Literature DB >> 19853216

Predicting seizures: a behavioral approach.

Sheryl R Haut1, Richard B Lipton2.   

Abstract

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.

Entities:  

Mesh:

Year:  2009        PMID: 19853216     DOI: 10.1016/j.ncl.2009.06.002

Source DB:  PubMed          Journal:  Neurol Clin        ISSN: 0733-8619            Impact factor:   3.806


  5 in total

1.  Predicting seizures: are we there yet?

Authors:  Sheryl Haut
Journal:  Epilepsy Curr       Date:  2013-11       Impact factor: 7.500

2.  Forecasting Individual Headache Attacks Using Perceived Stress: Development of a Multivariable Prediction Model for Persons With Episodic Migraine.

Authors:  Timothy T Houle; Dana P Turner; Adrienne N Golding; John A H Porter; Vincent T Martin; Donald B Penzien; Charles H Tegeler
Journal:  Headache       Date:  2017-07       Impact factor: 5.887

Review 3.  Toward new paradigms of seizure detection.

Authors:  Devin K Binder; Sheryl R Haut
Journal:  Epilepsy Behav       Date:  2012-12-12       Impact factor: 2.937

4.  Impact of corticosterone treatment on spontaneous seizure frequency and epileptiform activity in mice with chronic epilepsy.

Authors:  Olagide W Castro; Victor R Santos; Raymund Y K Pun; Jessica M McKlveen; Matthew Batie; Katherine D Holland; Margaret Gardner; Norberto Garcia-Cairasco; James P Herman; Steve C Danzer
Journal:  PLoS One       Date:  2012-09-28       Impact factor: 3.240

Review 5.  Current norms and practices in using a seizure diary for managing epilepsy: A scoping review.

Authors:  Chika K Egenasi; Anandan A Moodley; Wilhelm J Steinberg; Anthonio O Adefuye
Journal:  S Afr Fam Pract (2004)       Date:  2022-09-22
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.