Characteristics and Risk Factors for Hospitalization and Mortality among Persons with COVID-19 in Atlanta Metropolitan Area

  1. Nathaniel Chishinga
  2. Neel R. Gandhi
  3. Udodirim N. Onwubiko
  4. Carson Telford
  5. Juliana Prieto
  6. Sasha Smith
  7. Allison T. Chamberlain
  8. Shamimul Khan
  9. Steve Williams
  10. Fazle Khan
  11. Sarita Shah

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Abstract

Background: We present data on risk factors for severe outcomes among patients with coronavirus disease 2019 (COVID-19) in the southeast United States (U.S.). Objective: To determine risk factors associated with hospitalization, intensive care unit (ICU) admission, and mortality among patients with confirmed COVID-19. Design: A retrospective cohort study. Setting: Fulton County in Atlanta Metropolitan Area, Georgia, U.S. Patients: Community-based individuals of all ages that tested positive for SARS-CoV-2. Measurements: Demographic characteristics, comorbid conditions, hospitalization, ICU admission, death (all-cause mortality), and severe COVID-19 disease, defined as a composite measure of hospitalization and death. Results: Between March 2 and May 31, 2020, we included 4322 individuals with various COVID-19 outcomes. In a multivariable logistic regression random-effects model, patients in age groups ≥45 years compared to those <25 years were associated with severe COVID-19. Males compared to females (adjusted odds ratio [aOR] 1.4, 95% confidence interval [CI]: 1.1-1.6), non-Hispanic blacks (aOR 1.9, 95%CI: 1.5-2.4) and Hispanics (aOR 1.7, 95%CI: 1.2-2.5) compared to non-Hispanic whites were associated with increased odds of severe COVID-19. Those with chronic renal disease (aOR 3.6, 95%CI: 2.2-5.8), neurologic disease (aOR 2.8, 95%CI: 1.8-4.3), diabetes (aOR 2.0, 95%CI: 1.5-2.7), chronic lung disease (aOR 1.7, 95%CI: 1.2-2.3), and ″other chronic diseases″ (aOR 1.8, 95%CI: 1.3-2.6) compared to those without these conditions were associated with increased odds of having severe COVID-19. Conclusions: Multiple risk factors for hospitalization, ICU admission, and death were observed in this cohort from an urban setting in the southeast U.S. Improved screening and early, intensive treatment for persons with identified risk factors is urgently needed to reduce COVID-19 related morbidity and mortality.

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  1. ScreenIT

    SciScore for 10.1101/2020.12.15.20248214: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: It was approved by the Emory University institutional review board with a waiver of informed consent.
    Consent: It was approved by the Emory University institutional review board with a waiver of informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analyses were performed in Stata software version 15.1
    Stata
    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:
    Limitations: There were several limitations in our analysis. We utilized routinely collected public health surveillance data, which can have a reporting lag time of several weeks. To minimize this, we censored our data as of May 31, 2020, to allow sufficient time for complete reporting of key indicators, such as hospitalization and death. Data were incomplete for race, ethnicity, and comorbidities for persons whom we were unable to contact to complete a case investigation, which could be due to the absence of contact information or individuals declining to provide these data to the health department. These individuals may differ in important ways from those in whom we have complete information, including access to and utilization of healthcare services. However, our sensitivity analysis to account for missing data did not alter our results, supporting the robustness of the observed risk. Lastly, detailed information on clinical presentation and management of COVID-19 patients is not included in the surveillance database, limiting our ability to evaluate other factors that may be associated with severe disease.

    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 10.1101/2020.12.15.20248214v1 on medRxiv