A modified formula using energy system contributions to calculate pure maximal rate of lactate accumulation during a maximal sprint cycling test

Author:

Yang Woo-Hwi,Park So-Young,Kim Taenam,Jeon Hyung-Jin,Heine Oliver,Gehlert Sebastian

Abstract

Purpose: This study aimed at comparing previous calculating formulas of maximal lactate accumulation rate (νLa.max) and a modified formula of pure νLa.max (PνLa.max) during a 15-s all-out sprint cycling test (ASCT) to analyze their relationships.Methods: Thirty male national-level track cyclists participated in this study (n = 30) and performed a 15-s ASCT. The anaerobic power output (Wpeak and Wmean), oxygen uptake, and blood lactate concentrations (La) were measured. These parameters were used for different calculations of νLa.max and three energy contributions (phosphagen, WPCr; glycolytic, WGly; and oxidative, WOxi). The PνLa.max calculation considered delta La, time until Wpeak (tPCr−peak), and the time contributed by the oxidative system (tOxi). Other νLa.max levels without tOxi were calculated using decreasing time by 3.5% from Wpeak (tPCr −3.5%) and tPCr−peak.Results: The absolute and relative WPCr were higher than WGly and WOxi (p < 0.0001, respectively), and the absolute and relative WGly were significantly higher than WOxi (p < 0.0001, respectively); νLa.max (tPCr −3.5%) was significantly higher than PνLa.max and νLa.max (tPCr−peak), while νLa.max (tPCr−peak) was lower than PνLa.max (p < 0.0001, respectively). PνLa.max and νLa.max (tPCr−peak) were highly correlated (r = 0.99; R2 = 0.98). This correlation was higher than the relationship between PνLa.max and νLa.max (tPCr −3.5%) (r = 0.87; R2 = 0.77). νLa.max (tPCr−peak), PνLa.max, and νLa.max (tPCr −3.5%) were found to correlate with absolute Wmean and WGly.Conclusion: PνLa.max as a modified calculation of νLa.max provides more detailed insights into the inter-individual differences in energy and glycolytic metabolism than νLa.max (tPCr−peak) and νLa.max (tPCr −3.5%). Because WOxi and WPCr can differ remarkably between athletes, implementing their values in PνLa.max can establish more optimized individual profiling for elite track cyclists.

Publisher

Frontiers Media SA

Subject

Physiology (medical),Physiology

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