Simplified Outcome Prediction in Patients Undergoing Transcatheter Tricuspid Valve Intervention by Survival Tree-Based Modelling

Simplified Outcome Prediction in Patients Undergoing Transcatheter Tricuspid Valve Intervention by Survival Tree-Based Modelling

Background: Patients with severe tricuspid regurgitation (TR) typically present with heterogeneity in the extent of cardiac dysfunction and extra-cardiac comorbidities, which play a decisive role for survival after transcatheter tricuspid valve intervention (TTVI). Objectives: This aim of this study...

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Main Authors: Vera Fortmeier, MD, Mark Lachmann, MD, Lukas Stolz, MD, Jennifer von Stein, MD, Karl-Philipp Rommel, MD, Mohammad Kassar, MD, Muhammed Gerçek, MD, Anne R. Schöber, MD, Thomas J. Stocker, MD, Hazem Omran, MD, Michelle Fett, Jule Tervooren, Maria I. Körber, MD, Amelie Hesse, Gerhard Harmsen, PhD, Kai Peter Friedrichs, MD, Shinsuke Yuasa, MD, PhD, Tanja K. Rudolph, MD, Michael Joner, MD, Roman Pfister, MD, Stephan Baldus, MD, Karl-Ludwig Laugwitz, MD, Stephan Windecker, MD, Fabien Praz, MD, Philipp Lurz, MD, Jörg Hausleiter, MD, Volker Rudolph, MD
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:JACC: Advances
Subjects:
machine learning
transcatheter tricuspid valve intervention
tricuspid regurgitation
Online Access:http://www.sciencedirect.com/science/article/pii/S2772963X24008561
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