Key result
Non-exercise equations combining clinical data and spirometry accurately estimate peak VO2 and stratify mortality risk.
Why the study?
Peak oxygen consumption identifies pathophysiological mechanisms of exercise intolerance and stratifies risk in heart failure. This study aimed to develop a non-exercise equation to estimate peak oxygen consumption from clinical variables and determine its association with all-cause mortality.
Does a non-exercise multivariable equation combining clinical variables and spirometry accurately predict peak VO2 and all-cause mortality in patients with chronic heart failure?
Cohort (n=5,176)
Does a non-exercise multivariable equation combining clinical variables and spirometry accurately predict peak VO2 and all-cause mortality in patients with chronic heart failure?
Effect estimate: R 0.73
p-value: p=<0.001
Multivariable non-exercise equations integrating routine clinical variables and spirometry can reasonably estimate peak VO2 and stratify mortality risk in heart failure patients when CPET is unavailable.
Background Peak oxygen consumption (pVO2) has been widely recognized to identify potential pathophysiological mechanisms of exercise intolerance and to stratify risk in patients with heart failure (HF). Aims To develop a non-exercise equation to estimate pVO2 (esVO2) and to determine its association with all-cause mortality. Methods A total of 5176 HF patients (age 48 ± 17 years) who underwent a CPET for clinical reasons, and were followed between May 2011, and December 1, 2023. Clinical and historical variables and forced expiratory volume in 1-s (FEV 1 ) were used in a stepwise multivariate regression analysis to predict pVO2 measured from CPET. Kaplan-Meier curves and Cox proportional hazards analyses were used to determine the association between esVO2 and all-cause mortality. Results The first esVO2 model was significantly associated with pVO2 (multiple R = 0.73, P < 0.001). Two other models considered gender separately (male: multiple R = 0.72, P < 0.001 and female (multiple R = 0.70, P < 0.001). A fourth model was proposed when spirometry is not available (age, BMI, resting SBP, HR and gender (multiple R = 0.69, P < 0.001)). The fifth proposed model included history of atrial fibrillation and previous stroke (multiple R = 0.70, P < 0.001). Kaplan-Meier survival curves differentiated patients according to esVO2 and pVO2 ≤ and > 14 mL/kg −1 per min −1 . Univariate Cox proportional hazard analyses indicated significant prognostic value when esVO2 and pVO2 were ≤ 14 mL/kg −1 per min −1 ( P = 0.001). Conclusions Multivariable nonexercise models combining spirometry and/or clinical variables commonly obtained during a clinical assessment predict pVO2 reasonably accurately in HF.
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Borghi‐Silva et al. (2026) conducted a cohort in Chronic heart failure (n=5,176). Non-exercise equation to estimate peak VO2 (esVO2) vs. Measured peak VO2 (pVO2) from CPET was evaluated on Association with measured peak VO2 (pVO2) and all-cause mortality (R 0.73, p=<0.001). Non-exercise equations combining clinical variables and spirometry accurately predicted peak VO2 (multiple R=0.73, P<0.001) and stratified mortality risk at ≤14 mL/kg/min (P=0.001).
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