CONTACT US
White Papers

Utilizing artificial intelligence to predict the progression from moderate to severe aortic stenosis

As Presented at TCT and Published in JACC

Share on social: 

LinkedIn
Twitter
Facebook

Follow egnite on social:

Linkedin Twitter Youtube

Related Articles
Press

egnite 2026 Benchmark Report: Four-Class GDMT Prescribing in Systolic Heart Failure More Than Doubles, Yet Four in Five Patients Are Not Prescribed Full Guideline Therapy

Real-world data from 47 U.S. health systems shows three-year survival of 76% among systolic heart failure patients prescribed four GDMT classes, versus 52% among those prescribed none. ALISO VIEJO, Calif., Oct. 21, 2026 — egnite, Inc., a technology company advancing guideline-directed cardiovascular care and real-world evidence, today released its 2026 Benchmark Report
Press

egnite’s Call for Science Study on M-TEER Device Durability and Long-Term Patient Outcomes to be Featured at TCT 2026

The egnite Registry contributed de-identified, longitudinal data, linking serial echocardiograms with clinical outcomes, to help answer what happens to patients after a successful mitral transcatheter edge-to-edge repair (M-TEER) procedure.  ALISO VIEJO, Calif. — October 13, 2026 — egnite, Inc., a cardiovascular intelligence company that helps clinicians identify and manage patients with untreated heart disease, today announced that Dr. John T. Saxon, Director of the Advanced Cardiac Valve Center at University of Virginia
Publications

Mitral Regurgitation and Severe Aortic Stenosis: Clinical Characteristics, Prognostic Impact, and Response to TAVR: Insights From egnite Data

BACKGROUND Aortic stenosis (AS) and mitral regurgitation (MR) frequently co-occur, complicating diagnosis and treatment. We examined current US treatment trends and patient outcomes among patients with severe AS and at least moderate MR. METHODS We analyzed data from 2 992 362 patients (aged ≥18 years) undergoing 5 245 904 echocardiograms at 43 US institutions