Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m
                    Prediction in Running?

Quittmann, Oliver J.; Foitschik, Tina; Vafa, Ramin; Freitag, Finn Jannis; Sparmann, Nordin; Nolte, Simon; Abel, Thomas

doi:10.1055/a-1958-3876

“…These results might indicate that a high anaerobic power is more important for a high 400-m performance than a high aerobic capacity. The higher results of V Ȯ2 max and cLa max for the male runners compared with the female runners are in line with previous research and might be because of differences in muscle mass and muscle fiber distributions (19). In addition, because of the mathematical dependency (Eq (1)), the cLa max is affected by t 100 , which was higher for the female runners compared with the male runners (13.43 6 0.81 seconds and 11.86 6 0.46 seconds, respectively) resulting in lower cLa max for the female runners compared with the male runners.…”

Section: Discussionsupporting

confidence: 92%

Physiological and Locomotor Profiling Enables to Differentiate Between Sprinters, 400-m Runners, and Middle-Distance Runners

Thron,

Woll,

Doller

et al. 2024

Journal of Strength &Amp; Conditioning Research

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Thron, M, Woll, A, Doller, L, Quittmann, OJ, Härtel, S, Ruf, L, and Altmann, S. Physiological and locomotor profiling enables to differentiate between sprinters, 400-m runners, and middle-distance runners. J Strength Cond Res XX(X): 000–000, 2024—Different approaches exist for characterizing athletes, e.g., physiological and locomotor profiling. The aims of this study were to generate and compare physiological and locomotor profiles of male and female runners and to evaluate relationships between the different approaches. Thirty-four highly trained adolescent and young adult female and male athletes (n = 11 sprinters; n = 11,400-m runners; n = 12 middle-distance runners) performed two 100-m sprints on a running track to determine maximal sprinting speed (MSS) and maximal lactate accumulation rate (ċLamax). A cardiopulmonary exercise test was performed on a treadmill to determine maximal aerobic speed (MAS) and maximal oxygen uptake (V̇o 2max). Anaerobic speed reserve (ASR) was calculated as the difference between MSS and MAS. Group comparisons were conducted with a 2-way ANOVA (discipline × sex; p < 0.05) and Bonferroni post hoc tests and Cohen's d as effect size. Parameters were correlated by Pearson's correlation coefficients. Maximal aerobic speed and V̇o 2max were higher in 400-m and middle-distance runners compared with sprinters (p ≤ 0.02; −2.24 ≤ d ≤ −1.29). Maximal sprinting speed and ċLamax were higher in sprinters and 400-m runners compared with middle-distance runners (0.03 ≤ p ≤ 0.28; 0.73 ≤ d ≤ 1.23). Anaerobic speed reserve was highest in sprinters and lowest in middle-distance runners (p ≤ 0.03; 1.24 ≤ d ≤ 2.79). High correlations were found between ASR and MAS, MSS, and ċLamax (p < 0.01; −0.55 ≤ r ≤ 0.91) and between ċLamax and MSS (p < 0.01; r = 0.74). Our results indicate that athletes of different sprinting and running disciplines show differing physiological and locomotor profiles, and that the parameters of these approaches are related to each other. This can be of interest for assessing strengths and weaknesses (e.g., for talent identification) or training prescription in these disciplines.

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“…These items may be reported in the form of a checklist, as an in-text enumeration or in a sentence format. An example paragraph containing all the relevant information for the original data presented in this paper [ 34 , 35 ] would be: “We measured breath-by-breath data during the ramp tests with a ZAN 600 USB device (nSpire Health, Inc., Longmont, CO, United States of America). The unmodified raw data was filtered by using a low-pass forward-backward Butterworth filter (each filter: 3rd order, 0.04 Hz cut-off) implemented in the spiro package for R version 0.0.4 [ 36 ] .…”

Section: Discussionmentioning

confidence: 99%

“…Because of a miscalculation, the preregistration had incorrectly stated a number of 76 tests. The data were from previous research on the metabolic profile of endurance runners [ 34 , 35 ]. The tested individuals were experienced distance runners (15 female, 54 male; three of the male individuals participated in both studies).…”

Section: Methodsmentioning

confidence: 99%

“…The tested individuals were experienced distance runners (15 female, 54 male; three of the male individuals participated in both studies). The tests were conducted in March to September 2019 [ 34 ] and March to October 2021 [ 35 ], respectively, while using identical exercise protocols and test equipment. Participants ran on a treadmill (saturn 300/100; h/p/cosmos sports & medical 127 GmbH, Nussdorf-Traunstein, Germany) with 1% inclination for 8 min at a velocity of 2.8 m·s −1 as a warm-up.…”

Section: Methodsmentioning

confidence: 99%

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Data Processing Strategies to Determine Maximum Oxygen Uptake: A Systematic Scoping Review and Experimental Comparison with Guidelines for Reporting

