Ethnic and regional variations in hospital mortality from COVID-19 in Brazil: a cross-sectional observational study

  1. Pedro Baqui
  2. Ioana Bica
  3. Valerio Marra
  4. Ari Ercole
  5. Mihaela van der Schaar

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Abstract

No abstract available

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  1. Version published to 10.1016/s2214-109x(20)30285-0
  2. ScreenIT

    SciScore for 10.1101/2020.05.19.20107094: (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:
    Whilst we believe our work is the most comprehensive of its kind to date in Brazil, there are a number of limitations which are worthy of discussion. Limitations and possible biases in case ascertainment cannot be ruled out, in common with all observational / database research. Ethnicity is missing in 39% of our data. This is not specific to COVID-19 (32% for the full SIVEP-Gripe dataset) but we cannot be sure that this is not subject to bias. We have limited our analysis to patients who were hospitalised since testing in the community is more likely to be biased according to local factors. However, again here, we cannot be sure that the availability of testing practice is homogeneous even in this population. Indeed, the fact that a large fraction of patients that have tested positive are admitted to the hospital clearly shows that testing, at least as far as this dataset is concerned, is performed only when symptoms are severe, indicating in turn that the number of COVID-19 cases in Brazil is likely to be much higher than suggested by available data.2829 It is possible that health-seeking behaviour varies with both ethnicity and region and late presentation may be an important determinant of ultimate hospital outcome. We are not able to consider this in our analysis as physiological severity at hospital presentation / admission data is not available in the SIVEP-Gripe dataset. However, a recent UK study did not demonstrate an important effect of physiological severity16 at l...

    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.

  3. Version published to 10.1101/2020.05.19.20107094v1 on medRxiv