4.4 Article

Is the maximal lactate steady state concept really relevant to predict endurance performance?

期刊

EUROPEAN JOURNAL OF APPLIED PHYSIOLOGY
卷 122, 期 10, 页码 2259-2269

出版社

SPRINGER
DOI: 10.1007/s00421-022-05001-6

关键词

Aerobic endurance; Cycling; Exercise capacity; Exercise testing; Time trial

资金

  1. Swiss National Science Foundation [P2BSP3_191755]
  2. Swiss National Science Foundation (SNF) [P2BSP3_191755] Funding Source: Swiss National Science Foundation (SNF)

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The study found that there is no correlation between maximal oxygen consumption at the maximal lactate steady state and the ability to sustain a high fraction of maximum oxygen consumption for a given competition duration, and these factors do not improve the prediction of power output in time trials.
Purpose There is no convincing evidence for the idea that a high power output at the maximal lactate steady state (PO_(MLSS)) and a high fraction of (V)over dotO(2max) at MLSS (%(V)over dotO(2)_(MLSS)) are decisive for endurance performance. We tested the hypotheses that (1) %(V)over dotO(2)_(MLSS )is positively correlated with the ability to sustain a high fraction of (V)over dotO(2max) for a given competition duration (%(V)over dotO(2)_(TT)); (2) %(V)over dotO(2)_(MLSS) improves the prediction of the average power output of a time trial (PO_(TT)) in addition to (V)over dotO(2max) and gross efficiency (GE); (3) PO_(MLSS) improves the prediction of PO_(TT )in addition to (V)over dotO(2max) and GE. Methods Twenty-one recreationally active participants performed stepwise incremental tests on the first and final testing day to measure GE and check for potential test-related training effects in terms of changes in the minimal lactate equivalent power output (Delta PO_LEmin), 30-min constant load tests to determine MLSS, a ramp test and verification bout for (V)over dotO(2max), and 20-min time trials for %(V)over dotO(2)_(TT) and PO_(TT). Hypothesis 1 was tested via bivariate and partial correlations between %(V)over dotO(2)_(MLSS) and %(V)over dotO(2)_(TT). Multiple regression models with (V)over dotO(2max), GE, Delta PO_LEmin, and %(V)over dotO(2)_(MLSS) (Hypothesis 2) or PO_(MLSS) instead of %(V)over dotO(2)_(MLSS) (Hypothesis 3), respectively, as predictors, and PO_(TT )as the dependent variable were used to test the hypotheses. Results %(V)over dotO(2)_(MLSS) was not correlated with %(V)over dotO(2)_(TT) (r= 0.17, p = 0.583). Neither %(V)over dotO(2)_(MLSS) (p = 0.424) nor PO_(MLSS) (p = 0.208) did improve the prediction of PO_(TT )in addition to (V)over dotO(2max) and GE. Conclusion These results challenge the assumption that PO_(MLSS) or %(V)over dotO(2)_(MLSS) are independent predictors of supra-MLSS PO_(TT) and %(V)over dotO(2)_(TT).

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