Data_Sheet_1_Ictal ECG-based assessment of sudden unexpected death in epilepsy.docx

IntroductionPrevious 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.
MethodsWe 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.
ResultsAlpha 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.
DiscussionThis study develops a novel metric alpha, which highlights non-linear interactions between two rhythms in the ECG, and is predictive of SUDEP risk.

引言 此前针对癫痫猝死（Sudden Unexpected Death in Epilepsy，SUDEP）患者开展的病例对照研究，未能识别出可预测SUDEP风险的心电图（Electrocardiogram，ECG）特征，包括围发作期心率、心率变异性、校正QT间期、发作后心率恢复情况以及心脏节律。这表明亟需从心电图中提取新型指标以评估SUDEP风险。
方法 我们采用单谱分析与独立成分分析（Single Spectrum Analysis and Independent Component Analysis，SSA-ICA）去除心电图记录中的伪影。随后对发作中期20秒的时间段应用跨频相位耦合（Cross-Frequency Phase-Phase Coupling，PPC）分析，并确定了-3 dB耦合强度的等高线。计算得到该等高线质心的极坐标：幅度（alpha）与角度（theta）。评估了alpha与theta和SUDEP的相关性，并构建了针对alpha的逻辑回归分类器。
结果 与非SUDEP患者相比，SUDEP患者的alpha值更高（p < 0.001）。不同患者群体的theta值无显著差异。针对alpha的逻辑回归分类器的受试者工作特征曲线（Receiver Operating Characteristic，ROC）下面积（Area Under the ROC Curve，AUC）达94%，且正确分类了2例测试用SUDEP患者。
讨论 本研究提出了一种新型指标alpha，该指标可反映心电图中两种节律间的非线性相互作用，且能够预测SUDEP风险。