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Functional Threshold Power Is Not Equivalent to Lactate Parameters in Trained Cyclists
Owen Jeffries1, Richard Simmons2, Stephen D Patterson2
1School of Biomedical Sciences, Newcastle University, Newcastle Upon Tyne, United Kingdom.
Journal of Strength and Conditioning Research
|July 4, 2019
Summary
Functional threshold power (FTP) is not equivalent to lactate measurements in cyclists. While FTP correlates with a 4.0 mmol·L-1 blood lactate level, wide agreement limits show they are not interchangeable for performance prediction.
Area of Science:
- Sports Science
- Exercise Physiology
- Cycling Performance
Background:
- Functional threshold power (FTP) is a common field test metric for cyclists.
- The physiological underpinnings of FTP and its relationship to established lactate parameters are not fully understood.
Purpose of the Study:
- To investigate the relationship between FTP and various laboratory-derived blood lactate parameters in trained cyclists.
- To determine if FTP can be considered physiologically equivalent to specific lactate-based thresholds.
Main Methods:
- Twenty competitive male cyclists completed a maximal 20-minute time trial to determine FTP.
- An incremental exercise test was performed to measure blood lactate concentrations and derive various lactate parameters (LT, individual anaerobic threshold, LT4.0, Dmax, modified Dmax).
Main Results:
- FTP showed a strong correlation (r = 0.88) with the power output at 4.0 mmol·L-1 blood lactate (LT4.0) and was not significantly different (mean bias 2.9 ± 24.6 W).
- However, large limits of agreement (-45 to 51 W) were observed between FTP and LT4.0, indicating significant individual variability.
- All other lactate parameters (LT, individual anaerobic threshold, Dmax methods) were significantly different from FTP.
Conclusions:
- While FTP correlates with LT4.0, the substantial limits of agreement suggest they are not interchangeable measures for assessing cycling performance.
- Athletes and coaches should consider alternative field-based methods for predicting cycling performance due to the physiological discrepancies.
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