LONDON (Reuters) - British scientists have developed a four-level scoring model for predicting the death risk of patients hospitalised with COVID-19, saying it should help doctors quickly decide on the best care for each patient.
The tool, detailed in research published in the BMJ medical journal on Wednesday, helps doctors put patients into one of four COVID-19 risk groups - from low, to intermediate, high, or very high risk of death.
With hospitals around the world facing waves of patients with COVID-19, the disease caused by the novel coronavirus, doctors have said they need quicker and more accurate risk prediction tools to swiftly identify those patients at highest risk of dying and help get them targeted treatment.
The new model - called the 4C (Coronavirus Clinical Characterisation Consortium) Mortality Score - uses data such as age, sex, underlying conditions, breathing and blood oxygen levels. Study results showed it was able to more accurately predict risk than 15 comparable models, the researchers said, and it was also more useful in clinical decision-making.
“This will prove important in helping guide doctors to optimally care for the sickest of patients,” said Ewen Harrison, a professor of surgery and data science at Edinburgh University who co-led the research and presented it at a briefing.
Using the various data input, the risk calculator gives scores ranging from 0 to 21 points, he said. Patients with a score of 15 or more had a 62% mortality risk compared with 1% for those scoring 3 or lower.
The researchers said patients with a low 4C Mortality Score might not need to be admitted to hospital, while those in medium and higher risk groups could be expedited for more aggressive treatment, including steroid drugs and being admitted to critical care units if necessary.
Reporting by Kate Kelland; Editing by Christopher Cushing
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