Journal Article Meta-Analysis Systematic Review Ppublish 3 citations
PubMed: 38692202 DOI: 10.1016/j.diagmicrobio.2024.116309
A comprehensive meta-analysis and systematic review of breath analysis in detection of COVID-19 through Volatile organic compounds.
Diagn Microbiol Infect Dis 109(3):116309
Authors: Grace A Long, Qian Xu, Jahnavi Sunkara, Reagan Woodbury, Katherine Brown, Justin J Huang, Zhenzhen Xie, Xiaoyu Chen, Xiao-An Fu, Jiapeng Huang
Affiliations
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA.
- Biometrics and Data Science, Fosun Pharma, Beijing, PR China.
- Dupont Manual High School, Louisville, KY, USA.
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA.
- Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY, USA.
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA.
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA.
Abstract
BACKGROUND
The 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.
METHODS
This 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.
RESULTS
The 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.
CONCLUSION
Overall, these results support the use of breath analysis as a new detection method of COVID-19 infection.
MeSH
Volatile Organic Compounds, Microbiology, Covid-19, Communicable Diseases, Infections