ICU outcomes and survival in patients with severe COVID-19 in the largest health care system in central Florida

  1. Eduardo Oliveira
  2. Amay Parikh
  3. Arnaldo Lopez-Ruiz
  4. Maria Carrilo
  5. Joshua Goldberg
  6. Martin Cearras
  7. Khaled Fernainy
  8. Sonja Andersen
  9. Luis Mercado
  10. Jian Guan
  11. Hammad Zafar
  12. Patricia Louzon
  13. Amy Carr
  14. Natasha Baloch
  15. Richard Pratley
  16. Scott Silverstry
  17. Vincent Hsu
  18. Jason Sniffen
  19. Victor Herrera
  20. Neil Finkler

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Abstract

Observational studies have consistently described poor clinical outcomes and increased ICU mortality in patients with severe coronavirus disease 2019 (COVID-19) who require mechanical ventilation (MV). Our study describes the clinical characteristics and outcomes of patients with severe COVID-19 admitted to ICU in the largest health care system in the state of Florida, United States.

Methods

Retrospective cohort study of patients admitted to ICU due to severe COVID-19 in AdventHealth health system in Orlando, Florida from March 11 th until May 18th, 2020. Patients were characterized based on demographics, baseline comorbidities, severity of illness, medical management including experimental therapies, laboratory markers and ventilator parameters. Major clinical outcomes analyzed at the end of the study period were: hospital and ICU length of stay, MV-related mortality and overall hospital mortality of ICU patients.

Results

Out of total of 1283 patients with COVID-19, 131 (10.2%) met criteria for ICU admission (median age: 61 years [interquartile range (IQR), 49.5–71.5]; 35.1% female). Common comorbidities were hypertension (84; 64.1%), and diabetes (54; 41.2%). Of the 131 ICU patients, 109 (83.2%) required MV and 9 (6.9%) received ECMO. Lower positive end expiratory pressure (PEEP) were observed in survivors [9.2 (7.7–10.4)] vs non-survivors [10 (9.1–12.9] p = 0.004]. Compared to non-survivors, survivors had a longer MV length of stay (LOS) [14 (IQR 8–22) vs 8.5 (IQR 5–10.8) p< 0.001], Hospital LOS [21 (IQR 13–31) vs 10 (7–1) p< 0.001] and ICU LOS [14 (IQR 7–24) vs 9.5 (IQR 6–11), p < 0.001]. The overall hospital mortality and MV-related mortality were 19.8% and 23.8% respectively. After exclusion of hospitalized patients, the hospital and MV-related mortality rates were 21.6% and 26.5% respectively.

Conclusions

Our study demonstrates an important improvement in mortality of patients with severe COVID-19 who required ICU admission and MV in comparison to previous observational reports and emphasizes the importance of standard of care measures in the management of COVID-19.

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  1. Version published to 10.1371/journal.pone.0249038
  2. ScreenIT

    SciScore for 10.1101/2020.08.25.20181909: (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 institutional review board of AHCFD.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Cerner; Cerner Corp. Kansas City, MO) reporting database, and all analyses were performed using version 3.6.3 of the R programming language (R Project for Statistical Computing; R Foundation).
    R Project for Statistical
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)

    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:
    This report has several limitations. This was an observational study conducted at a single health care system in a confined geographic area thus limiting the generalizability of our results. As with all observational studies, it is difficult to ascertain causality with ICU therapies as opposed to an association that existed due to the patients’ clinical conditions. Additionally, when examining multiple factors associated with survival, potential confounders may remain unidentified without a multivariate regression analysis. Finally, additional unmeasured factors might have played a significant role in survival. Despite these limitations, our experience and results challenges previously reported high mortality rates. In fact, our mortality rates for mechanically ventilated COVID-19 patients were similar to APACHE IVB predicted mortality, which was based on critically ill patients admitted with respiratory failure secondary to viral and/or bacterial pneumonia. Our study demonstrates the possibility of better outcomes for COVID-19 associated with critical illness, including COVID-19 patients requiring mechanical ventilation. Conclusion: Our study is the first and the largest in the state Florida and probably one of the most encouraging in the United States to show lower overall mortality and MV-related mortality in patients with severe COVID-19 admitted to ICU compared to other previous cases series. Our study does not support the previously reported overwhelmingly poor outcomes...

    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 10.1101/2020.08.25.20181909v1 on medRxiv