Investigation of subsequent and co-infections associated with SARS-CoV-2 (COVID-19) in hospitalized patients

  1. Matthew P. Crotty
  2. Ronda Akins
  3. An Nguyen
  4. Rania Slika
  5. Kristen Rahmanzadeh
  6. Marie H. Wilson
  7. Edward A. Dominguez

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Abstract

Background

SARS-CoV-2 has drastically affected healthcare globally and causes COVID-19, a disease that is associated with substantial morbidity and mortality. We aim to describe rates and pathogens involved in co-infection or subsequent infections and their impact on clinical outcomes among hospitalized patients with COVID-19.

Methods

Incidence of and pathogens associated with co-infections, or subsequent infections, were analyzed in a multicenter observational cohort. Clinical outcomes were compared between patients with a bacterial respiratory co-infection (BRC) and those without. A multivariable Cox regression analysis was performed evaluating survival.

Results

A total of 289 patients were included, 48 (16.6%) had any co-infection and 25 (8.7%) had a BRC. No significant differences in comorbidities were observed between patients with co-infection and those without. Compared to those without, patients with a BRC had significantly higher white blood cell counts, lactate dehydrogenase, C-reactive protein, procalcitonin and interleukin-6 levels. ICU admission (84.0 vs 31.8%), mechanical ventilation (72.0 vs 23.9%) and in-hospital mortality (45.0 vs 9.8%) were more common in patients with BRC compared to those without a co-infection. In Cox proportional hazards regression, following adjustment for age, ICU admission, mechanical ventilation, corticosteroid administration, and pre-existing comorbidities, patients with BRC had an increased risk for in-hospital mortality (adjusted HR, 3.37; 95% CI, 1.39 to 8.16; P = 0.007). Subsequent infections were uncommon, with 21 infections occurring in 16 (5.5%) patients.

Conclusions

Co-infections are uncommon among hospitalized patients with COVID-19, however, when BRC occurs it is associated with worse clinical outcomes including higher mortality.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.29.20117176: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Study Population and Data Collection: The Aspire institutional review board approved this multicenter observational cohort study as minimal-risk research using data collected for routine clinical practice and waived the requirement for informed consent.
    Consent: Study Population and Data Collection: The Aspire institutional review board approved this multicenter observational cohort study as minimal-risk research using data collected for routine clinical practice and waived the requirement for informed consent.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All statistical analyses were performed using SPSS software (IBM SPSS Statistics, version 22.0; Chicago, IL, USA).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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.

  2. Version published to 10.1101/2020.05.29.20117176 on medRxiv