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

Abstract

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 nonexercise CRF prediction model for treadmill exercise including age, sex, weight, height, and physical activity level as determinants.

Results: Six hundred sixty patients underwent CPET during the study period. Within the entire cohort, R2 values had a range of 0.24 to 0.46. Predicted CRF was statistically different from measured CRF for 19 of the 21 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 -1 ) 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.