Predictors of death in severe COVID-19 patients at millennium COVID-19 care center in Ethiopia: a case-control study

  1. Tigist Workneh Leulseged
  2. Endalkachew Hailu Maru
  3. Ishmael Shemsedin Hassen
  4. Wuletaw Chane Zewde
  5. Nigat Hawariyat Chamiso
  6. Daniel Simeneh Abebe
  7. Tariku Bahiru Jagema
  8. Abdi Bekele Bayisa
  9. Mesfin Abebe Gezahegn
  10. Oli Seyoum Tefera
  11. Wondmagegn Genaneh Shiferaw
  12. Teketel Tilahun Admasu

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.10.07.20205575: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationAmendment on the tool was made after a pre-test of the data abstraction tool was made on 5% of randomly selected charts.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data Management and Analysis: The extracted data were coded, entered into Epi-Info version 7.2.1.0, cleaned, stored, and exported to SPSS version 25.0 software for analysis.
    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 10.11604/pamj.2021.38.351.28831
  3. Version published to 10.1101/2020.10.07.20205575 on medRxiv