Virological assessment of hospitalized patients with COVID-2019

  1. Roman Wölfel
  2. Victor M. Corman
  3. Wolfgang Guggemos
  4. Michael Seilmaier
  5. Sabine Zange
  6. Marcel A. Müller
  7. Daniela Niemeyer
  8. Terry C. Jones
  9. Patrick Vollmar
  10. Camilla Rothe
  11. Michael Hoelscher
  12. Tobias Bleicker
  13. Sebastian Brünink
  14. Julia Schneider
  15. Rosina Ehmann
  16. Katrin Zwirglmaier
  17. Christian Drosten
  18. Clemens Wendtner

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.03.05.20030502: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: Ethical approval statement: All patients provided informed consent to the use of their data and clinical samples for the purposes of the present study.
    IRB: Institutional review board clearance for the scientific use of patient data has been granted to the treating institution by the Ethikkommission bei der Medizinischen Fakultät der Ludwig Maximillians Universtität München.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Virus isolation: Virus isolation was done in two laboratories on Vero E6 cells.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Serology: We performed recombinant immunofluorescence assays to determine the specific reactivity against recombinant spike proteins in VeroB4 cells, as described11,12.
    VeroB4
    suggested: CCLV Cat# CCLV-RIE 1146, RRID:CVCL_1912)
    This assay used cloned CoV spike protein from HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1, and SARS-CoV-2.
    HCoV-NL63
    suggested: RRID:CVCL_RW88)
    Software and Algorithms
    SentencesResources
    Statistical Analyses: Statistical analyses were done using SPSS software (Version 25) or GrapPad Prism (Version 8).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1038/s41586-020-2196-x
  3. Version published to 10.1101/2020.03.05.20030502 on medRxiv