HealthDay Reports: Model May Help Predict Risk for Testing Positive for COVID-19
Risk reduced with pneumococcal polysaccharide, flu vaccine; melatonin, paroxetine, or carvedilol use.
THURSDAY, June 25, 2020 (HealthDay News) -- It is possible to predict the likelihood of testing positive for COVID-19, according to a study published online June 10 in CHEST.
Lara Jehi, M.D., from the Cleveland Clinic, and colleagues developed a prospective registry of all patients tested for COVID-19 at the Cleveland Clinic to create individualized risk prediction models. A total of 11,672 patients were included in the development cohort, of whom 818 were positive for COVID-19, and 2,295 patients were included in the validation cohort, with 290 positive for COVID-19.
The researchers found that the risk for being positive for COVID-19 was increased for males, African-Americans, older patients, and those with known COVID-19 exposure. Those who had a pneumococcal polysaccharide or influenza vaccine or were on melatonin, paroxetine, or carvedilol had a reduced risk. The model had favorable discrimination in the development and validation cohorts (C-statistic, 0.863 and 0.840, respectively) and calibration.