CVD-COVID-UK / COVID-IMPACT

CVD-COVID-UK focuses on heart and circulatory disease research, whilst COVID-IMPACT focuses on other health conditions. Both projects aim to answer three broad questions (see the protocol for more detail):

1. What are the effects of heart and circulatory diseases or other prior health conditions, their risk factors and medications on susceptibility and poor outcomes (including admission to hospital, requirement for intensive care and death) from COVID-19 disease?
2. What is the direct impact of COVID-19 on heart and circulatory disease complications or on other health complications, as well as on medium and longer-term heart and circulatory disease or other health condition risks?
3. What is the indirect impact of the COVID-19 pandemic and the government and NHS response to it on the presentation, diagnosis, management and outcomes of heart and circulatory diseases or other health conditions?

ACE inhibitors and angiotensin receptor blockers are drugs that are commonly used to lower high blood pressure. These drugs may affect the ability of the coronavirus to enter cells of the body and cause COVID-19. We plan to investigate whether use of these drugs affects people’s chance of becoming infected or unwell with COVID-19.

We will conduct carefully planned analyses of data from millions of people’s healthcare records. These records provide information about people’s health and prescribed medications, as well as on which people became infected or unwell with COVID-19.

People who take drugs to lower their blood pressure are more likely to have other risk factors for becoming infected or unwell with COVID-19. Our analysis methods will account for these risk factors, to work out whether any change in risk is due to the blood pressure lowering drugs themselves.

Our results will help to inform the way that blood pressure lowering drugs are used in the future, particularly while the pandemic continues.

Coronavirus infection (‘COVID-19’) or vaccination against coronavirus might increase a person’s chance of having a stroke, heart attack or clot in the deep veins or lungs (‘blood vessel diseases’).

During the COVID-19 pandemic, some doctors have looked after patients with COVID-19 who also had unusual strokes, clots or heart complaints. This suggests there could be a link between COVID-19 and blood vessel diseases. But no individual doctor will see enough patients to find out if COVID-19 really does increase the risk of blood vessel diseases.

To understand more, we will use healthcare records to study every person alive in England, Scotland and Wales at the beginning of the pandemic in 2020. We will find out how many people had a stroke, heart attack, heart condition or other disease of the blood vessels over the following year.

We will compare the number of people with COVID-19 infection who developed a blood vessel disease with the number of people without COVID-19 infection who developed a blood vessel disease. Different types of people might have different risks, so we will also examine people of different ages, ethnicities and medical history.

The result of this research will be an estimate of how much COVID-19 increases the risk of different blood vessel diseases. This information is needed so that people with COVID-19 know whether they need to worry about blood vessel diseases as they recover. If this research shows there is an increased risk, then treatments might be needed to reduce this.

Amendment

Following an urgent request from the MHRA and Chief Medical Officer, the analyses for this project will also address the urgent question of whether there is an association between the SARS-CoV-2 vaccine and vascular events, including very rare blood clotting events and myocarditis/pericarditis.

Outputs

Association of COVID-19 with major arterial and venous thrombotic diseases: a population-wide cohort study of 48 million adults in England and Wales

• Circulation publication 19/09/22 can be viewed here
• medRxiv preprint 24/11/21 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, or thrombocytopenic events: A population-based cohort study of 46 million adults in England

• PLOS Medicine publication 22/02/22 can be viewed here
• medRxiv preprint 23/08/21 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

Risk of myocarditis and pericarditis following BNT162b2 and ChAdOx1 COVID-19 vaccinations

• Paper submitted to a journal (decision pending)
• medRxiv preprint 08/03/22 can be viewed here
• Code and phenotypes used in this study are available in GitHub here

Coronavirus (COVID-19) directly impacts individuals who become infected with the virus. It can also influence people’s healthcare decisions (such as deciding not to attend medical appointments for fear of infection). In addition, hospitals have sometimes had to prioritise treatment of COVID-19 patients over routine healthcare.

Access to data from healthcare records will help to improve our understanding of what puts certain people at an increased level of risk. This includes people with cardiovascular disease, including heart disease and stroke.

This research project has three main priorities.

1. For people with cardiovascular disease, we will estimate by how much becoming infected or unwell with COVID-19 increases their risk of dying within one year of infection. This will involve analysing routine healthcare data from multiple sources, including from general practices, hospitals and national death registers.
2. We will study how the treatment of patients with cardiovascular disease has been affected during the pandemic.
3. We will develop and improve models that predict the risk of dying at one year among people with cardiovascular disease who have and who have not contracted COVID-19.

Our research will help to shape health policy, help patients and clinicians to make more informed decisions, and improve health outcomes.

Outputs

A retrospective cohort study measured predicting and validating the impact of the COVID-19 pandemic in individuals with chronic kidney disease

• Kidney International publication 17/06/22 can be viewed here
• Preprint 24/11/21 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19 – a data-driven retrospective cohort study

• Journal of the Royal Society of Medicine publication 14/11/22 can be viewed here
• Preprint 08/03/22 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

Effects of the COVID-19 pandemic on secondary care for cardiovascular disease in the UK: an electronic health record analysis across three countries

• European Heart Journal – Quality of Care and Clinical Outcomes publication 16/11/22 can be viewed here
• Preprint 17/10/22 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

Cardiovascular disease (CVD), comprising mostly heart attacks and strokes, is one of the UK’s leading causes of death and disability. It is far better and cheaper to prevent CVD than to treat patients after they get sick. Consequently, doctors aim to identify patients at high risk of future CVD and offer healthy lifestyle advice and medication, such as statins.

However, studies have found that such advice is poorly communicated to patients. This has resulted in low numbers of patients choosing to make healthy lifestyle changes and take medication, especially amongst patients living in more deprived areas. It is important to improve the way CVD risk is communicated to patients across the whole of society so that more people benefit from advice and medication, and also to reduce inequalities in CVD.

Currently, doctors use risk prediction calculators to help decide whether a patient is at high risk of future CVD. The most commonly used risk prediction calculators in England were developed using data from 2004-2016 from 2.3 million patients in England. More current data is now available from over 56 million patients in England, as well as 10 million patients from Wales, Scotland and Northern Ireland. These datasets also include information about whether a patient has had COVID-19 and any related complications. Patients with COVID-19 complications may be at higher risk of future CVD than patients without COVID-19 complications. Therefore, COVID-19 information may be useful information for doctors in helping to identify the right patients at high risk of CVD.

We plan to develop new risk prediction tools to assess and help communicate a patients’ future risk of CVD. Our aims are (i) to better identify patients at high risk of CVD in the UK and (ii) to improve communication of CVD risk to patients across the whole of society. Ultimately, this should reduce CVD in the UK.

Outputs

A nationwide deep learning pipeline to predict stroke and COVID-19 death in atrial fibrillation

• Paper submitted to a journal (decision pending)
• medRxiv preprint 21/12/21 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

Since the COVID-19 pandemic, there has been rapid progress made towards the availability and accessibility of national healthcare data for research. Consequently, for the first time we are analysing data from over 65 million patients across the UK to help us understand more about COVID-19. Our analyses have the advantages of being able to study individuals with and without different health-related problems across all age groups, ethnicities, geographies and socioeconomic settings. Our results will be directly relevant to everyone living in the UK.

