Predicting in-hospital mortality from Coronavirus Disease 2019: A simple validated app for clinical use

Abstract

Backgrounds: Validated tools for predicting individual in-hospital mortality of COVID-19 are lacking. We aimed to develop and to validate a simple clinical prediction rule for early identification of in-hospital mortality of patients with COVID-19.

Methods and findings: We enrolled 2191 consecutive hospitalized patients with COVID-19 from three Italian dedicated units (derivation cohort: 1810 consecutive patients from Bergamo and Pavia units; validation cohort: 381 consecutive patients from Rome unit). The outcome was in-hospital mortality. Fine and Gray competing risks multivariate model (with discharge as a competing event) was used to develop a prediction rule for in-hospital mortality. Discrimination and calibration were assessed by the area under the receiver operating characteristic curve (AUC) and by Brier score in both the derivation and validation cohorts. Seven variables were independent risk factors for in-hospital mortality: age (Hazard Ratio [HR] 1.08, 95% Confidence Interval [CI] 1.07-1.09), male sex (HR 1.62, 95%CI 1.30-2.00), duration of symptoms before hospital admission <10 days (HR 1.72, 95%CI 1.39-2.12), diabetes (HR 1.21, 95%CI 1.02-1.45), coronary heart disease (HR 1.40 95% CI 1.09-1.80), chronic liver disease (HR 1.78, 95%CI 1.16-2.72), and lactate dehydrogenase levels at admission (HR 1.0003, 95%CI 1.0002-1.0005). The AUC was 0.822 (95%CI 0.722-0.922) in the derivation cohort and 0.820 (95%CI 0.724-0.920) in the validation cohort with good calibration. The prediction rule is freely available as a web-app (COVID-CALC: https://sites.google.com/community.unipa.it/covid-19riskpredictions/c19-rp).

Conclusions: A validated simple clinical prediction rule can promptly and accurately assess the risk for in-hospital mortality, improving triage and the management of patients with COVID-19.

Fig 1

Cumulative incidence functions (CIFs) for in-hospital mortality and discharge of patients with Coronavirus Disease-19 in the derivation (1A) and validation cohorts (1B).

Fig 2. Cumulative Incidence Functions (CIFs) for in-hospital mortality of patients with Coronavirus Disease-19 according to three different patient profiles.

A: best profile (60 years old, female sex, duration of symptoms before hospital admission longer than 10 days, no comorbidities, and LDH levels of 250 U/L). B: intermediate profile (70 years old, male sex, duration of symptoms before hospital admission shorter than 10 days, chronic liver disease, LDH levels of 300 U/L.) C: worst profile (80 years old, male sex, duration of symptoms before hospital admission shorter than 10 days, coronary heart disease, chronic liver disease, diabetes, LDH levels of 400 U/L).