Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jul 13;16(7):e0254550.
doi: 10.1371/journal.pone.0254550. eCollection 2021.

Prediction of 28-day mortality in critically ill patients with COVID-19: Development and internal validation of a clinical prediction model

Affiliations

Prediction of 28-day mortality in critically ill patients with COVID-19: Development and internal validation of a clinical prediction model

Matteo Luigi Giuseppe Leoni et al. PLoS One. .

Abstract

Background: COVID-19 pandemic has rapidly required a high demand of hospitalization and an increased number of intensive care units (ICUs) admission. Therefore, it became mandatory to develop prognostic models to evaluate critical COVID-19 patients.

Materials and methods: We retrospectively evaluate a cohort of consecutive COVID-19 critically ill patients admitted to ICU with a confirmed diagnosis of SARS-CoV-2 pneumonia. A multivariable Cox regression model including demographic, clinical and laboratory findings was developed to assess the predictive value of these variables. Internal validation was performed using the bootstrap resampling technique. The model's discriminatory ability was assessed with Harrell's C-statistic and the goodness-of-fit was evaluated with calibration plot.

Results: 242 patients were included [median age, 64 years (56-71 IQR), 196 (81%) males]. Hypertension was the most common comorbidity (46.7%), followed by diabetes (15.3%) and heart disease (14.5%). Eighty-five patients (35.1%) died within 28 days after ICU admission and the median time from ICU admission to death was 11 days (IQR 6-18). In multivariable model after internal validation, age, obesity, procaltitonin, SOFA score and PaO2/FiO2 resulted as independent predictors of 28-day mortality. The C-statistic of the model showed a very good discriminatory capacity (0.82).

Conclusions: We present the results of a multivariable prediction model for mortality of critically ill COVID-19 patients admitted to ICU. After adjustment for other factors, age, obesity, procalcitonin, SOFA and PaO2/FiO2 were independently associated with 28-day mortality in critically ill COVID-19 patients. The calibration plot revealed good agreements between the observed and expected probability of death.

PubMed Disclaimer

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Survival of critically ill COVID-19 patients with pneumonia after the admission to the intensive care unit (ICU).
Dashed lines represent 95% CIs.
Fig 2
Fig 2. Calibration plot of the multivariable prediction model for 28-day mortality of critically ill COVID-19 patients admitted to ICU.

References

    1. Team NCPERE. Vital surveillances: the epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19)–China. China CDC Weekly 2020; 2(8):113–122. - PMC - PubMed
    1. Covid-19 coronavirus pandemic. Updated February 4, 2021. Accessed March 15, 2021. https://www.worldometers.info/coronavirus
    1. Guan WJ, Ni ZY, Hu Y, et al.. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020; 382: 1708–1720. doi: 10.1056/NEJMoa2002032 - DOI - PMC - PubMed
    1. Poggiali E, Vercelli A, Mazzoni S, Bastoni D, Iannicelli T, Demichele E et al.. COVID-19 pandemic, Piacenza calling. The survival strategy of an Italian Emergency Department. Acta Biomed. 2020. Jun 4;91(3). doi: 10.23750/abm.v91i3.9908 - DOI - PMC - PubMed
    1. Wang D, Hu B, Hu C, et al.. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020. doi: 10.1001/jama.2020.1585 - DOI - PMC - PubMed

LinkOut - more resources