• Adriano R Tonelli, Xiao-Feng Wang, Anara Abbay, Qi Zhang, José Ramos, and Kevin McCarthy.
• Department of Pulmonary, Allergy and Critical Care Medicine, Respiratory Institute, Cleveland Clinic tonella@ccf.org.
• Respir Care. 2015 Apr 1;60(4):517-25.

BackgroundWe hypothesize that oxygen consumption (V̇o2) estimation in patients with respiratory symptoms is inaccurate and can be improved by considering arterial blood gases or spirometric variables.MethodsFor this retrospective study, we included consecutive subjects who underwent cardiopulmonary exercise testing. Resting V̇o2 was determined using breath-by-breath testing methodology. Using a training cohort (n = 336), we developed 3 models to predict V̇o2. In a validation group (n = 114), we compared our models with 7 available formulae.ResultsOur first model (V̇o2 = -184.99 + 189.64 × body surface area [BSA, m(2)] + 1.49 × heart rate [beats/min] + 51.51 × FIO2 [21% = 0; 30% = 1] + 30.62 × gender [male = 1; female = 0]) showed an R(2) of 0.5. Our second model (V̇o2 = -208.06 + 188.67 × BSA + 1.38 × heart rate + 35.6 × gender + 2.06 × breathing frequency [breaths/min]) showed an R(2) of 0.49. The best R(2) (0.68) was obtained with our last model, which included minute ventilation (V̇o2 = -142.92 + 0.52 × heart rate + 126.84 × BSA + 14.68 × minute ventilation [L]). In the validation cohort, these 3 models performed better than other available equations, but had wide limits of agreement, particularly in older individuals with shorter stature, higher heart rate, and lower maximum voluntary ventilation.ConclusionsWe developed more accurate formulae to predict resting V̇o2 in subjects with respiratory symptoms; however, equations had wide limits of agreement, particularly in certain groups of subjects. Arterial blood gases and spirometric variables did not significantly improve the predictive equations.Copyright © 2015 by Daedalus Enterprises.

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