egnite Research

“These results further underscore the poor prognosis associated with untreated aortic stenosis of any severity and provide meaningful insights for the management of this patient population.”Philippe Généreux, MD, FACC Director of the Structural Heart Program of Morristown’s Gagnon Cardiovascular Institute and lead author of the study. BACKGROUND Previously, we described a novel aortic stenosis (AS) […]

“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.” Nicholas S. Amoroso, MDAssistant Professor […]

“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 to overcome is implementing care […]

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., reporting only valvular regurgitation or […]

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 developed from a deidentified dataset […]

BACKGROUND Progression from moderate to severe aortic stenosis (AS) warrants careful monitoring due to the increased risk of sudden death and heart failure, with disease progression significantly varying among patients and no accurate predictive tools presently available. OBJECTIVE A Disease Progression Algorithm was developed from a deidentified database of 1,163,923 echocardiographic (echo) reports from 35 […]