However, there are a number of challenges and limitations to using routinely collected healthcare data for research. The problems mainly arise because electronic health records are designed for clinical purposes, and do not necessary provide an accurate picture of the true health status on all patients at all times. If we do not address these problems properly in the analysis, then we will get biased results and make incorrect conclusions.

We aim to identify and provide solutions to address the challenges and limitations in the analysis of population-wide healthcare data. Ultimately, we want to ensure results arising from population-data healthcare data are accurately reported.

Outputs

Linked electronic health records for research on a nationwide cohort including over 54 million people in England

• BMJ publication 08/04/21 can be viewed here
• BMJ editorial 08/04/21 can be viewed here and public contributor opinion piece here
• The press release explaining this research can be viewed here
• medRxiv preprint 26/02/21 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration

• BMC Medical Informatics and Decision Making publication 16/01/23 can be viewed here
• Preprint 28/10/22 can be viewed here
• Related GitHub repo can be accessed here

Cardiac surgery is a necessary life-extending/saving procedure required by many adults and children every day in the UK. Despite it being prioritised during the COVID-19 pandemic, the true impact of the latter on case volume and outcome are unknown. The COVID-19 pandemic may significantly increase procedural morbidity and mortality. Patients who present with COVID-19 infection before surgery or patients who develop COVID-19 infection following surgery may be particularly vulnerable to the serious consequences of COVID-19 infection including respiratory, heart and renal failure. Moreover, the pandemic can affect outcomes following cardiac surgery due to limited resources including shortages of staff and equipment.

Thirteen babies in the UK are born with congenital heart disease every day, and most of these children as well as adults who experience heart disease will need several high-risk operations and treatments during their lives. There is currently very limited information available regarding how delays to treatment caused by the COVID-19 pandemic have affected children and adults with heart disease undergoing these very high-risk interventions.

Whether case mix and clinical outcomes differ from those achieved during normal operating conditions is also unknown. Moreover, individualised risk estimation in patients undergoing cardiac surgery accounting for COVID-19 exposure is to be determined. Therefore, there is an urgent need to assess the impact of the COVID-19 pandemic on outcomes following cardiac surgery to guide current and future clinical decision making.

We will be using available healthcare records from England and Wales to better understand the risks between delaying surgery because of the pandemic or not, and if so what length of delay remains safe for children and adults with heart disease. We will also evaluate whether the COVID-19 pandemic has affected the future health and wellbeing of these children and adults with heart disease. This will include seeing if there is impact of the pandemic on patients based on race and ethnicity.

The information obtained from this research will allow for better planning of operations and treatments, aiming to improve health outcomes for children and adults with heart disease. The findings of this project will help patients and clinicians to make more informed decisions during these challenging pandemic times.

Although cardiovascular disease (CVD), including heart attacks and strokes, is still the leading cause of death in the UK, the risk of CVD events and death can be reduced by identifying and treating major risk factors such as high blood pressure (BP), lipids (e.g. cholesterol), and fasting blood glucose (FBG) / haemoglobin A1c (HbA1c, marker for average blood glucose levels of last 3 months, widely used by doctors). Due to the COVID-19 pandemic, access to routine clinical care was dramatically disrupted during 2020. This led to changes in the patterns of attendance in primary care from March 2020 onwards, which in turn significantly altered patterns of drug prescribing and dispensing, including for cardiovascular drugs. Clinical observation has shown that an increasing number of people had risk factors, such as high body mass index (BMI) and BP, high cholesterol or triglyceride levels, and poor liver function markers, during the pandemic. The extent to which this occurred in the population and has had a lasting impact on some people’s risk factor trajectories is still unknown.

Although these changes in practice are likely to have had an influence on the nature of testing, treatment and control of major risk factors for CVD, the extent and potential impact of these changes is unknown. We propose to use routine healthcare records to examine patterns of BMI measurement, BP, lipid, HbA1c and liver function (ALT, AST, GGT) testing in the general population and evidence for control of these risk factors (according to expert clinical guideline recommendations) in patients with CVD and at high risk of developing CVD.

We will also examine whether differences in the quality of testing, diagnosis and control of risk factors are related to any particular patient characteristics (e.g. sex, area-based deprivation indices, ethnicity, common chronic conditions). Finally, we will compare the level of these risk factors during the pandemic with those in 2014-2019.

This work will be undertaken in close alignment with another approved CVD-COVID-UK project, examining changes in CVD drug prescribing during the same period. Considered together, these analyses will provide important insights into the potential impact of the COVID-19 pandemic on the detection and control of key changeable CVD risk factors in the UK population. Outputs from these analyses will be used to model the potential consequences for future CVD events in the UK and help to identify where efforts could potentially be focused most effectively to address emerging gaps in the provision of preventive care.

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.

When a patient visits their GP or is admitted into hospital, information about their symptoms, diagnosis, lab test results and prescriptions is inputted and stored in ‘Electronic Health Records’ (‘EHRs’). These EHR’s are a valuable resource for researchers and clinicians to be able to analyse the health data of large numbers of patients, with the aim of using this information to improve patient health and care.

However, as information in these EHRs is inputted by different health workers around the UK, there can be variations in the amount of detail that has been included and the records can contain many inconsistencies. This means that researchers need to initially spend a considerable amount of time and effort to be able to obtain the most relevant information from these EHRs, before they can then start to effectively analyse them. Examples include trying to identify which patients may or may not have a particular disease, or to extract individual measurements – such as high blood pressure or whether they are a smoker – from billions of rows of data.

To improve this, this project will create and evaluate different ways of being able to extract this valuable information from complex EHRs, so that the records can be most effectively analysed by the CVD-COVID-UK consortium. As our understanding of COVID-19 is developing rapidly, being able to access accurate information for research more quickly is especially important. This includes being able to accurately understand the impact that COVID-19 infection has in patients in the longer term – known as ‘long COVID’ – which affects multiple organs in the body.

The approaches developed in this project will benefit all of the research being undertaken by the CVD-COVID-UK consortium, and shared with the wider scientific and medical community by publishing the results openly. This will maximise the benefits of using information from EHRs, and ensure research can be reproduced effectively. Most importantly, this will speed up the ability to effectively analyse health information in EHRs, and directly improve benefits to patients and healthcare.

Outputs

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

• The Lancet Digital Health publication 08/06/22 can be viewed here
• medRxiv preprint 09/11/21 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

Cardiovascular disease (CVD, including heart attacks and strokes) remains one of the leading causes of death in the UK. There are a number of conditions that commonly increase an individual’s risk of developing CVD. Some of these conditions, such as diabetes and having high circulating levels of cholesterol in the blood, can be controlled by using medicines.

However, these conditions need to be diagnosed before an individual can be prescribed the medicines to control them. Because of disruption from the COVID-19 pandemic resulting in changes in health care services and fewer face-to-face medical appointments, it is likely that the number of conditions being diagnosed has fallen. Therefore some individuals are not being prescribed the medicines to control the condition.

One way to investigate this problem is to look at what changes there have been in the prescriptions for these conditions. This involves looking at new and repeat prescriptions that have been issued by the GP, and also the amount of prescriptions dispensed by the pharmacy.

