Abstract
Background
To develop a clinically applicable equation derived from direct assessment of maximal oxygen uptake (VO2max) to predict VO2max assessed indirectly during cycle ergometry.
Design
VO2max was assessed by open-circuit spirometry during a graded maximal exercise test using cycle ergometry. Multivariable linear regression analysis was applied to identify the most relevant variables and construct the best prediction model for VO2max using a random sample of 70% from each of the following age categories: <40, 40–50, 50–70 and >70 years; the remaining 30% was used for validation. Work rate (Watts*6.12/kg of body weight) and gender were considered in the final regression model as predictors of measured VO2max and the resulting equation was compared to the traditional American College of Sports Medicine (ACSM) equation.
Methods
Participants were part of the Fitness Registry and the Importance of Exercise National Database (FRIEND), a multi-institutional initiative with the primary objective of establishing normative VO2max values across the adult lifespan. The final cohort consisted of 5100 (3378 men; mean age 35.9 ± 12.1 years and 1722 women; mean age 47.5 ± 14.0 years).
Results
The following equation was generated: VO2max in ml O2·kg–1·min–1 = 1.74* (Watts*6.12/kg of body weight) + 3.5. The derived FRIEND-ergometry equation predicted VO2max with an overall relative bias of 0.51% ± 0.11 compared to a 15.46% ± 0.13 associated with the traditional ACSM equations (P < 0.001). This predictive value was independent of gender, race, cardiac risk factors and cardiac, antihypertensive, metabolic and/or lipid-lowering medication.
Conclusion
The FRIEND-ergometry equation is considerably more precise than the traditional ACSM equation with an overall error over 30 times lower than that associated with the ACSM equation.
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