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Novel risk calculator performance in athletes with arrhythmogenic right ventricular cardiomyopathy
Alessio Gasperetti1, Antonio Dello Russo2, Mattia Busana3
1Heart Rhythm Center, Centro Cardiologico Monzino, IRCCS, Milan, Italy; Department of Cardiology, University Hospital of Zurich, Zurich, Switzerland.
Background:
Disease progression and ventricular arrhythmias (VAs) in arrhythmogenic right ventricular cardiomyopathy (ARVC) are correlated with physical exercise, and clinical detraining and avoidance of competitive sport practice are suggested for ARVC patients. An algorithm assessing primary arrhythmic risk in ARVC patients was recently developed by Cadrin-Tourigny et al. Data regarding its transferability to athletes are lacking.
Objective:
The purpose of this study was to assess the reliability of the Cadrin-Tourigny risk prediction algorithm in a cohort of athletes with ARVC and to describe the impact of clinical detraining on disease progression.
Methods:
All athletes undergoing clinical detraining after ARVC diagnosis at our institution were enrolled. Baseline and follow-up clinical characteristics and data on VA events occurring during follow-up were collected. The Cadrin-Tourigny algorithm was used to calculate the a priori predicted VA risk, which was compared with the observed outcomes.
Results:
Twenty-five athletes (age 36.1 ± 14.0 years; 80% male) with definite ARVC who were undergoing clinical detraining were enrolled. Over median (interquartile range) follow-up of 5.3 (3.2-6.6) years, a reduction in premature ventricular complex (PVC) burden (P = .001) was assessed, and 10 VA events (40%) were recorded. The a priori algorithm-predicted risk seemed to fit with the observed cohort arrhythmic risk [mean observed-predicted risk difference over 5 years -0.85% (interquartile range -4.8% to +3.1%); P = .85]. At 1-year follow-up, 11 patients (44%) had an improved stress ECG response, and no significant changes in right ventricular ejection fraction were observed.
Conclusion:
Clinical detraining is associated with PVC burden reduction in athletes with ARVC. The novel risk prediction algorithm does not seem to require any correction for its application to ARVC athletes.
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