Video‐electroencephalography (vEEG) is an important component of epilepsy diagnosis and management. Nevertheless, inpatient vEEG monitoring fails to capture seizures in up to one third of patients. We hypothesized that personalized seizure forecasts could be used to optimize the timing of vEEG.

We used a database of ambulatory vEEG studies to select a cohort with linked electronic seizure diaries of more than 20 reported seizures over at least 8 weeks. The total cohort included 48 participants. Diary seizure times were used to detect individuals’ multiday seizure cycles and estimate times of high seizure risk. We compared whether estimated seizure risk was significantly different between conclusive and inconclusive vEEGs, and between vEEG with and without recorded epileptic activity. vEEGs were conducted prior to self‐reported seizures; hence, the study aimed to provide a retrospective proof of concept that cycles of seizure risk were correlated with vEEG outcomes.

This project was supported by the Epilepsy Foundation of America’s Epilepsy Innovation Institute “My Seizure Gauge” grant.

Philippa J. Karoly, Dominique Eden, Ewan S. Nurse, Mark J. Cook, Janelle Taylor, Sonya Dumanis, Mark P. Richardson, Benjamin H. Brinkmann, Dean R. Freestone

Read Epilepsia publication here.

Read medRxiv publication here.

Video‐electroencephalography (vEEG) is an important component of epilepsy diagnosis and management. Nevertheless, inpatient vEEG monitoring fails to capture seizures in up to one third of patients. We hypothesized that personalized seizure forecasts could be used to optimize the timing of vEEG. We used a database of ambulatory vEEG studies to select a cohort with linked…