Valvular heart diseases (VHD) occur when the valves of the heart don't work properly. They are influenced by various factors like age, gender, and socioeconomic status. As the population ages in the UK, it's expected that more people will develop VHD. However, access to healthcare may not be equal for everyone, leading to differences in how VHD is treated and managed.
This project aims to use national health data to study VHD in the UK. By combining statistics and data science methods, researchers will look into how VHD affects different groups of people. The goal is to understand how health inequalities impact the outcomes of VHD and develop better strategies for prevention and management.
The main goals of this research are:
To see how the number of cases of VHD has changed over time.
This will help understand how VHD is affecting the population, especially considering recent events like the COVID-19 pandemic.
To explore other health conditions that are linked to VHD.
By looking at connections between different health issues and VHD, we can improve how we care for people with VHD.
To understand what happens to people after they're diagnosed with VHD.
Using advanced statistical and data science techniques, researchers will explore how outcomes may vary amongst different groups of people with VHD, for example by age, sex, ethnicity and deprivation.
Overall, this project aims to shed light on how VHD affects people in the UK and find ways to reduce the impact of health inequalities on VHD care.
Valvular heart diseases (VHD) manifest as malfunctioning of the heart valves. VHD are multifactorial and have a complex aetiology; age, sex and deprivation are notable risk factors. Incidence of VHD will increase alongside the ageing population in the UK, and disparities in access to healthcare will widen inequalities in prognosis and care of the condition.
This project will utilise national data from CPRD and combine statistics and data science to explore the trends and outcomes of VHD, with additional analysis through the lens of health disparities. The output of this project will support new strategies for the prevention and management of valvular heart disease and mitigate the impact of health inequalities.
The research aim is to study the trends and outcomes of VHD in the UK.
The specific objectives are:
1) To investigate the temporal trends in incidence and prevalence of VHD.
The findings will show changes in incidence and prevalence of VHD over time to indicate the burden in the UK using primary and secondary care data. Subgroup analyses by age, sex, ethnicity, and deprivation will show disparities in the trends of VHD across patient groups.
2) To explore the comorbidities associated with VHD.
This objective will utilise AI network analysis (hypergraphs) to reveal more about the pattern of disease profile of patients with VHD using data from primary care and admitted patient care. Secondary analyses will show how the clinical needs of patients with VHD are different amongst patient groups.
3) To quantify the adverse clinical outcomes following diagnosis of VHD.
This objective will use machine learning (unsupervised cluster analysis)of demographic and clinical data to reveal phenotypes of VHD. Quantification of outcomes across clusters using Cox proportional hazard modelling will reveal inequalities of health outcomes across different patient groups.
Valvular heart disease incidence; cardiovascular* and non-cardiovascular** related hospital admission and diagnostic events; surgical procedures; blood transfusion.
*including hypertension; stroke; heart attack; ischemic heart disease; heart failure.
**including anaemia; arthritis; pneumonia; renal failure; liver disease; cancer; dementia.
Jianhua Wu - Chief Investigator - Queen Mary University of London
Harriet Larvin - Corresponding Applicant - Queen Mary University of London
Chris Gale - Collaborator - University of Leeds
Ramesh Nadarajah - Collaborator - University of Leeds
Rohan Devani - Collaborator - Barts and the London Queen Mary's School of Medicine and Dentistry
HES Admitted Patient Care;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation