Standardizing and Predicting Results From Cardiopulmonary Exercise Testing in Patients With Heart Failure

In Brief PURPOSE: Cardiopulmonary exercise testing is a common prognostic tool in heart failure, yet it is not standardized. The purpose of this study was to evaluate a means of standardizing oxygen consumption (VO2) measurement and to evaluate the ability to predict peak VO2 from submaximal exercise. METHODS: Fifty consecutive exercise tests with a respiratory exchange ratio ≥1.10 were evaluated. VO2 was graphed against respiratory exchange ratio and the peak VO2 was determined with logarithmic, linear, power, and exponential regression lines. To predict a peak VO2, each patient's submaximal exercise data (respiratory exchange ratio ≤0.98) were fitted to each regression line. The mean of the last 30 seconds of unaveraged breath-by-breath data was used as the reference value. Peak VO2 assessments are also provided from the metabolic cart, a rolling time average, and the graphical method. RESULTS: Logarithmic regression best standardized peak VO2. Mean absolute bias (mL·kg−1·min−1) was 0.60 ± 0.44 for logarithmic, 0.61 ± 0.47 for linear, 0.85 ± 0.67 for power, and 1.44 ± 2.22 for exponential. The mean absolute bias between the peak logarithmic predicted VO2 and the reference peak VO2 was 1.62 ± 1.20 mL·kg−1·min−1 (9.5% of the peak VO2). CONCLUSION: Among the methods studied, logarithmic regression analysis was the best method to standardize and predict peak VO2 in this cohort of patients with heart failure. Standardization of cardiopulmonary exercise testing was investigated because of the important prognostic role of peak oxygen consumption in patients with heart failure. The authors found that logarithmic regression analysis can standardize the reporting of exercise testing and it can also accurately predict peak oxygen consumption from submaximal exercise data.