Recently, a group of Chinese researchers have developed a clinical scoring system that can be used when patients are admitted to hospital to predict their risk of developing a critical illness, therefore allowing staff to better prioritise patient care and optimise the use of resources.
The team analysed data on various parameters such as clinical signs and symptoms, imaging results, laboratory findings, demographic variables and medical history from 1590 patients to create a model. In total, 72 variables were included in the model although after further refinement this was reduced to only ten significant variables. These factors included chest X-ray abnormality, age, haemoptysis, dyspnoea and the number of comorbidities.
The accuracy of the model was assessed by the area under the receiver operator curve, which assesses its discriminatory power, that is, the ability of the model to correctly classify those with and without a risk of developing critical illness. Values between 0.80 and 0.90 are considered to be good and anything above 0.90 excellent; the new model had a value of 0.88.
The authors note that the ten variables would normally be readily available to clinicians and although based on Chinese patients, it is a potentially useful tool for screening patients admitted to hospital with COVID-19 infection.
Reference
Liang W, Liang H, Qu L. Development and validation of a clinical risk score to predict the occurrence of critical illness in hospitalized patients with Covid-19. JAMA Intern Med 2020; doi:10.1001/jamainternmed.2020.2033
