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Seizure self-prediction; myth or missed opportunity?

Lookup NU author(s): Dr Michael Mackay, Dr Hector Mahlaba, Erika Gavillet, Professor Roger Whittaker



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract Purpose Many patients report being able to predict their own seizures, and yet most seizures appear to strike out of the blue. This inherent contradiction makes the topic of seizure self-prediction controversial as well as difficult to study. Here we review the evidence for whether this ability exists, how many patients are capable of self-prediction and the nature of this capability, and whether this could provide a target for intervention. MethodsSystematic searches of bibliographic databases including MEDLINE, EMBASE and PsycINFO through OVID were performed to identify relevant papers which were then screened by the study authors for inclusion in the study. 18 papers were selected for inclusion as the focus of this review.ResultsOn the basis of two studies, between 17% and 41% of patients demonstrate a significantly greater than chance ability to predict an upcoming seizure in the following 12-hour time window. This risk is correlated with self-reported anxiety, stress, sleep deprivation, mood and certain prodromal symptoms. However, there is no evidence for any subjective experience which directly heralds an imminent seizure. Thus, while patients may be aware of seizure risk, and have some ability to predict seizure occurrence over a wide time window, they are unable to subjectively recognise seizure onset in advance.ConclusionUtilising subjectively acquired knowledge of seizure risk may provide a widely implementable tool for targeted intervention. The risk fluctuates over a time course appropriate for pharmacotherapy which may improve seizure control and the side-effect profile of anti-epileptic medication.

Publication metadata

Author(s): Mackay M, Mahlaba H, Gavillet E, Whittaker RG

Publication type: Article

Publication status: Published

Journal: Seizure - European Journal of Epilepsy

Year: 2017

Volume: 51

Pages: 180-185

Print publication date: 01/10/2017

Online publication date: 01/09/2017

Acceptance date: 25/08/2017

Date deposited: 14/09/2017

ISSN (electronic): 1059-1311

Publisher: Elsevier


DOI: 10.1016/j.seizure.2017.08.011


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Funder referenceFunder name
Engineering and Physical Sciences 298 Research Council (EP SRC, grant reference : NS/A000026/1 ) .
Wellcome Trust grant reference: 102037/Z/13/Z