A risk scoring system to predict progression to severe pneumonia in patients with Covid-19

Abstract

Rapid outbreak of coronavirus disease 2019 (Covid-19) raised major concern regarding medical resource constraints. We constructed and validated a scoring system for early prediction of progression to severe pneumonia in patients with Covid-19. A total of 561 patients from a Covid-19 designated hospital in Daegu, South Korea were randomly divided into two cohorts: development cohort (N = 421) and validation cohort (N = 140). We used multivariate logistic regression to identify four independent risk predictors for progression to severe pneumonia and constructed a risk scoring system by giving each factor a number of scores corresponding to its regression coefficient. We calculated risk scores for each patient and defined two groups: low risk (0 to 8 points) and high risk (9 to 20 points). In the development cohort, the sensitivity and specificity were 83.8% and 78.9%. In the validation cohort, the sensitivity and specificity were 70.8% and 79.3%, respectively. The C-statistics was 0.884 (95% CI 0.833-0.934) in the development cohort and 0.828 (95% CI 0.733-0.923) in the validation cohort. This risk scoring system is useful to identify high-risk group for progression to severe pneumonia in Covid-19 patients and can prevent unnecessary overuse of medical care in limited-resource settings.

Figure 1

Selection of study patients.

Figure 2

Discrimination ability of the severe pneumonia in prediction model in patients with Covid-19. Receiver operating characteristics (ROC) curves for predictive value in the (A) development cohort: fitted value, (B) development cohort: KDDH score, (C) validation cohort: fitted value, and (D) validation cohort: KDDH score.

Figure 3

Calibration ability of the severe pneumonia prediction model in patients with Covid-19. The calibration bar plot in the development cohort (A) and the validation cohort (B).