Date Time
AI analytics predict COVID-19 patients’ daily trajectory in UK intensive care
Researchers used AI to identify which daily changing clinical parameters best predict intervention responses in critically ill COVID-19 patients.
The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) – a technique known as proning that is commonly used in this setting to improve oxygenation of the lungs.
This dynamic understanding is vitally important when trying to understand a new life-threatening disease and to know when and in whom each intervention works. Dr Brijesh Patel
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The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) - a technique known as proning that is commonly used in this setting to improve oxygenation of the lungs.
While the AI model was used on a retrospective cohort of patient data collected during the pandemic s first wave, the study demonstrates the ability of AI methods to predict patient outcomes using routine clinical information used by ICU medics.
The researchers say the approach, where each patient s data were analysed day-by-day instead of only on admission, could be used to improve guidelines in clinical practice going forward. It could be applied to potential future waves of the pandemic and other diseases treated in similar clinical settings.
11 May 2021
Researchers used AI to identify which daily changing clinical parameters best predict intervention responses in critically ill COVID-19 patients.
The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) – a technique known as proning that is commonly used in this setting to improve oxygenation of the lungs.
This dynamic understanding is vitally important when trying to understand a new life-threatening disease and to know when and in whom each intervention works. Dr Brijesh Patel Department of Surgery and Cancer
While the AI model was used on a retrospective cohort of patient data collected during the pandemic’s first wave, the study demonstrates the ability of AI methods to predict patient outcomes using routine clinical information used by ICU medics.
Fungal attack: Everything you need to know about India’s ‘black fungus’ and similar pathogens
Doctors say mucormycosis has been detected more frequently than usual in India, with fears it is linked to Covid drugs. What’s going on?
10 May 2021 • 5:59pm
A nurse rests in a makeshift ward at an emergency Covid-19 care center
Credit: T. Narayan/Bloomberg
There are concerning reports emerging from India that an aggressive flesh-eating “black fungal” infection is maiming Covid-19 patients and survivors, attacking their noses, eyes and sometimes brains.
Doctors have warned that the rare condition, called mucormycosis, has been detected far more frequently than usual in hospitals across the country, with some fears that it is linked to Covid-19 treatments. So what’s going on?
Between the caffeine and blue-light screens, it seems like everything we come into contact with is designed to keep us stimulated, awake and productive. And the pandemic has inevitably impacted sleep too. With no early morning commute or school drop-off to worry about, many were sleeping later for longer. Matthew Walker – professor of neuroscience and psychology at the University Of California, Berkeley, and author of
Why We Sleep – calls this the “revenge of the night owls”. However, lockdown has been a time of increased anxiety and stress for many others. Nearly 70 per cent of respondents to a 2020 British Sleep Society survey reported that the pandemic had impacted their sleep pattern, with less than half saying they were satisfied with their current sleep quality or felt refreshed from sleep.