An online tool to help predict the risk of COVID-19 mortality

Published: July 22, 2020

Coronavirus disease 2019 (COVID-19) has rapidly become a global pandemic. Since the severity of the disease is highly variable, predictive models to stratify patients according to their mortality risk are needed.

In a research article recently published in The Journal of Allergy and Clinical Immunology (JACI), Laguna-Goya and her colleagues present a predictive model which provides a quantifiable risk of death in COVID-19 patients, including patients without shortness of breath at the time of evaluation, which can help guide medical decisions.

The researchers included 501 patients diagnosed with COVID-19 in their analysis and assessed the ability of several biomarkers measured at the beginning of hospitalization to predict mortality. Increased levels of interleukin-6 (IL-6), C-reactive protein, lactate dehydrogenase (LDH), ferritin, D-dimer, neutrophil count, and neutrophil-to-lymphocyte (N/L) ratio, and decreased levels of albumin, lymphocyte count, monocyte count and peripheral blood oxygen saturation/fraction of inspired oxygen ratio (SpO2/FiO2), were all good predictors of mortality.

Of those, the five best biomarkers (SpO2/FiO2, N/L ratio, LDH, IL-6, and age) were selected to develop a multivariable mortality risk model, which showed high accuracy for the prediction of death by COVID-19. Based on this model, the online calculator COR+12 was developed, which provides a probability of death in a given patient by introducing the five biomarkers (https://utrero-rico.shinyapps.io/COR12_Score/).

This mortality risk model allows early risk stratification of COVID-19 hospitalized patients, before the appearance of obvious signs of clinical deterioration, and can be used as a tool to guide clinical decision-making.

The Journal of Allergy and Clinical Immunology (JACI) is an official scientific journal of the AAAAI, and is the most-cited journal in the field of allergy and clinical immunology.

Full Article