KATHMANDU: A team of researchers have developed a risk calculator to predict an individual’s risk of testing positive for Covid-19 and their outcomes for the disease.
The researchers at Cleveland Clinic developed a risk prediction model from the prospective registry of all patients tested for COVID-19 in Cleveland Clinic.
The data scientists used statistical algorithms to transform data from registry patients’ electronic medical records into the first-of-its-kind nomogram.
“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,” said Lara Jehi, M.D., Cleveland Clinic’s Chief Research Information Officer and corresponding author on the study. “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 risk calculator, a new tool for healthcare providers, was developed using the data from 11,672 patients enrolled in the Cleveland Clinic COVID-19 Registry which included all individuals tested at the clinic for the disease, not just those that test positive.
The study further elaborated that the patients who had pneumococcal polysaccharide or influenza vaccine were at the low risk of being infected with the novel coronavirus.
Similarly, the risk of contracting coronavirus was found to be low on those who were on melatonin (over-the-counter sleep aid), paroxetine (anti-depressant), or carvedilol (high blood pressure and heart failure treatment) medications.
These three medications were among the other drugs that were included as potential drugs for COVID-19 treatments in a network medicine study led by Lerner Research Institute scientists.
The study also found that people of Asian descent are less likely than Caucasian patients to test positive for the virus. The study also revealed that people in low socioeconomic status are more likely to test positive that high economic status.
“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 Michael Kattan, a co-author on the study and Chair of Lerner Research Institute’s Department of Quantitative Health Sciences.