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http://dx.doi.org/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  

Kim, Eun Young (Mental Health Center, Seoul National University Health Care Center)
Yoo, Cheol Seung (Department of Psychiatry, Institute of Clinical Psychopharmacology, Dongguk University Ilsan Hospital)
Jung, Dong Chung (Department of Neuropsychiatry, Seoul National University Hospital)
Yi, Sang Hoon (Department of Computer Simulation, Institute of Basic Science, Inje University)
Chung, In-Won (Department of Psychiatry, Institute of Clinical Psychopharmacology, Dongguk University Ilsan Hospital)
Kim, Yong Sik (Department of Psychiatry, Institute of Clinical Psychopharmacology, Dongguk University Ilsan Hospital)
Ahn, Yong Min (Department of Neuropsychiatry, Seoul National University Hospital)
Publication Information
Korean Journal of Biological Psychiatry / v.27, no.1, 2020 , pp. 1-8 More about this Journal
Abstract
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.
Keywords
Electroconvulsive therapy; Electrocardiography; Electroencephalography; Postictal suppression; Seizure duration;
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