Cardiovascular and Autonomic Responses to a Maximal Exercise Test in Elite Youngsters

Abstract

To analyze cardiovascular and autonomic responses in elite youngsters, 13 male cyclists (15.43±0.51 years) performed a graded-test until voluntary exhaustion. Oxygen consumption (VO), blood lactate (BLa), arterial oxygen saturation (SaO), respiratory exchange ratio (RER) and rating of perceived exertion (RPE) were collected, while heart rate (HR) was registered for heart rate variability (HRV) analyses, looking for linear and nonlinear comparisons. Cyclists reached maximal exertion [RPE: 19.14±0.94; BLa: 8.92±2.51 mmol.L; RER: 1.04±0.03; SaO: 92.43±2.5%] and high-level performance (4.41±0.46 W·Kg; 60.77±6.87 ml·Kg·min) once over 95% of age-predicted HR. VO and RPE increased, and RR intervals (RRi) decreased (p<0.005), whereas only the short-term scaling exponent of the Detrended Fluctuation Analysis technique (DFA1) displayed similar adaptive changes regarding intensity (p=0.011). After controlling for W·Kg and RRi, DFA1 (0.260±0.084) showed large-negative correlations with VO (r=-0.83; p<0.05) and RPE (r=-0.79; p<0.05), suggesting a strong association between the reduction in self-similar properties of the cardiac signal and the capacity to elicit at maximum in youths. Overall-HRV (lnRMSSD) and short-term variability (lnSD1) did not show any association at maximum, or significant differences regarding intensity. DFA1 might reflect ANS-CNS linkage related to cardiac respiratory controls through exercise, becoming a complementary criterion for VO testing in youths.

Fractal Correlation Properties of Heart Rate Variability: A New Biomarker for Intensity Distribution in Endurance Exercise and Training Prescription?

“…The state of research of DFA-alpha1 as an indicator for correlation properties of HR time series has been reviewed most recently (Gronwald and Hoos, 2020 ). In the corresponding studies investigating high intensity and incremental cycling exercise until voluntary exhaustion, the study results demonstrate a general loss of complexity and variability of R-R interval fluctuations with increasing exercise intensity (Hautala et al, 2003 ; Casties et al, 2006 ; Platisa and Gal, 2008 ; Platisa et al, 2008 ; Karavirta et al, 2009 ; Blasco-Lafarga et al, 2017 ; Hottenrott and Hoos, 2017 ; Gronwald et al, 2019a , b ). More precisely, from low to high intensity exercise, DFA-alpha1 indicates a biphasic course.…”

“…The rate of change per workrate elevation seems highest near the aerobic threshold and since it is a complexity index of overall organismic demands (Gronwald et al, 2019a), no curve calibration or normalization is needed. Studies by Casties et al (2006), ), Blasco-Lafarga et al (2017, and Gronwald et al (2019a) all indicate a clear decline in interbeat correlation properties with high work rates with values resembling white noise behavior at VO 2 levels historically in the realm between aerobic threshold (LT1, VT1) and anaerobic threshold (LT2, VT2). Within the context of different training models (e.g., polarized, pyramidal, or threshold training-intensity FIGURE 1 | Quantification and qualitative description of acute and chronic correlation properties (short-term scaling exponent alpha1 of DFA) within HR time series during resting conditions and during endurance-type exercise demands (Peng et al, 1995;Goldberger et al, 2002;Lipsitz, 2002;Tulppo et al, 2003;Gronwald et al, 2018).…”

“…More precisely, from low to high intensity exercise, DFA-alpha1 indicates a biphasic course. Depending on the resting value (usually around 1.0 and 1.5), constant or moderately increasing values (up to 1.5) have been reported at very low to moderate intensities, and strongly, almost linearly decreasing values down to around 0.3 from moderate to high exercise intensity (Hautala et al, 2003;Casties et al, 2006;Karavirta et al, 2009;Blasco-Lafarga et al, 2017;Gronwald et al, 2019a). This behavior indicates an intensity-dependent change of HR dynamics from strongly correlated to uncorrelated/stochastic or anti-correlated behavior due to a notably strong vagal withdrawal and/or sympathetic activation Hottenrott and Hoos, 2017) as well as other factors such as possible intracardiac biochemical changes or coupling mechanisms of different physiological subsystems (Casties et al, 2006;Papaioannou et al, 2013).…”

“…Despite well-functioning approaches (Tulppo et al, 1996 ; Karapetian et al, 2008 ), frequency-domain parameters such as high frequency (HF) power for example has been noted to be unreliable in a sizable fraction of individuals with up to 20% of subjects not having identified breakpoints (Cottin et al, 2006 ). Furthermore, Blasco-Lafarga et al ( 2017 ) noted that standard deviation 1 from Poincaré plot analysis (SD1, short-term) was already suppressed in young athletes at the first tested work rate of 60% VO 2MAX making it less useful for example for aerobic threshold delineation. However, in response to the concern over strongly decreased variability and weak reproducibility of amplitude dependent time- and frequency-domain HRV measures during exercise (Persson and Wagner, 1996 ; Tulppo et al, 2005 ), non-linear methods of HRV analysis reveal promising approaches gaining new insights for training-intensity distribution from a holistic autonomic nervous system (ANS) perspective, not depending on specific organismic subsystems.…”

The Relationship Between the Performance and Brain Oxygenation During Acute Supramaximal Exercise

“…Antrenmanın fizyolojik yanıtları arasında beyin dışında diğer fizyolojik yanıtlara ait bulgular iyi bilinmektedir. Yüksek antrenman düzeyine sahip sporcularda kemik yoğunluğu ve kas miktarının üst seviyelere çıkması, sol ventrikül büyümesi, toplam kan miktarının ve oksijen taşıma kapasitesinin artması, mikrovaskülaritenin artması ve inflamatuar sitokin seviyesinin azalması ve enerji metabolizmasındaki değişimler gibi uyum süreçleri bu fizyolojik yanıtlara örnek olarak verilebilir (31)(32)(33)(34). Özellikle gelişim çağında yapılan düzenli antrenmanların, uzun dönemde nöral gelişimin hızlanması, nöroplastisite oluşumu, beyinde vasküler yapının daha güçlü olması ve yeni kılcal damar yapılarının oluşumu gibi süreçlere katkı sağladığı deneyler ile gösterilmiştir (35)(36)(37).…”