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Estimating Equations for Cardiopulmonary Exercise Testing Variables in Fontan Patients: Derivation and Validation Using a Multicenter Cross-Sectional Database
Estimating Equations for Cardiopulmonary Exercise Testing Variables in Fontan Patients: Derivation and Validation Using a Multicenter Cross-Sectional Database
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Estimating Equations for Cardiopulmonary Exercise Testing Variables in Fontan Patients: Derivation and Validation Using a Multicenter Cross-Sectional Database
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Estimating Equations for Cardiopulmonary Exercise Testing Variables in Fontan Patients: Derivation and Validation Using a Multicenter Cross-Sectional Database
Estimating Equations for Cardiopulmonary Exercise Testing Variables in Fontan Patients: Derivation and Validation Using a Multicenter Cross-Sectional Database

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Estimating Equations for Cardiopulmonary Exercise Testing Variables in Fontan Patients: Derivation and Validation Using a Multicenter Cross-Sectional Database
Estimating Equations for Cardiopulmonary Exercise Testing Variables in Fontan Patients: Derivation and Validation Using a Multicenter Cross-Sectional Database
Journal Article

Estimating Equations for Cardiopulmonary Exercise Testing Variables in Fontan Patients: Derivation and Validation Using a Multicenter Cross-Sectional Database

2015
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Overview
Cardiopulmonary exercise testing (CPET) is a common method of evaluating patients with a Fontan circulation. Equations to calculate predicted CPET values are based on children with normal circulation. This study aims to create predictive equations for CPET variables solely based on patients with Fontan circulation. Patients who performed CPET in the multicenter Pediatric Heart Network Fontan Cross-Sectional Study were screened. Peak variable equations were calculated using patients who performed a maximal test (RER > 1.1) and anaerobic threshold (AT) variable equations on patients where AT was adequately calculated. Eighty percent of each cohort was randomly selected to derive the predictive equation and the remaining served as a validation cohort. Linear regression analysis was performed for each CPET variable within the derivation cohort. The resulting equations were applied to calculate predicted values in the validation cohort. Observed versus predicted variables were compared in the validation cohort using linear regression. 411 patients underwent CPET, 166 performed maximal exercise tests and 317 had adequately calculated AT. Predictive equations for peak CPET variables had good performance; peak VO2, R2 = 0.61; maximum work, R2 = 0.61; maximum O2 pulse, R2 = 0.59. The equations for CPET variables at AT explained less of the variability; VO2 at AT, R2 = 0.15; work at AT, R2 = 0.39; O2 pulse at AT, R2 = 0.34; VE/VCO2 at AT, R2 = 0.18; VE/VO2 at AT, R2 = 0.14. Only the models for VE/VCO2 and VE/VO2 at AT had significantly worse performance in validation cohort. Of the 8 equations for commonly measured CPET variables, six were able to be validated. The equations for peak variables were more robust in explaining variation in values than AT equations.