Abstract-A group of relatively uncommon but important genetic cardiovascular diseases (GCVDs) are associated with increased risk for sudden cardiac death during exercise, including hypertrophic cardiomyopathy, long-QT syndrome, Marfan syndrome, and arrhythmogenic right ventricular cardiomyopathy. These conditions, characterized by diverse phenotypic expression and genetic substrates, account for a substantial proportion of unexpected and usually arrhythmia-based fatal events during adolescence and young adulthood. Guidelines are in place governing eligibility and disqualification criteria for competitive athletes with these GCVDs (eg, Bethesda Conference No. 26 and its update as Bethesda Conference No. 36 in 2005). However, similar systematic recommendations for the much larger population of patients with GCVD who are not trained athletes, but nevertheless wish to participate in any of a variety of recreational physical activities and sports, have not been available. The practicing clinician is frequently confronted with the dilemma of designing noncompetitive exercise programs for athletes with GCVD after disqualification from competition, as well as for those patients with such conditions who do not aspire to organized sports. Indeed, many asymptomatic (or mildly symptomatic) patients with GCVD desire a physically active lifestyle with participation in recreational and leisure-time activities to take advantage of the many documented benefits of exercise. However, to date, no reference document has been available for ascertaining which types of physical activity could be regarded as either prudent or inadvisable in these subgroups of patients. Therefore, given this clear and present need, this American Heart Association consensus document was constituted, based largely on the experience and insights of the expert panel, to offer recommendations governing recreational exercise for patients with known GCVDs.
A new method is proposed to evaluate the dynamics of QT interval adaptation in response to heart rate (HR) changes. The method considers weighted averages of RR intervals (RR) preceding each cardiac beat to express RR interval history accounting for the influence on repolarization duration. A global optimization algorithm is used to determine the weight distribution leading to the lowest regression residual when curve fitting the [QT, RR1 data using a patient-specific regression model. From the optimum weight distribution, a memory lag L90 is estimated, expressing the delay in the QT adaptation to HR changes. On average, RR intervals of the past 150 beats (approximately 2.5 min) are required to model the QT response accurately. From a clinical point of view, the interval of the initial tens of seconds to one minute seems to be most important in the majority of cases. A measure of the optimum regression residual (r(opt)) has been calculated, discriminating between post-myocardial infarction patients at high and low risk of arrhythmic death while on treatment with amiodarone. A similar discrimination has been achieved with a variable expressing the character of QT lag behind the RR interval dynamics.
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