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Food Safety and Health
2021-06-28 - 2021-06-29    
All Day
The main objective is to bring all the leading academic scientists, researchers and research scholars together to exchange and share their experiences and research results [...]
Food Microbiology
2021-06-28 - 2021-06-29    
All Day
This conference provide a platform to share the new ideas and advancing technologies in the field of Food Microbiology and Food Technology. The objective of [...]
Smart Robots and Artificial Intelligence 2021
2021-07-05 - 2021-07-06    
All Day
Robotics is an imperative development that is related to the well-being of all individuals. A Robot is a useful gadget, multitasking operator sketched to move [...]
World Plant and Soil Science Congress
2021-07-23 - 2021-07-24    
All Day
It’s our greatest pleasure to welcome you to the official website of 2nd World Plant and Soil Science Congress that aims at bringing together the [...]
Food and Beverages
2021-07-26 - 2021-07-27    
12:00 am
The conference highlights the theme “Global leading improvement in Food Technology & Beverages Production” aimed to provide an opportunity for the professionals to discuss the [...]
Events on 2021-06-28
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Events on 2021-07-26
Food and Beverages
26 Jul 21
Latest News

Researchers analyse 17.4 million NHS patient EHRs in the world’s largest study to date on COVID-19 deaths

Researchers analyse 17.4 million NHS patient EHRs in the world’s largest study to date on COVID-19 deaths

A study on behalf of NHS England analysed the electronic health records (EHRs) of 17.4 million UK adults, to examine the risk factors associated with death from COVID-19. Academics at the University of Oxford and the London School of Hygiene & Tropical Medicine (LSHTM) carried out the research using the OpenSAFELY analytics platform, which allows GP records to be linked where they are stored for individual care.

The platform aims to minimise security risks associated with transferring and storing data elsewhere and deliver analyses quickly while preserving patient privacy. Researchers analysed primary care EHRs between 1 February and 25 April 2020, pseudonymously linked to patient-level data from the COVID-19 Patient Notification System (CPNS), for death of hospital inpatients with confirmed COVID-19.

WHY IT MATTERS

The study is the largest on COVID-19 conducted by any country to date, and therefore gives the strongest evidence on risk factors. There were 5,683 deaths attributed to the virus in the time period, with death strongly associated with being male, older age, deprivation, uncontrolled diabetes, severe asthma, and various other prior medical conditions.

People from asian and black groups were found to be at a markedly increased risk of in-hospital deaths, which is only partially attributable to pre-existing clinical risk factors or deprivation. Researchers concluded that further research into the drivers of this association is therefore urgently required.

THE LARGER CONTEXT

A further study using the OpenSAFELY platform will investigate the effects of specific drugs routinely prescribed in primary care. Meanwhile, University College London (UCL) has partnered with tech company Causaly to advance ongoing research into COVID-19. Researchers will use Causaly’s artificial intelligence platform to optimise data reading and interpretation of its investigations into the virus.

ON THE RECORD

Professor Liam Smeeth, professor of clinical epidemiology at LSHTM and co-lead on the study, said: “We need highly accurate data on which patients are most at risk in order to manage the pandemic and improve patient care. The answers provided by this OpenSAFELY analysis are of crucial importance to countries around the world.”

Dr Ben Goldacre, director of the DataLab in the Nuffield department of primary care health sciences at the University of Oxford, and co-lead on the study, said: “The UK has phenomenal coverage and quality of data. We owe it to patients to keep their data secure; and we owe it to the global community to make good use of this data. That’s why we have developed a new highly secure model, taking the analytics to where the data already resides.”