Abstract
Increased heart rate variability (HRV) and high-frequency content of the terminal region of the ventricular activation of signal-averaged ECG (SAECG) have been reported in athletes. The present study investigates HRV and SAECG parameters as predictors of maximal aerobic power (VO2max) in athletes. HRV, SAECG and VO2max were determined in 18 high-performance long-distance (25 +/- 6 years; 17 males) runners 24 h after a training session. Clinical visits, ECG and VO2max determination were scheduled for all athletes during the training period. A group of 18 untrained healthy volunteers matched for age, gender, and body surface area was included as controls. SAECG was acquired in the resting supine position for 15 min and processed to extract average RR interval (Mean-RR) and root mean squared standard deviation (RMSSD) of the difference of two consecutive normal RR intervals. SAECG variables analyzed in the vector magnitude with 40-250 Hz band-pass bi-directional filtering were: total and 40-microV terminal (LAS40) duration of ventricular activation, RMS voltage of total (RMST) and of the 40-ms terminal region of ventricular activation. Linear and multivariate stepwise logistic regressions oriented by inter-group comparisons were adjusted in significant variables in order to predict VO2max, with a P < 0.05 considered to be significant. VO2max correlated significantly (P < 0.05) with RMST (r = 0.77), Mean-RR (r = 0.62), RMSSD (r = 0.47), and LAS40 (r = -0.39). RMST was the independent predictor of VO2max. In athletes, HRV and high-frequency components of the SAECG correlate with VO2max and the high-frequency content of SAECG is an independent predictor of VO2max.
Highlights
Regular aerobic exercise training brings about beneficial changes in the cardiovascular system, with impact on individual and community health [1,2,3]
The present study investigates heart rate variability (HRV) and signal-averaged ECG (SAECG) parameters as predictors of maximal aerobic power (VO2max) in athletes
The objectives of the present study were: 1) to investigate HRV parameters and highfrequency content of the signal-averaged ECG (SAECG) as predictors of maximal aerobic power in trained athletes and healthy untrained subjects, and 2) to propose a mathematical model based on HRV and SAECG parameters to classify both trained and untrained healthy subjects according to maximal aerobic power
Summary
Regular aerobic exercise training brings about beneficial changes in the cardiovascular system, with impact on individual and community health [1,2,3]. The cardiovascular remodeling that follows aerobic fitness, reflected by both structural and functional changes of the heart, can be assessed by routine clinical examination. Mechanical remodeling following progressive upgrade in training level aiming at maximal aerobic power fitness is characterized by increased cardiac performance and a mild to moderate increase in left ventricular mass, and by increased contractile force of the cardiomyocyte in laboratory animal models [1,47]. The nature and the genesis of these components on the surface ECG in athletes, are still subject to investigation, and have been associated with both improvement of aerobic training level and incipient ventricular hypertrophy [6,8,9]. Conventional methods aiming at estimating maximal aerobic power consist of exercise testing (either field or ergospirometry) usually lasting 12 to 25 min
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