Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
3049921 | Epilepsy & Behavior | 2012 | 7 Pages |
Identifying the pre-ictal state clinically would improve our understanding of seizure onset and suggest opportunities for new treatments. In our previous paper-diary study, increased stress and less sleep predicted seizures. Utilizing electronic diaries, we expanded this investigation. Variables were identified by their association with subsequent seizure using logit-normal random effects models fit by maximum likelihood. Nineteen subjects with localization-related epilepsy kept e-diaries for 12–14 weeks and reported 244 eligible seizures. In univariate models, several mood items and ten premonitory features were associated with increased odds of seizure over 12 h. In multivariate models, a 10-point improvement in total mood decreased seizure risk by 25% (OR 0.75, CI 0.61–0.91, p = 004) while each additional significant premonitory feature increased seizure risk by nearly 25% (OR 1.24, CI 1.13–1.35, p < 001) over 12 h. Pre-ictal changes in mood and premonitory features may predict seizure occurrence and suggest a role for behavioral intervention and pre-emptive therapy in epilepsy.
► In this study, we explore clinical aspects of the pre-ictal state using e-diaries. ► Improvements in mood reduced the risk of a seizure within 12 hours by 25%. ► Each additional premonitory feature increased the risk of seizure by 25%. ► Pre-ictal changes in mood and premonitory features may predict seizure occurrence. ► Behavioral interventions and pre-emptive therapy may be appropriate for epilepsy.