We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
Sekisui Diagnostics UK Ltd.

Download Mobile App





SARS-CoV-2 Blood Biomarker Identifies Infected Patients Most at Risk of Dying of COVID-19

By HospiMedica International staff writers
Posted on 29 Nov 2021
Print article
Illustration
Illustration

A statistical model developed by researchers uses a blood biomarker of SARS-CoV-2 to identify infected patients who are most at risk of dying of COVID-19.

The study by researchers at the Université de Montréal (Montréal, Canada) found that 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. Despite advances in the management of COVID-19, doctors have found it hard to identify patients most at risk of dying of the disease and so be able to offer them new treatments. 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.

Using blood samples collected from 279 patients during their hospitalization for COVID-19, ranging in degrees of severity from moderate to critical, the research team measured amounts of inflammatory proteins, looking for any that stood out. At the same time, the researchers also measured the amounts of viral RNA and 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 was 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 and co-first author of the study. “We even found that including additional biomarkers did not improve predictive quality.”

“In our study, we were able to determine which biomarkers are predictors of mortality in the 60 days following the onset of symptoms,” said Dr. Daniel Kaufmann, Université de Montréal medical professor who led the research team. “Thanks to our data, we have successfully developed and validated a statistical model based on one blood biomarker,” viral RNA.

Related Links:
Université de Montréal 

Gold Member
Disposable Protective Suit For Medical Use
Disposable Protective Suit For Medical Use
Gold Member
POC Blood Gas Analyzer
Stat Profile Prime Plus
Silver Member
Compact 14-Day Uninterrupted Holter ECG
NR-314P
New
Ultra Low Floor Level Bed
Solite Pro

Print article

Channels

Surgical Techniques

view channel
Image: LUMISIGHT and Lumicell DVS offer 84% diagnostic accuracy in detecting residual cancer (Photo courtesy of Lumicell)

Cutting-Edge Imaging Platform Detects Residual Breast Cancer Missed During Lumpectomy Surgery

Breast cancer is becoming increasingly common, with statistics indicating that 1 in 8 women will develop the disease in their lifetime. Lumpectomy remains the predominant surgical intervention for treating... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The Quantra Hemostasis System has received US FDA special 510(k) clearance for use with its Quantra QStat Cartridge (Photo courtesy of HemoSonics)

Critical Bleeding Management System to Help Hospitals Further Standardize Viscoelastic Testing

Surgical procedures are often accompanied by significant blood loss and the subsequent high likelihood of the need for allogeneic blood transfusions. These transfusions, while critical, are linked to various... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.