Objective With increasing age, the prevalence of aortic stenosis grows exponentially, increasing left heart pressures and potentially leading to myocardial hypertrophy, myocardial fibrosis and adverse outcomes. To identify patients who are at greatest risk, an outpatient model for risk stratification would be of value to better direct patient imaging, frequency of monitoring and expeditious management of aortic stenosis with possible earlier surgical intervention. In this study, a relatively simple model is proposed to identify myocardial fibrosis in patients with a diagnosis of moderate or severe aortic stenosis. Design Patients with moderate to severe aortic stenosis were enrolled into the study; patient characteristics, blood work, medications as well as transthoracic echocardiography and cardiovascular magnetic resonance were used to determine potential identifiers of myocardial fibrosis. Setting The Royal Brompton Hospital, London, UK Participants One hundred and thirteen patients in derivation cohort and 26 patients in validation cohort. Main outcome measures Identification of myocardial fibrosis. Results Three blood biomarkers (serum platelets, serum urea, N-terminal pro-B-type natriuretic peptide) and left ventricular ejection fraction were shown to be capable of identifying myocardial fibrosis. The model was validated in a separate cohort of 26 patients. Conclusions Although further external validation of the model is necessary prior to its use in clinical practice, the proposed clinical model may direct patient care with respect to earlier magnetic resonance imagining, frequency of monitoring and may help in risk stratification for surgical intervention for myocardial fibrosis in patients with aortic stenosis.
Myocardial Fibrosis Quantified by Cardiac CT Predicts Outcome in Severe Aortic Stenosis After Transcatheter Intervention
