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JAMA Netw Open

Title:		Portable Breath-Based Volatile Organic Compound Monitoring for the Detection of COVID-19 During the Circulation of the SARS-CoV-2 Delta Variant and the Transition to the SARS-CoV-2 Omicron Variant
Author(s):		Sharma R; Zang W; Tabartehfarahani A; Lam A; Huang X; Sivakumar AD; Thota C; Yang S; Dickson RP; Sjoding MW; Bisco E; Mahmood CC; Diaz KM; Sautter N; Ansari S; Ward KR; Fan X;
Address:		"Department of Biomedical Engineering, University of Michigan, Ann Arbor. Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor. Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor. Department of Internal Medicine, Division of Pulmonary Critical Care Medicine, University of Michigan, Ann Arbor. Department of Emergency Medicine, University of Michigan, Ann Arbor"
Journal Title:		JAMA Netw Open
Year:		2023
Volume:		20230201
Issue:		2
Page Number:		e230982 -
DOI:		10.1001/jamanetworkopen.2023.0982
ISSN/ISBN:		2574-3805 (Electronic) 2574-3805 (Linking)
Abstract:		"IMPORTANCE: Breath analysis has been explored as a noninvasive means to detect COVID-19. However, the impact of emerging variants of SARS-CoV-2, such as Omicron, on the exhaled breath profile and diagnostic accuracy of breath analysis is unknown. OBJECTIVE: To evaluate the diagnostic accuracies of breath analysis on detecting patients with COVID-19 when the SARS-CoV-2 Delta and Omicron variants were most prevalent. DESIGN, SETTING, AND PARTICIPANTS: This diagnostic study included a cohort of patients who had positive and negative test results for COVID-19 using reverse transcriptase polymerase chain reaction between April 2021 and May 2022, which covers the period when the Delta variant was overtaken by Omicron as the major variant. Patients were enrolled through intensive care units and the emergency department at the University of Michigan Health System. Patient breath was analyzed with portable gas chromatography. MAIN OUTCOMES AND MEASURES: Different sets of VOC biomarkers were identified that distinguished between COVID-19 (SARS-CoV-2 Delta and Omicron variants) and non-COVID-19 illness. RESULTS: Overall, 205 breath samples from 167 adult patients were analyzed. A total of 77 patients (mean [SD] age, 58.5 [16.1] years; 41 [53.2%] male patients; 13 [16.9%] Black and 59 [76.6%] White patients) had COVID-19, and 91 patients (mean [SD] age, 54.3 [17.1] years; 43 [47.3%] male patients; 11 [12.1%] Black and 76 [83.5%] White patients) had non-COVID-19 illness. Several patients were analyzed over multiple days. Among 94 positive samples, 41 samples were from patients in 2021 infected with the Delta or other variants, and 53 samples were from patients in 2022 infected with the Omicron variant, based on the State of Michigan and US Centers for Disease Control and Prevention surveillance data. Four VOC biomarkers were found to distinguish between COVID-19 (Delta and other 2021 variants) and non-COVID-19 illness with an accuracy of 94.7%. However, accuracy dropped substantially to 82.1% when these biomarkers were applied to the Omicron variant. Four new VOC biomarkers were found to distinguish the Omicron variant and non-COVID-19 illness (accuracy, 90.9%). Breath analysis distinguished Omicron from the earlier variants with an accuracy of 91.5% and COVID-19 (all SARS-CoV-2 variants) vs non-COVID-19 illness with 90.2% accuracy. CONCLUSIONS AND RELEVANCE: The findings of this diagnostic study suggest that breath analysis has promise for COVID-19 detection. However, similar to rapid antigen testing, the emergence of new variants poses diagnostic challenges. The results of this study warrant additional evaluation on how to overcome these challenges to use breath analysis to improve the diagnosis and care of patients"
Keywords:		United States Adult Humans Male Middle Aged Female SARS-CoV-2/genetics *COVID-19/diagnosis *Volatile Organic Compounds Breath Tests;
Notes:		"MedlineSharma, Ruchi Zang, Wenzhe Tabartehfarahani, Ali Lam, Andres Huang, Xiaheng Sivakumar, Anjali Devi Thota, Chandrakalavathi Yang, Shuo Dickson, Robert P Sjoding, Michael W Bisco, Erin Mahmood, Carmen Colmenero Diaz, Kristen Machado Sautter, Nicholas Ansari, Sardar Ward, Kevin R Fan, Xudong eng K24 HL159247/HL/NHLBI NIH HHS/ R01 HL144599/HL/NHLBI NIH HHS/ U18 TR003812/TR/NCATS NIH HHS/ Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S. 2023/03/01 JAMA Netw Open. 2023 Feb 1; 6(2):e230982. doi: 10.1001/jamanetworkopen.2023.0982"