We already know that the COVID-19 pandemic caused a disruption to the usual pattern of prescribing of medicines for these conditions. For example, there was a significant increase in the number of repeat prescriptions issued in March 2020, presumably as doctors and patients ensured they had sufficient medication for the first lockdown. Subsequent patterns in the prescribing of medicines for these conditions during 2020 have not yet been adequately studied.

The number of GP appointments also fell during Spring-Summer 2020, presumably resulting in a reduced number of individuals being diagnosed with CVD. It is also presumed that there would be a reduction in the diagnosis in new patients of conditions that can increase their risk of developing CVD, and therefore a decrease in the amount of prescriptions for medicines to control these conditions.

For this project, we therefore propose to examine patterns in the prescription of medicines for these conditions. This will enable us to understand how the COVID-19 pandemic has had an impact on the control of CVD and its related conditions in the UK population. We will use this information to understand how many people are likely to be affected by cardiovascular disease in the future. It is hoped that this will enable more accurate planning for better patient care.

Amendment

The scope of this project has been extended to understand the impact of COVID-19 on a number of clinical pathways using medicines as an approach.  This additional work is funded through a funding call by Health Data Research UK and the Alan Turing Institute as part of the wider Data and Connectivity National Core Study.

Further details are available here.

Outputs

The impact of the COVID-19 pandemic on cardiovascular disease prevention and management

• Nature Medicine publication 19/01/23 can be viewed here
• medRxiv preprint 02/01/22 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

People living with dementia have been amongst the hardest hit during the COVID-19 pandemic. A group of drugs called ‘antipsychotics’ are sometimes used to treat distress and agitation in people living with dementia. However, there is evidence to suggest that these medicines may increase the risk of stroke and heart attacks when given to people with dementia. They should therefore only be used as a last resort, when other treatments have failed.

Since March 2020, the prescribing of these drugs for people with dementia has increased. We think this may be because social distancing restrictions have caused more people to need treatment for distress or agitation as they do not have access to their normal support structures. This increase in antipsychotic prescribing during the COVID-19 pandemic is concerning, as it may have led to an increase in heart attacks and strokes in these patients.

We will investigate whether this increase in antipsychotic prescribing has led to an increase in strokes or heart attacks. To do this, we will use information that is collected routinely by health services, such as GP records, prescriptions and diagnoses recorded in hospital. We hope that the results of this study will help inform decision making between doctors, patients and carers, by enabling them to weigh up the risks and benefits of prescribing an antipsychotic.

Outputs

Antipsychotic prescribing and mortality in people with dementia before and during the COVID-19 pandemic: retrospective cohort study

• Paper submitted to a journal (decision pending)
• medRxiv preprint 19/02/23 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

COVID-19 infection during pregnancy may increase the risk of cardiovascular health problems related to pregnancy and giving birth. Small hospital-based studies have suggested a relationship between COVID-19 infections during pregnancy and severe complications for mothers and their babies. However, since some complications are rare, detailed analyses from large population-based studies are required. Along with this, it is of great interest to understand the possible protective effect of vaccination against COVID-19 infection considering the increasing proportion of the population vaccinated against COVID-19 also among pregnant women.

We will assess and quantify the role of COVID-19 infection during pregnancy on cardiovascular-related maternal health outcomes (for example, pre-eclampsia, gestational hypertension, gestational diabetes, miscarriage, preterm birth, stillbirth, peripartum cardiomyopathy), and on longer-term cardiovascular related diseases for the mother and child.

Results from our study will help to inform women on potential risks related to COVID-19 infection during pregnancy, identify women with greatest risks, understand the possible protective effect of vaccination against COVID-19 infection, and help evaluate if any preventative interventions are needed.

We know individuals with underlying health conditions have greater risk of developing severe COVID-19 and ending up with poorer outcomes. That is why governments and public health services have been providing dedicated and prioritised protections for these more clinically vulnerable people – for example, via recommending shielding or being prioritised to have COVID-19 vaccinations.

However, the majority of those living with rare diseases – around 5.8% of the UK population, or 3.7 million people – are often overlooked. Rare diseases are often poorly recorded in clinical data leading to a challenge in identifying patients whose rare condition makes them clinically vulnerable. We don’t know the most effective way to personalise and manage treatments for patients with rare diseases who contracted COVID-19. Furthermore, there are many people who are not diagnosed but share similar clinical presentations (so-called phenotypes) to those diagnosed rare-disease patients. We know some of them are likely to share similar vulnerabilities. However, we don’t know how to identify them currently.

In this project, we aim to tackle these challenges by bringing together a comprehensive set of knowledge about rare diseases, and applying the most up to date data science technologies to use such knowledge and resources on CVD-COVID-UK datasets.

In this way, we hope to develop a more accurate identification system for people living with rare diseases who are clinically vulnerable. We will also provide the much needed information on the risk of severe COVID-19 in people with rare diseases, hopefully leading to an improvement in their care by providing evidence on treatments that may work better for them. Furthermore, we will analyse the compound risks of severe COVID-19 in people bearing clinical risks and disadvantaged socioeconomic backgrounds, aiming to inform policy responses for providing better management and treatment for these most vulnerable groups who might previously have been overlooked.

We are matched with a data analyst from the Department of Health and Social Care. This will enable us a speedy dissemination of our work to the policy makers realising swift and actionable suggestions. We will also disseminate our findings to charities and societies of rare diseases in the UK and beyond to maximise the impact of our work.

Outputs

A nationwide study of 331 rare diseases among 58 million individuals: prevalence, demographics and COVID-19 outcomes

• Paper submitted to a journal (decision pending)
• Code and phenotypes used to produce this paper are available in GitHub here

Antithrombotics are blood thinning medications that are used to treat a range of cardiovascular diseases. Atrial fibrillation (AF) is one such disease, and is the most common disturbance of heart rhythm and a common cause of stroke. In individuals who have AF, antithrombotics are used to lower stroke risk. However, around a third of those with AF are not on the most effective type of antithrombotic or take no medication at all.

New evidence is emerging that individuals already taking antithrombotic medication (whether for AF or for another disease) may have improved outcomes if they become infected with COVID-19. However, the evidence for a protective association between antithrombotics and COVID-19 remains inconclusive.

This project will, therefore, explore three questions:

1. How many individuals in the UK with AF are not currently on antithrombotic medication
2. Do individuals with AF taking antithrombotic medication prior to COVID-19 infection have better outcomes (e.g. hospitalisation, mortality) than those that don’t?
3. What factors (e.g. location, age) are associated with a lack of antithrombotic medication in individuals with AF?

In addressing these questions, this project will create the software to automatically evaluate antithrombotic use in near real-time across the whole UK population. This will provide the information to help ensure individuals with AF are given the most effective treatments and confirm whether antithrombotics offer some protection against COVID-19.

Outputs

Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort

• Heart publication 10/03/22 can be viewed here
• medRxiv preprint 10/09/21 can be viewed here
• Code and phenotypes used to produce this paper are available in GitHub here

Physical and mental health consequences of COVID-19 infection, termed long-COVID, occur frequently. Our understanding of long-COVID – including how best to diagnose, risk factors, health and economic consequences – is poor, limiting efforts to help people.

