High seizure frequency prior to antiepileptic treatment is a predictor of pharmacoresistant epilepsy in a rat model of temporal lobe epilepsy.

Epilepsia

Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, and Center for Systems Neuroscience, Bünteweg 17, D-30559 Hannover, Germany.

Published: January 2010

Purpose: Progress in the management of patients with medically intractable epilepsy is impeded because we do not fully understand why pharmacoresistance happens and how it can be predicted. The presence of multiple seizures prior to medical treatment has been suggested as a potential predictor of poor outcome. In the present study, we used an animal model of temporal lobe epilepsy to investigate whether pharmacoresistant rats differ in seizure frequency from pharmacoresponsive animals.

Methods: Epilepsy with spontaneous recurrent seizures (SRS) was induced by status epilepticus. Frequency of SRS was determined by video/EEG (electroencephalography) monitoring in a total of 33 epileptic rats before onset of treatment with phenobarbital (PB).

Results: Thirteen (39%) rats did not respond to treatment with PB. Before treatment with PB, average seizure frequency in PB nonresponders was significantly higher than seizure frequency in responders, which, however, was due to six nonresponders that exhibited > 3 seizures per day. Such high seizure frequency was not observed in responders, demonstrating that high seizure frequency predicts pharmacoresistance in this model, but does not occur in all nonresponders.

Discussion: The data from this study are in line with clinical experience that the frequency of seizures in the early phase of epilepsy is a dominant risk factor that predicts refractoriness. However, resistance to treatment also occurred in rats that did not differ in seizure frequency from responders, indicating that disease severity alone is not sufficient to explain antiepileptic drug (AED) resistance. These data provide further evidence that epilepsy models are useful in the search for predictors and mechanisms of pharmacoresistance.

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http://dx.doi.org/10.1111/j.1528-1167.2009.02183.xDOI Listing

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