| Title: | Human exhaled air diagnostic markers for respiratory tract infections in subjects receiving mechanical ventilation |
| Author(s): | Chen D; Mirski MA; Chen S; Devin AP; Haddaway CR; Caton ER; Bryden WA; McLoughlin M; |
| Address: | "Zeteo Tech, Inc., Sykesville, MD 21784, United States of America. Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States of America. Division of Biostatistics and Bioinformatics, School of Medicine, University of Maryland, Baltimore, MD 21201, United States of America" |
| ISSN/ISBN: | 1752-7163 (Electronic) 1752-7155 (Linking) |
| Abstract: | "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 thep-values of 2.0 x 10(-5), 1.1 x 10(-4), and 1.7 x 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" |
| Keywords: | "Humans Respiration, Artificial Breath Tests/methods *Respiratory Tract Infections/diagnosis Exhalation *Volatile Organic Compounds/analysis critical care human exhaled air noninvasive diagnosis respiratory tract infections;" |
| Notes: | "MedlineChen, Dapeng Mirski, Marek A Chen, Shuo Devin, Alese P Haddaway, Caroline R Caton, Emily R Bryden, Wayne A McLoughlin, Michael eng Research Support, Non-U.S. Gov't England 2022/12/22 J Breath Res. 2023 Jan 19; 17(2). doi: 10.1088/1752-7163/acad92" |
