Functional Threshold Power Is Not Equivalent to Lactate Parameters in Trained Cyclists

Owen Jeffries; Richard Simmons; Stephen D. Patterson; Mark Waldron

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Functional Threshold Power Is Not Equivalent to Lactate Parameters in Trained Cyclists

Owen Jeffries ^[1] ; Richard Simmons ^[3] ; Stephen D. Patterson ^[3] ; Mark Waldron ^[2]
1. [1] Newcastle University
  
  Newcastle University
  
  Reino Unido
2. [2] University of New England
  
  University of New England
  
  Australia
3. [3] School of Sport, Health and Applied Science, St Mary's University, London, United Kingdom
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Localización: Journal of strength and conditioning research: The Official Research Journal of the NSCA, ISSN 1064-8011, Vol. 35, Nº. 10, 2021, págs. 2790-2794
Idioma: inglés
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Resumen
- Functional threshold power (FTP) is derived from a maximal self-paced 20-minute cycling time trial whereby the average power output is scaled by 95%. However, the physiological basis of the FTP concept is unclear. Therefore, we evaluated the relationship of FTP with a range of laboratory-based blood lactate parameters derived from a submaximal threshold test. Twenty competitive male cyclists completed a maximal 20-minute time trial and an incremental exercise test to establish a range of blood lactate parameters. Functional threshold power (266 +/- 42 W) was strongly correlated (r = 0.88, p < 0.001) with the power output associated with a fixed blood lactate concentration 4.0 mmol[middle dot]L-1 (LT4.0) (268 +/- 30 W) and not significantly different (p > 0.05). While mean bias was 2.9 +/- 24.6 W, there were large limits of agreement (LOA) between FTP and LT4.0 (-45 to 51 W). All other lactate parameters, lactate threshold (LT) (236 +/- 32 W), individual anaerobic threshold (244 +/- 33 W), and LT thresholds determined using the Dmax method (221 +/- 25 W) and modified Dmax method (238 +/- 32 W) were significantly different from FTP (p < 0.05). While FTP strongly correlated with LT4.0, the large LOA refutes any equivalence as a measure with physiological basis. Therefore, we would encourage athletes and coaches to use alternative field-based methods to predict cycling performance.