A Clinical Risk Score to Predict In-hospital Mortality from COVID-19 in South Korea

J Korean Med Sci. 2021 Apr 19;36(15):e108. doi: 10.3346/jkms.2021.36.e108.

Abstract

Background: Early identification of patients with coronavirus disease 2019 (COVID-19) who are at high risk of mortality is of vital importance for appropriate clinical decision making and delivering optimal treatment. We aimed to develop and validate a clinical risk score for predicting mortality at the time of admission of patients hospitalized with COVID-19.

Methods: Collaborating with the Korea Centers for Disease Control and Prevention (KCDC), we established a prospective consecutive cohort of 5,628 patients with confirmed COVID-19 infection who were admitted to 120 hospitals in Korea between January 20, 2020, and April 30, 2020. The cohort was randomly divided using a 7:3 ratio into a development (n = 3,940) and validation (n = 1,688) set. Clinical information and complete blood count (CBC) detected at admission were investigated using Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression to construct a predictive risk score (COVID-Mortality Score). The discriminative power of the risk model was assessed by calculating the area under the curve (AUC) of the receiver operating characteristic curves.

Results: The incidence of mortality was 4.3% in both the development and validation set. A COVID-Mortality Score consisting of age, sex, body mass index, combined comorbidity, clinical symptoms, and CBC was developed. AUCs of the scoring system were 0.96 (95% confidence interval [CI], 0.85-0.91) and 0.97 (95% CI, 0.84-0.93) in the development and validation set, respectively. If the model was optimized for > 90% sensitivity, accuracies were 81.0% and 80.2% with sensitivities of 91.7% and 86.1% in the development and validation set, respectively. The optimized scoring system has been applied to the public online risk calculator (https://www.diseaseriskscore.com).

Conclusion: This clinically developed and validated COVID-Mortality Score, using clinical data available at the time of admission, will aid clinicians in predicting in-hospital mortality.

Keywords: COVID-19; Death; In-hospital Mortality; Prediction; Risk Score.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • COVID-19 / mortality*
  • Child
  • Child, Preschool
  • Female
  • Hospital Mortality*
  • Humans
  • Infant
  • Infant, Newborn
  • Logistic Models
  • Male
  • Middle Aged
  • Prospective Studies
  • Republic of Korea / epidemiology
  • SARS-CoV-2*
  • Young Adult