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

Endurance running performance can be predicted by maximal oxygen uptake (V̇O (2) max), the fractional utilisation of oxygen uptake (%V̇O (2) max) and running economy at lactate threshold (RE (OBLA) ). This study aims to assess maximal lactate accumulation rate (ċLa (max) ) in terms of improving runn...

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Autores principales: Quittmann, Oliver Jan, Foitschik, Tina, Vafa, Ramin, Freitag, Finn Jannis, Sparmann, Nordin, Nolte, Simon, Abel, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Georg Thieme Verlag 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072929/
https://www.ncbi.nlm.nih.gov/pubmed/36529130
http://dx.doi.org/10.1055/a-1958-3876
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author Quittmann, Oliver Jan
Foitschik, Tina
Vafa, Ramin
Freitag, Finn Jannis
Sparmann, Nordin
Nolte, Simon
Abel, Thomas
author_facet Quittmann, Oliver Jan
Foitschik, Tina
Vafa, Ramin
Freitag, Finn Jannis
Sparmann, Nordin
Nolte, Simon
Abel, Thomas
author_sort Quittmann, Oliver Jan
collection PubMed
description Endurance running performance can be predicted by maximal oxygen uptake (V̇O (2) max), the fractional utilisation of oxygen uptake (%V̇O (2) max) and running economy at lactate threshold (RE (OBLA) ). This study aims to assess maximal lactate accumulation rate (ċLa (max) ) in terms of improving running performance prediction in trained athletes. Forty-four competitive female and male runners/triathletes performed an incremental step test, a 100-m sprint test and a ramp test to determine their metabolic profile. Stepwise linear regression was used to predict 5000-m time trial performance. Split times were recorded every 200-m to examine the ‘finishing kick’. Females had a slower t (5k) and a lower V̇O (2) max, ċLa (max) , ‘finishing kick’ and RE (OBLA) . Augmenting Joyner’s model by means of ċLa (max) explained an additional 4.4% of variance in performance. When performing the same analysis exclusively for males, ċLa (max) was not included. ċLa (max) significantly correlated with %V̇O (2) max (r=-0.439, p=0.003) and the ‘finishing kick’ (r=0.389, p=0.010). ċLa (max) allows for significant (yet minor) improvements in 5000-m performance prediction in a mixed-sex group. This margin of improvement might differ in middle-distance events. Due to the relationship to the ‘finishing kick’, ċLa (max) might be related to individual pacing strategies, which should be assessed in future research.
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spelling pubmed-100729292023-04-05 Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running? Quittmann, Oliver Jan Foitschik, Tina Vafa, Ramin Freitag, Finn Jannis Sparmann, Nordin Nolte, Simon Abel, Thomas Int J Sports Med Endurance running performance can be predicted by maximal oxygen uptake (V̇O (2) max), the fractional utilisation of oxygen uptake (%V̇O (2) max) and running economy at lactate threshold (RE (OBLA) ). This study aims to assess maximal lactate accumulation rate (ċLa (max) ) in terms of improving running performance prediction in trained athletes. Forty-four competitive female and male runners/triathletes performed an incremental step test, a 100-m sprint test and a ramp test to determine their metabolic profile. Stepwise linear regression was used to predict 5000-m time trial performance. Split times were recorded every 200-m to examine the ‘finishing kick’. Females had a slower t (5k) and a lower V̇O (2) max, ċLa (max) , ‘finishing kick’ and RE (OBLA) . Augmenting Joyner’s model by means of ċLa (max) explained an additional 4.4% of variance in performance. When performing the same analysis exclusively for males, ċLa (max) was not included. ċLa (max) significantly correlated with %V̇O (2) max (r=-0.439, p=0.003) and the ‘finishing kick’ (r=0.389, p=0.010). ċLa (max) allows for significant (yet minor) improvements in 5000-m performance prediction in a mixed-sex group. This margin of improvement might differ in middle-distance events. Due to the relationship to the ‘finishing kick’, ċLa (max) might be related to individual pacing strategies, which should be assessed in future research. Georg Thieme Verlag 2022-12-18 /pmc/articles/PMC10072929/ /pubmed/36529130 http://dx.doi.org/10.1055/a-1958-3876 Text en The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/). https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
spellingShingle Quittmann, Oliver Jan
Foitschik, Tina
Vafa, Ramin
Freitag, Finn Jannis
Sparmann, Nordin
Nolte, Simon
Abel, Thomas
Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?
title Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?
title_full Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?
title_fullStr Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?
title_full_unstemmed Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?
title_short Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?
title_sort is maximal lactate accumulation rate promising for improving 5000-m prediction in running?
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072929/
https://www.ncbi.nlm.nih.gov/pubmed/36529130
http://dx.doi.org/10.1055/a-1958-3876
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