Critical oxygenation: Can muscle oxygenation inform us about critical power?

Feldmann, Andri; Erlacher, Daniel (2021). Critical oxygenation: Can muscle oxygenation inform us about critical power? Medical hypotheses, 150, p. 110575. Elsevier 10.1016/j.mehy.2021.110575

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The power-duration relationship is well documented for athletic performance and is formulated out mathematically
in the critical power (CP) model. The CP model, when applied properly, has great predictive power, e.
g. pedaling at a specific power output on an ergometer the model precisely calculates the time over which an
athlete can sustain this power. However, CP presents physiological inconsistencies and process-oriented problems.
The rapid development of near-infrared spectroscopy (NIRS) to measure muscle oxygenation (SmO2) dynamics
provides a physiological exploration of the CP model on a conceptual and empirical level. Conceptually,
the CP model provides two components: first CP is defined as the highest metabolic rate that can be achieved
through oxidative means. And second, work capacity above CP named W’. SmO2 presents a steady-state in oxygen
supply and demand and thereby represents CP specifically at a local level of analysis. Empirically,
exploratory data quickly illustrates the relationship between performance and SmO2, as shown during 3-min allout
cycling tests to assess CP. During these tests, performance and SmO2 essentially mirror each other, and both
CP and W’ generate solid correlation with what would be deemed their SmO2 counterparts: first, the steady-state
of SmO2 correlates with CP. And second, the tissue oxygen reserve represented in SmO2, when calculated as an
integral corresponds to W’. While the empirical data presented is preliminary, the proposition of a concurring
physiological model to the current CP model is a plausible inference. Here we propose that SmO2 steady-state
representing CP as critical oxygenation or CO. And the tissue oxygen reserve above CO would then be identified
as O’. This new CO model could fill in the physiological gap between the highly predictive CP model and at
times its inability to track human physiology consistently. For simplicity’s sake, this would include acute changes
in physiology as a result of changing climate or elevation with travel, which can affect performance. These types
of acute fluctuations, but not limited to, would be manageable when applying a CO model in conjunction with
the CP model. Further, modeling is needed to investigate the true potential of NIRS to model CP, with a focus on
repeatability, recovery, and systemic vs local workloads.

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