Predicting seizures: a behavioral approach.
This article reviews the epilepsy cycle, distinguishing the interictal, preictal, ictal, and postictal phases. Evidence suggesting that the preictal phase can sometimes be identified based on neurophysiologic signals, premonitory features, the presence of trigger factors, or self-report is also reviewed. Diary studies have shown that seizures are not randomly distributed in time and that a subgroup of persons with epilepsy can predict an impending seizure. Paper diary data and preliminary analysis of electronic diary data suggest that seizure prediction is feasible. Whereas all of this evidence sets the stage for seizure prediction and preemptive therapy, several questions remain unanswered. First, what proportion of persons with epilepsy can predict their seizures? Second, within and among individuals, how accurate is prediction? Third, can prediction be improved through education about group level or individual predictors? And finally, in a group that can make robust predictions what are the most effective interventions for reducing seizure probability at times of high risk? The answers to these questions could reduce the burden of epilepsy by making seizures predictable and setting the stage for preemptive therapy. This work could improve the understanding of epilepsy by providing a context for studying the transitions from the interictal to preictal and ictal states. More prospective studies are needed; challenges certainly exist, but as the studies discussed here demonstrate, the field is rich with promise for improving the lives of patients with epilepsy.
Haut
Sheryl R
SR
Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, New York, NY 10467, USA. Electronic address: haut@aecom.yu.edu.
Lipton
Richard B
RB
Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, New York, NY 10467, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, NY 10461, USA.
D004827:Epilepsy / Q000150:complications / Q000503:physiopathology*; D006801:Humans; D012640:Seizures / Q000209:etiology / Q000503:physiopathology* / Q000517:prevention & control