Characteristics and outcomes of COVID-19 patients in New York City’s public hospital system

  1. Roopa Kalyanaraman Marcello
  2. Johanna Dolle
  3. Sheila Grami
  4. Richard Adule
  5. Zeyu Li
  6. Kathleen Tatem
  7. Chinyere Anyaogu
  8. Stephen Apfelroth
  9. Raji Ayinla
  10. Noella Boma
  11. Terence Brady
  12. Braulio F. Cosme-Thormann
  13. Roseann Costarella
  14. Kenra Ford
  15. Kecia Gaither
  16. Jessica Jacobson
  17. Marc Kanter
  18. Stuart Kessler
  19. Ross B. Kristal
  20. Joseph J. Lieber
  21. Vikramjit Mukherjee
  22. Vincent Rizzo
  23. Madden Rowell
  24. David Stevens
  25. Elana Sydney
  26. Andrew Wallach
  27. Dave A. Chokshi
  28. Nichola Davis
  29. New York City Health + Hospitals COVID-19 Population Health Data Team

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Abstract

New York City (NYC) bore the greatest burden of COVID-19 in the United States early in the pandemic. In this case series, we describe characteristics and outcomes of racially and ethnically diverse patients tested for and hospitalized with COVID-19 in New York City’s public hospital system.

Methods

We reviewed the electronic health records of all patients who received a SARS-CoV-2 test between March 5 and April 9, 2020, with follow up through April 16, 2020. The primary outcomes were a positive test, hospitalization, and death. Demographics and comorbidities were also assessed.

Results

22254 patients were tested for SARS-CoV-2. 13442 (61%) were positive; among those, the median age was 52.7 years (interquartile range [IQR] 39.5–64.5), 7481 (56%) were male, 3518 (26%) were Black, and 4593 (34%) were Hispanic. Nearly half (4669, 46%) had at least one chronic disease (27% diabetes, 30% hypertension, and 21% cardiovascular disease). Of those testing positive, 6248 (46%) were hospitalized. The median age was 61.6 years (IQR 49.7–72.9); 3851 (62%) were male, 1950 (31%) were Black, and 2102 (34%) were Hispanic. More than half (3269, 53%) had at least one chronic disease (33% diabetes, 37% hypertension, 24% cardiovascular disease, 11% chronic kidney disease). 1724 (28%) hospitalized patients died. The median age was 71.0 years (IQR 60.0, 80.9); 1087 (63%) were male, 506 (29%) were Black, and 528 (31%) were Hispanic. Chronic diseases were common (35% diabetes, 37% hypertension, 28% cardiovascular disease, 15% chronic kidney disease). Male sex, older age, diabetes, cardiac history, and chronic kidney disease were significantly associated with testing positive, hospitalization, and death. Racial/ethnic disparities were observed across all outcomes.

Conclusions and relevance

This is the largest and most racially/ethnically diverse case series of patients tested and hospitalized for COVID-19 in New York City to date. Our findings highlight disparities in outcomes that can inform prevention and testing recommendations.

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  1. Version published to 10.1371/journal.pone.0243027
  2. ScreenIT

    SciScore for 10.1101/2020.05.29.20086645: (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 Biomedical Research Alliance of New York Institutional Review Board.
    Consent: Waivers of informed consent and of the Health Information Portability and Privacy Act were granted due to the retrospective nature of the study.
    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:
    Limitations: Our study includes several limitations. BMI and clinical history were not uniformly available for the study population, with a greater proportion of non-hospitalized patients missing such a history. Having diagnoses recorded in the EHR was correlated with hospitalization, as, in many cases, a diagnosis history was completed upon admission as a part of the patient’s COVID-19 care plan. Additionally, some individuals had incomplete documentation of comorbidities due to variations in the format of historical electronic databases. NYC H+H recently completed a transition to a single EHR platform for the entire health system, resulting in data from the previous platform not being uniformly carried over to the current platform. Community testing was initially available at ambulatory sites and temporary appointment-only drive-through sites but was restricted starting on March 20 to individuals presenting at an emergency department with severe symptoms.23,24,25 Because the criteria for testing in NYC became more strict toward the end of the study period, individuals whose tests and hospital admissions were in the later portion of the study period were more likely to test positive or have more severe illness that required hospitalization. While this may reduce the generalizability of findings to other localities with a lower burden of COVID-19 and, accordingly, less restrictive testing policies, our findings are aligned with those from other health systems in the NYC area....

    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 10.1101/2020.05.29.20086645 on medRxiv