Mortality Associated With Intubation and Mechanical Ventilation in Patients with COVID-19

  1. Patrick W. Zimmerman
  2. Stephanie J. Stroever
  3. Timothy Burton
  4. Karri E. Hester
  5. Minha Kim
  6. Ryan T. Fahy
  7. Kimberly A. Corbitt
  8. Joann R. Petrini
  9. Jeffrey Nicastro

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Abstract

Objective

The need for critical care, hemodynamic support, renal replacement therapy, and mechanical ventilation have emerged as key features of the SARS-nCoV-2 (COVID-19) pandemic. The primary aim of this study was to determine the in-hospital mortality rate of mechanically ventilated patients. We also sought to determine the risk of in-hospital mortality by age, gender, race, ethnicity, and body mass index.

Methods

We performed a retrospective cohort study to determine the mortality rate among inpatient adults with COVID-19 on mechanical ventilation in the Nuvance Health system between March 1, 2020 and July 17, 2020. Patients were included if they were 18 years or older, had a laboratory confirmed COVID-19 diagnosis, were admitted to hospitals within the Nuvance Health network (7 hospitals), and were on mechanical ventilation at any time during their inpatient stay.

Results

Overall mortality in our cohort of 304 patients was 53.3%. Multivariable logistic regression including age, gender, race, ethnicity, and BMI demonstrated patients over 71 years old had greater risk of mortality compared to patients ages 61-70, and females had half the risk compared to males. There was no significant difference in risk of mortality given race, ethnicity, or BMI.

Conclusions

In adult patients with confirmed COVID-19 infection requiring mechanical ventilation and intensive care, advanced age (>71 years old) and male gender are associated with increased risk of mortality. This information contributes to a collective body of evidence to support ongoing planning and decision-making among clinicians and for directed infection prevention programming.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.13.20174524: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableWe defined gender as male or female and race as White, Black or African American, Asian and Native Hawaiian/Pacific Islander, and other.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Investigators gathered and compiled the appropriate data using the Research Electronic Data Capture application (REDCap) [16,17].
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    We defined gender as male or female and race as White, Black or African American, Asian and Native Hawaiian/Pacific Islander, and other.
    Islander
    suggested: (Islander, RRID:SCR_007758)

    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 10.1101/2020.08.13.20174524v1 on medRxiv