S81. The first hour sleep EEG recording predicts the occurrence of interictal epileptiform discharges during long-term video-EEG monitoring. (May 2018)

• Record Type: Journal Article
• Authors: Liu, Xi; Rose, Sandra; Issa, Naoum; Wu, Shasha; Towle, Leo; Warnke, Peter; Tao, James X.
• Is Part Of: Clinical neurophysiology. Volume 129(2018)Supplement 1
• Page Start: e172
• Publication Date: 2018-05
• Subjects: Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2018.04.441
• Languages: English
• ISSNs: 1388-2457

Abstract

Abstract : Introduction: To determine the predictive value of the first hour sleep EEG recording in identifying patients with interictal epileptiform discharges (IEDs) during long-term video-EEG monitoring in an adult epilepsy monitoring unit. Methods: We retrospectively reviewed 255 consecutive patients who underwent continuous long-term video-EEG monitoring in the University of Chicago EMU. The complete video-EEG recording was reviewed, and the occurrence of IEDs was determined for each patient. We compared the occurrence of IEDs observed during the first hour sleep EEG recordings with the occurrence of IEDs observed during the complete long-term video-EEG recordings; inclusive of the first hour of sleep. Results: Overall, IEDs were observed in 134(53%) of 255 patients during the full long-term video-EEG recording with a duration of 4 ± 0.8 days. IEDs were identified in the first hour sleep EEG recording in 125 (sensitivity 93%) of the 134 patients. IEDs were found in the first hour sleep EEG recording in 92 (94%) of 98 patients with temporal lobe epilepsy, 11 (92%) of 12 patients with frontal lobe epilepsy, 3 (100%) of 3 patients with parietal lobe epilepsy, 1 (50%) of the 2 patients with occipital lobe epilepsy, and 15 (88%) of the 17 patients with generalized epilepsy. The ictal onset in remaining 2 patients with multi-focal IEDs could not be localized due to muscle artifacts. The negative predictive value of the first hour EEG was 93%. Conclusion: The first hour of sleep EEG recording reliably predicts the occurrence of interictal epileptiform activity in a long-term video-EEG recording, and therefore can be used efficiently for identifying patients with IEDs during long-term video-EEG recording in the adult epilepsy monitoring unit.