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Pilot Study on Non-Invasive Diagnostics of Volatile Organic Compounds over Urine from COVID-19 Patients

Author(s): T Boeselt, P Terhorst, J Kroenig, C Nell, M Spielmanns, H Heers, U Boas, M Veith, C Vogelmeier, T Greulich, AR Koczulla, B Beutel

Introduction: The new beta - coronavirus SARS-CoV 2, which causes the disease COVID-19, can be detected by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) from a nasopharyngeal and/or oropharyngeal swab or Bronchoalveolar Lavage (BAL). The diagnosis of COVID-19 infection is based on the detection of the virus in addition to the typical symptoms. Pre-analytics play a crucial role in this process, as a meaningful result can only be obtained if a sufficient sample quantity is available. This pilot study investigated the possibility of detecting volatile organic compounds (VOCs) from the urine of positive COVID-19 patients using an electronic nose. A SARS-CoV 2-negative control group was additionally studied.

Methods: Between June 2020 and February 2021, the urine of 65 symptomatic, SARS-CoV -2 PCR positive, patients was analyzed. 65 asymptomatic and PCR negative subjects served as control group. VOCs in the headspace of the samples were analyzed using an electronic nose (Cyranose 320) and signals were analyzed in a linear discriminant assay.

Results: Discriminant analysis of a total of 130 urine samples, 65 of which were SARS-CoV-2 positive and 65 negative, showed good overall separation. A sensitivity of 92% and a specificity of 89 % could be determined. The Mahalanobis distance was 1.5. Overall, 92 % of COVID-19 positive urine samples could be correctly matched. This resulted in a positive predictive value of 90 %.

Discussion: The results show for the first time that Cyranose can differentiate between air over urine (Headspace) of SARS-CoV-2 positive patients versus negative subjects. Thus, urine could become a promising, non-invasive and cost-effective diagnostic medium. Further urine-based studies on SARS-CoV-2 using other VOC detection methods need to follow to confirm validity.

Journal Statistics

Impact Factor: * 3.1

CiteScore: 2.9

Acceptance Rate: 11.01%

Time to first decision: 10.4 days

Time from article received to acceptance: 2-3 weeks

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