Diagnosis of Electrical Status Epilepticus During Slow-Wave Sleep With 100 Seconds of Sleep. Issue 1 (January 2017)

• Record Type: Journal Article
• Authors: Weber, Amanda B.; Albert, Dara V.; Yin, Han; Held, Timothy P.; Patel, Anup D.
• Is Part Of: Journal of clinical neurophysiology. Volume 34:Issue 1(2017)
• Publication Date: 2017-01
• Subjects: Electrical status epilepticus during slow wave sleep -- Spike-wave index -- Neurophysiologic assessment; Electroencephalography -- Periodicals; Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electroencephalography; Periodicals; 612.805
• DOI: 10.1097/WNP.0000000000000307
• Languages: English
• ISSNs: 0736-0258

Abstract

Abstract : Purpose: Strategies for diagnosing electrical status epilepticus during slow-wave sleep (ESES) vary among interpreting neurologists. Our aim was to evaluate if the spike-wave index (SWI) for the first 100 seconds of sleep is reflective of the SWI when compared with a conventional method. Methods: We reviewed EEGs from 2005 to 2011 that were considered diagnostic of ESES based on unspecified methods. The SWI for the first nonrapid eye movement sleep cycle (long method) was calculated by two neurophysiologists. Two different neurophysiologists calculated SWI for the first 100 seconds of sleep (short method). For the purposes of this study, ESES was defined as an SWI of >85%. The two SWI scores were compared. Results: Fourteen EEGs were reviewed. Despite being considered by the initial interpreter as diagnostic of ESES, only 4 of the studies had an SWI of >85% based on each of the methods. For a diagnosis of ESES, the sensitivity of the short method is 80% and the specificity is 89%. Wilcoxon signed rank test was used to compare the long and short methods. A P value of 0.70 indicates no significant difference between the methods. Additionally, the Spearman correlation coefficient is 0.553 ( P = 0.04), indicating moderate correlation between the methods. Conclusions: The SWI for the first 100 seconds of nonrapid eye movement sleep is predictive of the SWI for the entire first sleep cycle with a good sensitivity and specificity in our cohort. This suggests an alternative method for diagnosing ESES, which is comparable to analysis of a full night of sleep.