Kidney disease is associated with in-hospital death of patients with COVID-19

  1. Yichun Cheng
  2. Ran Luo
  3. Kun Wang
  4. Meng Zhang
  5. Zhixiang Wang
  6. Lei Dong
  7. Junhua Li
  8. Ying Yao
  9. Shuwang Ge
  10. Gang Xu

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.02.18.20023242: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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:
    Even though this study included a large number of patients from a tertiary teaching hospital in Wuhan, there are several limitations. First, this was an observational study, which may lead to underestimate of AKI or erroneous associations. However, the large number of COVID-19 case in this study may minimize the potential for bias. Second, although we attempted to adjust for many confounders, there may exist confounders either unmeasured or unknown that could explain our observed results. Third, the clinic data of patient after discharge is lacking, so we could not assess the effect of COVID-19 on long-term outcome. The further impact of COVID-19 on patients’ kidney function, especially the incidence of chronic kidney disease in these patients should be the focus of future research.

    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.kint.2020.03.005
  3. Version published to 10.1101/2020.02.18.20023242v1 on medRxiv