AUTHOR=Gravitis Adam C. , Tufa Uilki , Zukotynski Katherine , Streiner David L. , Friedman Daniel , Laze Juliana , Chinvarun Yotin , Devinsky Orrin , Wennberg Richard , Carlen Peter L. , Bardakjian Berj L. 

TITLE=Ictal ECG-based assessment of sudden unexpected death in epilepsy

JOURNAL=Frontiers in Neurology

VOLUME=14

YEAR=2023

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2023.1147576

DOI=10.3389/fneur.2023.1147576

ISSN=1664-2295

ABSTRACT=<sec><title>Introduction</title><p>Previous case-control studies of sudden unexpected death in epilepsy (SUDEP) patients failed to identify ECG features (peri-ictal heart rate, heart rate variability, corrected QT interval, postictal heart rate recovery, and cardiac rhythm) predictive of SUDEP risk. This implied a need to derive novel metrics to assess SUDEP risk from ECG.</p></sec><sec><title>Methods</title><p>We applied Single Spectrum Analysis and Independent Component Analysis (SSA-ICA) to remove artifact from ECG recordings. Then cross-frequency phase-phase coupling (PPC) was applied to a 20-s mid-seizure window and a contour of −3 dB coupling strength was determined. The contour centroid polar coordinates, amplitude (alpha) and angle (theta), were calculated. Association of alpha and theta with SUDEP was assessed and a logistic classifier for alpha was constructed.</p></sec><sec><title>Results</title><p>Alpha was higher in SUDEP patients, compared to non-SUDEP patients (<italic>p</italic> &lt; 0.001). Theta showed no significant difference between patient populations. The receiver operating characteristic (ROC) of a logistic classifier for alpha resulted in an area under the ROC curve (AUC) of 94% and correctly classified two test SUDEP patients.</p></sec><sec><title>Discussion</title><p>This study develops a novel metric <italic>alpha</italic>, which highlights non-linear interactions between two rhythms in the ECG, and is predictive of SUDEP risk.</p></sec>