Clinical Manifestations of Hospitalized COVID-19 Patients in Bangladesh: A 14-day Observational Study

  1. Sheikh MF Akbar
  2. Modhusudon Shaha
  3. Md A Islam
  4. Faizul Huq
  5. Bithi Roy
  6. Md A Kabir
  7. Md Salimullah

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  1. Version published to 10.5005/jp-journals-10018-1340
  2. ScreenIT

    SciScore for 10.1101/2021.04.27.21256018: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This study was approved by the institutional ethics committee (approval number: FGH/2020/01) of Farabi General Hospital, Dhaka, Bangladesh.
    Sex as a biological variableOf these patients, female (mean age: 32.13; SEM: 5.313) and male (mean age: 41.88; SEM: 1.91) patients were approximately 19% and 81%, respectively.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All statistical analysis was performed using GraphPad Prism v9.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.
    • Thank you for including a protocol registration statement.

    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 10.1101/2021.04.27.21256018v1 on medRxiv