Rutgers researchers developed a way to help hospitals identify life-threatening COVID-19 cases using machine-learning software. The newly developed tool uses patient age and results from five routine tests to predict coronavirus disease progression. Its creators said they believe this new model could significantly improve outcomes for patients hospitalized with the virus, which remains the nation’s third leading cause of death.

“Accurate prognoses are extremely valuable,” said Payal Parikh, an internist, Robert Wood Johnson Medical School (RWJMS) associate professor and coauthor of the new paper in the journal mBio. “They let patients understand what’s coming while they’re still healthy enough to make informed treatment choices. They also let hospitals allocate resources efficiently by anticipating patient needs. Also, with better prognostication, we can start treatment early in the disease process, which leads to better patient care outcomes.” To read the full story.