A new generalized cycle ergometry equation for predicting maximal oxygen uptake: The Fitness Registry and the Importance of Exercise National Database (FRIEND).

Background To develop a clinically applicable equation derived from direct assessment of maximal oxygen uptake (VO) to predict VO assessed indirectly during cycle ergometry. Design VO 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 VO 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 (Watts6.12/kg of body weight) and gender were considered in the final regression model as predictors of measured VO 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 VO 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: VO in ml O·kg·min= 1.74 (Watts*6.12/kg of body weight) + 3.5. The derived FRIEND-ergometry equation predicted VO 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.