Health Life

Researchers develop model to predict likelihood of testing positive for COVID-19, disease outcomes

Credit: CC0 Public Domain

Cleveland Clinic researchers have developed the world’s first risk prediction model for healthcare providers to forecast an individual patient’s likelihood of testing positive for COVID-19 as well as their outcomes from the disease.

According a new study published in Chest, the risk prediction model (called a nomogram) shows the relevance of age, race, gender, , vaccination history and current medications in COVID-19 risk. The risk calculator is a new tool for to aid them in predicting patient risk and tailoring decision-making about care. It provides a more scientific approach to testing which is important for the healthcare community which has faced increased demand for testing and limited resources.

“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 nomogram, which has been deployed as a freely available online risk calculator at , was developed using data from nearly 12,000 patients enrolled in Cleveland Clinic’s COVID-19 Registry, which includes all individuals tested at Cleveland Clinic for the disease, not just those that test positive.

Data scientists, including co-author on the study Michael Kattan, Ph.D., Chair of Lerner Research Institute’s Department of Quantitative Health Sciences, used statistical algorithms to transform data from registry patients’ electronic medical records into the first-of-its-kind nomogram.

This study revealed several novel insights into disease risk, including:

  • Patients who have received the pneumococcal polysaccharide vaccine