Racial and Ethnic Disparities in Hospital Admissions from COVID-19: Determining the Impact of Neighborhood Deprivation and Primary Language

  1. Nicholas E. Ingraham
  2. Laura N. Purcell
  3. Basil S. Karam
  4. R. Adams Dudley
  5. Michael G. Usher
  6. Christopher A. Warlick
  7. Michele L. Allen
  8. Genevieve B. Melton
  9. Anthony Charles
  10. Christopher J. Tignanelli

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Abstract

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  1. Version published to 10.1007/s11606-021-06790-w
  2. ScreenIT

    SciScore for 10.1101/2020.09.02.20185983: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the University of Minnesota institutional review board (STUDY00001489) which provided a waiver of consent for this study.
    Consent: This study was approved by the University of Minnesota institutional review board (STUDY00001489) which provided a waiver of consent for this study.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analyses were performed using Stata MP, version 16 (StataCorp, College Station, TX).
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    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:
    Despite our best efforts to address potential racial and ethnic confounders, multiple limitations need to be considered when interpreting our results. First, the need for hospitalization may vary by site. With our current dataset, we are unable to determine whether that is the case for the population under study. Also, using hospitalization as an endpoint may be underwhelming (relative to other endpoints such as intensive care unit admission and mortality); however, there are many confounding factors that occur once the patient is hospitalized that may influence the observed effects. Hospitalization is a proxy for not only severity but also objective healthcare resource use and thus we argue, is not only of critical importance for physicians but can also assist administrators when assessing resource utilization in their communities. Testing deficiencies in low risk minorities (creating the perception of higher risk) has the potential to bias the results; however, the lack of testing in these patients is unlikely to alter the findings in our study and would only highlight another potential driver in observed disparities (i.e. lack of testing equality in the outpatient setting). Insurance status was not included in our analysis. However, this variable is commonly used to control for SES, and given that we have adjusted for multiple socioeconomic attributes, we feel this may attenuate the contribution insurance may have on our outcomes. Furthermore, there remains a possibility o...

    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 10.1101/2020.09.02.20185983v3 on medRxiv
  4. Version published to 10.1101/2020.09.02.20185983v2 on medRxiv
  5. Version published to 10.1101/2020.09.02.20185983v1 on medRxiv