We wish to address the following patient defined questions:

1. What is long-COVID and how is it diagnosed?
2. Why have I got long-COVID?
3. What effects will long-COVID have on my health, ability to work and family? What are my chances of recovery?
4. How will this research ensure I am getting the right treatment and support for long-COVID?

We will compare rates of symptoms and diseases in people who had COVID-19 with those in the general population, and examine which symptoms occur together. We will study risk factors for long COVID, and longer-term outcomes in people who live with it. We will share findings with bodies involved in developing treatment guidelines (NICE, who are also part of this project), with government (via the Chief Scientific Advisor), with the public via social media and other outputs, and the scientific community via research publications.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new virus responsible for the COVID-19 pandemic, which has caused many deaths worldwide. We are worried that some long-term (“chronic”) diseases, such as heart disease and diabetes, can worsen COVID-19 infection and lead to increased risk of death. Also, these diseases often occur together in groups, and a person can have multiple diseases. When this happens, we call this “multimorbidity”. However we do not fully understand why this happens, nor how they may be linked to COVID-19.

We therefore wish to study electronic health records (EHR) from hospitals and doctor’s clinics, as well as large-scale electronic databases of genetic and biological data, that cover people from a broad range of social and ethnic backgrounds from across the UK. Our team has expertise in using advanced computer-assisted techniques that can effectively make sense of such complex data, to find patterns and results beyond what is possible with traditional methods.

Ultimately, we aim to identify groups of individuals with cardiovascular-related multimorbidities and assess their response to COVID-19 infection, and explore how genetic, biological, and social factors interact to change this response. Our results may help us better identify people who are at greatest risk of disease, and find new possibilities to treat or prevent the disease.

COVID-19 vaccine rollout in the UK has been very successful. However, how long immunity from SARS-Cov-2 – the virus that causes COVID-19 – will last with vaccines is unknown. It is also unknown if new vaccines will need to be generated every year because of mutations in the virus, which commonly happens with flu. One other potential way that COVID-19 could be prevented would be to use medicines that act as anti-viral agents – but there are currently no such treatments available.

Our project aims to begin to address this by examining medicines that are already used in clinical practice but for different diseases. Based on knowledge of how these medicines work, we have found that some medicines may be useful as anti-viral medicines. If this is true, they could be used to help to prevent COVID-19 alongside vaccines. This project will use data to test if people taking some medicines might also be protected from infection with SARS-Cov-2. These analyses will be supplemented by laboratory analyses where we will test these medicines to see if they can neutralise the effect of SARS-CoV-2.

If these medicines are shown to have a protective signal in these analyses, this could lead to randomised controlled trials to test if they do prevent infection with SARS-CoV-2. If they work in clinical trials, this could mean the medicines could be used alongside vaccines for the prevention of COVID-19 infection and improve the population’s health.

This project was funded through a rapid funding call by Health Data Research UK, Office for National Statistics and UK Research and Innovation (UKRI) as part of the wider Data and Connectivity National Core Study.

Further details on this project are available here.

Outputs

Better End of Life 2022. Mind the gaps: understanding and improving out-of-hours care for people with advanced illness and their informal carers. Research report.

• Marie Curie report 28/11/22 can be viewed here
• Code and phenotypes used in this study when accessing English data are available in GitHub here

People with multiple blockages in their heart arteries may need open heart surgery and bypass surgery. For the surgery to remain successful, patients need to take certain types of medicines long-term after their operation.

Even before Covid-19 we had insufficient information on how many patients receive and keep taking these medicines. Emerging research has suggested that some cardiovascular medications may increase the risk or severity of Covid-19 infection; others may protect against Covid-19. However, data is limited, and dis-information is rampant. The use of these medications may have changed as a result of the pandemic. The aim of our study is to observe what proportion of patients were prescribed and received the guideline-advised medications after cardiac surgery before and during the Covid-19 pandemic.

Our project will help to identify if there has been a change in the use of appropriate medications because of the pandemic. This is very important as being on appropriate medications can help patients feel well and remain protected from heart attacks, stroke and other adverse events.

Our study will identify if prescribing of life-saving medications for patients with heart disease has changed over the years before and during the course of the pandemic. Obtaining this information is the first step towards developing solutions to counter any adverse change.

Policy makers in the NHS can use our information to develop recommend sharing of key messages and information with patients and to guide targeted educational programmes for general practitioners on appropriate prescribing for patients with heart disease.

Angina is a chronic heart condition that has a substantial impact on our health and social services, and on the population, society and the economy. Treatment with a coronary stent (thin metal tube) is intended to relieve angina, and around 100,000 people are treated with a stent in the NHS each year. Coronary artery bypass graft (CABG) surgery is reserved for patients with extensive coronary atherosclerosis – a condition where arteries become clogged with fatty substances called plaques, or ‘atheroma’. Around 14,000 patients undergo CABG in the NHS each year.

In this study, we will focus on angina and stents. Recent research has suggested that around 2 in 5 patients report angina within one year of receiving a stent. This implies that a considerable number of patients in the UK may be affected – potentially around 40,000 people each year. The underlying reasons for this are currently under-researched and poorly understood. The explanations may include problems with the small vessels within the heart muscle that lead to a condition called ‘microvascular angina’. Stents do not help with small vessel problems, and in fact, may even make small vessel problems worse.

COVID-19 infection leads to heart and blood vessel injury. Whether COVID-19 infection impacts on angina and clinical outcomes, including in patients who have received a coronary stent, is unknown.

This research will focus on angina before and after COVID-19 infection. The research will also assess angina occurring after stents in patients who have had COVID-19 infection. Advances in linked electronic patient records now enable studies of episodes of care in hospital and at the GP. We will therefore study NHS data at a national (UK) level. We will assess the number (%) of patients who attend their GP and hospitals for angina, including after receiving a stent, and we will estimate the NHS costs attached to these visits and medication use. We wish to make these assessments before, during and after the COVID-19 pandemic by examining a period of at least 10-years before and at least 5-years after the pandemic. This should provide sufficient information to assess the impact of angina, including after stent treatment in the NHS before, during and after the COVID-19 pandemic.

We will assess the costs and health economic impact associated with these episodes of care, and their changes over time. We will then estimate whether alternative treatment approaches could be cost-effective for the NHS. A future study is anticipated to assess the effects of COVID-19 infection status on anginal symptoms in patients following CABG.

During the first year of the COVID-19 pandemic, the risks to children related to COVID-19 infection were considered very low. Nonetheless, a subset of children with severe infections were admitted to hospital, required intensive care and experienced longer-term health issues.  After society re-opened in 2021, infection rates were very high in children, but the consequences of this, in terms of any severe disease and re-infections with COVID-19 are poorly understood.

In children under 18 years old, we will explore factors, which may affect the risk of certain types of significant illness with COVID-19 infection such as needing hospital admission, health complications such as seizures and diabetes. The factors we will consider include age, pre-existing diseases, obesity, ethnicity and socioeconomic deprivation. We will explore the relationship between these risk factors and COVID-19 re infections in children. We will also use the fact that the dominant type (or ‘variant’) of COVID-19 has changed to different ones in specific and known time periods, to explore whether these risks or any potential disease impacts in children have changed over time with pandemic waves. We will use the same dataset to explore the risks versus benefit of COVID-19 vaccination in children.

