Frontiers in Physiology (Apr 2023)

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

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

DOI
https://doi.org/10.3389/fphys.2023.1147321
Journal volume & issue
Vol. 14

Abstract

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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.

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