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
Observational Study
. 2020 Oct 7;10(1):16726.
doi: 10.1038/s41598-020-73962-9.

A novel severity score to predict inpatient mortality in COVID-19 patients

David J Altschul  1   2   3 , Santiago R Unda  4 , Joshua Benton  5   6 , Rafael de la Garza Ramos  5   7   6 , Phillip Cezayirli  5   7   6 , Mark Mehler  8   6 , Emad N Eskandar  5   7   6
Affiliations
Observational Study

A novel severity score to predict inpatient mortality in COVID-19 patients

David J Altschul et al. Sci Rep. .

Abstract

COVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifically for COVID-19 to help predict disease severity and mortality. 4711 patients with confirmed SARS-CoV-2 infection were included. We derived a risk model using the first half of the cohort (n = 2355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2356 patients. Mortality incidence was 26.4% in the derivation cohort and 22.4% in the validation cohort. A COVID-19 severity score ranging from 0 to 10, consisting of age, oxygen saturation, mean arterial pressure, blood urea nitrogen, C-Reactive protein, and the international normalized ratio was developed. A ROC curve analysis was performed in the derivation cohort achieved an AUC of 0.824 (95% CI 0.814-0.851) and an AUC of 0.798 (95% CI 0.789-0.818) in the validation cohort. Furthermore, based on the risk categorization the probability of mortality was 11.8%, 39% and 78% for patient with low (0-3), moderate (4-6) and high (7-10) COVID-19 severity score. This developed and validated novel COVID-19 severity score will aid physicians in predicting mortality during surge periods.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
ROC curve analysis in derivation cohort. Area under the curve (AUC) of the COVID-19 in-hospital mortality score in the 2355 patients that constituted the derivation cohort.
Figure 2
Figure 2
Validation of COVID-19 severity score. (a) Area under the curve (AUC) of the COVID-19 in-hospital mortality score in the 2356 patients that constituted the validation cohort. (b) Percentage death patients in low, moderate and high-risk categories.
See this image and copyright information in PMC

References

    1. City DoHNY. COVID-19 Data. Department of Health, New York City. https://www1.nyc.gov/site/doh/covid/covid-19-data.page (2020)
    1. Total International Passenger Traffic. https://aci.aero/news/2019/03/13/preliminary-world-airport-traffic-ranki... (2019)
    1. Medicine JHU. Johns Hopkins Coronavirus Resource Center.https://coronavirus.jhu.edu/ (2020)
    1. Zhou F, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395:1054–1062. doi: 10.1016/S0140-6736(20)30566-3. - DOI - PMC - PubMed
    1. Yang X, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir. Med. 2020;8:475–481. doi: 10.1016/S2213-2600(20)30079-5. - DOI - PMC - PubMed

Publication types

MeSH terms

Substances