Better understanding of any significant health consequences linked to COVID-19 infection in children, and risk factors for these, could help to inform child health policy, for example, policies on vaccination in children and the provision of expert health services to address health care needs in affected children.

Outputs

Hospital admissions linked to SARS-CoV-2 infection in children: a cohort study of 3.2 million first ascertained infections in England

• Paper submitted to a journal (decision pending)
• Code and phenotypes used to produce this paper are available in GitHub here

People living with intellectual and developmental disabilities (i.e. intellectual disabilities and/or autism) are more likely to be admitted to hospital and die from infection with COVID-19. We do not know why people living with intellectual and developmental disabilities experience poorer outcomes following infection with COVID-19.

These poorer outcomes from COVID-19 infection may be caused by people living with intellectual and developmental disabilities:

• having higher rates of health problems
• being more likely to have two or more serious health problems (multimorbidity)
• commonly taking several different medications (polypharmacy).

This distinct pattern of health problems experienced by people living with intellectual and developmental disabilities may increase the risk of poorer outcomes from COVID-19 infection. For example, epilepsy is more commonly experienced by people living with intellectual and developmental disabilities, and epilepsy is a known risk factor for premature death from respiratory infections, like COVID-19.  Lower rates of vaccination and the type of vaccine that people receive might also influence the higher risk of poorer outcomes.

We will investigate whether the complex health problems experienced by people living with intellectual and developmental disabilities and vaccination patterns are linked to poorer COVID-19 outcomes. We hope that the results of this study will help improve outcomes of people living with intellectual and developmental disabilities who are infected with COVID-19.

There is still a pressing need to identify drug-based treatments for the continuing COVID-19 pandemic. Large-scale immunisation has been successful in stemming the tide of hospital admissions, but infections remain high with the ever-present risk of new variants arising against which current vaccines may be ineffective.

When lung cells are infected by the coronavirus, they mount a viral defence response. We have found that specific drugs, which stimulate this response, have potent antiviral properties. In particular, a class of drugs prescribed for certain heart conditions have been shown to inhibit the COVID virus replicating. One of these drugs, digoxin, is currently in clinical use.

By analysing electronic health record data, we can determine if people taking digoxin are less likely to get COVID or develop less severe symptoms when infected. If our hypothesis proves to be correct, people on alternative heart medications could be switched to digoxin and, depending on the benefit, it could subsequently be deployed to the wider public as a preventative drug.

The specific aims of the proposal are to:

1. Determine whether digoxin medication provides protection against SARS-Cov-2 infection and whether it is associated with a better outcome post infection in terms of hospital and critical care admissions. We will look at digoxin effectiveness by making two comparisons:- We will firstly look at SARS-Cov-2 incidence/severity in the digoxin versus non digoxin cohorts.
   – Secondly, we will compare SARS-Cov-2 incidence/severity in the digoxin cohort versus the cohort on alternative arrhythmia medications. We will initially ignore the small population on both digoxin and beta blockers.
   – We will initially define the digoxin cohort to comprise those individuals with at least one dose of the drug. We will then do a sensitivity analysis by including dosing information.

2. Analyse other possible factors that are correlated with digoxin medication and assess to what extent they explain the beneficial effects.

We predict that the incidence of COVID will be lower, and/or symptoms will be less severe, in people taking digoxin. If this proves to be the case then digoxin could be readily and rapidly prescribed, initially to frontline health workers and carers and then to the wider general population as a preventative/protective treatment against COVID-19 and other strains of coronavirus as they appear.

This would have a massive beneficial impact on the NHS and related services by helping to maintain normal staffing levels and reducing patient admissions due to COVID.  In turn, there would be a more rapid resumption of non-COVID related care and procedures which would help to reduce the huge patient waiting lists.

Heart Failure (HF) is a complex set of conditions that results in the heart performing less well than it did – it is no longer pumping blood as well as it would in perfect health. HF affects around 1 million patients in the UK, and accounts for 2% of NHS direct costs. HF also disproportionally affects socioeconomically deprived groups, and is associated with a high rate of hospitalisation and mortality.

Emerging evidence suggests that many of the risk factors of HF are similar to those of poor outcomes in COVID-19 patients.  Also, reductions in hospital activity in dealing with cardiovascular diseases during the pandemic are likely to worsen HF patient outcomes. It is therefore important to take a closer look at HF patients and study the effects of COVID-19 and vaccines in different HF subtypes using large-scale, representative data. 

The CVD-COVID-UK programme links various large health data sources from across the UK. Looking at this combined data will provide reliable evidence about the risk of COVID-19 complications and the efficacy of vaccines in groups of people with different subtypes of HF.

Given the high number of people living with HF (around 1 million) and its huge impact on quality of life, the proposed analysis will provide directly useful evidence to inform clinical decision making and vaccination efforts for HF patients. 

Sight is the sense that is the most valued by the general public. The impact of the COVID-19 pandemic on sight loss and how the NHS manages eye disease remains under-researched. Some reports suggest that COVID-19 infection and/or vaccination may trigger sight-threatening inflammation in the eye. There is also emerging evidence suggesting that certain eye diseases may be associated with poorer health outcomes following COVID-19 infection. As one example, this may include age-related macular degeneration, an eye disease which affects around 20% of people aged 75 years and above, which is an age group experiencing some of the worst COVID-19 outcomes. However, these studies to date have been small, and the conclusions need to be confirmed with studies of larger numbers of people.

Using health data from England, we aim to answer the following questions:

1. Does COVID-19 infection and/or vaccination trigger or worsen sight-threatening eye diseases?
2. Do people with certain eye conditions have poorer health outcomes after infection with COVID-19?
3. What is the scale of disruption to NHS care for eye disease and what is the potential indirect impact, such as delayed appointments or treatments, of COVID-19 on sight-impairment and blindness?

This research aims to provide crucial insights and guide government and NHS policy to reduce avoidable blindness.

If some eye diseases are shown to be associated with poorer outcomes for patients following COVID-19 infection, this information could potentially be used to identify patients at a higher risk to be prioritised to receive early preventative or supportive treatment measures.

Addressing these questions will enable us to understand how the COVID-19 pandemic has impacted on the management of eye disease by the NHS in England – for example, by comparing the number of eye disease operations carried out or cancelled before and during the COVID-19 pandemic. We will see if this has recovered – and if not, results from this research may provide evidence to help to aid this recovery. We will also begin to understand the direct and indirect effects of COVID-19 infection as well as vaccination on the development, progression, and severity of eye disease.

This research project is awarded through a funding call by Health Data Research UK and the Alan Turing Institute as part of the wider Data and Connectivity National Core Study.

Further details on this project are available here.

Outputs

Risk of cardiovascular events following COVID-19 in people with and without pre-existing chronic respiratory disease

• Paper submitted to a journal (decision pending)
• medRxiv preprint 03/03/23 can be viewed here
• Code and phenotypes used in this study are available in GitHub here

This research project is awarded through a funding call by Health Data Research UK and the Alan Turing Institute as part of the wider Data and Connectivity National Core Study.

Further details on this project are available here.

This research project is awarded through a funding call by Health Data Research UK and the Alan Turing Institute as part of the wider Data and Connectivity National Core Study.

Further details on this project are available here.

