SynthesisDiagnostic microbiology and infectious disease2024
A comprehensive meta-analysis and systematic review of breath analysis in detection of COVID-19 through Volatile organic compounds.
Synthesis in Diagnostic microbiology and infectious disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 12 citations in OpenAlex.
- Urine volatile organic compounds (VOCs) combined with machine learning algorithm in the diagnosis of gallstones with cholecystitis.Scientific reports · 2026Article
- Volatile Organic Compounds Induced upon Viral Infection in Cell Culture: Uniform Background Study with Use of Viruses from Different Families.Molecules (Basel, Switzerland) · 2025Article
- Opportunities and Challenges in Gas Sensor Technologies for Accurate Detection of COVID-19.Biosensors · 2025Review
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 2 countries.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.