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 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.