Viral RNA Levels Can Predict COVID Mortality
Viral RNA levels in the blood is a reliable indicator in predicting COVID mortality, according to a study published in Science Advances.
“In our study, we were able to determine which biomarkers are predictors of mortality in the 60 days following the onset of symptoms,” said Université de Montréal medical professor Dr. Daniel Kaufmann, the study’s co-lead author alongside colleagues Nicolas Chomont and Andrés Finzi.
“Thanks to our data, we have successfully developed and validated a statistical model based on one blood biomarker,” viral RNA, Prof Kaufmann said.
Despite advances in COVID management, identifying patients at greater risk of dying of the disease has been difficult. Other studies identified various biomarkers, but assessing so many parameters is not possible in a clinical setting and gets in the way of doctors’ quick clinical decision-making ability.
Using blood samples from 279 patients hospitalised for COVID of differing severity, Kaufmann’s team measured amounts of inflammatory proteins, looking for any that stood out.
At the same time, Chomont’s team measured the amounts of viral RNA and in Finzi’s the levels of antibodies targeting the virus. Samples were collected 11 days after the onset of symptoms and patients were monitored for a minimum of 60 days after that.
The goal: to test the hypothesis that immunological indicators were associated with increased mortality.
“Among all of the biomarkers we evaluated, we showed that the amount of viral RNA in the blood was directly associated with mortality and provided the best predictive response, once our model was adjusted for the age and sex of the patient,” said Elsa Brunet-Ratnasingham, a doctoral student in Kaufmann’s lab and co-first author of the study.
“We even found that including additional biomarkers did not improve predictive quality,” she added.
Prof Kaufmann and Brunet-Ratnasingham tested the model on two independent cohorts of infected patients from Montreal’s Jewish General Hospital (recruited during the first wave of the pandemic) and the CHUM (recruited during the second and third waves).
No matter which hospital the patients were treated at, nor which period of the pandemic they fell into: in all cases, the predictive model worked. Now Prof Kaufmann and his colleagues want to put it to practical use.
“It would be interesting to use the model to monitor patients,” he said, “with the following question in mind: when you administer new treatments that have proven effective, is viral load still a predictive marker of mortality?”
Source: University of Montreal