Outputs

Digital ethnicity data in population-wide electronic health records in England: a description of completeness, coverage, and granularity of diversity

• Paper submitted to a journal (decision pending)
• medRxiv preprint 11/11/22 can be viewed here
• Code and phenotypes used in this study are available in GitHub here

The COVID-19 pandemic created unprecedented critical care demand to provide breathing support (ventilation) to the sickest patients. As a result, many patients received ventilation in repurposed areas outside of existing intensive care units (ICUs) and usual admissions to ICU, such as after major surgery, were disrupted. Over the course of the pandemic, the way in which COVID-19 was treated in ICU changed as lessons were learned. Unfortunately, our previous research has shown that in spite of this, a similar proportion of those admitted to ICU with COVID-19 still die, and the risk of death appears even greater for those receiving ventilation outside ICU.

By identifying all patients receiving ventilation, or admitted to ICU, during their COVID-19 hospital admission and studying their details, such as demographics and comorbidities, we will explore which factors are associated with a patient’s risk of death and whether these factors have changed over the course of the pandemic. Comparing all patients admitted to ICU during COVID-19 with pre-pandemic years will reveal the extent to which the pandemic has impacted other ICU admissions not related to the virus.

Better understanding of an individual’s likely need of receiving ventilatory support, being admitted to ICU or of dying, when admitted to hospital with COVID-19, has multiple important implications. At an individual level such information may allow patients, and their treating clinicians, to better understand the risks they personally face, facilitating better informed treatment discussions. At trust and national levels, and in combination with understanding the disruption to pre-pandemic care, we aim to provide evidence of the demand for critical care services, and whether when this is stretched it affects outcomes, with important implications including future pandemic preparedness and addressing the elective backlog.

Mass rollout of several highly-effective Covid-19 vaccines has helped prevent severe cases of Covid-19, protecting against hospitalisation and death. However, uptake of Covid-19 vaccination has not been equal across the population, potentially exacerbating existing health inequalities and leaving some communities more vulnerable to the severe impacts of Covid-19.

We will use statistical analysis to identify inequalities in Covid-19 vaccine uptake, looking at differences by income deprivation, ethnic group, and geographical area. In each case, we will look at inequalities in vaccine uptake within vulnerable groups (defined by age and clinical vulnerability) as well as overall inequalities. We will also compare inequalities in Covid-19 vaccine uptake to inequalities in seasonal Influenza vaccine uptake to ask whether inequalities differ from those for routine vaccinations. Finally, we are also interested in exploring whether there is regional variation in the extent of income-related inequalities in vaccine uptake.

This research is part of a larger project which also includes interviews and focus groups with members of the public and professionals involved in the vaccine rollout to better understand the drivers behind unequal vaccine uptake.

Better understanding of inequalities in vaccine uptake can inform policy aimed at improving access to and uptake of vaccination.

Diabetes is a condition affecting approximately 4 million people in the UK. People with diabetes have high levels of blood glucose, which if unmanaged, can lead to serious damage to the heart, feet, eyes and kidneys. Previous research has shown that people with diabetes are more likely to become seriously unwell, or die, following a coronavirus infection. However, the exact reasons for that are still largely unknown.

We will report on how much more likely a person with diabetes is to become unwell or die following a COVID infection. We will also look at what factors (such as weight, BMI, blood glucose level, age, sex, ethnicity etc.) affect the likelihood of poor outcomes in patients with diabetes and a COVID infection. Analysing these factors in patients with and without diabetes, will help us to unpick to what extent the worse outcomes are related to the diabetes diagnosis, as opposed to the underlying factors such as BMI. Type 1 and type 2 diabetes patients will be analysed separately as these are different conditions and the underlying factors may not be the same.

We recently submitted findings from the city-wide Greater Manchester Care Record (GMCR) database that include identification of specific risk factors for people with type 1 and type 2 diabetes in relation to serious illness or death following a COVID-19 infection. We now wish to extend the analysis from the GMCR data to a much larger dataset. The findings of this study will inform policy decisions at a national level in relation to reducing the risk of people with diabetes of all types becoming seriously ill after contracting COVID-19, as we move out of the pandemic to a ‘status quo’ of long-term coexistence with the virus.

Over the last 24 months, evidence has consistently reported that certain long-term diseases, such as diabetes,  are very common in people with COVID-19. Diabetes has also been linked with an increased risk of severity (i.e. worsened symptoms) and mortality (i.e. more deaths) in patients with COVID-19. A number of recent studies have also examined the link between having consistently high blood sugar levels, in people with and without diabetes, with COVID-19 outcomes. These studies show that patients with high sugar levels have a higher risk of death compared to those with normal range glucose levels or without diabetes. Further, there has been discussion on ‘new onset diabetes’ following COVID-19; however, long-term follow-up assessments in patients without pre-existing diabetes post-COVID-19 is limited.

This project will be the first population analysis to quantify the risk of developing new onset diabetes post-COVID-19 and in those with and without a host of cardiovascular diseases (such as stroke). It will also quantify its potential links with outcomes (such as death), compared to current and historical trends seen in developing new onset diabetes in those with post-seasonal influenza (i.e. flu). This project will assess and compare whether patients with and without cardiovascular diseases may need longer-term assessment to determine longer-term risk of diabetes and other outcomes after discharge.

This study will improve our understanding in this area and determine the epidemiology of new onset diabetes following COVID-19. It may allow us to make recommendations on whether patients require specialised diabetes screening and management following COVID-19 infection. This may improve patient care and wellbeing in those with and without prevalent cardiovascular disease and inform policy within the NHS and beyond.

Plain English summary to follow.

Heart Failure (HF) continues to be a major global health-care problem. Despite some recent advances  in therapy it still has an unacceptably high mortality rate. It is estimated that, to date, more than 38 million people suffer from HF world-wide. It affects approximately 2% of the general adult population and up to 10% of the elderly. As HF causes many symptoms, including breathlessness and fatigue, it has a dramatic impact on the quality of life of those affected, and limits their abilities to enjoy normal lives.

The COVID-19 pandemic is a global public health emergency that has dramatically affected all healthcare systems. During the pandemic sudden reconfiguration of healthcare services, including suspension of routine, face-to-face treatment, and follow-up appointments for many cardiovascular conditions occurred. This was necessary to accommodate the high number of patients arriving with COVID-19. Community care was also affected by the pandemic and had to adapt to the extreme scenario.

Throughout the first wave of the pandemic, we observed locally a significant decline in admission rates for decompensated HF. Furthermore, patients presenting to hospital were sicker compared to those being admitted before the pandemic. This resulted in a higher in-hospital mortality rate than the previous year. The increased HF mortality during the peak of the COVID-19 pandemic indicates the need for further research, to understand the underlying reasons for it, so that it can be avoided in the future.

To address these questions, we will use data available through the CVD-COVID-UK program to examine the impact of the COVID-19 pandemic on the epidemiology and treatment of HF at a national level, both in the hospital sector and the community.

Using these methods, we aim to:

• Establish the epidemiology of HF during COVID-19;
• Examine its management both in hospital and in primary care;
• Investigate the changes in hospitalization rates and patients characteristics;
• Determine the factors which were associated with different outcomes.

We will also consider changes in mortality and hospitalisations that occurred during the pandemic and compare them with those in previous years.

