CAP TODAY Pathology/Laboratory Medicine/Laboratory Management
Aug. 12, 2021—Siemens Healthineers has developed the Atellica COVID-19 Severity Algorithm, a model designed to help predict the potential likelihood of progression to severe disease and life-threatening multiorgan dysfunction in COVID-19 patients. Using deidentified COVID-19 patient data from more than 14,000 COVID-19 patients from health care institutions around the world, nine clinically significant lab parameters were selected for inclusion in the algorithm. Patient age, D-dimer, lactate dehydrogenase, lymphocyte percentage, eosinophil percentage, creatinine, C-reactive protein, ferritin, PT-INR, and high-sensitivity cardiac troponin-I are used to help predict the likelihood of disease progression.
“We want health care providers to have access to a predictive tool that leverages our expertise in artificial intelligence and helps advance the understanding of how to improve patient care for those affected by COVID-19,” Deepak Nath, PhD, president of laboratory diagnostics at Siemens Healthineers, said in a press release. “With much of the world still in the throes of the pandemic, facing strict resource allocations, the ability to quickly identify patients at risk of progressing to severe disease in real time could potentially assist in expediting triage.”