Outcomes Among HIV-Positive Patients Hospitalized With COVID-19

  1. Savannah Karmen-Tuohy
  2. Philip M. Carlucci
  3. Fainareti N. Zervou
  4. Ioannis M. Zacharioudakis
  5. Gabriel Rebick
  6. Elizabeth Klein
  7. Jenna Reich
  8. Simon Jones
  9. Joseph Rahimian

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Abstract

SARS-CoV-2 infection continues to cause significant morbidity and mortality worldwide. Preliminary data on SARS-CoV-2 infection suggest that some immunocompromised hosts experience worse outcomes. We performed a retrospective matched cohort study to characterize outcomes in HIV-positive patients with SARS-CoV-2 infection.

Methods:

Leveraging data collected from electronic medical records for all patients hospitalized at NYU Langone Health with COVID-19 between March 2, 2020, and April 23, 2020, we matched 21 HIV-positive patients with 42 non-HIV patients using a greedy nearest-neighbor algorithm. Admission characteristics, laboratory test results, and hospital outcomes were recorded and compared between the 2 groups.

Results:

Although there was a trend toward increased rates of intensive care unit admission, mechanical ventilation, and mortality in HIV-positive patients, these differences were not statistically significant. Rates for these outcomes in our cohort are similar to those previously published for all patients hospitalized with COVID-19. HIV-positive patients had significantly higher admission and peak C-reactive protein values. Other inflammatory markers did not differ significantly between groups, although HIV-positive patients tended to have higher peak values during their clinical course. Three HIV-positive patients had superimposed bacterial pneumonia with positive sputum cultures, and all 3 patients died during hospitalization. There was no difference in frequency of thrombotic events or myocardial infarction between these groups.

Conclusions:

This study provides evidence that HIV coinfection does not significantly impact presentation, hospital course, or outcomes of patients infected with SARS-CoV-2, when compared with matched non-HIV patients. A larger study is required to determine whether the trends we observed apply to all HIV-positive patients.

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  1. Version published to 10.1097/qai.0000000000002423
  2. ScreenIT

    SciScore for 10.1101/2020.05.07.20094797: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Study approval: The study was approved by the NYU Grossman School of Medicine Institutional Review Board.
    Consent: A waiver of informed consent and a waiver of the Health Information Portability Privacy act were granted.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Greedy 1:2 nearest neighbor matching was employed using the MatchIt package, Version 3.0.2, in RStudio, Version 1.2.5042, to generate 42 matched non-HIV patients for our comparison group6.
    MatchIt
    suggested: None
    RStudio
    suggested: (RStudio, RRID:SCR_000432)
    All analyses were performed using STATA/SE 16.0 software (STATA Corp.).
    STATA/SE
    suggested: None

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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 10.1101/2020.05.07.20094797v1 on medRxiv