Is it feasible to predict maximal oxygen uptake without an ergoespirometry?

Abstract

Abstract Introduction To determine the aerobic capacity and the cardiopulmonary response to exercise is an important tool to assess functional capacity and a pronostic factor in patients with coronary artery disease (CAD). Maximal oxygen uptake (VO2) is considered the gold standard for measuring aerobic capacity, and a maximal graded exercise test is required for its direct measurement. Nevertheless, it requires long duration sessions, qualified medical personal and expensive equipment in order to perform it. These are the main reasons why its use is not widely spread in daily clinical practice and more accessible tests are needed. The aim of this study is to determine if we can predict the VO2 in patients with CAD, depending on basal characteristics of the patient. Objective To develop an equation to predict VO2 based on the 6-minute walk test (6MWT), basal characteristics and the presence of cardiovascular risk factors in patients with CAD and preserved left ventricular ejection fraction (LVEF). Methods We performed a cross-sectional prospective study with 202 patients with CAD and preserved LVEF, who were consecutively included in a conventional cardiac rehabilitation programme from March of 2019 to March of 2020 and underwent a 6-minute walk distance test and an ergoespirometry. The presence of cardiovascular risk factors, comorbidities and anthropometric variables were also evaluated. The tests were performed following ATS recommendations. The predictive equation for VO2 was obtained with a multivariate regression analysis. To assess the fit of the predictive model, we used conventional linear regression models according to the coefficient of determination (R2). A P value <0,05 was statistically significant. Results A total of 202 patients were analysed. The mean age was 57,5±9,3 years, mean LVEF was 61,2±6,14%, 13,4% were female, 54,4% arterial hypertension, 30,2% with diabetes, 76,7% dyslipidemia, 36,1% obese, 6,4% with peripheric artery disease, 9,4% with pulmonary disease. Correlations of the mentioned characteristics and the 6MWT with VO2 were statistically significant (p<0,001). Objectively measured VO2 had a significant correlation with age, gender, type II diabetes mellitus, BMI and 6MWT. Multiple regression analysis revealed the following VO2 prediction equation: 32,590-[2,784x gender (0=male/1=female)]-(0,177x age)-(2,756x DM (0=ausence/1= presence)]+(0,027x6MWT)-(0,468xBMI). There was acceptable correlation between measured and predicted VO2 max (R2=0,6). There were not stadistically significant differences between measured VO2 max by ergoespirometry and predicted VO2 max by our equation (22,52±5,82 vs 23,02±4,28, p=0,057). Conclusions Our study provides an VO2 prediction equation based on the demographical characteristics, the presence of cardiovascular risk factors and the results in the 6MWT in patients with CAD, which might be used as an alternative in the case of unavailability of an ergoespirometry. Funding Acknowledgement Type of funding sources: None.