QUANTIFICATION METHODS OF ELECTROENCEPHALOGRAPHIC SPIKES DURING SLEEP AND WAKEFULNESS IN PATIENTS WITH ELECTRICAL STATUS EPILEPTICUS IN SLEEP
Abstract number :
2.424
Submission category :
Year :
2014
Submission ID :
1868976
Source :
www.aesnet.org
Presentation date :
12/6/2014 12:00:00 AM
Published date :
Dec 4, 2014, 06:00 AM
Authors :
Ahmet Tanritanir, Michele Jackson, Lindsay St. Louis, Jacquelyn Klehm and Tobias Loddenkemper
Rationale: Quantification of electroencephalographic (EEG) spike frequency and spike-wave index are currently used to assess the therapeutic effects of anti-epileptic drugs (AEDs) for the treatment of Continuous Spikes and Waves and the Electrical Status Epilepticus in Sleep (ESES) pattern. Further developments in quantification of EEG features during both sleep and wakefulness would improve clinical management and ESES treatment. This study aims to describe the correlation and evolution of three EEG features in ESES, spike-wave index (SWI), spike frequency (SF) and the one hour spike frequency (OHSF) during the sleep and wakefulness periods and to present a novel quantification tool, the sleep to wakefulness ratio, for clinical use in evaluating the course and treatment of ESES. Methods: We retrospectively evaluated SWI, SF and OHSF in 15 patients diagnosed with ESES who underwent overnight video-EEG monitoring at a tertiary pediatric center between 2012 and 2014. Patients with at least 50% spike percentage during slow wave sleep were included. We determined the correlation between SWI and SF during the first 5 minutes of sleep and a 5 minute period of wakefulness on EEG, as well as the correlation with OHSF during a longer period of one hour in sleep and wakefulness. The ratio of sleep to wakefulness for SWI, SF and OHSF was also evaluated. SWI was defined as the percentage of 1-second bins containing at least one spike-wave complex for a period of 5 minutes. SF was defined as the number of spikes during the same exact 5 minute period and OHSF was defined as the number of spikes for a period of one hour. Results: The median age was 7.73 (range: 3 -11, SD: 2.7) years and 66.7% were males. The median SWI was 70.7 (IQR: 52-83, SD: 15.4) during sleep and 24 (IQR: 9.7-43, SD: 16.8) during wakefulness. The median SF was 265.5 (IQR: 235-335, SD: 102.9) during sleep and 100 (IQR: 30-200, SD: 83.1) during wakefulness. The median OHSF was 2650 (IQR: 1976-4322, SD: 1651.4) during sleep and 879 (IQR: 326-2001, SD: 1172.6) during wakefulness. SWI and SF during both sleep (Spearman correlation coefficient, R =0.921; p=0.0001) and wakefulness (R =0.971; p=0.0001) correlated well. OHSF and SWI also correlated during both sleep (R= 0.771; p=0.001) and wakefulness (R=0.874; p=0.0001). Furthermore, OHSF and SF also demonstrate a correlation during both sleep (R=0.711, p=0.003) and wakefulness (R=0.886, p=0.0001). The ratio of sleep to wakefulness for SWI, SF and OHSF was determined as 3.83, 4.45 and 5.98 respectively. Conclusions: The study confirmed the correlation between SWI, SF, and OHSF and details a novel quantification tool, the sleep to wakefulness ratio, in patients with ESES. This biomarker (sleep to wakefulness ratio) may provide an additional method for EEG quantification that can be used clinically in evaluating ESES in patients.