New risk models may help doctors predict mortality in hospitalized COVID patients

As the COVID-19 pandemic continues, researchers have developed and validated two simple risk measurement tools to help clinicians more accurately estimate a hospitalized patient’s COVID-19 risk of death. The two measurement models are called COVID-NoLab and COVID-SimpleLab. In collaboration with the Biobanque Québécoise de la COVID-19 in Montreal, Quebec, Canada, researchers examined patient records of individuals receiving care for COVID-19 in 11 hospitals between March 2020 and February 2021. Patient records were separated into two groups, and each patient record was categorized as low-, moderate-, or high-risk, identified from both the COVID-NoLab and COVID-SimpleLab models. 

Researchers found the two scoring systems could predict patient mortality rates with reasonable accuracy, offering clinicians a reliable way to quickly identify low-risk patients who could potentially be managed as outpatients in the event of a bed shortage. These prediction models may help decrease unnecessary hospital admissions during COVID-19 surges. 

External Validation of the COVID-NoLab and COVID-SimpleLab Prognostic Tools
Mark H. Ebell M.D., MS, et al
Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia

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