Open Access, Peer-reviewed

ISSN 2005-7571 (Online)
Volume 27, Number 1 (1/2020)
Original Article <page. 1-8 >
DOI : 10.22857/kjbp.2020.27.1.001

The Determination of the Duration of Electroconvulsive Therapy-Induced Seizure Using Local Standard Deviation of the Electroencephalogram Signal and the Changes of the RR Interval of Electrocardiogram

Eun Young Kim, MD1,2;Cheol Seung Yoo, PhD3;Dong Chung Jung, MD4,5;Sang Hoon Yi, PhD6;In-Won Chung, MD3;Yong Sik Kim, MD3,7; and Yong Min Ahn, MD4,8;

1;Mental Health Center, Seoul National University Health Care Center, Seoul, 2;Department of Medicine, Seoul National University College of Medicine, Seoul, 3;Department of Psychiatry, Institute of Clinical Psychopharmacology, Dongguk University Ilsan Hospital, Goyang, 4;Department of Neuropsychiatry, Seoul National University Hospital, Seoul, 5;Seoul Chung Psychiatry Clinic, Seoul, 6;Department of Computer Simulation, Institute of Basic Science, Inje University, Gimhae, 7;Department of Psychiatry, Eulji Medical Center, Eulji Univertisy, Seoul, 8;Department of Psychiatry and Behavioral Science, Institute of Human Behavioral Medicine, Seoul National University College of Medicine, Seoul, Korea

Objectives : In electroconvulsive therapy (ECT) research and practice, the precise determination of seizure duration is important in the evaluation of clinical relevance of the ECT-induced seizure. In this study, we have developed computerized algorithms to assess the duration of ECT-induced seizure.

Methods : Subjects included 5 males and 6 females, with the mean age of 33.1 years. Total 55 ECT sessions were included in the analysis. We analyzed the standard deviation of a finite block of electroencephalography (EEG) data and the change in the local slope of RR intervals in electrocardiography (ECG) signals during ECT-induced seizure. And then, we compared the calculated seizure durations from EEG recording (EEG algorithm) and ECG recording (ECG algorithm) with values determined by consensus of clinicians based on the recorded EEG (EEG consensus), as a gold standard criterion, in order to testify the computational validity of our algorithms.

Results : The mean seizure durations calculated by each method were not significantly different in sessions with abrupt flattened postictal suppression and in sessions with non-abrupt flattened postictal suppression. The intraclass correlation coefficients (95% confidence interval) of the three methods (EEG algorithm, ECG algorithm, EEG consensus) were significant in the total sessions [0.79 (0.70-0.86)], the abrupt flattened postictal suppression sessions [0.84 (0.74-0.91)], and the non-abrupt flattened postictal suppression sessions [0.67 (0.45-0.84)]. Correlations between three methods were also statistically significant, regardless of abruptness of transition.

Conclusions : Our proposed algorithms could reliably measure the duration of ECT-induced seizure, even in sessions with non-abrupt transitions to flat postictal suppression, in which it is typically difficult to determine the seizure duration.

Key words : Electroconvulsive therapy;Electrocardiography;Electroencephalography;Postictal suppression;Seizure duration.


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