Prediction of Exercise Tolerance in the Severe and Extreme Intensity Domains by a Critical Power Model.

This study aimed to assess the predictive capability of different critical power (CP) models on cycling exercise tolerance in the severe- and extreme-intensity domains. Nineteen cyclists (age: 23.0 ± 2.7 y) performed several time-to-exhaustion tests (Tlim) to determine CP, finite work above CP (W'), and the highest constant work rate at which maximal oxygen consumption was attained (I_HIGH). Hyperbolic power-time, linear power-inverse of time, and work-time models with three predictive trials were used to determine CP and W'. Modeling with two predictive trials of the CP work-time model was also used to determine CP and W'. Actual exercise tolerance of I_HIGH and intensity 5% above I_HIGH (I_HIGH+5%) were compared to those predicted by all CP models. Actual I_HIGH (155 ± 30 s) and I_HIGH+5% (120 ± 26 s) performances were not different from those predicted by all models with three predictive trials. Modeling with two predictive trials overestimated Tlim at I_HIGH+5% (129 ± 33 s; p = 0.04). Bland-Altman plots of I_HIGH+5% presented significant heteroscedasticity by all CP predictions, but not for I_HIGH. Exercise tolerance in the severe and extreme domains can be predicted by CP derived from three predictive trials. However, this ability is impaired within the extreme domain.