Heart Rate Variability by Dynamical Patterns in Windows of Holter Electrocardiograms: A Method to Discern Left Ventricular Hypertrophy in Heart Transplant Patients Shortly after the Transplant

Abstract

Background: The Holter electrocardiogram (ECG) provides a long signal that represents the heart’s responses to both autonomic regulation and various phenomena, including heart tissue remodeling. Loss of information is a common result when using global statistical metrics. Method: Breaking the signal into short data segments (e.g., windows) provides access to transient heart rate characteristics. Symbolization of the ECG by patterns of accelerations and/or decelerations allows using entropic metrics in the assessment of heart rate complexity. Two types of analysis are proposed: (i) visualization of the pattern dynamics of the whole signal, and (ii) scanning the signal for pattern dynamics in a sliding window. The method was applied to a cohort of 42 heart transplant (HTX) recipients divided into the following groups: a left ventricle of normal geometry (NG), concentrically remodeled (CR), hypertrophic remodeled (H), and to the control group (CG) consisting of signals of 41 healthy coevals. The Kruskal–Wallis test was used to assess group differences. Statistical conclusions were verified via bootstrap methods. Results: The visualization of the group pattern dynamics showed severely limited autonomic regulations in HTX patients when compared to CG. The analysis (in segments) prove that the pattern dynamics of the NG group are different from the pattern dynamics observed in the CR and H groups. Conclusion: Dynamic pattern entropy estimators tested in moving windows recognized left ventricular remodeling in stable HTX patients.