PURPOSE: Chronic epilepsy frequently develops after brain injury, but prediction of which individual patient will develop spontaneous recurrent seizures (i.e., epilepsy) is not currently possible. Here, we use continuous radiotelemetric electroencephalography (EEG) and video monitoring along with automated computer detection of EEG spikes and seizures to test the hypothesis that EEG spikes precede and are correlated with subsequent spontaneous recurrent seizures. METHODS: The presence and pattern of EEG spikes was studied during long recording epochs between the end of status epilepticus (SE) induced by three different doses of kainate and the onset of chronic epilepsy. RESULTS: The presence of spikes, and later spike clusters, over several days after SE before the first spontaneous seizure, was consistently associated with the development of chronic epilepsy. The rate of development of epilepsy (i.e., increase in seizure frequency) was strongly correlated with the frequency of EEG spikes and the cumulative number of EEG spikes after SE. CONCLUSIONS: The temporal features of EEG spikes (i.e., their presence, frequency, and pattern [clusters]) when analyzed over prolonged periods, may be a predictive biomarker for the development of chronic epilepsy after brain injury. Future clinical trials using prolonged EEG recordings may reveal the diagnostic utility of EEG spikes as predictors of subsequent epilepsy in brain-injured humans.
PURPOSE:Chronic epilepsy frequently develops after brain injury, but prediction of which individual patient will develop spontaneous recurrent seizures (i.e., epilepsy) is not currently possible. Here, we use continuous radiotelemetric electroencephalography (EEG) and video monitoring along with automated computer detection of EEG spikes and seizures to test the hypothesis that EEG spikes precede and are correlated with subsequent spontaneous recurrent seizures. METHODS: The presence and pattern of EEG spikes was studied during long recording epochs between the end of status epilepticus (SE) induced by three different doses of kainate and the onset of chronic epilepsy. RESULTS: The presence of spikes, and later spike clusters, over several days after SE before the first spontaneous seizure, was consistently associated with the development of chronic epilepsy. The rate of development of epilepsy (i.e., increase in seizure frequency) was strongly correlated with the frequency of EEG spikes and the cumulative number of EEG spikes after SE. CONCLUSIONS: The temporal features of EEG spikes (i.e., their presence, frequency, and pattern [clusters]) when analyzed over prolonged periods, may be a predictive biomarker for the development of chronic epilepsy after brain injury. Future clinical trials using prolonged EEG recordings may reveal the diagnostic utility of EEG spikes as predictors of subsequent epilepsy in brain-injured humans.
Authors: Philip Williams; Andrew White; Damien Ferraro; Suzanne Clark; Kevin Staley; F Edward Dudek Journal: J Neurosci Methods Date: 2006-03-27 Impact factor: 2.390
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Authors: Asla Pitkänen; Katarzyna Lukasiuk; F Edward Dudek; Kevin J Staley Journal: Cold Spring Harb Perspect Med Date: 2015-09-18 Impact factor: 6.915