Clinical severity of COVID-19 in patients admitted to hospital during the omicron wave in South Africa: a retrospective observational study

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Abstract

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  1. SciScore for 10.1101/2022.02.22.21268475: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot 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:
    One of the limitations of this study is that clinical outcomes are not known for 11% of patients in the Omicron wave as it ended at the time of analysis and some patients are still in hospital. As clinical outcomes have varied little over the course of the Omicron wave, it is not anticipated that these results will change substantially when the outstanding clinical outcomes are added. Additionally, testing strategies for determining cases have changed over time, though most testing during the waves has focused on testing those with symptoms and those with exposure. While the criteria for hospital admission with Covid-19 may have changed over time, they have been minimal over the last six months when both the Delta and Omicron waves occurred. This study has some data limitations as well. Firstly, disease severity relies on clinical parameters like oxygen and ventilation treatment and not laboratory parameters, although oxygen is usually initiated based on an objectively measured oxygen saturation. Secondly, the incompleteness of reporting in DATCOV and missing values in some patient data may under-estimate severity, but the completeness of reporting is unlikely to have changed substantially over the four waves. Thirdly, while the dataset did not have individual-level data on infecting lineage for cases included in this analysis, each of the four waves included in this study had a predominant variant that allows for wave period to be used as a proxy for dominant variant. During...

    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.