1887

Abstract

Clinical microbiology laboratories have had to cope with an increase in the volume of tests due to the emergence of the SARS-CoV-2 virus. Short turnaround times (TATs) are important for case tracing and to help clinicians in patient management. In such a context, high-throughput systems are essential to process the bulk of the tests. Rapid tests are also required to ensure shorter TATs for urgent situations. In our laboratory, SARS-CoV-2 assays were initially implemented on our custom platform using a previously published method. The commercial cobas 6800 (Roche diagnostics) assay and the GeneXpert Xpress (Cepheid) SARS-CoV-2 assay were implemented on 24 March and 8 April 2020, respectively, as soon as available.

Despite the abundant literature on SARS-CoV-2 assays, the articles focus mainly on the diagnostic performances. This is to our knowledge the first article that specifically studies the TAT of different assays.

We aimed to describe the impact of various SARS-CoV-2 assays on the TAT at the beginning of the outbreak.

In this study, we retrospectively analysed the TAT of all SARS-CoV-2 assays performed in our centre between 24 February and 9 June, 2020.

We retrieved 33 900 analyses, with a median TAT of 6.25 h. TATs were highest (6.9 h) when only our custom platform was used (24 February to 24 March, 2020). They were reduced to 6.1 h when the cobas system was introduced (24 March to 8 April, 2020). The implementation of the GeneXpert further reduced the median TAT to 4.8 h (8 April to 9 June, 2020). The GeneXpert system had the shortest median TAT (1.9 h), followed by the cobas (5.5 h) and by our custom platform (6.9 h).

This work shows that the combination of high-throughput systems and rapid tests allows the efficient processing of a large number of tests with a short TAT. In addition, the use of a custom platform allowed the quick implementation of an in-house test when commercial assays were not yet available.

Funding
This study was supported by the:
  • Université de Lausanne (Award Jürg Tschopp MD-PhD scholarship)
    • Principle Award Recipient: BastianMarquis
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/content/journal/jmm/10.1099/jmm.0.001280
2021-05-06
2021-06-24
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References

  1. Chen N, Zhou M, Dong X, Qu J, Gong F et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020; 395:507–513 [View Article][PubMed]
    [Google Scholar]
  2. Spiteri G, Fielding J, Diercke M, Campese C, Enouf V et al. First cases of coronavirus disease 2019 (COVID-19) in the WHO European region, 24 January to 21 February 2020. Euro Surveill 2020; 25: [View Article][PubMed]
    [Google Scholar]
  3. Maladie coronavirus (COVID-19) Rapport sur La situation épidémiologique en Suisse et dans La Principauté de Liechtenstein; 2019
  4. Lippi G, Plebani M. The critical role of laboratory medicine during coronavirus disease 2019 (COVID-19) and other viral outbreaks. Clin Chem Lab Med 2020; 58:1063–1069 [View Article][PubMed]
    [Google Scholar]
  5. Weemaes M, Martens S, Cuypers L, Van Elslande J, Hoet K et al. Laboratory information system requirements to manage the COVID-19 pandemic: a report from the Belgian national reference testing center. J Am Med Inform Assoc 2020; 27:1293–1299 [View Article][PubMed]
    [Google Scholar]
  6. Hawkins RC. Laboratory turnaround time. Clin Biochem Rev 2007; 28:179–194[PubMed]
    [Google Scholar]
  7. Muenchhoff M, Mairhofer H, Nitschko H, Grzimek-Koschewa N, Hoffmann D et al. Multicentre comparison of quantitative PCR-based assays to detect SARS-CoV-2, Germany, March 2020. Eurosurveillance 2020; 25:2001057
    [Google Scholar]
  8. Moran A, Beavis KG, Matushek SM, Ciaglia C, Francois N et al. The detection of SARS-CoV-2 using the Cepheid Xpert Xpress SARS-CoV-2 and Roche Cobas SARS-CoV-2 assays. J Clin Microbiol 2020
    [Google Scholar]
  9. Lieberman JA, Pepper G, Naccache SN, Huang M-L, Jerome KR et al. Comparison of commercially available and laboratory-developed assays for in vitro detection of SARS-CoV-2 in clinical laboratories. J Clin Microbiol 2020; 58: [View Article][PubMed]
    [Google Scholar]
  10. Wang W, Xu Y, Gao R, Lu R, Han K et al. Detection of SARS-CoV-2 in different types of clinical specimens. JAMA 2020
    [Google Scholar]
  11. Pfefferle S, Reucher S, Nörz D, Lütgehetmann M. Evaluation of a quantitative RT-PCR assay for the detection of the emerging coronavirus SARS-CoV-2 using a high throughput system. Euro Surveill 2020; 25: [View Article][PubMed]
    [Google Scholar]
  12. Poljak M, Korva M, Knap Gašper N, Fujs Komloš K, Sagadin M et al. Clinical evaluation of the COBAS SARS-CoV-2 test and a diagnostic platform switch during 48 hours in the midst of the COVID-19 pandemic. J Clin Microbiol 2020; 58:
    [Google Scholar]
  13. Greub G, Sahli R, Brouillet R, Jaton K. Ten years of R&D and full automation in molecular diagnosis. Future Microbiol 2016; 11:403–425 [View Article][PubMed]
    [Google Scholar]
  14. Corman VM, Landt O, Kaiser M, Molenkamp R, Meijer A et al. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Eurosurveillance 2020; 25: [View Article]
    [Google Scholar]
  15. Pillonel T, Scherz V, Jaton K, Greub G, Bertelli C. Letter to the editor: SARS-CoV-2 detection by real-time RT-PCR. Euro Surveill 2020; 25: [View Article][PubMed]
    [Google Scholar]
  16. Cobb B, Simon CO, Stramer SL, Body B, Mitchell PS et al. The cobas® 6800/8800 system: a new era of automation in molecular diagnostics. Expert Rev Mol Diagn 2017; 17:167–180 [View Article][PubMed]
    [Google Scholar]
  17. Opota O, Brouillet R, Greub G, Jaton K. Comparison of SARS-CoV-2 RT-PCR on a high-throughput molecular diagnostic platform and the COBAS SARS-CoV-2 test for the diagnostic of COVID-19 on various clinical samples. Pathog Dis 2020; 78: [View Article][PubMed]
    [Google Scholar]
  18. Mueller L, Scherz V, Greub G, Jaton K, Opota O. Computer-Aided medical microbiology monitoring tool: a strategy to adapt to the SARS-CoV-2 epidemic and that highlights RT-PCR consistency. MedRxiv 2020
    [Google Scholar]
  19. Van Rossum G, Drake FL. Python 3 Reference Manual Scotts Valley, CA: CreateSpace; 2009
    [Google Scholar]
  20. Jones E, Oliphant T, Peterson P. Others. SciPy: open source scientific tools for python; 2001
  21. Opota O, Jaton K, Greub G. Microbial diagnosis of bloodstream infection: towards molecular diagnosis directly from blood. Clinical Microbiology and Infection 2015; 21:323–331 [View Article]
    [Google Scholar]
  22. Tahamtan A, Ardebili A. Real-Time RT-PCR in COVID-19 detection: issues affecting the results. Expert Rev Mol Diagn 2020; 20:1–2 [View Article][PubMed]
    [Google Scholar]
  23. Greub G, Opota O, Brouillet R, Jaton K. Diagnostic par RT-PCR de l’infection par le virus SARS-CoV-2. Pipette - Swiss Lab Med 2020
    [Google Scholar]
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