Infection with SARS-CoV-2 and development of COVID-19 disease is associated with a deleterious effect in renal function and structure. This was expected to potentially alter the molecular composition of urine. Since COVID-19 evolved in 2019, there have been numerous reports of acute kidney injury (AKI) associated with this infection. The incidence of AKI in COVID-19 patients has been estimated to range from about 27–50+%. Early in the pandemic, several groups noted a correlation of disease severity, hospitalization, and intensive care admissions with increased risk for developing AKI. This was not surprising. The contribution of cardiopulmonary dysfunction, renal hypoperfusion, and/or multidrug therapy leading to the development AKI has been well-known for decades prior to COVID-19 .

In collaboration with community physicians and physicians affiliated with Carilion Clinic, the RTI Team conducted a study focused on using UMF to detect COVID19 infection.  UMF had an overall prediction accuracy of 97.6% for detecting complex, multimolecular fingerprints in urine associated with COVID-19 disease. The sensitivity of this model for detecting COVID-19 was 90.9%. The specificity was 98.8%, the positive predictive value was 93.0%, and the negative predictive value was 98.4%. In assessing severity, the method showed to be accurate in identifying symptoms as mild, moderate, or severe (random chance = 33%) based on the urine multimolecular fingerprint.

A UMF fingerprint of ‘Long COVID-19’ symptoms (defined as lasting longer than 30 days) was located in urine. Our methods were able to locate the presence of this fingerprint with 70.0% sensitivity and 98.7% specificity in leave-one-out cross-validation analysis (Robertson JL, Senger RS, et al)