Is the Functional Threshold Power Interchangeable With the Maximal Lactate Steady State in Trained Cyclists?

in International Journal of Sports Physiology and Performance
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Purpose: Functional threshold power (FTP), determined as 95% of the average power during a 20-min time trial, is suggested as a practical test for the determination of the maximal lactate steady state (MLSS) in cycling. Therefore, the objective of the present study was to determine the validity of FTP in predicting MLSS. Methods: A total of 15 cyclists, 7 classified as trained and 8 as well trained (mean [SD] maximal oxygen uptake 62.3 [6.4] mL·kg−1·min−1, maximal aerobic power 329 [30] W), performed an incremental test to exhaustion, an FTP test, and several constant-load tests to determine the MLSS. The bias ± 95% limits of agreement (LoA), typical error of the estimate (TEE), and Pearson coefficient of correlation (r) were calculated to assess validity. Results: For the power-output measures, FTP presented a bias ± 95% LoA of 1.4% ± 9.2%, a moderate TEE (4.7%), and nearly perfect correlation (r = .91) with MLSS in all cyclists together. When divided by training level, the bias ± 95% LoA and TEE were higher in the trained group (1.4% ± 11.8% and 6.4%, respectively) than in the well-trained group (1.3% ± 7.4% and 3.0%, respectively). For the heart-rate measurement, FTP presented a bias ± 95% LoA of −1.4% ± 8.2%, TEE of 4.0%, and very large correlation (r = .80) with MLSS. Conclusion: Therefore, trained and well-trained cyclists can use FTP as a noninvasive and practical alternative to estimate MLSS.

The authors are with the Human Performance Research Group, Center for Health and Sport Sciences, Santa Catarina State University, Florianópolis, Brazil.

Costa (vitor.costa@udesc.br) is corresponding author.
  • 1.

    Faude O, Kindermann W, Meyer T. Lactate threshold concepts: how valid are they? Sports Med. 2009;39(6):469–490. doi:10.2165/00007256-200939060-00003

  • 2.

    Beneke R. Methodological aspects of maximal lactate steady state—implications for performance testing. Eur J Appl Physiol. 2003;89(1):95–99. PubMed ID: 12627312 doi:10.1007/s00421-002-0783-1

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Beneke R, Leithäuser RM, Ochentel O. Blood lactate diagnostics in exercise testing and training. Int J Sports Physiol Perform. 2011;6(1):8–24. PubMed ID: 21487146 doi:10.1123/ijspp.6.1.8

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Allen H, Coggan A. Training and Racing With a Power Meter. 2nd ed. Boulder, CO: Velopress; 2010.

  • 5.

    Baron B, Noakes TD, Dekerle J, et al. Why does exercise terminate at the maximal lactate steady state intensity? Br J Sports Med. 2008;42(10):528–533. doi:10.1136/bjsm.2007.040444

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Faude O, Hecksteden A, Hammes D, et al. Reliability of time-to-exhaustion and selected psycho-physiological variables during constant-load cycling at the maximal lactate steady-state. Appl Physiol Nutr Metab. 2017;42(2):142–147. PubMed ID: 28128633 doi:10.1139/apnm-2016-0375

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Teixeira AS, Grossl T, De Lucas RD, Guglielmo LGA. Cardiorespiratory response and energy expenditure during exercise at maximal lactate steady state. Rev Bras Cineantropometria e Desempenho Hum. 2014;16(2):212–222. doi:10.5007/1980-0037.2014v16n2p212

    • Search Google Scholar
    • Export Citation
  • 8.

    Grossl T, de Lucas RD, de Souza KM, Guglielmo LGA. Time to exhaustion at intermittent maximal lactate steady state is longer than continuous cycling exercise. Appl Physiol Nutr Metab. 2012;37(6):1047–1053. PubMed ID: 22891876 doi:10.1139/h2012-088

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Harnish CR, Swensen TC, Pate RR. Methods for estimating the maximal lactate steady state in trained cyclists. Med Sci Sports Exerc. 2001;33(6):1052–1055. doi:10.1097/00005768-200106000-00027

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    Campbell CSG, Souza WH, Ferreira JN, Assenço F, Simões HG. Prediction of maximal lactate steady state velocity based on performance in a 5 km cycling test. Rev Bras Cineantropometria e Desempenho Hum. 2007;9(3):223–230.

    • Search Google Scholar
    • Export Citation
  • 11.

    Borszcz FK, Tramontin AF, Bossi AH, Carminatti LJ, Costa VP. Functional threshold power in cyclists: validity of the concept and physiological responses. Int J Sports Med. 2018;39(10):737–742. PubMed ID: 29801189 doi:10.1055/s-0044-101546

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Valenzuela PL, Morales JS, Foster C, Lucia A, de la Villa P. Is the functional threshold power a valid surrogate of the lactate threshold?. Int J Sports Physiol Perform. 2018;13(10):1293–1298. doi:10.1123/ijspp.2018-0008

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    Sanders D, Taylor RJ, Myers T, Akubat I. A field-based cycling test to assess predictors of endurance performance and establishing training zones [published online ahead of print May 25, 2017]. J Strength Cond Res. doi:10.1519/JSC.0000000000001910

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Borszcz FK, Tramontin AF, de Souza KM, Carminatti LJ, Costa VP. Physiological correlations with short, medium, and long cycling time-trial performance. Res Q Exerc Sport. 2018;89(1):120–125. PubMed ID: 29334005 doi:10.1080/02701367.2017.1411578

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Heck H, Beneke R. 30 jahre laktatschwellen–was bleibt zu tun? [30 years of lactate thresholds—what remains to be done?] Dtsch Zeitschirft Für Sport. 2008;59(12):297–302

    • Search Google Scholar
    • Export Citation
  • 16.

