Researchers discover predictors of COVID-19 cases that fare the worst
Mount Sinai scientists have identified two markers of inflammation that reliably predict the severity of COVID-19 cases and likelihood of survival, providing a foundation for a diagnostic platform and therapeutic targets, according to a study published in Nature Medicine in August.
The researchers studied four proteins known as cytokines that circulate in blood and are commonly associated with infections, and found that two of them, called IL-6 and TNF-α, were able to predict which patients were likely to develop more severe forms of COVID-19 and die.
The results from the tests showed that the risk of death in patients with elevated IL-6 or TNF-α was twofold or higher, even when considering other known risk factors. Scientists then validated their predictive model using samples from an additional cohort of 231 hospitalized COVID-19 patients.
The researchers looked at how various treatments attempted in a subset of these patients affected the cytokines they measured. They found that treatments recently found to benefit COVID-19 patients, such as the antiviral remdesivir or the corticosteroid dexamethasone, could lower the levels of the cytokines.
Based on these results, scientists propose that monitoring COVID-19 patients for these cytokines can help determine their prognosis, and that any treatment should be potentially administered in the context of cytokine measurements, since it affects outcome.
The researchers propose that these findings also call for the use of drugs targeting IL-6 and TNF-α by themselves or combined at the same time, to be tested for their potential benefit based on elevated starting levels.