Risk Factors of Fatal Outcome in Hospitalized Subjects With Coronavirus Disease 2019 From a Nationwide Analysis in China
- PMID: 32304772
- PMCID: PMC7158802
- DOI: 10.1016/j.chest.2020.04.010
Risk Factors of Fatal Outcome in Hospitalized Subjects With Coronavirus Disease 2019 From a Nationwide Analysis in China
Abstract
Background: The novel coronavirus disease 2019 (COVID-19) has become a global health emergency. The cumulative number of new confirmed cases and deaths are still increasing out of China. Independent predicted factors associated with fatal outcomes remain uncertain.
Research question: The goal of the current study was to investigate the potential risk factors associated with fatal outcomes from COVID-19 through a multivariate Cox regression analysis and a nomogram model.
Study design and methods: A retrospective cohort of 1,590 hospitalized patients with COVID-19 throughout China was established. The prognostic effects of variables, including clinical features and laboratory findings, were analyzed by using Kaplan-Meier methods and a Cox proportional hazards model. A prognostic nomogram was formulated to predict the survival of patients with COVID-19.
Results: In this nationwide cohort, nonsurvivors included a higher incidence of elderly people and subjects with coexisting chronic illness, dyspnea, and laboratory abnormalities on admission compared with survivors. Multivariate Cox regression analysis showed that age ≥ 75 years (hazard ratio [HR], 7.86; 95% CI, 2.44-25.35), age between 65 and 74 years (HR, 3.43; 95% CI, 1.24-9.5), coronary heart disease (HR, 4.28; 95% CI, 1.14-16.13), cerebrovascular disease (HR, 3.1; 95% CI, 1.07-8.94), dyspnea (HR, 3.96; 95% CI, 1.42-11), procalcitonin level > 0.5 ng/mL (HR, 8.72; 95% CI, 3.42-22.28), and aspartate aminotransferase level > 40 U/L (HR, 2.2; 95% CI, 1.1-6.73) were independent risk factors associated with fatal outcome. A nomogram was established based on the results of multivariate analysis. The internal bootstrap resampling approach suggested the nomogram has sufficient discriminatory power with a C-index of 0.91 (95% CI, 0.85-0.97). The calibration plots also showed good consistency between the prediction and the observation.
Interpretation: The proposed nomogram accurately predicted clinical outcomes of patients with COVID-19 based on individual characteristics. Earlier identification, more intensive surveillance, and appropriate therapy should be considered in patients at high risk.
Keywords: COVID-19; fatal outcome; nomogram; risk factors.
Copyright © 2020 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.
Figures





Comment in
-
Risk Factors for Mortality in Hospitalized Coronavirus Disease 2019 Patients.Chest. 2020 Dec;158(6):2699-2700. doi: 10.1016/j.chest.2020.07.097. Chest. 2020. PMID: 33280753 Free PMC article. No abstract available.
-
Response.Chest. 2020 Dec;158(6):2700-2701. doi: 10.1016/j.chest.2020.08.2107. Chest. 2020. PMID: 33280754 Free PMC article. No abstract available.
References
-
- World Health Organization Coronavirus disease 2019 (COVID-19) situation report-72. https://www.who.int/docs/default-source/coronaviruse/situation-reports/2...
-
- Kattan M.W. Judging new markers by their ability to improve predictive accuracy. J Natl Cancer Inst. 2003;95(9):634–635. - PubMed
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical