Early follow-up data from seizure diaries can be used to predict subsequent seizures in same cohort by borrowing strength across participants

Accurate prediction of seizures in persons with epilepsy offers opportunities for both precautionary measures and preemptive treatment. Previously identified predictors of seizures include patient-reported seizure anticipation, as well as stress, anxiety, and decreased sleep. In this study, we developed three models using 30 days of nightly seizure diary data in a cohort of 71 individuals with a history of uncontrolled seizures to predict subsequent seizures in the same cohort over a 30-day follow-up period. The best model combined the individual's seizure history with that of the remainder of the cohort, resulting in 72% sensitivity for 80% specificity, and 0.83 area under the receiver operating characteristic curve. The possibility of clinically relevant prediction should be examined through electronic data capture and more specific and more frequent sampling, and with patient training to improve prediction.