The Critical Power Model as a Potential Tool for Anti-doping.

Michael J Puchowicz,Michael S Koehle,David C Clarke,Nathan E Townsend,Assaf Yogev,Eliran Mizelman

doi:10.3389/fphys.2018.00643

Abstract

Existing doping detection strategies rely on direct and indirect biochemical measurement methods focused on detecting banned substances, their metabolites, or biomarkers related to their use. However, the goal of doping is to improve performance, and yet evidence from performance data is not considered by these strategies. The emergence of portable sensors for measuring exercise intensities and of player tracking technologies may enable the widespread collection of performance data. How these data should be used for doping detection is an open question. Herein, we review the basis by which performance models could be used for doping detection, followed by critically reviewing the potential of the critical power (CP) model as a prototypical performance model that could be used in this regard. Performance models are mathematical representations of performance data specific to the athlete. Some models feature parameters with physiological interpretations, changes to which may provide clues regarding the specific doping method. The CP model is a simple model of the power-duration curve and features two physiologically interpretable parameters, CP and W′. We argue that the CP model could be useful for doping detection mainly based on the predictable sensitivities of its parameters to ergogenic aids and other performance-enhancing interventions. However, our argument is counterbalanced by the existence of important limitations and unresolved questions that need to be addressed before the model is used for doping detection. We conclude by providing a simple worked example showing how it could be used and propose recommendations for its implementation.

Highlights

Athletes have long used exogenous substances to enhance performance for personal gain (McHugh et al, 2005)
Inspection of the parameter estimates revealed that the W and CP estimates for “clean” year 2006 both fell within the 99% interval, while the CP but not W fell outside the interval in the 2007 “doped” year (Figures 3D,E)
We reviewed the potential of the CP model for use in anti-doping

Summary

Introduction

Athletes have long used exogenous substances to enhance performance for personal gain (McHugh et al, 2005). The original strategy of doping detection was to detect evidence of banned substances by assaying biological fluids for illicit substances or their metabolites. Critical Power Model in Anti-doping detection methods have advantages, they are limited in important ways, especially for substances that are synthetic versions of naturally occurring endogenous hormones such as growth hormone (McHugh et al, 2005) and erythropoietin (EPO) (Pascual et al, 2004). Indirect detection methods, which test for the biological effects of the substance rather than the substance itself, have shown both promise and limitations for detecting blood doping and exogenous EPO use. One strategy is to infer doping based on performance per se, which is sensible given that the within-subject coefficient of variation in performance is relatively low for elite athletes (Malcata and Hopkins, 2014), and performance is the outcome that athletes are attempting to manipulate

Methods

Results

Conclusion