycle and the intrinsic circadian pacemaker. High density of ED in sleep suggests that 24-hour EEG recording with the capture of natural sleep may be more useful than routine EEG to diagnose GGE.