一项综合的荟萃分析和系统评价，通过挥发性有机化合物对 COVID-19 进行呼吸分析检测。
A comprehensive meta-analysis and systematic review of breath analysis in detection of COVID-19 through Volatile organic compounds.
机构信息
Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA.
Biometrics and Data Science, Fosun Pharma, Beijing, PR China.
出版信息
Diagn Microbiol Infect Dis. 2024 Jul;109(3):116309. doi: 10.1016/j.diagmicrobio.2024.116309. Epub 2024 Apr 27.
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.
背景
COVID-19 大流行对日常生活、经济稳定和医疗保健系统产生了深远的全球影响。通过 RT-PCR 对 COVID-19 感染进行诊断对于减少疾病传播和指导治疗管理至关重要。虽然 RT-PCR 是一种重要的诊断测试，但在制定诊断标准方面仍有改进的空间。呼气中挥发性有机化合物 (VOC) 的鉴定为疾病检测提供了一种快速、可靠且经济有利的替代方法。
方法
本荟萃分析分析了基于 VOC 的呼吸分析在 COVID-19 感染检测中的诊断性能。使用纽卡斯尔-渥太华量表 (NOS) 和 PRISMA 指南的分级标准对 29 篇论文进行了系统评价。
结果
累积结果显示，敏感性为 0.92(95%CI,90%-95%)，特异性为 0.90(95%CI,87%-93%)。按变异体进行的亚组分析显示，与 Omicron 和 Delta 变体相比，原始菌株对 SARS-CoV-2 感染的检测具有很强的敏感性。对检测方法的进一步亚组分析表明，与 GC-MS、GC-IMS 和高灵敏度-MS 相比，eNose 技术的敏感性最高。
结论
总的来说，这些结果支持将呼吸分析作为 COVID-19 感染的新检测方法。
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