Systematic errors and susceptibility to noise of four methods for calculating anatomical dead space from the CO2 expirogram

Abstract

Background: Anatomical dead space is usually measured using the Fowler equal area method. Alternative methods include the Hatch, Cumming, and Bowes methods, in which first, second, and third order polynomials, respectively, fitted to an expired CO2 volume vs expired volume curve, intercept the x-axis at the anatomical dead space. This study assessed systematic errors and susceptibility to noise of the Fowler, Hatch, Cumming, and Bowes dead spaces calculated over 40-80% of the CO2 expirogram.

Methods: Simulated CO2 expirograms with 220 ml anatomical dead space and varying alveolar plateau slopes were generated digitally and zero-mean Gaussian noise added. CO2 expirograms were recorded in 10 anaesthetized human subjects. Anatomical dead space was calculated by the Fowler, Hatch, Cumming, and Bowes methods.

Results: The Fowler, Hatch, Cumming, and Bowes methods displayed systematic biases of -1.8%, 13.2%, 2.4%, and -1.3%, respectively, at a normalized simulated alveolar plateau slope of 1.6 litre(-1). At a noise level of 0.0066 vol/vol, the standard deviations of recovered simulated dead spaces were 70.6, 1.8, 2.4, and 3.7 ml, respectively. The Hatch, Cumming, and Bowes methods applied to human expirograms differed significantly from that of Fowler by 13, -4, and -11 ml, respectively. In the human study, the Hatch and Cumming methods yielded the lowest intra-individual dead space variability.

Conclusions: The Fowler method shows greatest susceptibility to measurement noise and the Hatch method exhibits the largest systematic error. The Cumming method, which exhibits both low bias and low noise susceptibility, is preferred for estimating anatomical dead space from CO2 expirograms.