Researchers at Cleveland Clinic have created the first risk prediction model that allows healthcare providers to find the likelihood of an individual patient testing positive for COVID—19, as well as possible outcomes from the virus.
The team published findings from a study of their risk prediction model, which is known as nomogram, in CHEST.
“The ability to accurately predict whether or not a patient is likely to test positive for COVID-19, as well as potential outcomes including disease severity and hospitalization, will be paramount in effectively managing our resources and triaging care,” Lara Jehi, MD, Cleveland Clinic’s chief research information officer and corresponding author on the study, said in a statement. “As we continue to battle this pandemic and prepare for a potential second wave, understanding a person’s risk is the first step in potential care and treatment planning.”
The model found several insights, including that those who received the flu vaccine and the pneumococcal polysaccharide vaccine (PPSV23) are less likely to test positive for COVID19 compared to those who are non-vaccinated. Patients who take certain drugs, such as melatonin, carvedilol or paroxetine, are also less likely to test positive. However, more studies are needed to determine if this association has an effect on disease progression, researchers noted.
Further, patients of lower socioeconomic status are more likely to test positive compared to patients of greater economic means, and patients of Asian descent are less likely to test positive than Caucasian patients.
“Our findings corroborated several risk factors already reported in existing literature––including that being male and of advancing age both increase the likelihood of testing positive for COVID-19––but we also put forth some new associations,” Jehi said. “Further validation and research are needed into these initial insights, but these correlations are extremely intriguing.”
The nomogram is being deployed as an online risk calculator, taking into account age, race, gender, socioeconomic status, vaccination history and current medications, as a free tool. Cleveland Clinic used data from nearly 12,000 enrolled patients in its COVID-19 Registry, which includes all patients that are tested whether or not they are positive.
“This nomogram will bring precision medicine to the COVID-19 pandemic, helping to enable researchers and physicians to predict an individual’s risk of testing positive,” said co-author on the study Michael Kattan, PhD, chair of Lerner Research Institute’s Department of Quantitative Health Sciences. “Additionally, while testing solutions continue to be needed, it is so important to make sure we are responsibly and optimally dispatching our resources - including clinical personnel, personal protective equipment and hospital beds. Our risk prediction model stands to greatly assist hospital systems in this planning.”
Amy joined TriMed Media as a Senior Writer for HealthExec after covering home care for three years. When not writing about all things healthcare, she fulfills her lifelong dream of becoming a pirate by sailing in regattas and enjoying rum. Fun fact: she sailed 333 miles across Lake Michigan in the Chicago Yacht Club "Race to Mackinac."