COVID-19 Cases from the First Local Outbreak of the SARS-CoV-2 B.1.1.7 Variant in China May Present More Serious Clinical Features: A Prospective, Comparative Cohort Study

  1. Yang Song
  2. Ziruo Ge
  3. Shuping Cui
  4. Di Tian
  5. Gang Wan
  6. Shuangli Zhu
  7. Xianbo Wang
  8. Yu Wang
  9. Xiang Zhao
  10. Pan Xiang
  11. Yanli Xu
  12. Tingyu Zhang
  13. Long Liu
  14. Gang Liu
  15. Yanhai Wang
  16. Jianbo Tan
  17. Wei Zhang
  18. Wenbo Xu
  19. Zhihai Chen

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Abstract

The SARS-CoV-2 B.1.1.7 variant, which was first identified in the United Kingdom, has increased sharply in number of cases worldwide and was reported to be more contagious than the nonvariant. To our knowledge, no studies investigating the detailed clinical features of COVID-19 cases infected with the B.1.1.7 variant have been published.

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  1. Version published to 10.1128/spectrum.00273-21
  2. ScreenIT

    SciScore for 10.1101/2021.05.04.21256655: (What is this?)

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

    Table 1: Rigor

    EthicsField Sample Permit: Role of the funding source: The study was funded by the National Key Research and Development Program (grant nos. 2020YFC0846200 and 2020YFC0848300) and National Natural Science Foundation of China (grant no. 82072295).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Corresponding serum samples were tested for anti-SARS-CoV-2 antibodies using a chemiluminescence immunoassay (CLIA, Bioscience, Qingchong, China).
    anti-SARS-CoV-2
    suggested: None
    Software and Algorithms
    SentencesResources
    Libraries were prepared using a Nextera XT Library Prep Kit (Illumina, San Diego, CA, USA), and the resulting DNA libraries were sequenced on either a MiSeq or an iSeq platform (Illumina) using a 300-cycle reagent kit.
    MiSeq
    suggested: (A5-miseq, RRID:SCR_012148)
    The whole-genome sequence alignment was conducted using the Muscle tool in MEGA (v7.0).
    Muscle
    suggested: (MUSCLE, RRID:SCR_011812)
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)
    Statistical analysis: The statistical analyses were performed using SPSS Version 24.0 (SPSS IBM, Armonk, NY, USA).
    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: We detected the following sentences addressing limitations in the study:
    Limitations of this study exist. Firstly, due to the very low morbidity of COVID-19 now in China, the sample size in the two groups of this study was relatively small; secondly, we were not able to compare the clinical features of the cases infected with the B.1.1.7 variant with the cases infected with other SARS-CoV-2 lineages other than B.1.470. Because during December, 2020 – January 2021, only these two clustered outbreaks had taken place in Beijing, the data of these two groups was more comparable.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  3. Version published to 10.1101/2021.05.04.21256655 on medRxiv