Siemens Healthineers launched an AI-based tool that helps predict which patients with COVID-19 are at risk of progressing to severe medical outcomes.
Leveraging de-identified COVID-19 patient data from more than 14,000 COVID-19 patients from multiple healthcare institutions worldwide, nine clinically significant lab parameters were identified and selected for inclusion in the algorithm. In addition to patient age, they are D-dimer, Lactate dehydrogenase (LDH), Lymphocyte %, Eosinophil %, Creatinine, C-reactive protein (CRP), Ferritin, PT-INR, and high-sensitivity Cardiac Troponin-I.
The Atellica COVID-19 Severity Algorithm, which is for educational use only, is available on the company's website. By entering a potential patient’s lab values and age, the algorithm will generate a COVID-19 clinical severity score, including the projected probability of progression to ventilator use, end-stage organ damage, and 30-day in-hospital mortality.
The company partnered with the Hospital Universitario of La Paz, Spain, to gather COVID-19 patient data to build the algorithm and later to test the accuracy of the tool via a retrospective analysis.
