In Severe COVID-19 Patients, Arthritis Drug Shows No Response by Pooja Shete on January 24, 2021 at 1:00 AM
The findings of this trial are published in the journal
The BMJ
The trial was stopped early as there was an increased number of deaths in patients receiving tocilizumab.
The result of this study contradicts the previous observational studies that suggested possible benefits of tocilizumab. Observational studies are limited as they have a high risk of other unknown factors which can influence the study.
Tocilizumab acts by blocking interleukin 6, a specific part of the immune system that can go into overdrive in some COVID-19 patients. This can help reduce the body s inflammatory response to the virus and avoid some of the more dire consequences of the disease. However, its effects are not well defined.
Researchers evaluate the accuracy of NEWS2 scoring system for predicting COVID outcomes
In the first systematic large-scale evaluation of the UK National Early Warning Risk Score (NEWS) 2 as a scoring system for predicting severe COVID-19 outcomes in patients, researchers at King s College London have found poor-to-moderate accuracy for identifying patients at risk of being transferred to intensive care units (ICUs) or dying after 14 days of hospitalization. Accuracy of predictions in short term (three days) showed moderate success.
For people who are hospitalized with severe COVID-19, it is vital to quickly identify which patients may deteriorate and require transfer to an intensive care unit (ICU) for organ support or may die. NEWS2 is an early warning score that combines physiological parameters such as respiration rate, oxygen saturation, blood pressure and temperature. NEWS2 is currently used almost universally in UK NHS Trusts to identify which patients are at risk of deterio
An algorithm used by the NHS to predict which patients are most likely to deteriorate is inaccurate when used on Covid-19 patients, a new study shows.
The algorithm has ben used for years and is endorsed by NHS England. It gives each patient a score which predicts how their condition will change.
King s College London researchers studied how good the algorithm was at predicting the health outcomes of 1,276 Covid-19 patients admitted to hospital in March and April 2020.
The data reveals poor-to-moderate accuracy for spotting patients who are at risk of being admitted to ICU or dying two weeks later.
It performed moderately in the short term, three days later, the study authors say.
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In the first systematic large-scale evaluation of the UK National Early Warning Risk Score (NEWS) 2 as a scoring system for predicting severe COVID-19 outcomes in patients, researchers at King s College London have found poor-to-moderate accuracy for identifying patients at risk of being transferred to intensive care units (ICUs) or dying after 14 days of hospitalisation. Accuracy of predictions in short term (three days) showed moderate success.
For people who are hospitalised with severe COVID-19, it is vital to quickly identify which patients may deteriorate and require transfer to an intensive care unit (ICU) for organ support or may die. NEWS2 is an early warning score that combines physiological parameters such as respiration rate, oxygen saturation, blood pressure and temperature. NEWS2 is currently used almost universally in UK NHS Trusts to identify which patients are at risk of deteriorating early.