University Of Montreal Study Shows That The Amount Of Viral RNA In The Blood Is A Reliable Indicator Of COVID-19 Mortality Risk
: A new study by researchers from the University of Montreal-Canada has shown that measuring the amount of viral RNA in the blood is a reliable indicator of COVID-19 mortality risk.
To date, despite advances in COVID-19 management, identifying patients evolving toward death remains challenging.
In order the to identify early predictors of mortality within 60 days of symptom onset (DSO), the study team performed immunovirological assessments on plasma from 279 individuals.
On samples collected at DSO11 in a discovery cohort, high severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA (vRNA), low receptor binding domain–specific immunoglobulin G and antibody-dependent cellular cytotoxicity, and elevated cytokines and tissue injury markers were strongly associated with mortality, including in patients on mechanical ventilation.
A three-variable model of vRNA, with predefined adjustment by age and sex, robustly identified patients with fatal outcome (adjusted hazard ratio for log-transformed vRNA = 3.5). This model remained robust in independent validation and confirmation cohorts. Since plasma vRNA’s predictive accuracy was maintained at earlier time points, its quantitation can help doctors and researchers understand disease heterogeneity and identify patients who may benefit from new therapies.
The study findings were published in the peer reviewed journal: Science Advances. https://www.science.org/doi/10.1126/sciadv.abj5629
Medical professor Dr Daniel Kaufmann from the Université de Montréal told Thailand Medical News
, “The amount of a SARS-CoV-2 genetic material-;viral RNA-;in the blood is a reliable indicator in detecting which patients will die of the disease.”
Dr Kaufmann and his team conducted the research work at the CRCHUM, the research arm of Univerity of Montreal's teaching hospital, the Centre hospitalier de l'Université de Montréal.
Dr Kaufmann added, "In our study, we were able to determine which biomarkers are predictors of mortality in the 60 days following the onset of symptoms."
CRCHUM researchers Dr Nicolas Chomont and Dr Andrés Finzi who assisted on the study added, "Thanks to our data, we have successfully developed and validated a statistical model based on one blood biomarker-viral RNA.”
To date physicians have found it hard to identify patients most at risk of dying of the disease and so be able to offer them new treatments.
study found that although several biomarkers have been identified in other studies, but juggling the profusion of parameters is not possible in a clinical setting and hinders doctors' ability to make quick medical decisions.
Utilizing blood samples collec
ted from 279 patients during their hospitalization for COVID-19, ranging in degrees of severity from moderate to critical, Dr Kaufmann's team measured amounts of inflammatory proteins, looking for any that stood out.
Simultaneously, Dr Chomont's team measured the amounts of viral RNA and Dr 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 key objective of the study was to test the hypothesis that immunological indicators were associated with increased mortality.
Elsa Brunet-Ratnasingham, a doctoral student in Kaufmann's lab and co-first author of the study added, “Interestingly among all of the biomarkers evaluated, the study findings 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.”
The young researcher, whose work benefited from an UdeM COVID-19 Excellence Grant further added, "We even found that including additional biomarkers did not improve predictive quality.”
In order to confirm its effectiveness, Dr Kaufmann and Dr 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).
Importantly it made no difference which hospital the patients were treated at, nor which period of the pandemic they fell into: in all cases, the predictive model worked. Currently Dr Kaufmann and his colleagues want to put it to practical use.
Dr Kaufmann added, "It would be interesting to use the model to monitor patients, with the following question in mind: when you administer new treatments that have proven effective, is viral load still a predictive marker of mortality?"
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