Publications

Mitral regurgitation (MR) is highly prevalent both in the United States and worldwide and is an important determinant of morbidity and mortality.[1] The mechanisms of MR are divided broadly into primary (affecting valve leaflets) and secondary (affecting nonvalvular structures such as the left ventricle or atrium).2 Mixed MR occurs when

“This is one of the first artificial intelligence-driven studies providing critical insights into care patterns for patients with moderate or greater AR in the community. The urgency for digital technologies to identify AR patients earlier and novel therapies to improve outcomes for this vulnerable patient population has never been greater.”

“Over the last five years, new therapies to treat heart failure emerged with promising improvements in survival benefit. This study represents the first time we’ve seen an assessment of ‘5-class’ guideline-directed therapy — up to 4 foundational medication classes plus ICD/CRT-D therapy — for these patients. The next big challenge

BACKGROUND Valvular heart disease (VHD) is progressive and deadly, requiring timely diagnosis for optimal outcomes1 Prior landmark analyses of VHD prevalence in the United States (US), including the Framingham Heart Study2 and Nkomo et al.3 , have reported notable prevalence of disease However, these analyses were limited in scope (e.g.,

BACKGROUND Severe aortic stenosis (AS) remains a life-threatening form of valvular heart disease. Missed diagnosis of severe AS can lead to a delay in treatment and poor outcomes, but there are limited tools available to help physicians minimize the risk of missed diagnoses. OBJECTIVE Here, a Diagnostic Precision Algorithm was