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Electrocardiographic Screening of Arrhythmogenic Cardiomyopathy in Genotype-Positive and Phenotype-Negative Relatives
Jose Maria Lopez-Ayala1, Javier Gimeno-Blanes2, David Lopez-Cuenca3
1Department of Cardiology, San Juan General University Hospital, Alicante, Spain.
Insights
A flattened ST segment on electrocardiograms may indicate early electrical changes in healthy genetic carriers of arrhythmogenic cardiomyopathy. This digital ECG analysis helps identify subtle abnormalities before disease onset.
Area of Science:
- Cardiology
- Genetics
- Biomedical Engineering
Background:
- Arrhythmogenic cardiomyopathy (ACM) is an inherited condition causing ventricular arrhythmias and sudden cardiac death.
- Early identification of healthy genetic carriers who will develop ACM is crucial but challenging.
- Digital electrocardiogram (ECG) signal processing offers a novel approach to detect early abnormalities.
Purpose of the Study:
- To investigate early electrocardiographic abnormalities in genotype-positive/phenotype-negative individuals carrying ACM-associated mutations.
- To assess the utility of digital ECG analysis in identifying subclinical electrical remodeling.
Main Methods:
- Retrospective case-control study analyzing digital 12-lead ECGs from 41 genotype-positive/phenotype-negative individuals and 73 wild-type relatives.
- Automatic digital ECG analysis included QRS duration, terminal activation delay, QRS fragmentation, ST slope, and T-wave voltage.
- Individuals were classified as simple carriers, double mutation carriers, or wild-type.
Main Results:
- No significant differences were found in QRS duration, QRS fragmentation, or T-wave voltage between groups.
- Double mutation carriers exhibited a significantly flatter ST slope compared to simple carriers and wild-type individuals (p=0.005).
- A negative correlation between ST slope and age was observed in genotype-positive/phenotype-negative individuals, but not in wild-type relatives.
Conclusions:
- A flattened ST segment may represent an early sign of electrical remodeling in ACM genetic carriers, preceding T-wave inversion.
- Comprehensive digital ECG signal analysis can detect and quantify early electrical abnormalities in individuals at risk for ACM.
Abstract:
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-pathological 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.
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