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A Statistical Method and Tool to Account for Indirect Calorimetry Differential Measurement Error in a Single-Subject Analysis.

Tenan MS - Front Physiol (2016)

Bottom Line: Moreover, systems commonly report multiple decimal places of precision, giving the clinician a false sense of device accuracy.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.

View Article: PubMed Central - PubMed

Affiliation: United States Army Research Laboratory, Human Research and Engineering Directorate, Integrated Capability Enhancement Branch, Aberdeen Proving Ground Aberdeen, MD, USA.

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.

No MeSH data available.


Overlapping probability density plots for VO2 measures of 3.3 L/min and 3.5 L/min collected with the Parvomedics 2400 TrueOne system. The dark overlapping section results in an overlapping coefficient of 0.358.
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Figure 2: Overlapping probability density plots for VO2 measures of 3.3 L/min and 3.5 L/min collected with the Parvomedics 2400 TrueOne system. The dark overlapping section results in an overlapping coefficient of 0.358.

Mentions: The change in VO2 after training protocols is an example of how VO2sim can be used to determine if repeated VO2 measurements are within the differential measurement error based on the specific system used to obtain the measurement. In examples 1 and 2, the measurements were obtained with the Parvomedics 2400 TrueOne system. When the baseline VO2 is 1.5 L/min and post-intervention VO2 is 1.7 L/min, there is a 10.3% probability that they are the same measure (Figure 1). When the baseline VO2 is 3.3 L/min and post-intervention VO2 is 3.5 L/min, there is a 35.8% probability that they are the same measure (Figure 2).


A Statistical Method and Tool to Account for Indirect Calorimetry Differential Measurement Error in a Single-Subject Analysis.

Tenan MS - Front Physiol (2016)

Overlapping probability density plots for VO2 measures of 3.3 L/min and 3.5 L/min collected with the Parvomedics 2400 TrueOne system. The dark overlapping section results in an overlapping coefficient of 0.358.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4863070&req=5

Figure 2: Overlapping probability density plots for VO2 measures of 3.3 L/min and 3.5 L/min collected with the Parvomedics 2400 TrueOne system. The dark overlapping section results in an overlapping coefficient of 0.358.
Mentions: The change in VO2 after training protocols is an example of how VO2sim can be used to determine if repeated VO2 measurements are within the differential measurement error based on the specific system used to obtain the measurement. In examples 1 and 2, the measurements were obtained with the Parvomedics 2400 TrueOne system. When the baseline VO2 is 1.5 L/min and post-intervention VO2 is 1.7 L/min, there is a 10.3% probability that they are the same measure (Figure 1). When the baseline VO2 is 3.3 L/min and post-intervention VO2 is 3.5 L/min, there is a 35.8% probability that they are the same measure (Figure 2).

Bottom Line: Moreover, systems commonly report multiple decimal places of precision, giving the clinician a false sense of device accuracy.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.

View Article: PubMed Central - PubMed

Affiliation: United States Army Research Laboratory, Human Research and Engineering Directorate, Integrated Capability Enhancement Branch, Aberdeen Proving Ground Aberdeen, MD, USA.

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.

No MeSH data available.