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CCU010: In people with CVD and Covid-19, what is the influence of multi-morbidity on risk of poorer outcomes?
Safe People
Organisation name
University of Leicester
Organisation sector
Academic Institute
Applicant name(s)
Claire Lawson
Sub-licence arrangements (if any)?
No
Safe Projects
Project ID
CCU010
Lay summary
Since the first case of COVID-19 in the UK in January 2020, there have been nearly 4 million cases reported. Whilst most people have recovered with only mild to moderate symptoms, others have more severe symptoms requiring admission to hospital. There have been over 120,000 COVID-19 related deaths reported in the UK. We know that certain groups of people are more susceptible to severe COVID-19 disease and to dying from their infection. People with long term conditions (LTCs), particularly cardiovascular disease, have been found to be particularly vulnerable to complications related to COVID-19. We also know that the risk of complications after contracting COVID-19 in people with cardiovascular disease increases for those who have multiple LTCs, and in those with certain ‘characteristics’ including being older, male, or from non-Caucasian ethnic groups. However, because people with COVID-19 often have a combination of different high risk characteristics, it can be difficult to know which are the most likely cause of complications. For example, we don’t know whether some or all of the higher risk of COVID-19 complications in people with cardiovascular disease who are older, male or non-Caucasian is explained by their multiple LTCs. This 12 month study will investigate people with different types of cardiovascular disease to understand what role multiple LTCs and other characteristics play in increasing the risk of COVID-19 complications. This will help us to identify those patients who may be at greater risk from COVID-19 complications, so that we can provide tailored interventions to improve their outcomes.
Public benefit statement
This 12 month study will investigate people with different types of cardiovascular disease to understand what role multiple LTCs and other characteristics play in increasing the risk of COVID-19 complications. This will help us to identify those patients who may be at greater risk from COVID-19 complications, so that we can provide tailored interventions to improve their outcomes. Visit the BHF Data Science Centre website for more detailed information about project outputs. https://bhfdatasciencecentre.org/projects/ccu010/
Technical summary
This project accessed the following datasets within the Trusted Research Environment(s) for CVD-COVID-UK / COVID-IMPACT: - ENGLAND: - Civil Registration - Deaths - COVID-19 SARI-Watch (formerly CHESS) - Covid-19 Second Generation Surveillance System - GPES Data for Pandemic Planning and Research (COVID-19) - Hospital Episode Statistics Accident and Emergency - Hospital Episode Statistics Admitted Patient Care - Hospital Episode Statistics Critical Care - Hospital Episode Statistics Outpatients - ICNARC: Intensive Care National Audit and Research Centre - NICOR – MINAP: Myocardial Ischaemia National Audit Project - NICOR – NACRM: National Audit of Cardiac Rhythm Management - NICOR – NACSA: National Adult Cardiac Surgery Audit - NICOR – NCHDA: National Congenital Heart Disease Audit - NICOR – NHFA: National Heart Failure Audit - NICOR – PCI: Percutaneous Coronary Interventions - NICOR – TAVI: Transcatheter Aortic Valve Implantation - Secondary Uses Services Payment By Results - Sentinel Stroke National Audit Programme Clinical Dataset
Latest approval date
29/04/2021
Safe Data
Dataset(s) name
Data sensitivity level
De-Personalised
Safe Setting
Access type
TRE