Objective: To develop and validate a prediction model of mortality in patients with COVID-19 attending hospital emergency rooms.
Design: Multivariable prognostic prediction model.
Setting: 127 Spanish hospitals.
Participants: Derivation (DC) and external validation (VC) cohorts were obtained from multicentre and single-centre databases, including 4035 and 2126 patients with confirmed COVID-19, respectively.
Interventions: Prognostic variables were identified using multivariable logistic regression.
Main outcome measures: 30-day mortality.
Results: Patients' characteristics in the DC and VC were median age 70 and 61 years, male sex 61.0% and 47.9%, median time from onset of symptoms to admission 5 and 8 days, and 30-day mortality 26.6% and 15.5%, respectively. Age, low age-adjusted saturation of oxygen, neutrophil-to-lymphocyte ratio, estimated glomerular filtration rate by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, dyspnoea and sex were the strongest predictors of mortality. Calibration and discrimination were satisfactory with an area under the receiver operating characteristic curve with a 95% CI for prediction of 30-day mortality of 0.822 (0.806-0.837) in the DC and 0.845 (0.819-0.870) in the VC. A simplified score system ranging from 0 to 30 to predict 30-day mortality was also developed. The risk was considered to be low with 0-2 points (0%-2.1%), moderate with 3-5 (4.7%-6.3%), high with 6-8 (10.6%-19.5%) and very high with 9-30 (27.7%-100%).
Conclusions: A simple prediction score, based on readily available clinical and laboratory data, provides a useful tool to predict 30-day mortality probability with a high degree of accuracy among hospitalised patients with COVID-19.
Keywords: clinical epidemiology; critical care; emergency medicine; pneumonia; respiratory infection; viral infection.
© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.