Electrocardiographic Screening of Arrhythmogenic Cardiomyopathy in Genotype-Positive and Phenotype-Negative Relatives - Lopez-Ayala, Jose Maria; Gimeno-Blanes, Javier; Lopez-Cuenca, David; Molina, Maria Sabater; Gimeno-Blanes, Juan Ramon (Frontiers in Cardiovascular Medicine, 2021)
Background Arrhythmogenic cardiomyopathy is a hereditary cause of ventricular arrhythmias and sudden death. Identifying the healthy genetic carriers who will develop the disease remains a challenge. A novel approach to the analysis of the digital electrocardiograms of mutation carriers through signal processing may identify early electrocardiographic abnormalities. Methods A retrospective case-control study included a population of healthy genetics carriers and their wild-type relatives. Genotype-positive/phenotype-negative individuals bore mutations associated with the development of arrhythmogenic cardiomyopathy. The relatives included had a non-pathologic 12-lead electrocardiogram, echocardiogram, and a cardiac magnetic resonance. Automatic digital electrocardiographic analyses comprised QRS and terminal activation delay duration, the number of QRS fragmentations, ST slope, and T-wave voltage. Results Digital 12-lead electrocardiograms from 41 genotype-positive/phenotype-negative (29 simple carriers and 12 double mutation carriers) and 73 wild-type relatives were analyzed. No differences in the QRS length, the number of QRS fragmentations, and the voltage of the T-wave were observed. After adjusting for potential confounders, double carriers showed an average ST-slope flatter than those of the simple carriers and wild-type (5.18° [0.73-8.01], 7.15° [5.14-11.05] and 11.46° [3.94-17.49] respectively, p:0.005). There was a significant negative correlation between the ST-slope and the age in genotype positive/phenotype negative relatives (r: 0.376, p: 0.021) not observed in their wild-type counterparts (r: 0.074, p: 0.570). Conclusions A flattened ST segment may be an early sign of electrical remodeling that precedes T- wave inversion in healthy genetic carriers. A thorough analysis of the digital electrocardiographic signal may help identify and measure early electrical abnormalities.