A preliminary study on serological assay for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 238 admitted hospital patients

  1. Lei Liu
  2. Wanbing Liu
  3. Yaqiong Zheng
  4. Xiaojing Jiang
  5. Guomei Kou
  6. Jinya Ding
  7. Qiongshu Wang
  8. Qianchuan Huang
  9. Yinjuan Ding
  10. Wenxu Ni
  11. Wanlei Wu
  12. Shi Tang
  13. Li Tan
  14. Zhenhong Hu
  15. Weitian Xu
  16. Yong Zhang
  17. Bo Zhang
  18. Zhongzhi Tang
  19. Xinhua Zhang
  20. Honghua Li
  21. Zhiguo Rao
  22. Hui Jiang
  23. Xingfeng Ren
  24. Shengdian Wang
  25. Shangen Zheng

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.03.06.20031856: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study was approved by the Hospital Ethics Committee and written informed consent was waived for emerging infectious diseases.
    Consent: The study was approved by the Hospital Ethics Committee and written informed consent was waived for emerging infectious diseases.
    RandomizationMeanwhile, the serum samples from 70 ordinary patients and 50 healthy blood donors were randomly selected as the controls.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    For IgM detection, ELISA plates were previously coated with mouse anti-human IgM (μ chain) monoclonal antibody.
    anti-human IgM (μ chain)
    suggested: None
    After incubation and washing, HRP-conjugated mouse anti-human IgG monoclonal antibody was added into the plates for detection.
    anti-human IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) version 22.0 software.
    Statistical Package for the Social Sciences
    suggested: (SPSS, RRID:SCR_002865)
    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 10.1016/j.micinf.2020.05.008
  3. Version published to 10.1101/2020.03.06.20031856 on medRxiv