• LOGIN
    Login with username and password
Repository logo

BORIS Portal

Bern Open Repository and Information System

  • Publications
  • Theses
  • Research Data
  • Projects
  • Organizations
  • Researchers
  • More
  • Collections
  • Statistics
  • LOGIN
    Login with username and password
Repository logo
Unibern.ch
  1. Home
  2. Publications
  3. Predicting Outcomes in Patients With Tricuspid Regurgitation Undergoing Transcatheter Edge-to-Edge Repair Using an Artificial Intelligence-Derived Risk Score: The EuroTR Risk Score.
 

Predicting Outcomes in Patients With Tricuspid Regurgitation Undergoing Transcatheter Edge-to-Edge Repair Using an Artificial Intelligence-Derived Risk Score: The EuroTR Risk Score.

Options
  • Details
  • Files
BORIS DOI
10.48620/96867
10.48620/96867
Publisher DOI
10.1016/j.jcin.2025.11.034
PubMed ID
41813281
Description
Background
Risk stratification for tricuspid valve transcatheter edge-to-edge repair (T-TEER) is paramount in the decision-making process to appropriately select patients with severe tricuspid regurgitation.
Objectives
The aim of this study was to develop and validate an artificial intelligence-driven risk score, the EuroTR (European Registry of Transcatheter Repair for Tricuspid Regurgitation) score, to predict 1-year mortality in patients undergoing T-TEER.
Methods
The EuroTR score was developed using data from the EuroTR registry, comprising 1,225 patients in the derivation cohort and 601 patients in the validation cohort. On the basis of 18 clinical, laboratory, echocardiographic, and hemodynamic parameters, an extreme gradient boosting algorithm was trained and independently validated against established risk models.
Results
Among the entire study cohort (N = 1,826), the overall 1-year survival rate was 82.1% (95% CI: 80.1%-84.2%), with no significant differences between the derivation and validation cohorts. The EuroTR score successfully stratified patients into low-risk and high-risk groups for 1-year mortality after T-TEER (HR: 4.26; 95% CI: 2.71-6.67; P < 0.001), and it significantly outperformed established risk scores such as the EuroScore and the TRI-SCORE in the validation cohort. Beyond mortality prediction (Harrell's C index [validation cohort] = 0.741; 95% CI: 0.699-0.783), increasing EuroTR score values were associated with a higher likelihood of a clinically relevant combined endpoint of 1-year mortality, need for heart failure hospitalization, or persistent dyspnea corresponding to NYHA functional class ≥III. The likelihood of poor outcomes increased from 30.6% in patients with the lowest EuroTR scores (EuroTR risk rank <5%) to 85.5% in the highest risk group (EuroTR risk rank ≥95%). The EuroTR score's performance was confirmed in several subgroups (atrial vs nonatrial tricuspid regurgitation, TRILUMINATE-eligible vs TRILUMINATE-noneligible patients, and patients with vs without cardiac implantable electronic device leads).
Conclusions
The EuroTR score offers an easy-to-use, externally validated, accurate risk stratification tool for patients undergoing T-TEER. It supports personalized treatment strategies and the design of future clinical trials, helping optimize patient selection and enhance shared decision-making within multidisciplinary heart teams.
Date of Publication
2026-03-09
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
Keyword(s)
artificial intelligence
•
edge-to-edge repair
•
machine learning
•
mortality prediction
Language(s)
en
Contributor(s)
Hausleiter, Jörg
Stolz, Lukas
Kresoja, Karl-Patrik
von Stein, Jennifer
Fortmeier, Vera
Koell, Benedikt
Rottbauer, Wolfgang
Kassar, Mohammadorcid-logo
Clinic of Cardiology
Goebel, Bjoern
Denti, Paolo
Achouh, Paul
Rassaf, Tienush
Barreiro-Perez, Manuel
Boekstegers, Peter
Rück, Andreas
Zdanyte, Monika
Adamo, Marianna
Vincent, Flavien
Schlegel, Philipp
Rosch, Sebastian
Wild, Mirjam G
Besler, Christian
Toggweiler, Stefan
Brunner, Stephanie
Grapsa, Julia
Patterson, Tiffany
Thiele, Holger
Kister, Tobias
Tarantini, Giuseppe
Masiero, Giulia
De Carlo, Marco
Sticchi, Alessandro
Voss, Fabian
Polzin, Amin
Rubbio, Antonio Popolo
Bedogni, Francesco
Laugwitz, Karl-Ludwig
Konstandin, Mathias H
Van Belle, Eric
Metra, Marco
Geisler, Tobias
Estévez-Loureiro, Rodrigo
Mahabadi, Amir Abbas
Karam, Nicole
Maisano, Francesco
Lauten, Philipp
Praz, Fabien
Clinic of Cardiology
Kessler, Mirjam
Kalbacher, Daniel
Rudolph, Volker
Iliadis, Christos
Lachmann, Mark
Lurz, Philipp
Additional Credits
Clinic of Cardiology
Graduate School for Health Sciences (GHS)
Series
JACC: Cardiovascular Interventions
Publisher
Elsevier
ISSN
1876-7605
1936-8798
Access(Rights)
open.access
Show full item
BORIS Portal
Bern Open Repository and Information System
Build: dd892c [ 9.04. 8:30]
Explore
  • Projects
  • Funding
  • Publications
  • Research Data
  • Organizations
  • Researchers
  • Audiovisual Material
  • Software & other digital items
  • Events
More
  • About BORIS Portal
  • Send Feedback
  • Cookie settings
  • Service Policy
Follow us on
  • Mastodon
  • YouTube
  • LinkedIn
UniBe logo