Seizure prediction and recall

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.