Abstracts

Anesthetic Regimen Impacts Duration of Post-Ictal Generalized Electroencephalographic Suppression Following Electroconvulsive Therapy-Induced Seizures

Abstract number : 2.085
Submission category : 3. Neurophysiology / 3G. Computational Analysis & Modeling of EEG
Year : 2019
Submission ID : 2421533
Source : www.aesnet.org
Presentation date : 12/8/2019 4:04:48 PM
Published date : Nov 25, 2019, 12:14 PM

Authors :
Leonard B. Hickman, Washington University School of Medicine; Ben J. Palanca, Washington University School of Medicine; Courtney Chan, Washington University School of Medicine; Emma R. Trammel, University of Michigan; ShiNung Ching, Washington University

Rationale: Post-ictal generalized electroencephalographic suppression (PGES) is defined as the initial occurrence of EEG activity less than 10 microvolts following termination of a generalized seizure. PGES duration has been implicated as a marker for increased risk of sudden unexplained death in epilepsy. This pattern of suppressed EEG activity can also follow generalized seizures induced during electroconvulsive therapy (ECT), where qualitative ratings of PGES are correlated with treatment efficacy. Using a novel, automated algorithm for PGES detection, we quantified the duration of suppressed EEG following ECT-induced seizures. We investigated the impact of anesthetic regimen on detected suppression. Methods: Fifteen patients with major depressive or bipolar affective disorder underwent right unilateral ECT with either high-dose ketamine (2-2.5 mg/kg) or low-dose etomidate (0.2 mg/kg) anesthesia in a randomized cross-over trial (NCT02761330). Recordings were obtained using modified 65-sensor EEG caps. The 5-minute period following seizure termination was assessed for the presence of PGES using a voltage threshold-based classification algorithm. PGES was defined as periods of EEG amplitude of less than 10 microvolts in the majority of channels. Algorithm performance was validated in comparisons among four epileptologist readings of PGES during the initial 30 seconds after seizure termination. Cohen's kappa as a measure of agreement was determined, based upon classification of each 1-second window. We assessed the temporal, spatial, and frequency characteristics of detected PGES and the relationship between PGES duration and anesthetic condition. Results: The algorithm showed moderate agreement with epileptologist readings of PGES (median kappa coefficient: 0.44, range 0.11-0.63). In contrast, lower agreement was observed between epileptologists (median kappa coefficient: 0.26, range 0.05-0.49). Across 50 post-ictal recordings, 35 contained PGES as detected by the automated classification algorithm. PGES most commonly began in the first 10 seconds following seizure termination. However, intermittent epochs of suppression were detected up to five minutes after seizure termination. Instantaneous probability of PGES demonstrated a log-linear relationship with time across participants and conditions (R2: 0.822, p < 0.001). The median total duration of PGES was 5.5 seconds (IQR: 0 to 27). Spatial topography of PGES demonstrated generalized low amplitude without lateralization. The total duration of PGES was greater following high-dose ketamine (median: 21.5 seconds, IQR: 6.5 to 64) than low-dose etomidate (median: 1.5 seconds, IQR: 0 to 9) general anesthesia. Pairwise comparison demonstrated significant difference between anesthetic regimens (Wilcoxon signed rank test, p = 0.021). Conclusions: Electroconvulsive therapy presents a controlled setting for investigating PGES. PGES following ECT-induced seizures can be detected using a simple voltage-based algorithm. Probability of PGES decreases over time in a log-linear fashion, which suggests constraints on the underlying neural dynamics involved in generating PGES. PGES can occur intermittently for minutes following seizure termination, particularly during recovery from ketamine anesthesia. The impact of anesthetic type and dose should be considered when interpreting PGES duration after ECT-induced seizures. Funding: James S. McDonnell Foundation, NIH Clinical and Translational Science Award (CTSA) program under TL1 TR002344.
Neurophysiology