Ictal ECG-based assessment of sudden unexpected death in epilepsy

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

doi:10.3389/fneur.2023.1147576

Ictal ECG-based assessment of sudden unexpected death in epilepsy

Front Neurol. 2023 Mar 13:14:1147576. doi: 10.3389/fneur.2023.1147576. eCollection 2023.

Authors

Adam C Gravitis¹, Uilki Tufa¹, Katherine Zukotynski^{2

3}, David L Streiner⁴, Daniel Friedman⁵, Juliana Laze⁵, Yotin Chinvarun⁶, Orrin Devinsky⁵, Richard Wennberg⁷, Peter L Carlen^{1

7}, Berj L Bardakjian^{1

3}

Affiliations

¹ Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
² Department of Radiology, McMaster University, Hamilton, ON, Canada.
³ Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada.
⁴ Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.
⁵ Grossman School of Medicine, New York University, New York, NY, United States.
⁶ Department of Medicine, Phramongkutklao Royal Army Hospital, Bangkok, Thailand.
⁷ Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada.

Abstract

Introduction: 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.

Methods: 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.

Results: Alpha was higher in SUDEP patients, compared to non-SUDEP patients (p < 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.

Discussion: This study develops a novel metric alpha, which highlights non-linear interactions between two rhythms in the ECG, and is predictive of SUDEP risk.

Keywords: ECG; cross-frequency coupling; epilepsy; non-linear interaction in cardiac rhythms; risk assessment; signal processing; sudden unexpected death in epilepsy.

Grants and funding

BB acknowledges grant support by the Natural Sciences and Engineering Research Council of Canada (NSERC), and EpLink—the Epilepsy Research Program of the Ontario Brain Institute. The Ontario Brain Institute is an independent non-profit corporation, funded partially by the Ontario Government. The opinions, results and conclusions are those of the authors and no endorsement by the Ontario Brain Institute is intended or should be inferred. Computations were performed on the Niagara supercomputer at the SciNet HPC Consortium. SciNet was funded by the Canada Foundation for Innovation; the Government of Ontario; Ontario Research Fund—Research Excellence; and the University of Toronto. Finding A Cure for Epilepsy and Seizures (FACES) supported the collection and processing of NYU Langone Epilepsy Center data.