Projects Delivered

Frailty is a clinical condition that makes an older person more vulnerable to worsening health, increasing disability, and even death. In recent times, the COVID-19 pandemic may have led to more people becoming frail in the UK. Mandated lockdowns during the pandemic led to older adults doing less physical activity and experiencing poor mental health, and these are known to worsen frailty. To date, there is no research on how frailty levels have changed in the population before, during, and after the pandemic. In this study, we will examine frailty changes during the pre-pandemic and pandemic periods (2015–present) in Scotland. We plan to use primary care and hospital data of older adults aged 50 and over living in Scotland. Our findings would help identify older adults who developed frailty during the pandemic, and whose frailty levels worsened. We can also identify factors that contributed to worsening frailty, helping clinicians design targeted plans for patients.

Asthma is a common, long-term lung condition. The main symptoms of asthma are coughing, wheezing, chest tightness, and feeling out of breath. The UK has one of the highest rates of asthma in the world. 1 in 11 children and 1 in 12 adults suffer from asthma in the UK.

Some groups of people tend to become more unwell with asthma or find it more difficult to control their asthma. For example, asthma often leads to worse health outcomes and worse quality of life for women and people with lower incomes.

In this study, we will investigate how asthma affects different groups, including those with high and low incomes, men and women, and people from different ethnic groups. We will also look at how this has changed over the past 10 years.

The results will help the NHS provide better care for asthma patients.

Respiratory syncytial virus (RSV) causes a common respiratory infection in young children – almost all children have been infected with RSV by their second birthday. For most children RSV infection is mild, causing temporary symptoms such as fever, cough, and runny nose. However, up to 5% of children require treatment at a hospital. Data from electronic health records in Scotland can be used to explore how many children develop the more serious forms of RSV infection and to help sooner identify and treat children who might be at a higher risk. Additionally, studies have shown that an RSV infection in early childhood might increase the risk of developing asthma in later life. Asthma is a common, long-term lung disease that causes wheezing, coughing, and breathing difficulties and affects almost 10% of the population in the UK. Studying this link is important in understanding how RSV treatment or vaccines in early life might help protect people from developing asthma and reduce costs to the NHS.

Our project aims to understand how often GPs are checking the health of people with severe mental illness (SMI). SMI are a group of conditions that affect the day to day functioning of those who suffer with them. People with SMI are at increased risk of heart disease. They are more likely to smoke or be obese, and the drugs they take for their mental health can affect their physical health. Medical data in the UK is complicated, and so we want to provide resources for researchers who want to study heart disease in people with SMI. We want to see how six risk factors for heart disease are recorded in the different UK databases that hold medical information. This project will look at the data specifically for the NHS Lothian population. Then we want to see how often GPs are recording these risk factors and whether there are changes over time or by groups, such as ethnicity. The results will then be compared with the results from similar analysis we have completed using other health data from England and Wales.

In Scotland blood pressure (BP) monitoring accounts for 1.2 million primary care appointments annually. Reducing high BP decreases cardiovascular disease. However, BP checked by patients at home is more accurate than when checked by doctors or nurses in the surgery. The Scale Up BP and successor Florence services aimed to improve the quality of BP monitoring and management by allowing patients to measure their own BP at home and electronically report it to their practice. In the current covid19 emergency it could support remote management of BP. 
 
In the pilot phase people found Scale Up BP helped them manage their BP more effectively, this was then followed up by a larger programme - Florence. This should lead to reduced rates of cardiovascular disease, but this is difficult to measure without a matched comparison group. This project therefore aims to use anonymised data to compare rates of hospital admission for cardiovascular disease for Scale Up BP/Florence users with multiple matched patients from GP practices which do not offer this service yet. It will also compare patterns of service use before and during the current COVID-19 pandemic.

Similarly two other studies will investigate the use and impact of cardiovascular rehabilitation services and medicines optimisation on outcomes for people at risk of stroke and heart attack.

Using health data that is collected when someone interacts with clinical services can help researchers to better understand depression and its treatment. Most people who are diagnosed with depression are diagnosed by their GP, yet GP data are not readily available for research use across Scotland. We will use DataLoch data to study depression and its treatment across multiple sources of health data. This will include hospital data, data about prescription medications, and importantly GP records. The outputs of the project will be academic papers, as well as data tools (analysis scripts and phenotype definitions) that will be both returned to DataLoch and deposited in open science communities (e.g., HDR UK Phenotype library) to benefit future researchers. This study will result in a better understanding of how depression and its treatment are reflected in electronic health records, including better methods for identifying and treating those with depression.

Patient groups in intensive care units (ICUs) exhibit considerable diversity in terms of their health conditions and demographic profiles. This variance has been inadequately addressed, leading to a notable disparity in applying scientific findings to practical care. Elements contributing to critical illness include pre-disposing factors, such as multimorbidity, polypharmacy, and frailty, and precipitating factors such as diagnosis and illness severity. The complex interplay of these factors in determining patient trajectories and outcomes is poorly understood.

The first aim of the project will be to bring together healthcare datasets to understand the scale of the multimorbidity burden in the critical care population, alongside other pre-disposing and precipitating factors. I will aim to derive distinct patient clusters and explore the relationships between these clusters and patterns of multiple organ dysfunction and outcomes including early and late mortality, care-transitions and hospital readmission. This will help elucidate mechanistic pathways and identify targets for tailored interventions.

The second aim will be to use prediction modelling and causal inference techniques, such as target trial emulation, to identify and explore customised treatments within the different patient clusters identified that can lead to improved outcomes.  

When the heart is damaged cardiac troponin is being released in the bloodstream. Cardiac troponin tests measure the troponin level in the blood and are the preferred choice for the diagnosis of a heart attacks. However, clear cut-offs above which troponin values are suggestive of heart injury in children and young adults have not yet been defined. Additionally major concerns were raised within the COVID-19 pandemic in regards to heart involvement such as myocarditis in children and young adults after vaccinations.

We will therefore examine whether an increase in troponin measurements has been observed over this time period and will further try to evaluate a cut-off above which troponin measurements in children and young adults are suggestive of heart injury.