Human exhaled air diagnostic markers for respiratory tract infections in subjects receiving mechanical ventilation.

Autor:	Chen D; Zeteo Tech, Inc., Sykesville, MD 21784, United States of America., Mirski MA; Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States of America., Chen S; Division of Biostatistics and Bioinformatics, School of Medicine, University of Maryland, Baltimore, MD 21201, United States of America., Devin AP; Zeteo Tech, Inc., Sykesville, MD 21784, United States of America., Haddaway CR; Zeteo Tech, Inc., Sykesville, MD 21784, United States of America., Caton ER; Zeteo Tech, Inc., Sykesville, MD 21784, United States of America., Bryden WA; Zeteo Tech, Inc., Sykesville, MD 21784, United States of America., McLoughlin M; Zeteo Tech, Inc., Sykesville, MD 21784, United States of America.
Jazyk:	angličtina
Zdroj:	Journal of breath research [J Breath Res] 2023 Jan 19; Vol. 17 (2). Date of Electronic Publication: 2023 Jan 19.
DOI:	10.1088/1752-7163/acad92
Abstrakt:	Diagnosing respiratory tract infections (RTIs) in critical care settings is essential for appropriate antibiotic treatment and lowering mortality. The current diagnostic method, which primarily relies on clinical symptoms, lacks sensitivity and specificity, resulting in incorrect or delayed diagnoses, putting patients at a heightened risk. In this study we developed a noninvasive diagnosis method based on collecting non-volatile compounds in human exhaled air. We hypothesized that non-volatile compound profiles could be effectively used for bacterial RTI diagnosis. Exhaled air samples were collected from subjects receiving mechanical ventilation diagnosed with or without bacterial RTI in intensive care units at the Johns Hopkins Hospital. Truncated proteoforms, a class of non-volatile compounds, were characterized by top-down proteomics, and significant features associated with RTI were identified using feature selection algorithms. The results showed that three truncated proteoforms, collagen type VI alpha three chain protein, matrix metalloproteinase-9, and putative homeodomain transcription factor II were independently associated with RTI with the p -values of 2.0 × 10 -5 , 1.1 × 10 -4 , and 1.7 × 10 -3 , respectively, using multiple logistic regression. Furthermore, a score system named 'TrunScore' was constructed by combining the three truncated proteoforms, and the diagnostic accuracy was significantly improved compared to that of individual truncated proteoforms, with an area under the receiver operator characteristic curve of 96.9%. This study supports the ability of this noninvasive breath analysis method to provide an accurate diagnosis for RTIs in subjects receiving mechanical ventilation. The results of this study open the doors to be able to potentially diagnose a broad range of diseases using this non-volatile breath analysis technique. (© 2023 IOP Publishing Ltd.)
Databáze:	MEDLINE
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