Uncovering multimorbidity clusters for patients with atrial fibrillation

Applications are invited from graduates with a BSc (First or Upper Second) or MSc (Distinction), or equivalent, to work within the Wolfson Institute of Population Health. This 4-year studentship can commence in Spring or Autumn 2023 and will be based at the Whitechapel Campus. This is an exciting opportunity for a graduate from disciplines related to epidemiology, statistics, or health data sciences.

Project description

Background: Atrial fibrillation (AF) is a heart condition that causes an irregular and often abnormally fast heart rate, and is the most common serious cardiac arrhythmia in Western countries. AF is classified into paroxysmal, persistent or permanent AF. Guidelines recommend the use of oral anticoagulation for stroke prevention in AF, and have placed increasing emphasis on the use of oral anticoagulants in preference to anti-platelet drugs. Patients with AF often face an increased risk of developing stroke, congestive heart failure (CHF) and death. However, the risk of these and other long-term outcome events is influenced by AF and their types, and to what extent, is still debated. Therefore, this study is to investigate the cardiovascular and non-cardiovascular burden among patients with incident AF using large scale electronic health records covering both primary and secondary care patient pathways. Data from the Clinical Practice Research Datalink (CPRD) will be used to address the aims of this project.

Research aims:

The PhD project will address 3 main aims:

1)    To quantify the association between receipt of guideline recommended care and existing multimorbidity for patients with AF.

2)    To quantify the incidence of diagnosis or hospital admission of cardiovascular, non-cardiovascular outcomes and mortality for patients with AF compared to the matched general non-AF population.

3)    To identify factors associated with cardiovascular, non-cardiovascular outcomes and mortality for patients with AF in primary and secondary care and to quantify the loss in life expectancy of such factors between AF and non-AF populations.

Method: All three aims of this PhD will be addressed by conducting analyses of electronic health records from CPRD. Sample and measures: In CPRD, there are a total of 205,026 research quality (acceptable) patients within CPRD GOLD during the period 01/01/1998-31/12/2018, who were newly diagnosed with atrial fibrillation, whilst registered at a practice. For the same period, there are a total of 326,039 new AF patients within CPRD AURUM. A control cohort matched to the AF cohort by age, gender and practice is available. Analyses: survival models including Cox proportional hazard models will be conducted on CPRD. This will allow us to investigate the association between receipt of guideline recommended care and existing multimorbidity for patients with AF (aim 1). The incidence of diagnosis or hospital admission of cardiovascular, non-cardiovascular outcomes and mortality for patients with AF will be assessed through survival models and survival curves (Kaplan-Meier plot) (aim 2). Flexible parametric models will be conducted to identify factors associated with cardiovascular and non-cardiovascular outcomes and mortality for patients with AF in primary and secondary care (aim 3).

Timetable:

Year 1: Ethical approval for CPRD data access, data management and pre-processing. Study 1- systematic review of current literature and perform survival analysis for existing multimorbidity for patients with AF.

Year 2: Complete analyses for aim 2 and write up for aim 1 and 2 and draft papers for publication. Attend an international conference to present findings from aim 1 and 2.

Year 3: Complete analyses and write up for aim 3 and draft papers for publication. Attend an international conference and present findings

Year 4: complete thesis writeup and submit.

About the candidate: This PhD would be suitable for a candidate with a background in public health, epidemiology, statistics, computer science, or related areas with an interest in big data, health analytics, electronic health records and cardiovascular disease. The successful candidate will be keen to undertake interdisciplinary work using advanced statistics and data mining techniques.

Informal enquiries can be made via email to: Professor Jianhua Wu, [Email Address Removed] 

How to apply

Your application should consist of a CV and contact details of two academic referees. You must also include a personal statement (1,000 words maximum) describing your suitability for the selected project including how your research experience and interests relate to the project.

Please submit your application to: Patrick Mullan ([Email Address Removed]).