    Arratibel-Imaz I, Calleja-González J, Emparanza JI, Terrados N, Mjaanes JM, Ostojic SM. Lack of concordance amongst measurements of individual anaerobic threshold and maximal lactate steady state on a cycle ergometer. Phys Sportsmed. 2016;44(1):34–45. PubMed ID: 26578151 doi:10.1080/00913847.2016.1122501

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    De Pauw K, Roelands B, Cheung SS, de Geus B, Rietjens G, Meeusen R. Guidelines to classify subject groups in sport-science research. Int J Sports Physiol Perform. 2013;8(2):111–122. PubMed ID: 23428482 doi:10.1123/ijspp.8.2.111

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18.

    Abbiss CR, Quod MJ, Levin G, Martin DT, Laursen PB. Accuracy of the Velotron ergometer and SRM power meter. Int J Sports Med. 2009;30(2):107–112. PubMed ID: 19177315 doi:10.1055/s-0028-1103285

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Kuipers H, Verstappen F, Keizer H, Geurten P, van Kranenburg G. Variability of aerobic performance in the laboratory and its physiologic correlates. Int J Sports Med. 1985;6(4):197–201. PubMed ID: 4044103 doi:10.1055/s-2008-1025839

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 20.

    Currell K, Jeukendrup AE. Validity, reliability and sensitivity of measures of sporting performance. Sports Med. 2008;38(4):297–316. doi:10.2165/00007256-200838040-00003

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Hopkins WG. Spreadsheets for analysis of validity and reliability. Sportscience. 2015;19:36–42.

  • 22.

    Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41(1):3–13. doi:10.1249/MSS.0b013e31818cb278

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Cohen J. Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum; 1986.

  • 24.

    Bland MJ, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;327(8476):307–310. doi:10.1016/S0140-6736(86)90837-8

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25.

    Smith TB, Hopkins WG. Variability and predictability of finals times of elite rowers. Med Sci Sports Exerc. 2011;43(11):2155–2160. doi:10.1249/MSS.0b013e31821d3f8e

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Jeukendrup A, Van Diemen A. Heart rate monitoring during training and competition in cyclists. J Sports Sci. 1998;16(suppl 1):91–99. doi:10.1080/026404198366722

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27.

    Pringle JSM, Jones AM. Maximal lactate steady state, critical power and EMG during cycling. Eur J Appl Physiol. 2002;88(3):214–226. PubMed ID: 12458364 doi:10.1007/s00421-002-0703-4

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Grossl T, De Lucas RD, De Souza KM, Antonacci Guglielmo LG. Maximal lactate steady-state and anaerobic thresholds from different methods in cyclists. Eur J Sport Sci. 2012;12(2):161–167. doi:10.1080/17461391.2010.551417

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29.

    Pallarés JG, Morán-Navarro R, Ortega JF, Fernánndez-Elías VE, Mora-Rodriguez R. Validity and reliability of ventilatory and blood lactate thresholds in well-trained cyclists. PLoS ONE. 2016;11(9):e0163389. doi:10.1371/journal.pone.0163389

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Smekal G, Von Duvillard SP, Pokan R, et al. Blood lactate concentration at the maximal lactate steady state is not dependent on endurance capacity in healthy recreationally trained individuals. Eur J Appl Physiol. 2012;112(8):3079–3086. PubMed ID: 22194004 doi:10.1007/s00421-011-2283-7

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Hauser T, Adam J, Schulz H. Comparison of selected lactate threshold parameters with maximal lactate steady state in cycling. Int J Sports Med. 2013;35(6):517–521. doi:10.1055/s-0033-1353176

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 32.

    Mattioni Maturana F, Keir DA, McLay KM, Murias JM. Can measures of critical power precisely estimate the maximal metabolic steady-state? Appl Physiol Nutr Metab. 2016;41(11):1197–1203. PubMed ID: 27819154 doi:10.1139/apnm-2016-0248

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33.

    Keir DA, Fontana FY, Robertson TC, et al. Exercise intensity thresholds: identifying the boundaries of sustainable performance. Med Sci Sports Exerc. 2015;47(9):1932–1940. doi:10.1249/MSS.0000000000000613

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Nimmerichter A, Williams C, Bachl N, Eston R. Evaluation of a field test to assess performance in elite cyclists. Int J Sports Med. 2010;31(3):160–166. PubMed ID: 20221996 doi:10.1055/s-0029-1243222

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35.

    Karsten B, Jobson SA, Hopker J, Stevens L, Beedie C. Validity and reliability of critical power field testing. Eur J Appl Physiol. 2015;115(1):197–204. PubMed ID: 25260244 doi:10.1007/s00421-014-3001-z

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36.

    MacInnis MJ, Thomas ACQ, Phillips SM. The reliability of 4-minute and 20-minute time trials and their relationships to functional threshold power in trained cyclists. Int J Sports Physiol Perform. 2019;14(1):38–45. doi:10.1123/ijspp.2018-0100

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 37.

    de Souza KM, de Lucas RD, do Nascimento Salvador PC, et al. Maximal power output during incremental cycling test is dependent on the curvature constant of the power–time relationship. Appl Physiol Nutr Metab. 2015;40(9):895–898. doi:10.1139/apnm-2015-0090

    • Crossref
    • Search Google Scholar
    • Export Citation
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