Prediction of Functional Threshold Power from Graded Exercise Test Data in Highly-Trained Individuals.

The purpose of the current investigation was to derive an equation that could predict Functional Threshold Power (FTP) from Graded Exercise Test (GxT) data. The FTP test has been demonstrated to represent the highest cycling power output that can be maintained in a quasi-steady state for 60-min. Previous investigations to determine a comparable marker derived from a Graded Exercise test have had limited success to date. Consequently, the current study aimed to predict FTP from GxT data to provide an additional index of cycling performance. FTP has been reported to provide an insight not provided by a GxT and, in addition, does not require a formal exercise testing facility. The study design facilitated a deliberate and transparent sequence of statistical decisions, resolved in part from the perspective of exercise physiology. Seventy triathletes (male n=50, female n=20) completed cycling GxT and FTP tests in sequential order. Collected data (power output, blood lactate indices, VO2peak, body mass) were analysed using stepwise regression to identify the key parameters for predicting FTP, and confirmed using a Leave One Out (LOO) cross-validation. As a consequence of wittingly including some likely transiently highly correlated parameters on the basis of a physiological argument, the model's function is limited to predicting FTP. This investigation concluded the model (FTP = -6.62 + 0.32 FBLC-4 + 0.42 BM + 0.46 Pmax) was the prediction model of choice.