Risk Factors of Fatal Outcome in Hospitalized Subjects With Coronavirus Disease 2019 From a Nationwide Analysis in China

Chest. 2020 Jul;158(1):97-105. doi: 10.1016/j.chest.2020.04.010. Epub 2020 Apr 15.


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.

MeSH terms

  • Aged
  • Aspartate Aminotransferases / blood*
  • Betacoronavirus / isolation & purification
  • COVID-19
  • Cardiovascular Diseases / epidemiology*
  • China / epidemiology
  • Coronavirus Infections* / blood
  • Coronavirus Infections* / diagnosis
  • Coronavirus Infections* / mortality
  • Coronavirus Infections* / physiopathology
  • Correlation of Data
  • Dyspnea* / epidemiology
  • Dyspnea* / etiology
  • Female
  • Humans
  • Male
  • Nomograms
  • Pandemics*
  • Pneumonia, Viral* / blood
  • Pneumonia, Viral* / diagnosis
  • Pneumonia, Viral* / mortality
  • Pneumonia, Viral* / physiopathology
  • Procalcitonin / blood*
  • Prognosis
  • Risk Assessment / methods
  • Risk Factors
  • SARS-CoV-2
  • Survival Analysis


  • Procalcitonin
  • Aspartate Aminotransferases