Ramesh Nadarajah is a British Heart Foundation Clinical Research Fellow at the University of Leeds and a Cardiology Speciality Registrar at Leeds Teaching Hospitals NHS Trust. He qualified in medicine at the University of Cambridge and obtained a MA (Hons) in neuroscience. He has worked as a doctor for the last nine years across London and Yorkshire.
After becoming a member of the Royal College of Physicians he was awarded a Clinical Research Fellowship by the British Heart Foundation.
Dr Nadarajah is a member of the British Cardiovascular Society, British Society for Echocardiography, Royal College of Physicians of London and the European Society of Cardiology. He is a member of the IMPACT steering group. His clinical interests are in general cardiology.
His research incorporates the use of large routinely-collected datasets to answer clinical questions and develop and validate prediction models, particularly in the area of atrial fibrillation. He has published previously on heart attacks cardiomyopathy, cardiovascular imaging, heart failure, and the effect of the COVID-19 pandemic on cardiovascular services and the care of patients with cardiovascular disease.
Atrial fibrillation (AF) is the most common abnormal heart rhythm and confers a five-fold increased risk of stroke, which can be reduced by two-thirds by oral anticoagulants. However, because AF can be asymptomatic up to 30% of people living with AF in the UK are undiagnosed and up to 15% of strokes occur due to undiagnosed AF. There is rationale for the early diagnosis of AF, before this tragic complication occurs, but population-based screening is not recommended.
Prediction models could contribute to AF screening by identify individuals at higher risk of developing AF. Previously developed models are limited by one or more of their use of small, geographically remote or historical datasets, suboptimal performance and/or predictor variables not readily available in usual practice. None have yet reached widespread clinical practice.
In this research project Ramesh aims to develop a prediction model that could make targeted screening for AF feasible in the UK within the data sources available in the NHS. He is developing the model in a large dataset of routinely-collected primary care electronic health records (EHRs) which is representative of the UK population in terms of age, sex and ethnicity. He is investigating a number of techniques and engaging with EHR system providers to verify that the final product can be implemented within the NHS. He is also exploring ethical considerations, implementation in practice, and the views of patients and healthcare professionals.