Noninvasive measurement of plasma glucose from exhaled breath in healthy and type 1 diabetic subjects.

Autor: Minh, Timothy D. C., Oliver, Stacy R., Ngo, Jerry, Rebecca Flores, Jason Midyett, Simone Meinardi, Matthew K. Carlson, F. Sherwood Rowland, Blake, Donald R., Galassetti, Pietro R.
Předmět:
Zdroj: American Journal of Physiology: Endocrinology & Metabolism; Jun2011, Vol. 300, pE1166-E1175, 10p
Abstrakt: Effective management of diabetes mellitus, affecting tens of millions of patients, requires frequent assessment of plasma glucose. Patient compliance for sufficient testing is often reduced by the unpleasantness of current methodologies, which require blood samples and often cause pain and skin callusing. We propose that the analysis of volatile organic compounds (VOCs) in exhaled breath can be used as a novel, alternative, noninvasive means to monitor glycemia in these patients. Seventeen healthy (9 females and 8 males, 28.0 ± 1.0 yr) and eight type 1 diabetic (T1DM) volunteers (5 females and 3 males, 25.8 ± 1.7 yr) were enrolled in a 240-min triphasic intravenous dextrose infusion protocol (baseline, hyperglycemia, euglycemia-hyperinsulinemia). In T1DM patients, insulin was also administered (using differing protocols on 2 repeated visits to separate the effects of insulinemia on breath composition). Exhaled breath and room air samples were collected at 12 time points, and concentrations of ∼100 VOCs were determined by gas chromatography and matched with direct plasma glucose measurements. Standard least squares regression was used on several subsets of exhaled gases to generate multilinear models to predict plasma glucose for each subject. Plasma glucose estimates based on two groups of four gases each (cluster A: acetone, methyl nitrate, ethanol, and ethyl benzene; cluster B: 2-pentyl nitrate, propane, methanol, and acetone) displayed very strong correlations with glucose concentrations (0.883 and 0.869 for clusters A and B, respectively) across nearly 300 measurements. Our study demonstrates the feasibility to accurately predict glycemia through exhaled breath analysis over a broad range of clinically relevant concentrations in both healthy and T1DM subjects. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index