Literature DB >> 36114839

Anaerobic work capacity in cycling: the effect of computational method.

Erik P Andersson1,2, Philipp Bachl3,4, Anna Schmuttermair4, Craig A Staunton3, Thomas L Stöggl4,5.   

Abstract

PURPOSE: To compare the anaerobic work capacity (AnWC, i.e., attributable anaerobic mechanical work) assessed using four different approaches/models applied to time-trial (TT) cycle-ergometry exercise.
METHODS: Fifteen male cyclists completed a 7 × 4-min submaximal protocol and a 3-min all-out TT (TTAO). Linear relationships between power output (PO) and submaximal metabolic rate were constructed to estimate TT-specific gross efficiency (GE) and AnWC, using either a measured resting metabolic rate as a Y-intercept (7 + YLIN) or no measured Y-intercept (7-YLIN). In addition, GE of the last submaximal bout (GELAST) was used to estimate AnWC, and critical power (CP) from TTAO (CP3´AO) was used to estimate mechanical work above CP (W', i.e., "AnWC").
RESULTS: Average PO during TTAO was 5.43 ± 0.30 and CP was 4.48 ± 0.23 W∙kg-1. The TT-associated GE values were ~ 22.0% for both 7 + YLIN and 7-YLIN and ~ 21.1% for GELAST (both P < 0.001). The AnWC were 269 ± 60, 272 ± 55, 299 ± 61, and 196 ± 52 J∙kg-1 for the 7 + YLIN, 7-YLIN, GELAST, and CP3´AO models, respectively (7 + YLIN and 7-YLIN versus GELAST, both P < 0.001; 7 + YLIN, 7-YLIN, and GELAST versus CP3´AO, all P < 0.01). For the three pair-wise comparisons between 7 + YLIN, 7-YLIN, and GELAST, typical errors in AnWC values ranged from 7 to 11 J∙kg-1, whereas 7 + YLIN, 7-YLIN, and GELAST versus CP3´AO revealed typical errors of 55-59 J∙kg-1.
CONCLUSION: These findings demonstrate a substantial disagreement in AnWC between CP3´AO and the other models. The 7 + YLIN and 7-YLIN generated 10% lower AnWC values than the GELAST model, whereas 7 + YLIN and 7-YLIN generated similar values of AnWC.
© 2022. The Author(s).

Entities:  

Keywords:  All-out pacing; Maximal accumulated oxygen deficit method; Metabolic demand; Reliability; Supramaximal exercise; Time trial

Year:  2022        PMID: 36114839     DOI: 10.1007/s00421-022-05038-7

Source DB:  PubMed          Journal:  Eur J Appl Physiol        ISSN: 1439-6319            Impact factor:   3.346


  38 in total

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Authors:  J M Bland; D G Altman
Journal:  Stat Methods Med Res       Date:  1999-06       Impact factor: 3.021

2.  Validity of the two-parameter model in estimating the anaerobic work capacity.

Authors:  J Dekerle; G Brickley; A J P Hammond; J S M Pringle; H Carter
Journal:  Eur J Appl Physiol       Date:  2005-11-01       Impact factor: 3.078

3.  A 3-min all-out test to determine peak oxygen uptake and the maximal steady state.

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Review 4.  Respiratory muscle perfusion and energetics during exercise.

Authors:  J A Dempsey; C A Harms; D M Ainsworth
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5.  Predicting Critical Power in Elite Cyclists: Questioning the Validity of the 3-Minute All-Out Test.

Authors:  Jason C Bartram; Dominic Thewlis; David T Martin; Kevin I Norton
Journal:  Int J Sports Physiol Perform       Date:  2016-11-11       Impact factor: 4.010

6.  An approach to estimating gross efficiency during high-intensity exercise.

Authors:  Jos J de Koning; Dionne A Noordhof; Tom P Uitslag; Rianna E Galiart; Christopher Dodge; Carl Foster
Journal:  Int J Sports Physiol Perform       Date:  2012-09-19       Impact factor: 4.010

7.  Unwarranted manipulation of the critical power concept: response to Dr. Burnley.

Authors:  Raffy Dotan
Journal:  Eur J Appl Physiol       Date:  2022-05-22       Impact factor: 3.078

8.  Laboratory-Based Factors Predicting Skiing Performance in Female and Male Biathletes.

Authors:  Marko S Laaksonen; Erik Andersson; Malin Jonsson Kårström; Hampus Lindblom; Kerry McGawley
Journal:  Front Sports Act Living       Date:  2020-08-05

9.  A Comparison between Different Methods of Estimating Anaerobic Energy Production.

Authors:  Erik P Andersson; Kerry McGawley
Journal:  Front Physiol       Date:  2018-02-08       Impact factor: 4.566

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