Researchers at the University of Texas Medical Branch have developed a quick and affordable model to predict if a COVID-19 patient will get a more severe case of the disease, according to a news release.
Identifying those patients at most risk can be done within the first 12 hours of hospital admission, researchers from the Infectious Disease Division at UTMB wrote in a study published in BMJ Open.
From a global perspective, the world needs this type of help, one of the study’s authors said.
“While the pandemic might be near an end in the United States, other places are not nearly through with COVID,” said John Davis, one of the authors who is a medical student in Population Health Sciences at UTMB. Davis is also the Clinical Education Activities and Operations Director for St. Vincent's Clinics.
These other places with fewer resources don’t have effective vaccines and therapies, Davis said. They could benefit from an easy, fast assessment that would cost about $25 per person. That way, they could better allocate the resources they do have.
While researchers measured many variables in their study of 329 hospital patients, three factors stood out as the most consistent indicators of severe COVID-19: age, body mass index (BMI) and a blood test to measure lactate dehydrogenase (LDH). The higher all three of these indicators were, the worse the patient’s case of COVID progressed.
“We’re making it user-friendly so that you could go to MyChart and find the values to put in this model,” Davis said.
Even though the cases of COVID-19 have declined, the chance of a new variant surge is possible. This type of research—building models based on demographic and clinical data—can help the demand for healthcare when the next pandemic strikes, Davis said.
