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Model May Help Predict Risk for Testing Positive for COVID-19

Last Updated: June 25, 2020.

It is possible to predict the likelihood of testing positive for COVID-19, according to a study published online June 10 in CHEST.

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.

"We provide an online risk calculator that can effectively identify individualized risk of a positive COVID-19 test," the authors write. "Such a tool provides immediate benefit to our patients and health care providers as we face anticipated increased demand and limited resources, but does not obviate the critical need for adequate testing."

One author disclosed financial ties to the pharmaceutical industry.

Abstract/Full Text (subscription or payment may be required)


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