Implementation of the effects of hypertension in a patient-level model of atrial fibrillation

This thesis focuses on incorporating hypertension effects into a patient-level model of atrial fibrillation developed at Maastricht University. The model has been designed to simulate the lifespan of a virtual patient cohort, from birth to 100 years of age. This is based on a Markov model that comprises states characterizing the clinical conditions of virtual patients, but it doesn’t explicit atrial fibrillation risk factors. Hypertension constitutes the comorbidity most encountered by patients affected by atrial fibrillation, and prehypertension is also linked to an increased risk of experiencing stroke and atrial fibrillation. Therefore, to improve the model, the effects of both hypertension and prehypertension have been included into the patient-level model of atrial fibrillation. In this work, the impact of high blood pressure is integrated introducing a parallel Markov model to characterize individual blood pressure states, improving the atrial fibrillation model. The effects of hypertension on clinical outcomes such as stroke, death, and atrial fibrillation were also included. The model was successively validated through comparison with literature data. The results exhibit a notable alignment with real-world prevalence trends, demonstrating the model's ability to capture age-dependent dynamics and contribute valuable insights into cardiovascular health.