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Experts create new COVID-19 death prediction model – this is how you can calculate your risk

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Manish Saini
Manish works as a Journalist and writer at Revyuh.com. He has studied Political Science and graduated from Delhi University. He is a Political engineer, fascinated by politics, and traditional businesses. He is also attached to many NGO's in the country and helping poor children to get the basic education. Email: Manish (at) revyuh (dot) com

COVID-19 patients with underlying medical conditions are at a higher risk of infection-related death. Scientists have now created a model that can predict whether or not someone infected with COVID-19 will die as a result of the infection.

Many studies have found that patients infected with COVID-19 have a higher risk of death if they have underlying health problems. The presence of underlying cardiovascular comorbidities in COVID-19 patients is linked to a higher mortality rate.

However, using six different risk factors, researchers have developed a new model to help clinicians predict the risk of death within 40 days in patients hospitalised with a COVID-19 infection.

The model, created by researchers at Hackensack Meridian University Medical Center and Berry Consultants, takes into account six risk factors, including age, respiratory and oxygenation rates, as well as preexisting conditions like high blood pressure, coronary artery disease, or chronic kidney disease, all of which play a role in COVID-19 deaths.

According to data collected from patients who were hospitalized with the virus, older age was found to be a strong predictor of death.

A report from the CDC also suggests 38 percent of COVID-19 patients had one or more underlying conditions.

Patients with comorbidities, or the presence of one or more health conditions in addition to a primary illness, are more likely to require hospitalization than those without additional risk factors.

Andrew IP of Hackensack University Medical Center’s Division of Outcomes and Value Research stated:

“It’s significant that severe COVID-19 disease has occurred principally among individuals with pre-existing comorbid conditions.”

Furthermore, high fatality rates among the elderly and those residing in nursing homes have been reported.

The team created and validated a prognostic mortality model that took into account pre-existing comorbidities using data from over 3,000 COVID-19 patients, 700 of whom died.

Using this cohort, the researchers were able to calculate the risk of death within 40 days of being admitted to the hospital for COVID-19 illness.

Six factors were identified as independent predictors of mortality from 22 potential candidates and were included in the risk score: age, respiratory rate, oxygenation, high blood pressure, coronary artery disease, or chronic renal disease.

This 40-day COVID mortality risk score can be calculated online here.

Brett Lewis, one of the study authors, noted:

“The ability to predict death or survival of patients with severe COVID-19 infection, upon entry to hospital, based on preexisting comorbidities and presenting features, would permit healthcare teams to strategise individual treatment planning, more accurately evaluate the efficacy of new therapies, and assist in public-health resource allocations.”

Image Credit: Getty

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