Nolte,

Rein,

Quittmann

2023

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Background Gas exchange data from maximum oxygen uptake ($$\dot{V}{\text{O}}_{2\max }$$ V ˙ O 2 max ) testing typically require post-processing. Different processing strategies may lead to varying $$\dot{V}{\text{O}}_{2\max }$$ V ˙ O 2 max values affecting their interpretation. However, the exact processing strategies used in the literature have yet to be systematically investigated. Previous research investigated differences across methods at the group level only. Methods Out of a random sample, we investigated 242 recently published articles that measured $$\dot{V}{\text{O}}_{2\max }$$ V ˙ O 2 max during ramp tests. Reported data processing methods and their rationale were extracted. We compared the most common processing strategies on a data set of 72 standardized exercise tests in trained athletes. Results Half of the included studies did not report their data processing strategy and almost all articles failed to provide a rationale for the particular strategy chosen. Most studies use binned time averages to determine $$\dot{V}{\text{O}}_{2\max }$$ V ˙ O 2 max , with a minority using moving time or moving breath averages. The processing strategies found in the literature can lead to mean differences in $$\dot{V}{\text{O}}_{2\max }$$ V ˙ O 2 max of more than 5% (range 0–7%) with considerable variation at the individual level. Conclusions We advise researchers to change their processing strategy and use moving averages or digital filters instead of binned averages. Researchers should report their data processing strategy used to determine $$\dot{V}{\text{O}}_{2\max }$$ V ˙ O 2 max . We provide a reporting checklist of seven items that can function as a template for reporting.

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“…Many test procedures and physiological variables exist to judge the aerobic and anaerobic metabolic components involved in high‐intensity cycling. In recent years the post‐exercise level of capillary blood lactate accumulation has received increasing interest in order to calculate the glycolytic capacity in cycling (Adam et al., 2015; Dunst et al., 2023; Quittmann, Abel, et al., 2021; Quittmann, Schwarz, et al., 2021; Yang et al., 2023), hand‐cycling (Quittmann, Abel, et al., 2021; Quittmann et al., 2018) and other endurance sports including running (Quittmann et al., 2022; Quittmann, Appelhans, et al., 2020; Quittmann, Schwarz, et al., 2021), swimming (Mavroudi et al., 2023; Teixeira et al., 2022) and rowing (Schünemann et al., 2023). In this regard the peak accumulation of capillary blood lactate within 10 min after a 15‐s all‐out sprint (often abbreviated as νLa max ) has been widely discussed among athletes and within the coaching community as a feasible indicator to calculate the glycolytic capacity during sprint cycling (note: here νLa max is preferred over “ċLa max ” due to its established recognition) (Heck & Schulz, 2002; Mader, 2003; Mader & Heck, 1986; Quittmann et al., 2022).…”

Section: Introductionmentioning

confidence: 99%

Reliability of power output, maximal rate of capillary blood lactate accumulation, and phosphagen contribution time following 15‐s sprint cycling in amateur cyclists

Meixner,

Nusser,

Koehler

et al. 2024

Physiological Reports

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Based on Mader's mathematical model, the rate of capillary blood lactate concentration (νLamax) following intense exercise is thought to reflect the maximal glycolytic rate. We aimed to investigate the reliability of important variables of Mader's model (i.e. power output, lactate accumulation, predominant phosphagen contribution time frames (tPCr)) and resulting νLamax values derived during and after a 15‐s cycling sprint. Fifty cyclists performed a 15‐s all‐out sprint test on a Cyclus2 ergometer three times. The first sprint test was considered a familiarization trial. Capillary blood was sampled before and every minute (for 8 min) after the sprint to determine νLamax. Test–retest analysis between T2 and T3 revealed excellent reliability for power output (Pmean and Ppeak; ICC = 0.99, 0.99), ∆La and νLamax with tPCr of 3.5 s (ICC = 0.91, 0.91). νLamax calculated with tPCr = tPpeak (ICC = 0.87) and tPCr = tPpeak–3.5% (ICC = 0.79) revealed good reliability. tPpeak and tPpeak–3.5% revealed only poor and moderate reliability (ICC = 0.41, 0.52). Power output and ∆La are reliable parameters in the context of this test. Depending on tPCr, reliability of νLamax varies considerably with tPCr of 3.5 s showing excellent reliability. We recommend standardization of this type of testing especially tPCr.

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Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?

Cited by 4 publications

References 67 publications

Physiological and Locomotor Profiling Enables to Differentiate Between Sprinters, 400-m Runners, and Middle-Distance Runners

Physiological and Locomotor Profiling Enables to Differentiate Between Sprinters, 400-m Runners, and Middle-Distance Runners

Data Processing Strategies to Determine Maximum Oxygen Uptake: A Systematic Scoping Review and Experimental Comparison with Guidelines for Reporting

Reliability of power output, maximal rate of capillary blood lactate accumulation, and phosphagen contribution time following 15‐s sprint cycling in amateur cyclists

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