A new UK-developed risk prediction tool has proved accurate in calculating the risk of severe COVID-19 in hospitalised patients, according to an article published in the BMJ.
The risk prediction tool (known as QCOVID) uses data from the QResearch database, comprising 1205 general practices in England with linkage to COVID-19 test results, Hospital Episode Statistics and death registry data. The derivation cohort (n=6,083,102 adults aged 19-100 years) period was 24 January 2020 to 30 April 2020. The second temporal validation cohort covered the period 1 May 2020 to 30 June 2020.
The primary outcome was time to death from COVID-19, defined as a death due to confirmed or suspected COVID-19 as per the death certification or death occurring in a person with confirmed SARS-CoV-2 infection in the period 24 January 2020 to 30 April 2020. The secondary outcome was time to hospital admission with confirmed SARS-CoV-2 infection.
The QCOVID population-based risk algorithm performed well, showing very high levels of discrimination for deaths and hospital admissions due to COVID-19.
In the top 5 per cent of patients with the highest predicted risk of death, the sensitivity for identifying deaths within 97 days was 75.73 per cent. People in the top 20 per cent for predicted risk of death accounted for 94 per cent of all deaths from COVID-19.
The authors point out that the absolute risk will change over time in line with the infection rate and the extent of social distancing measures in place. They say the estimates should be interpreted with caution.
