Development and calibration of a simple mortality risk score for hospitalized COVID-19 adults
Authors: Yoo Edwin , Percha Bethany , Tomlinson Max , Razuk Victor , Pan Stephanie , Basist Madeleine , Tandon Pranai , Wang Jing Gennie , Gao Cynthia , Bose Sonali , Gidwani Umesh 
Published: September 2020

Objectives

Mortality risk scores, such as SOFA, qSOFA, and CURB-65, are quick, effective tools for communicating a patient’s prognosis and guiding therapeutic decisions. Most use simple calculations that can be performed by hand. While several COVID-19 specific risk scores exist, they lack the ease of use of these simpler scores. The objectives of this study were (1) to design, validate, and calibrate a simple, easy-to-use mortality risk score for COVID-19 patients and (2) to recalibrate SOFA, qSOFA, and CURB-65 in a hospitalized COVID-19 population.

Design

Retrospective cohort study incorporating demographic, clinical, laboratory, and admissions data from electronic health records.

Setting

Multi-hospital health system in New York City. Five hospitals were included: one quaternary care facility, one tertiary care facility, and three community hospitals.

Participants

Patients (n=4840) with laboratory-confirmed SARS-CoV2 infection who were admitted between March 1 and April 28, 2020.

Main outcome measures

Gray’s K-sample test for the cumulative incidence of a competing risk was used to assess and rank 48 different variables’ associations with mortality. Candidate variables were added to the composite score using DeLong’s test to evaluate their effect on predictive performance (AUC) of in-hospital mortality. Final AUCs for the new score, SOFA, qSOFA, and CURB-65 were assessed on an independent test set.

Results

Of 48 variables investigated, 36 (75%) displayed significant (p<0.05 by Gray’s test) associations with mortality. The variables selected for the final score were (1) oxygen support level, (2) troponin, (3) blood urea nitrogen, (4) lymphocyte percentage, (5) Glasgow Coma Score, and (6) age. The new score, COBALT, outperforms SOFA, qSOFA, and CURB-65 at predicting mortality in this COVID-19 population: AUCs for initial, maximum, and mean COBALT scores were 0.81, 0.91, and 0.92, compared to 0.77, 0.87, and 0.87 for SOFA. We provide COVID-19 specific mortality estimates at all score levels for COBALT, SOFA, qSOFA, and CURB-65.

Conclusions

The COBALT score provides a simple way to estimate mortality risk in hospitalized COVID-19 patients with superior performance to SOFA and other scores currently in widespread use. Evaluation of SOFA, qSOFA, and CURB-65 in this population highlights the importance of recalibrating mortality risk scores when they are used under novel conditions, such as the COVID-19 pandemic. This study’s approach to score design could also be applied in other contexts to create simple, practical and high-performing mortality risk scores.

Trial registration

NA

Funding source

The authors declare that there was no external funding provided.

Summary box

What is already known on this topic

Mortality risk scores are widely used in clinical settings to facilitate communication with patients and families, guide goals of care discussions, and optimize resource allocation.

Although popular mortality risk scores like SOFA, qSOFA, and CURB-65 are routinely used in COVID-19 populations, they were originally calibrated in different contexts and their true performance among hospitalized COVID-19 patients is unknown.

Several dedicated COVID-19 mortality risk scores have been created during the 2019-2020 pandemic, but all use complicated formulae or machine learning algorithms and are difficult or impossible to calculate by hand, limiting their applicability at the bedside.

What this study adds

We describe a data-driven, simple, and hand-calculable COVID-specific mortality risk score (COBALT) that has superior performance to SOFA, qSOFA, and CURB-65 in a hospitalized COVID-19 patient population.

We provide COVID-specific mortality estimates for SOFA, qSOFA, and CURB-65 using data from 4840 patients in a large and diverse New York City multihospital health system.