By providing detailed information on the burden of HF and how it was managed, at a national level, this work will undercover the changes that occurred to HF care during COVID-19 pandemic. This project will highlight new insights into the possible reconfiguration of services that could improve the overall service provided to HF patients. This review is timely given NHS England’s introduction of Integrated Care Systems as a means of offering end-to-end care, independent of the place of care. The results of this project will provide valuable information for future HF care. The ultimate aim is to ascertain the best approaches to caring for patients with HF,  to improve outcomes, in any future tragic situations.

Severe mental illness (SMI), which includes schizophrenia, bipolar disorder and major depression, affects about one in ten people. People with SMI die 10-20 years sooner than the general population, largely due to poorer physical health, in particular conditions such as heart attack. Survival after a heart attack is lower in people with SMI compared to those without. The reasons are poorly understood, but differences in care may contribute. We also do not know how the COVID-19 pandemic has affected any differences in receipt of care and risk of dying after a heart attack.

Using health data from England, we will study links between SMI and receipt of care and death following a heart attack, and whether these have been affected by the COVID-19 pandemic. To help us to understand our findings and to provide insight into experiences of the care pathway, including during the COVID-19 pandemic, we will also interview patients with SMI who have had a heart attack and their families or carers, as well as relevant healthcare workers involved with hospital care for patients with a heart attack.

Our project will identify points in the care pathway where patients with SMI may be disadvantaged and/or where healthcare workers could be better supported to deliver the best possible care for these vulnerable patients. Identifying whether any differences in care have worsened as a result of the COVID-19 pandemic will inform future responses to outbreaks or other disruptions to delivery of care.

Epilepsy, a tendency to repeated seizures, is common, affecting 600,000 people in the UK of all ages.  People with epilepsy face significant physical health, mental health and social problems. Small studies have shown that people with epilepsy may have more seizures, worse mental health and trouble getting medication due to COVID-19. Two large studies in England and the USA have shown a slightly increased risk of COVID-19 death in people with epilepsy.

To our knowledge, there are no studies that have examined whether COVID-19 has changed the lives of people with epilepsy in England.

Through a Health and Care Research Wales (HCRW) funded study, we have already started to address the knowledge gap in the Welsh population through an experienced and expert team making use of the Secure Anonymised Information Linkage (SAIL) databank and the Controlling COVID19 through enhanced population surveillance and intervention (Con-COV) project.  We propose to build on that and extend the work to look at data from the CVD-COVID-UK initiative as it holds data from linked, nationally collated electronic health records (EHRs) in England. We will analyse data from Wales and England separately to see if there are any differences between the nations given their differences in health and social care.  If possible, we will carry out analyses by combining data from the Welsh study and data obtained in this study from the English population.

If our results highlight issues or differences in the care for people with epilepsy, we will use professional and patient networks to improve epilepsy services and the lives of people with epilepsy. For example, if we find that people with epilepsy are more at risk from COVID related hospitalisations and/or death, this will provide evidence to support prioritisation of COVID vaccinations, and vaccinations in future pandemics. If we find that outcomes for people with epilepsy have worsened during the pandemic, this will provide evidence for prioritising resources to address “treatment gaps”.  Given the lack of a clear definition of long-Covid, and the study is reliant on analysing already collected rather than new data, it is beyond the scope of this study to investigate long-Covid.  However, within the available data, we will explore GP fitness for practice certification (ability to go back to work) as an additional proxy measure for severity other than hospitalisation and death.

There is strong evidence that infections with certain viruses making it more likely for someone to develop psychotic disorders, such as schizophrenia. Since the start of the COVID-19 pandemic, we have seen more people seeking treatment for psychosis symptoms in the UK. We currently do not know whether this is because of COVID-19 and its potential effects on the brain. Similarly, there have been some cases of psychosis after people have received COVID-19 vaccines. In this study, we will test whether people are more likely to develop psychosis after positive COVID-19 tests and after vaccination.

There have been reports of individual patients who have developed psychosis shortly after COVID-19 infection and after vaccination. However, we do not know whether these cases are representative of the whole population. Through this project, we will be able to assess the relationship between COVID-19 infection/vaccination and psychosis that will be more meaningful to the whole population.

If people are more likely to develop psychosis after COVID-19 infection and/or vaccination, this would suggest that there may be more psychosis cases than usual in the coming years. This would provide evidence to support increased funding to prevention and early intervention of psychosis in the NHS.

Plain English summary to follow.

The benefits of Covid-19 vaccinations are well-known; they reduce the risk of infection and lower the risk of serious illness or death associated with Covid-19. Evidence in England and Scotland suggests rates of COVID-19 hospitalisation and COVID-19 death are around five times higher in unvaccinated individuals in comparison to fully vaccinated individuals. Therefore, Covid-19 vaccination is key to society’s recovery from the Covid-19 pandemic. However, across the four nations of the UK and despite vaccines being freely available, millions of individuals remain completely unvaccinated or are under-vaccinated (defined as not having had all available doses of the vaccine). The rates of unvaccinated or under-vaccinated individuals vary by nation, age, ethnicity and other demographic characteristics.

We will extend current knowledge by investigating unvaccination and under-vaccination across all four nations of the UK and will harmonise the results to give an overall UK representation.

By using population-wide detailed electronic health records across the four nations, we will estimate how many individuals in the United Kingdom are completely unvaccinated, or who are under-vaccinated.  We will describe the demographic and clinical characteristics of those who are unvaccinated and under-vaccinated. We will further our understanding by characterising serious outcomes (COVID-19 related hospitalisations, critical care unit admission and death) among unvaccinated and under-vaccinated people in the UK.

We will provide insights for governments and national public health agencies to help improve vaccine uptake and coverage to as many people in the UK as possible. Our proposed work will feed into public messaging that will highly likely save lives, reduce hospitalisation and morbidity, particularly for the most vulnerable members of society.

Outputs

Under-vaccination and severe COVID-19 outcomes: meta-analysis of national cohort studies of over 64 million people in England, Northern Ireland, Scotland and Wales

• Paper submitted to a journal (decision pending)
• Code and phenotypes used to produce this paper are available in GitHub here

Asthma, interstitial lung disease (ILD) and chronic obstructive pulmonary disease (COPD) are chronic respiratory diseases that cause substantial disability and are associated with increased risk of death. Past studies have usually provided high-level snapshot pictures of their frequencies and associated impacts and costs. Given the impact of the COVID-19 pandemic we need to understand how these diseases are changing at a national level, to inform public health policy and planning.

Acute flare ups of asthma, or COPD, termed “exacerbations” represent a substantial socio-economic impact and preventing them is a high priority for management.  Several countries reported a substantial reduction in asthma or COPD exacerbations during the pandemic. To our knowledge, the largest study assessing routinely collected data from over 100,000 asthma patients from England reported a substantial and sustained reduction in asthma exacerbations during the pandemic until October 2021. However, it is still unclear if the substantial reduction has been sustained beyond October 2021, and whether vaccination to protect against COVID-19 or having COVID-19 has any impact on asthma or COPD exacerbations.

