Researchers develop new model to predict death for COVID-19 patients – calculate your risk

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Many studies have determined the risk of mortality in patients infected with COVID-19 is greater among those with underlying health conditions. Mainly, the presence of underlying cardiovascular comorbidities in patients with COVID-19 is associated with higher mortality. However, researchers have developed a new model to help clinicians predict the risk of death within 40 days in patients who are hospitalised with a COVID-19 infection, drawing on six different risk factors.

The model, developed by researchers at Hackensack Meridian University Medical Centre and Berry Consultants, considers six risk factors: age, respiratory and oxygenation rates, as well as preexisting conditions such as high blood pressure, coronary artery disease or chronic kidney disease that play a role in COVID-19 deaths .

Data gathered from patients who were hospitalised with the virus showed that older age was determined to be the strong predictor of death.

A report from the US Centers for Disease Control and Prevention noted that 38 percent of COVID-19 patients had one or more underlying conditions.

Patients with comorbidities – which refers to the presence of one or more health conditions a patient is having with a primary illness – are more likely to require hospitalisation compared to individuals without additional risk factors.

Andrew IP, from the Division of Outcomes and Value Research at Hackensack University Medical Center, said: “It’s significant that severe COVID-19 disease has occurred principally among individuals with pre-existing comorbid conditions.”

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

The researchers developed and validated a prognostic mortality model that incorporated pre-existing comorbidities, drawing on data from more than 3,000 COVID-19 patients, 700 of which died.

Using this cohort, the researchers were able to quantify the risk of mortality within 40 days of hospitalisation for COVID-19 illness.

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

An online calculator of this 40-day COVID mortality risk core is available 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.”

The innovation comes as 21,052 new people have tested positive for Covid and 24 people died in the UK, according to latest government figures.

The figures compare with 24,470 infections and 65 fatalities reported yesterday, and 24,950 cases and 14 deaths announced this time last week.

This means the seven-day average for infections is currently down 27 percent from the previous week, while fatalities are up by 20.2 percent.

The data also shows that 6,326 COVID-19 patients were admitted to hospital in the last seven days, indicating a weekly rise of 14.8 percent.

Meanwhile, 21,266 people had their first dose of the coronavirus vaccine in the UK on Sunday, taking the total to 46,872,411.

The government has announced plans to rollout booster shots later this year.

The booster jabs will be administered to the first nine priority groups first.

Some 60 million doses of the Pfizer/BioBTech vaccine have been ordered – although it remains unclear whether this will be the only vaccine available.

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