Atrial fibrillation (AF) is the most common clinical heart rhythm disorders that disrupts quality of life through symptoms such as palpitations and shortness of breath, and substantially increases the risk of further diagnoses such as stroke, dementia and heart failure. Our aim is to consider how a broad range of risk factors may predict AF and the subsequent events that can often be more significant to the patient. We will use carefully constructed models to consider which patients may be at most risk of AF and its subsequent events. By doing so, we hope to improve the risk prediction of these often devastating events. Importantly, we also anticipate that some risk factors may be specific to the biological sex of the individual. To account for this, we will consider sex-specific risk factors such as complicated pregnancies for women, to develop sex-specific prediction models. To achieve these aims, this study will run for a duration of 36 months. We anticipate that improved risk prediction models will enable better identification of the more ‘at-risk’ patients and may enable prioritisation of treatment for patients in which this risk is high. In doing so, we are hopeful that the disease burden of AF can be substantially reduced.