The aim of this study is to describe the number and population structure (e.g. age, sex, region, ethnicity and socioeconomic status) of people with asthma, ILD and COPD, across England and by region, from 2019 comparing how this has changed in the past three years since the start of the COVID-19 pandemic.  We will also describe trends in treatments, healthcare utilisation and disease outcomes such as deaths and hospital admissions over the same time period. To do this, we are developing an observatory, i.e. a large dataset of asthma, ILD and COPD patients which can potentially be maintained and regularly updated in the long term to answer further research questions about these diseases. In addition, we will describe the rate of asthma and COPD exacerbations across England and in different groups by population characteristics (e.g., age, sex, region, ethnicity, covid vaccination status and socioeconomic status). This project will tell us if the asthma or COPD exacerbations have bounced back to normal levels now that society is fully open, and whether getting infected with COVID-19 or vaccination has any role.

Our results will provide insights into how common and severe these diseases are in different areas and populations. This knowledge will play a crucial role in public health planning and identifying areas for future research and development and help us to better understand the impact of the COVID-19 pandemic on respiratory diseases. We will add value to these data, sharing respiratory clinical and data expertise. Our work could be used to develop disease specific risk models’ clinicians, healthcare providers and policy makers and influencers can use to better understand these diseases at a population level.

Plain English summary to follow.

Aortic stenosis (AS), or narrowing of the aortic valve, is the commonest reason for having heart valve surgery in the west, that causes poor quality of life and death, if untreated. It affects ~1-in-20 adults aged >65, but the exact number and characteristics of those affected is unknown. The only treatment is to replace the valve, either through open heart surgery: surgical aortic valve replacement (SAVR) or less invasive, ‘keyhole’ approach called transcatheter aortic valve implantation (TAVI).

Differences in treatment and outcomes in people from ethnic minorities and poorer backgrounds have been reported. The Covid-19 pandemic has highlighted, and possibly increased health inequalities in the UK.

The first step in tackling health inequalities is to understand the problem. We will use national data to describe the characteristics of patients undergoing SAVR/TAVI in England and explore the impact of Covid-19 on this.

This project will aim to:

1. describe and compare the characteristics of patients treated for AS by sex, ethnicity and socioeconomic status; and
2. see if the profile of patients treated for AS differs between pre and during Covid-19 pandemic time-periods.

The high-quality data generated from this nationwide study will lead to patient benefit by:

• Describing the characteristics of those being treated for AS, and enabling a better understanding of the extent of the problem if any are identified.
• Identifying areas for improvement.
• Informing future research and health policies to address any health inequalities that may be identified.

There is limited information describing the different ways people who have COVID-19 are managed. Different people have different treatments, sometimes no treatment at all. It is not known if outcomes (death or re-hospitalisation or other complications) vary depending upon how people are managed.

The aim of this study is to first describe the number and population structure (e.g. age, sex, region, ethnicity and socioeconomic status) of people diagnosed with COVID-19 in England. We will then describe trends in treatments, healthcare utilisation and disease outcomes such as death and hospital admissions over the same time period. We will take a closer look at people considered to be at high risk of poor outcomes, COVID-19 vaccination status, and specifically people who have a weakened immune system.

COVID-19 remains a problem and there have been multiple changes in management and severity over time. This work will help us to summarise how changes in treatment, including vaccination have changed over time and how this has impacted outcomes. We will add value to these data, sharing clinical and data expertise.

Our results will provide insights into how different groups of patients diagnosed with COVID-19 are treated and how their outcomes differ. This knowledge will play a crucial role in public health planning by finding patient groups that may benefit more from specific treatments. Our work could be used to develop risk models that healthcare providers and policy makers can use to make more informed decisions about the nature of COVID-19 treatment.

Plain English summary to follow.

Plain English summary to follow.

Plain English summary to follow.

An inclusive, open and transparent consortium has been established to work on CVD-COVID-UK / COVID-IMPACT projects. The consortium has over 360 members across more than 50 institutions including data custodians, data scientists with methodological and analytical expertise (statisticians, epidemiologists, health informaticians, bioinformaticians, computer scientists and others), and clinicians (including cardiologists, stroke physicians, vascular surgeons and others) – all of whom have signed up to an agreed set of principles.

If you’re interested in becoming a member of the consortium, please e-mail: bhfdsc@hdruk.ac.uk for more details.

Please refer to the ways of working document for detail on how the CVD-COVID-UK/COVID-IMPACT programme is managed.

Consortium members can submit project proposals, using our standard form, to the CVD-COVID-UK / COVID-IMPACT Approvals & Oversight Board.  Proposals must either be within the scope of the ethical and regulatory approvals for CVD-COVID-UK, which covers the relationship between cardiovascular disease and COVID-19, or for COVID-IMPACT, which covers the relationship between COVID-19 and other health conditions, and their related risk factors.

The Approvals & Oversight Board consists of representatives from data custodians, data controllers, researchers and public contributors.  It is coordinated by BHF Data Science Centre’s core team and chaired by the BHF Data Science Centre Operations Director.  The Board reviews submitted proposals (a process which includes a meeting between the project lead and public contributors – see the PPIE section below) to ensure that the:

• Project falls within the scope of the approvals in place for CVD-COVID-UK/COVID-IMPACT and is feasible using the available data sources/environments;
• Stated aims and objectives are clear;
• The project doesn’t unnecessarily overlap with existing projects;
• Requested data sources are either currently available in the TRE(s) or will be in the future (including whether there is sufficient coverage within specific datasets);
• Data source requests align with the project’s needs;
• The project is of relevance to patients and the public;
• Language used within the plain English summary is clear;
• There are adequate plans in place for PPIE.

Once reviewed, proposals are either approved, approved with conditions or rejected.  In some cases, project leads will be encouraged to collaborate with and perform their analyses as part of one of the approved projects.

CVD-COVID-UK/COVID-IMPACT project approval process

For any queries regarding project governance and approvals, please e-mail: bhfdsc@hdruk.ac.uk

The CVD-COVID-UK / COVID-IMPACT Approvals & Oversight Board membership includes five public contributors who ensure that the public/patient voice is considered and embedded appropriately in our projects.

The public contributors review and discuss project proposals (and research outputs) with researchers to ensure work being carried out meets the interests of people affected by heart and circulatory disease or other health conditions, to address any patient and/or public concerns, and to advise on best approaches for patient and public involvement throughout the project lifecycle.

Meetings with the public contributors are planned for the dates listed below (all meetings take place between 09:30-11:00 and you will be assigned a 30-minute slot) and new project proposals should be submitted a minimum of 2 weeks before these dates to allow sufficient time for triage by the centre and review by the public contributors, prior to the meeting:

• 15 June 2023
• 20 July 2023
• 17 August 2023
• 21 September 2023
• 19 October 2023
• 16 November 2023

The CVD-COVID-UK / COVID-IMPACT privacy statement explains how the partners involved in the consortium collect, store, manage and protect your personal data. It outlines the types of data that are accessed and how we use them.

To appropriately acknowledge our funders and recognise the use of patient data in the respective TREs, the relevant statements (from the document via the link below) should be included in our research outputs and publications.

CVD-COVID-UK/COVID-IMPACT Acknowledgements

In line with our principles:

• Manuscripts/reports must be published with open access
• Publications must be written ‘on behalf of the CVD-COVID-UK/COVID-IMPACT Consortium’