Outils de partage

COVID-19: A blood sample to predict risk of death

A simple blood test could help physicians assess a person’s risk of death from COVID-19. More specifically, a significant quantity of viral RNA (genetic code) has emerged as a good indicator of whether a patient with coronavirus will survive. A study led by Daniel Kaufmann, professor in the Faculty of Medicine at Université de Montréal, and his colleagues Nicolas Chomont and Andrés Finzi at the Centre de recherche du CHUM, has revealed that combining the parameter and the patient’s age and sex helps better determine the risk.

Since the start of the pandemic, the researchers have been seeking a way to anticipate the risk of death in patients hospitalized with moderate to severe COVID-19 in order to identify the most effective treatment options.

The experts recruited their first cohort at the CHUM. They used the blood samples they collected to measure the quantity of inflammatory proteins, viral RNA and antibodies in patients’ blood about 11 days after the onset of their first symptoms and then followed the individuals for at least 60 days. The aim was to pinpoint the markers linked to high mortality, and the work led to the development of a statistical model that relies on the quantity of viral RNA to predict a patient’s risk of succumbing to COVID-19.

During the second and third waves of the pandemic, the same analyses were conducted with patients hospitalized at the Jewish General Hospital and CHUM to confirm the model’s reliability. The researchers are currently repeating the studies on vaccinated subjects. Indeed, the vaccine is game-changing on account of the increased presence of antibodies in the bloodstream. The team also refined the tests and approach by taking different variants into account.

But is viral RNA in blood a valid indicator when new treatments such as cortisone, anti-inflammatories and antivirals are administered? The question is still open but, if viral RNA turns out to be a critical parameter, Daniel Kaufmann believes it could also be used to assess the effectiveness of COVID-19 treatments.

When the model has been confirmed and tested in clinical trials, it could be rolled out across the health network to support professionals treating coronavirus, as well as other respiratory viruses.