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University of Michigan issued the following announcement on Dec. 23.
New algorithm helps clinicians flag patients who need more care.
A patient enters the hospital struggling to breathe— they have COVID-19. Their healthcare team decides to admit them to the hospital. Will they be one of the fortunate ones who steadily improves and are soon discharged? Or will they end up needing mechanical ventilation?
That question may be easier to answer, thanks to a recent study from Michigan Medicine describing an algorithm to predict which patients are likely to quickly deteriorate while hospitalized.
“You can see large variability in how different patients with COVID-19 do, even among close relatives with similar environments and genetic risk,” says Nicholas J. Douville, M.D., Ph.D., of the Department of Anesthesiology, one of the study’s lead authors. “At the peak of the surge, it was very difficult for clinicians to know how to plan and allocate resources.”
Combining data science and their collective experiences caring for COVID-19 patients in the intensive care unit, Douville, Milo Engoren, M.D., and their colleagues explored the potential of predictive machine learning. They looked at a set of patients with COVID-19 hospitalized during the first pandemic surge from March to May 2020 and modeled their clinical course.
Original source can be found here.
Source: University of Michigan
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