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A Comprehensive Meta-Analysis and Systematic Review of Breath Analysis in Detection of COVID-19 Through Volatile Organic Compounds

Grace A. Long,Qian Xu, Jahnavi Sunkara, Reagan Woodbury, Katherine Brown, Justin J. Huang,Zhenzhen Xie,Xiaoyu Chen,Xiao-an Fu,Jiapeng Huang

Diagnostic microbiology and infectious disease(2024)

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Abstract
BackgroundThe COVID-19 pandemic had profound global impacts on daily lives, economic stability, and healthcare systems. Diagnosis of COVID-19 infection via RT-PCR was crucial in reducing spread of disease and informing treatment management. While RT-PCR is a key diagnostic test, there is room for improvement in the development of diagnostic criteria. Identification of volatile organic compounds (VOCs) in exhaled breath provides a fast, reliable, and economically favorable alternative for disease detection.MethodsThis meta-analysis analyzed the diagnostic performance of VOC-based breath analysis in detection of COVID-19 infection. A systematic review of twenty-nine papers using the grading criteria from Newcastle-Ottawa Scale (NOS) and PRISMA guidelines was conducted.ResultsThe cumulative results showed a sensitivity of 0.92 (95% CI, 90%-95%) and a specificity of 0.90 (95% CI 87%-93%). Subgroup analysis by variant demonstrated strong sensitivity to the original strain compared to the Omicron and Delta variant in detection of SARS-CoV-2 infection. An additional subgroup analysis of detection methods showed eNose technology had the highest sensitivity when compared to GC-MS, GC-IMS, and high sensitivity-MS.ConclusionOverall, these results support the use of breath analysis as a new detection method of COVID-19 infection.
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Key words
Artificial Intelligence Models,Breath analysis,COVID-19,Pandemic,RT-PCR,Volatile organic compounds
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