Authors: odunsi, s. t.¹; camilleri, m.¹; szarka, l. a.¹; zinsmeister, a. r.²

Source: Neurogastroenterology and Motility, Volume 21, Number 7, July 2009 , pp. 706-e38(-705)

Publisher: Wiley-Blackwell

Abstract:

 

Breath tests (BT) using ¹³C-substrates have been proposed for the measurement of gastric emptying (GE). The mathematical analysis of the breath ¹³CO₂ excretion that most accurately predicts GE t_1/2 from simultaneous scintigraphy is unresolved. To compare five mathematical methods to estimate GE t_1/2 by BT with t_1/2 from simultaneous scintigraphy. Data acquired from a dual-labelled solid-liquid meal containing ^99mTc sulphur colloid and ¹³C-Spirulina platensis from 57 healthy volunteers were used to compare four mathematical methods reported in the literature [Ghoos method; generalized linear regression (Viramontes); linear regression (Szarka); Wagner-Nelson method] and the total cumulative breath ¹³CO₂ excretion with ≥12 breath samples collected over at least 4 h. The concordance correlation coefficient (CCC) for the t_1/2 results obtained with each method using BT data was compared with the results obtained with scintigraphy. The linear regression and generalized linear regression methods used five samples at 45, 90, 120, 150 and 180 min. All methods, except for the Wagner-Nelson method, resulted in mean GE t_1/2 that approximated t_1/2 obtained with scintigraphy. The highest CCC was observed with the linear regression method. Simple cumulative excretion of breath ¹³CO₂ provides a better CCC than the Ghoos method. The linear regression and generalized linear regression methods (which also require relatively few breath samples) provide the most accurate analyses of breath ¹³CO₂ excretion in stable isotope GEBT.

Keywords: scintigraphy; spirulina

Document Type: Research article

DOI: http://dx.doi.org/10.1111/j.1365-2982.2009.01283.x

Affiliations: 1: Clinical Enteric Neuroscience Translational and Epidemiological Research (CENTER), Mayo Clinic, Rochester, MN, USA 2: Department of Health Sciences Research, Division of Biostatistics, Mayo Clinic, Rochester, MN, USA

Publication date: 2009-07-01

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