Key result
Standard V˙O2peak prediction equations from general populations perform poorly in competitive endurance athletes.
Why the study?
Commonly used VO2peak prediction equations derived from general population cohorts perform poorly among competitive endurance athletes.
Do newly derived V˙O2peak prediction equations improve accuracy compared to general population equations in endurance athletes?
Cohort (n=272)
Do newly derived V˙O2peak prediction equations improve accuracy compared to general population equations in endurance athletes?
Newly derived CPET reference values and V˙O2peak prediction equations specifically for endurance athletes improve accuracy over standard equations, preventing significant underestimation of fitness in this population.
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Captured external expert commentary on this paper, strongest first. Original sources are linked where available.
“The sessions emphasized the importance of using normative values derived in cohorts of athletes because supranormal values are the baseline for endurance athletes.”
Caution advised with general population VO2peak equations in endurance athletes; leaves open utility of tailored references to improve CPET accuracy.
AIMS: Accurate interpretation of cardiopulmonary exercise testing (CPET) relies on age, gender, and exercise modality-specific reference values. To date, clinically applicable CPET reference values derived from a source population of endurance athletes (EAs) have been lacking. The purpose of this study was to generate CPET reference values for use in the clinical assessment of EA. METHODS AND RESULTS: Prospective data accrued during the clinical care of healthy EA were used to derive CPET reference values and to develop novel equations for V˙O2peak. The performance of these equations was compared to the contemporary standard of care equations and assessed in a discrete EA validation cohort. A total of 272 EA (age = 42 ± 15 years, female = 31%, V˙O2peak = 3.6 ± 0.83 L/min) met inclusion criteria and comprised the derivation cohort. V˙O2peak prediction equations derived from general population cohorts described a modest amount of V˙O2peak variability [R2 = 0.58-0.70, root mean square error (RMSE) = 0.46-0.54 L/min] but were mis-calibrated (calibration-in-the-large = 0.45-1.18 L/min) among EA leading to significant V˙O2peak underestimation. Newly derived, externally validated V˙O2peak prediction equations for EA that included age, sex, and height for both treadmill (R2 = 0.74, RMSE = 0.42 L/min) and cycle ergometer CPET (Cycle: R2 = 0.69, RMSE = 0.42 L/min) demonstrated improved accuracy. CONCLUSION: Commonly used V˙O2peak prediction equations derived from general population cohorts perform poorly among competitive EA. Newly derived CPET reference values including novel V˙O2peak prediction equations may improve the clinical utility of CPET in this rapidly growing patient population.
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Petek et al. (2021) conducted a cohort in Healthy endurance athletes (n=272). Newly derived V˙O2peak prediction equations vs. General population cohort prediction equations was evaluated on V˙O2peak prediction accuracy (R2 and RMSE). Newly derived V˙O2peak prediction equations for endurance athletes demonstrated improved accuracy (treadmill R2=0.74, RMSE=0.42 L/min) compared to standard general population equations.
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