Researchers publish COVID-19 “prediction model”

Using demographic and clinical data gathered from seven weeks of novel coronavirus  (COVID-19) patient care across five hospitals, Johns Hopkins researchers published a prediction model they say can help other hospitals care for COVID-19 patients, and make decisions about planning and resource allocations, according to a new study published in the Annals of Internal Medicine.

For the study, researchers examined data a registry of all patients treated for COVID-19 infection at hospitals in the Johns Hopkins system between March 4 and April 24. During that time, The Johns Hopkins Hospital, Johns Hopkins Bayview Medical Center, Howard County General Hospital, Suburban Hospital and Sibley Memorial Hospital admitted a combined 827 people age 18 years or older, 336 Black, 264 white, 135 Hispanic, 48 Asian, 2 Native American and 42 multiracial, who tested positive for the coronavirus and had symptoms of COVID-19.

From the data those patients generated, the researchers developed a prediction model using a set of risk factors known to be associated with COVID-19 to forecast how likely a patient's disease is to worsen while being treated in a hospital and at what point in their care that might happen. Among the risk factors researchers considered as part of the model were a patient's age, body mass index (BMI), lung health and chronic disease, as well as vital signs and the severity of a patient's COVID-19 symptoms at the time of admission.

The model, COVID Inpatient Risk Calculator (CIRC), is available online. The researchers said the calculator is meant to help hospital physicians and other healthcare providers assess the risk of a patient's condition worsening.

Among the highlights of the study was the rapidity with which the disease can progress from mild or moderate to severe, particularly if a patient had all or some of the risk factors associated with the disease. Forty-five of the patients in the study had severe COVID-19 when they were admitted to the hospital. But 120 patients developed severe disease or died within 12 hours of being admitted. Of the 302 patients in the study who developed severe disease or died, the median time of disease progression was 1.1 days.

For example, the researchers estimate that a 60-year-old white woman with a BMI of 28, no chronic disease and no fever who is hospitalized for COVID-19 has a 10 percent chance of her disease worsening by day two of her hospital stay. The longer she's in the hospital, the greater that chance becomes, at 15 percent after four days and 16 percent after a week.

Conversely, the researchers considered an 81-year-old Black woman admitted to the hospital with COVID-19. The hypothetical patient has a BMI of 35, diabetes, hypertension, and a fever. CIRC forecasts her probability of progressing to severe disease or even death by just the second day of her hospital stay is 89 percent. That percentage increases to higher than 95 percent by days four and seven.

By June 24, 694 of the patients in the study had been discharged from the hospital, 131 had died, and seven were still hospitalized with severe COVID-19, according to the study.

“This is some of what we've learned in the months since we started seeing patients with COVID-19 at our hospitals,” said Brian Garibaldi, MD, lead author and associate professor of medicine at the Johns Hopkins University School of Medicine, in a statement. “As we continue to grapple with high numbers of COVID-19 infections across the United States, it's important to share knowledge with our colleagues at other hospitals."

Editor's note: Click here for more information and ongoing COVID-19 updates for integrative healthcare professionals.