Generalized equations for predicting functional capacity from treadmill performance

Abstract The evaluation of functional capacity is an important aspect of the graded exercise test. It provides data which may be of diagnostic and prognostic significance 1–3 as well as of importance for exercise prescription. 4 Functional capacity is a general term most closely associated with the maximal oxygen uptake (VO 2 max), which represents the integrated product of maximal cardiac output and maximal arteriovenous oxygen difference. 5,6 Because of the technical requirements of measuring VO 2 max, and because of concern over difficulties with patient communication, many laboratories do not directly measure VO 2 max during exercise testing. Typically, VO 2 max is estimated through linear regression equations relating treadmill performance to oxygen uptake. 6–8 These prediction equations, however, tend to be population specific and valid only through a limited range. Bruce et al., 6 who developed the most widely cited prediction equations, have developed three separate linear regression equations, which take into account treadmill performance, health status (known cardiovascular disease/healthy), and physical activity habits (sedentary/active). Examination of the slope of Bruce's equations, however, suggests that the overall relationship between treadmill performance and VO 2 max may be nonlinear. Taken together with the problems inherent in evaluating health status (Bruce includes asymptomatic hypertensive patients as well as patients with exertional angina or prior myocardial infarction) and activity habits, this apparent nonlinearity suggests that using a family of population-specific linear regression equations may not be the optimal method of approaching the estimation of VO 2 max. The problems of predicting VO 2 max enumerated previously are analogous to the problems of estimating body composition from anthropometric measurements. We have dealt with these problems and have developed generalized equations for predicting body composition employing a nonlinear regression model that estimates body density from the quadratic sum of skinfold measurements adjusted for sex and age. 9,10 It seems possible that a similar approach might prove to be a useful way of combining the several, partially overlapping linear equations for predicting VO 2 max. It may also, by virtue of a heterogeneous sample, increase the applicability of the regression approach. Since the direct measurement of VO 2 max during exercise testing is unlikely to become universally employed in clinical laboratories, the development of a single, easy to use regression equation with wide applicability would be a valuable tool for the clinician. Accordingly, the purpose of the present investigation was to develop a multifactorial regression equation for predicting VO 2 max from treadmill performance and clinical characteristics and to determine if such an equation could simplify the prediction of VO 2 max without sacrificing accuracy. This investigation is limited to evaluating responses to the Bruce treadmill protocol, since this protocol is the most widely employed clinically 11 and has already been the subject of considerable study relative to predicting oxygen uptake. 6–8