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Seizure prediction and recall
J M DuBois1, L S Boylan, M Shiyko
1Department of Neurology, NYU Langone School of Medicine, NYU Epilepsy Center, 223 East 34th Street, New York, NY 10016, USA. jonathan.m.dubois@gmail.com
None:
Using separate generalized mixed-effects models, we assessed seizure recall and prediction, as well as contributing diagnostic variables, in 83 adult patients with epilepsy undergoing video/EEG monitoring. The model revealed that when participants predicted a seizure, probability equaled 0.320 (95% CI: 0.149-0.558), a significant (P<0.05) increase over negative predictions (0.151, 95% CI: 0.71-0.228]). With no seizure, the rate of remembering was approximately 0.130 (95% CI: 0.73-0.219), increasing significantly to 0.628 (95% CI: 0.439 to 0.784) when a seizure occurred (P<0.001). Of the variables analyzed, only inpatient seizure rate influenced predictability (P<0.001) or recollection (P<0.001). These models reveal that patients were highly aware of their seizures, and in many cases, were able to make accurate predictions, for which seizure rate may be an important factor.
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