| Title: | Breath analysis for detection and trajectory monitoring of acute respiratory distress syndrome in swine |
| Author(s): | Sharma R; Zhou M; Tiba MH; McCracken BM; Dickson RP; Gillies CE; Sjoding MW; Nemzek JA; Ward KR; Stringer KA; Fan X; |
| Address: | "Dept of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA. Dept of Emergency Medicine, University of Michigan, Ann Arbor, MI, USA. Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, MI, USA. Dept of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, MI, USA. Michigan Institute for Data Science, Office of Research, University of Michigan, Ann Arbor, MI, USA. Unit of Laboratory Animal Medicine, University of Michigan, Ann Arbor, MI, USA. Dept of Pathology, University of Michigan, Ann Arbor, MI, USA. Dept of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, USA" |
| DOI: | 10.1183/23120541.00154-2021 |
| ISSN/ISBN: | 2312-0541 (Print) 2312-0541 (Electronic) 2312-0541 (Linking) |
| Abstract: | "Despite the enormous impact on human health, acute respiratory distress syndrome (ARDS) is poorly defined, and its timely diagnosis is difficult, as is tracking the course of the syndrome. The objective of this pilot study was to explore the utility of breath collection and analysis methodologies to detect ARDS through changes in the volatile organic compound (VOC) profiles present in breath. Five male Yorkshire mix swine were studied and ARDS was induced using both direct and indirect lung injury. An automated portable gas chromatography device developed in-house was used for point of care breath analysis and to monitor swine breath hourly, starting from initiation of the experiment until the development of ARDS, which was adjudicated based on the Berlin criteria at the breath sampling points and confirmed by lung biopsy at the end of the experiment. A total of 67 breath samples (chromatograms) were collected and analysed. Through machine learning, principal component analysis and linear discrimination analysis, seven VOC biomarkers were identified that distinguished ARDS. These represent seven of the nine biomarkers found in our breath analysis study of human ARDS, corroborating our findings. We also demonstrated that breath analysis detects changes 1-6 h earlier than the clinical adjudication based on the Berlin criteria. The findings provide proof of concept that breath analysis can be used to identify early changes associated with ARDS pathogenesis in swine. Its clinical application could provide intensive care clinicians with a noninvasive diagnostic tool for early detection and continuous monitoring of ARDS" |
| Notes: | "PubMed-not-MEDLINESharma, Ruchi Zhou, Menglian Tiba, Mohamad Hakam McCracken, Brendan M Dickson, Robert P Gillies, Christopher E Sjoding, Michael W Nemzek, Jean A Ward, Kevin R Stringer, Kathleen A Fan, Xudong eng K01 HL136687/HL/NHLBI NIH HHS/ R35 GM136312/GM/NIGMS NIH HHS/ England 2022/02/18 ERJ Open Res. 2022 Feb 14; 8(1):00154-2021. doi: 10.1183/23120541.00154-2021. eCollection 2022 Jan" |
