COVID-19 mortality risk assessment: An international multi-center study

Abstract

Timely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality risk calculator for hospitalized COVID-19 patients. De-identified data was obtained for 3,927 COVID-19 positive patients from six independent centers, comprising 33 different hospitals. Demographic, clinical, and laboratory variables were collected at hospital admission. The COVID-19 Mortality Risk (CMR) tool was developed using the XGBoost algorithm to predict mortality. Its discrimination performance was subsequently evaluated on three validation cohorts. The derivation cohort of 3,062 patients has an observed mortality rate of 26.84%. Increased age, decreased oxygen saturation (≤ 93%), elevated levels of C-reactive protein (≥ 130 mg/L), blood urea nitrogen (≥ 18 mg/dL), and blood creatinine (≥ 1.2 mg/dL) were identified as primary risk factors, validating clinical findings. The model obtains out-of-sample AUCs of 0.90 (95% CI, 0.87–0.94) on the derivation cohort. In the validation cohorts, the model obtains AUCs of 0.92 (95% CI, 0.88–0.95) on Seville patients, 0.87 (95% CI, 0.84–0.91) on Hellenic COVID-19 Study Group patients, and 0.81 (95% CI, 0.76–0.85) on Hartford Hospital patients. The CMR tool is available as an online application at covidanalytics.io/mortality_calculator and is currently in clinical use. The CMR model leverages machine learning to generate accurate mortality predictions using commonly available clinical features. This is the first risk score trained and validated on a cohort of COVID-19 patients from Europe and the United States.

Development of a multivariable prediction model for severe COVID-19 disease: a population-based study from Hong Kong

“…As reported, the most frequently reported predictors were age, clinical status such as temperature, imaging results from chest radiography, and lymphocyte count. Recently, a study including 3927 patients from 33 hospitals developed the COVID-19 Mortality Risk (CMR) tool using the XGBoost algorithm 27 . This score is based on age, blood urea nitrogen, CRP, creatinine, glucose, AST, and platelet counts.…”

Mortality Rate of Patients With COVID-19 Based on Underlying Health Conditions

“…1 Generally, COVID-19 is more severe in people aged >60 years or those with underlying diseases. 2,3 Research on COVID-19 has been conducted from various perspectives, such as infection cases, 4,5 clinical characteristics, [6][7][8] and preventive measures. 9 In addition, several studies have confirmed that COVID-19 is more severe in older people and those with underlying diseases, such as lung or heart disease, diabetes, and immunological diseases.…”

Predictive Values of Biochemical Markers As Early Indicators for Severe COVID-19 Cases in Admission

“…It has been reported that levels of CRP above 130 mg/l may be associated with increased mortality [ 3 ]. Albumin levels are significantly lower in severe COVID-19, but the change in albumin levels does not parallel the severity of hepatocellular damage.…”

“…In recent years, combined analysis of liver enzymes and platelet counts has provided important information on new biomarkers used to determine the severity of infectious and neoplastic diseases [ 1 , 2 ]. Moreover, thrombocytopenia and lymphopenia in severe COVID-19 patients are associated with an increased risk and even coagulopathy has poor prognosis [ 3 , 4 ]. Elevated aspartate aminotransferase lymphocyte ratio index (ALRI) levels prior to treatment seem to be indicators of poor prognosis in colorectal cancer [ 5 ].…”