Impact of Advanced Imaging and Enhanced Risk Profiling on Mitral Valve Prolapse

SUMMARY: Mitral valve prolapse (MVP) is a common cardiac condition that is frequently associated with trace to mild mitral regurgitation, is usually asymptomatic, and most often ignored. When MVP progresses to significant regurgitation, patients may develop heart failure, atrial fibrillation, and pulmonary hypertension and is a frequent

indication for intervention. However, MVP is a phenotypical presentation of numerous underlying diseases and is commonly encountered in collagen vascular disorders and a large variety of congenital disorders. Underlying tissue characteristics including fibrosis of the left ventricle and papillary muscles, and mitral annulus disjunction

are associated with MVP, predispose to ventricular arrhythmias which may be fatal, and do not necessarily correlate with severity of MVP and regurgitation. The purpose of this project is to enhance the clinical identification of people who are at risk of moderate to severe MVP or have associated factors that indicate risk

of unexpected health events or complicate the treatment. In Aim 1, this project will describe the history of MVP, related cardiac morbidities, and other conditions that may contribute to or identify the risk of poor health outcomes. This will involve evaluation of a large population in Intermountain Health, a health system with more

than 30-years of data warehousing of electronic health record (EHR) data. Intermountain’s 33 hospitals, 385 medical clinics, and integrated services provide health and healthcare services to people across 7 mountain states and includes a broad rural health component. Outcomes will include MVP diagnosis and post-diagnosis

health events. For Aim 2, the project will evaluate heritable risk factors for MVP endpoints. This will first leverage a unique population genealogy of tens of millions of people in family pedigrees and linked EHR data to examine familial risks. It will also employ a large-scale genetic testing project with hundreds of thousands of participants

to evaluate polygenic risk scores. Unfortunately, no risk stratification nomogram exists for assessing MVP risks and predictors of MVP onset and progression are reported in piecemeal form, thus in Aim 3, drawing together clinical and genetic risk prediction approaches, a novel set of clinical decision tools will be created using EHR

data to empower the identification of people who are at risk of MVP-associated outcomes. Most importantly, this will include multivariable risk equations for stratifying risk of severe health endpoints for people with MVP that can be used to inform risk assessment and clinical care plans in guiding management and treatment of people

with elevated risk of death or major health events. One set of risk models will be developed with the aim of creating a clinical decision tool that predicts a near-maximum amount of variance in risk using a parsimonious set of clinically-available factors that can be used in the EHR background to calculate a risk score that the EHR

delivers to the point of care without needing modified data collection or clinician input in the EHR process. This project will resolve disconnects in MVP risk assessment and treatment, providing decision tools that can be clinically implemented for standardized MVP risk assessment to achieve the healthiest MVP outcomes possible.