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

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.

Methodological Approaches and Related Challenges Associated With the Determination of Critical Power and Curvature Constant

“…Moreover, the combination of CS and the running equivalent of W' (D') predicts 5000-m running performance within 1% (85). Finally, with the advantages of the aforementioned applications, it is not surprising that the P-T relationship has been used to evaluate and monitor performance, and proposed as a tool for anti-doping (37,93,116).…”

“…(93,105,107). Nonetheless, the test-retest reliability seems to be poorer for W' than CP using other methodological approaches (e.g.…”

Technological capability of doping control laboratories: a metric proposal

“…The first cases of doping were detected with a lapse of 25 years after the first use of anabolic steroids (de Rose 1989). Scientists around the world have been developing studies to strengthen detection methods and techniques so that the time between the emergence of a new substance or method and its detection is as short as possible and may in some cases be reduced to weeks (Puchowicz et al 2018). This imposes an even greater scientific challenge, given the complexity of anti-doping tests, and the economic interests at stake, both from the perspective of sponsors and athletes, who in some cases are veritable pop stars.…”

Annual banned‐substance review: Analytical approaches in human sports drug testing

“…Consequently, additional information of an analytical/chemical nature as well as from complementary sources such as performance profiles have received growing attention, and especially the concept of an athlete performance passport has been the subject of intense debate . Here (potential) benefits (eg, the possibility of identifying atypical changes in the athlete's performance triggering target testing) as well as yet unresolved and unaddressed questions (eg, accuracy and validity of collected performance data, environmental factors) have been discussed …”

“…27 Here (potential) benefits (eg, the possibility of identifying atypical changes in the athlete's performance triggering target testing) as well as yet unresolved and unaddressed questions (eg, accuracy and validity of collected performance data, environmental factors) have been discussed. [28][29][30][31][32] In continuation of previous editions, 33 advances in and contributions to analytical means for human sports drug testing published over the past 12 months are evaluated in this annual banned-substance review, with a focus on substances and methods of doping as detailed in the WADA Prohibited List of 2018. 34 The 2018 version of the Prohibited List was modified compared to the 2017 edition and is now composed of only 11 classes of banned substances (S0-S9 plus P1) and three categories of prohibited methods (M1-M3) after "Alcohol" (formerly "P1") was removed ( Table 1) monitoring program continued to cover the in-competition use of the stimulants bupropion, caffeine, nicotine, phenylephrine, phenylpropanolamine, pipradrol, and synephrine, and the narcotic analgesics codeine, hydrocodone, and tramadol.…”