Abstract

Indirect calorimetry and oxygen consumption (VO2) are accepted tools in human physiology research. It has been shown that indirect calorimetry systems exhibit differential measurement error, where the error of a device is systematically different depending on the volume of gas flow. Moreover, systems commonly report multiple decimal places of precision, giving the clinician a false sense of device accuracy. The purpose of this manuscript is to demonstrate the use of a novel statistical tool which models the reliability of two specific indirect calorimetry systems, Douglas bag and Parvomedics 2400 TrueOne, as univariate normal distributions and implements the distribution overlapping coefficient to determine the likelihood that two VO2 measures are the same. A command line implementation of the tool is available for the R programming language as well as a web-based graphical user interface (GUI). This tool is valuable for clinicians performing a single-subject analysis as well as researchers interested in determining if their observed differences exceed the error of the device.

Highlights

  • Since the original description of gas exchange indirect calorimetry (Atwater and Benedict, 1983) and progression toward mobility with the Douglas Bag method (Douglas, 1911), the measurement of ventilatory gases has been a mainstay methodology in the field of human physiology

  • All VO2 data is input in L/min as this is typically the most “raw” and unnormalized form of the data produced by indirect calorimetry

  • In examples 1 and 2, the measurements were obtained with the Parvomedics 2400 TrueOne system

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Summary

Introduction

Since the original description of gas exchange indirect calorimetry (Atwater and Benedict, 1983) and progression toward mobility with the Douglas Bag method (Douglas, 1911), the measurement of ventilatory gases has been a mainstay methodology in the field of human physiology. Indirect calorimetry is commonly used to examine the metabolic cost of performing different tasks or to examine the effectiveness of a chronic exercise intervention on cardiovascular fitness. Both of these types of studies share a study design whereby a “baseline” test is performed and a second “experimental” test follows. The Hecksteden et al method (Hecksteden et al, 2015) uses a similar framework as those proposed by Hopkins (2004, 2015), requiring a measurement and coefficient of variation for the measure Both of these proposed methodologies are helpful in characterizing test-retest

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