Prevalence and clinical significance of isolated low QRS voltages in young athletes.

AIMS: Low QRS voltages (peak to peak <0.5 mV) in limb leads (LQRSV) on the athlete's electrocardiogram (ECG) may reflect an underlying cardiomyopathy, mostly arrhythmogenic cardiomyopathy (ACM) or non-ischaemic left ventricular scar (NILVS). We studied the prevalence and clinical meaning of isolated LQRSV in a large cohort of competitive athletes. METHODS AND RESULTS: The index group included 2229 Italian competitive athletes [median age 18 years (16-25), 67% males, 97% Caucasian] without major ECG abnormalities at pre-participation screening. Three control groups included Black athletes (N = 1115), general population (N = 1115), and patients with ACM or NILVS (N = 58). Echocardiogram was performed in all athletes with isolated LQRSV and cardiac magnetic resonance (CMR) in those with ventricular arrhythmias or echocardiographic abnormalities. The isolated LQRSV pattern was found in 1.1% index athletes and was associated with increasing age (median age 28 vs. 18 years; P < 0.001), elite status (71% vs. 34%; P < 0.001), body surface area, and body mass index but not with sex, type of sport, and echocardiographic left ventricular mass. The prevalence of isolated LQRSV was 0.2% in Black athletes and 0.3% in young individuals from the general population. Cardiomyopathy patients had a significantly greater prevalence of isolated LQRSV (12%) than index athletes, Black athletes, and general population. Five index athletes with isolated LQSRV and exercise-induced ventricular arrhythmias underwent CMR showing biventricular ACM in 1 and idiopathic NILVS in 1. CONCLUSIONS: Unlike cardiomyopathy patients, the ECG pattern of isolated LQRSV was rarely observed in athletes. This ECG sign should prompt clinical work-up for exclusion of an underlying cardiomyopathy.

A novel method for patient-specific QTc--modeling QT-RR hysteresis.

BACKGROUND: Cardiac repolarization adaptation to cycle length change is patient dependent and results in complex QT-RR hysteresis. We hypothesize that accurate patient-specific QT-RR curves and rate corrected QT values (QTc) can be derived through patient-specific modeling of hysteresis. METHOD AND RESULTS: Model development was supported by QT-RR observations from 1959 treadmill tests, allowing extensive exploration of the influences of autonomic function on QT adaptation to rate changes. The methodology quantifies and then removes patient-specific repolarization adaptation rates. The estimated average 95% QT confidence limit was approximately 1 msec for the studied population. The model was validated by comparing QT-RR curves derived from a submaximal exercise protocol with rapid exercise and recovery phases, characterized by high hysteresis, with QT-RR values derived from an incremental stepped protocol that held heart rate constant for 5 minutes at each stage of exercise and recovery. CONCLUSIONS: The underlying physiologic changes affecting QT dynamics during the transitions from rest to exercise to recovery are quite complex. Nevertheless, a simple patient-specific model, comprising only three parameters and based solely on the preceding history of RR intervals and trend, is sufficient to accurately model QT hysteresis over an entire exercise test for a diverse population. A brief recording of a resting ECG, combined with a short period of submaximal exercise and recovery, provides sufficient information to derive an accurate patient-specific QT-RR curve, eliminating QTc bias inherent in population-based correction formulas.

Prediction of cardiovascular death using a novel heart rate recovery parameter.

INTRODUCTION: Reassertion of vagal tone after exercise is an important component in mediating heart rate recovery (HRR), and both vagal tone and HRR have been associated with mortality. HRR is strongly related to the increase in HR from resting to peak exercise. We hypothesized that a score normalized for HR increase would better isolate the vagal influences in recovery from the sympathetic influences supporting maximal exercise. METHODS: HRR data from 1959 veterans were analyzed. During a mean follow-up of 5.3 years, 187 (9.5%) subjects died-70 (37%) due to cardiovascular (CV) causes. A method was developed to compare HRR curve shapes normalized for differences in HR increase. Differences in the slopes of the normalized curves over the range 50-70 s were observed between the survivors and nonsurvivors, and a prognostic measurement, HRRS50-70, was developed. The incremental increases in predictive power and discriminative accuracy provided by Duke Treadmill Score (DTS), clinical parameters, HR increase, recovery variables, and HRRS50-70 were assessed. RESULTS: In the age-adjusted Cox analysis, the only significant exercise indices associated with CV mortality were HR increase (P < 0.0001), HRRS50-70 (P = 0.01), and DTS (P < 0.001). The increased risk for patients in the lowest tertile for all three indices, relative to those with normal scores, was 22 (95% CI, 7.9-63; P < 0.0001). CONCLUSIONS: HRRS50-70 is independent of and complementary to HR increase and DTS. Patients with abnormal HRRS50-70 and abnormal DTS and/or HR increase are at substantially increased risk of CV mortality.

Autonomic nervous system interaction with the cardiovascular system during exercise.

There is considerable recent evidence that parameters thought to reflect the complex interaction between the autonomic nervous system and the cardiovascular system during exercise testing can provide significant prognostic information. Specific variables of great importance include heart rate (HR) response to exercise (reserve), HR recovery after exercise, and multiple components of HR variability both at rest and with exercise. Poor HR response to exercise has been strongly associated with sudden cardiac death and HR recovery from a standard exercise test has been shown to be predictive of mortality. In addition, there are limited studies evaluating the components of HR variability at rest and during exercise and their prognostic significance. Research continues seeking to refine these exercise measurements and further define their prognostic value. Future findings should augment the power of the exercise test in risk-stratifying cardiovascular patients.