Comparison of Cardiorespiratory Fitness Prediction Equations and Generation of New Predictive Model for Patients with Obesity.

PURPOSE:Cardiorespiratory fitness (CRF) is a critical marker of overall health and a key predictor of morbidity and mortality, but the existing prediction equations for CRF are primarily derived from general populations and may not be suitable for patients with obesity. METHODS:Predicted CRF from different non-exercise prediction equations was compared with measured CRF of patients with obesity who underwent maximal cardiopulmonary exercise testing (CPET). Multiple linear regression was used to develop a population-specific non-exercise CRF prediction model for treadmill exercise including age, sex, weight, height and physical activity level as determinants. RESULTS:660 patients underwent CPET during the study period. Within the entire cohort, R2 values had a range of 0.24-0.46. Predicted CRF was statistically different from measured CRF for 19 included equations. Only 50% of patients were correctly classified into the measured CRF categories according to predicted CRF. A multiple model for CRF prediction (ml/min) was generated (R2 = 0.78) and validated using two cross-validation methods. CONCLUSIONS:Most used equations provide inaccurate estimates of CRF in patients with obesity, particularly in cases of severe obesity and low CRF. Therefore, a new prediction equation was developed and validated specifically for patients with obesity, offering a more precise tool for clinical CPET interpretation and risk stratification in this population.