This online tool can identify COVID-19 patients at high risk of deterioration IANS
A new risk-stratification tool, which can accurately predict the likelihood of deterioration in adults hospitalised with COVID-19, has been developed by a team of researchers, including an Indian-origin.
According to the researchers, the online tool could support clinicians’ decision making helping to improve patient outcomes and ultimately save lives.
“Accurate risk-stratification at the point of admission to hospital will give doctors greater confidence about clinical decisions and planning ahead for the needs of individual patients,” said co-author Mahdad Noursadeghi, Professor at University College London.
The tool assesses 11 measurements routinely collected from patients, including age, gender, and physical measurements (such as oxygen levels) along with some standard laboratory tests and calculates a percentage risk of deterioration, known as the ‘4C Deterioration Sc
The research was led by the UK Coronavirus Clinical Characterisation Consortium (known as ISARIC4C).
Researchers say the online tool, made freely available to NHS doctors from today (Friday 8 January 2021), could support clinicians decision making - helping to improve patient outcomes and ultimately save lives.
The tool assesses 11 measurements routinely collected from patients, including age, gender, and physical measurements (such as oxygen levels) along with some standard laboratory tests and calculates a percentage risk of deterioration, known as the 4C Deterioration Score .
This innovation, published in The Lancet Respiratory Medicine, builds on the Consortium s previous work developing the 4C Mortality Score to predict the percentage risk of death from COVID-19 after admission to hospital. The 4C Mortality Score is already recommended for use by NHS England to guide anti-viral treatments (Remdesivir).
New online tool ‘can identify Covid patients at highest risk of deterioration’
An online tool can identify Covid-19 patients who are at highest risk of deterioration (Peter Byrne/PA)
An online tool that can identify Covid-19 patients who are at highest risk of deterioration is being made freely available to NHS doctors from Friday.
The new risk-stratification tool, developed by researchers from the UK Coronavirus Clinical Characterisation Consortium (known as ISARIC4C), assesses data collected from hospital patients along with some standard laboratory tests.
It then calculates a percentage risk of deterioration based on the information, which is known as the 4C Deterioration Score.
New online tool identifies COVID-19 patients at highest risk of deterioration ANI | Updated: Jan 09, 2021 07:35 IST
London [UK], January 9 (ANI): A new risk-stratification tool that can accurately predict the likelihood of deterioration in adults hospitalised with COVID-19 has been developed by researchers.
The research was led by the UK Coronavirus Clinical Characterisation Consortium (known as ISARIC4C).
Researchers say the online tool, made freely available to NHS doctors from today (Friday 8 January 2021), could support clinicians decision making - helping to improve patient outcomes and ultimately save lives.
The tool assesses 11 measurements routinely collected from patients, including age, gender, and physical measurements (such as oxygen levels) along with some standard laboratory tests and calculates a percentage risk of deterioration, known as the deterioration-score >4C Deterioration Score .
Date Time
Online tool identifies COVID-19 patients at highest risk of deterioration
A new risk-stratification tool which can accurately predict the likelihood of deterioration in adults hospitalised with COVID-19 has been developed by researchers from the UK Coronavirus Clinical Characterisation Consortium (known as ISARIC4C).
ISARIC4C is a consortium of NHS doctors and scientists from universities including the University of Liverpool, UCL, Imperial College London, the University of Edinburgh, and the University of Oxford.
Researchers say the online tool, made freely available to NHS doctors from today, could support clinicians’ decision making – helping to improve patient outcomes and ultimately save lives.