Paper Info
Title
Statistical analysis of the age dependence of the normal capnogram
Abstract
The age dependence of the time-based capnogram from normal, healthy subjects has not been quantitatively characterized. The existence of age dependence would impact the development and operation of automated quantitative capnographic tools. Here, we quantitatively assess the relationship between normal capnogram shape and age. Capnograms were collected from healthy subjects, and physiologically-based features (exhalation duration, end-tidal CO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> and time spent at this value, normalized time spent at end-tidal CO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> , end-exhalation slope, and instantaneous respiratory rate) were computationally extracted. The mean values of the individual features over 30 exhalations were linearly regressed against subject age, accounting for inter-feature correlation. After data collection, 154 of 178 subjects were eligible for analysis, with an age range of 3–78 years (mean age 39, std. dev. 20 years). The Bonferroni-corrected joint 95% confidence intervals (CIs) of the regression line slopes contained the origin for five of six features (the remaining CI was only slightly offset from the origin). The associated individual r <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> values for the regressions were all below 0.07. We conclude that age is not a significant explanatory factor in describing variations in the shape of the normal capnogram. This finding could be exploited in the design of automated methods for quantitative capnogram analysis across a range of ages.
Year
DOI
Venue
2017
10.1109/EMBC.2017.8036833
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Keywords
Field
DocType
Adolescent,Adult,Aged,Capnography,Carbon Dioxide,Child,Child, Preschool,Exhalation,Humans,Middle Aged,Respiratory Rate,Young Adult
Subject Age,Exhalation,Computer science,Respiratory rate,Correlation,Normalized Time,Confidence interval,Statistics,Statistical analysis,Linear regression
Conference
Volume
ISSN
ISBN
2017
1557-170X
978-1-5090-2810-8
Citations 
PageRank 
References 
0
0.34
1
Authors
7
Name
Order
Citations
PageRank
Rebecca J Mieloszyk132.22
Baruch S Krauss231.88
Diana Montagu300.34
Gary Andolfatto400.34
Egidio Barbi500.34
George C. Verghese620826.26
Thomas Heldt729.54