Slope entropy as a complexity metric for the characterization of electrograms in post-ischemic ventricular tachycardia

Slope Entropy (SlopEn) has been recently introduced as a robust estimator of the complexity degree in physiological time series. Post-ischemic ventricular tachycardia (VT) patients exhibit highly fragmented and unstructured intracardiac electrograms (EGMs), called abnormal ventricular potentials (AVPs), referable to arrhythmogenic areas. This study aims to characterize VT EGMs, specifically physiological EGMs and AVPs, in terms of SlopEn metric, to support AVPs identification. A dataset of 344 EGMs, (65% AVPs, 35% physiological EGM), was used to assess the impact of each parameter of SlopEn (i.e., the embedded dimension m, the vertical increment threshold γ, and the proximity-to-zero difference threshold δ) in terms of significant differences, by non-parametric statistical tests, in SlopEn values between physiological EGMs and AVPs. This analysis allowed us to identify a good set of SlopEn parameters (i.e., m=3, δ=0.0003, and γ=0.0055) able to achieve a statistically significant difference (p<0.0001). According to these results, SlopEn effectively characterizes physiological and pathological EGMs in post-ischemic VT, and can be considered to support the identification of arrhythmogenic areas in VT electrophysiological studies.