TY - JOUR
T1 - Simplified Outcome Prediction in Patients Undergoing Transcatheter Tricuspid Valve Intervention by Survival Tree-Based Modelling
AU - Fortmeier, Vera
AU - Lachmann, Mark
AU - Stolz, Lukas
AU - von Stein, Jennifer
AU - Rommel, Karl Philipp
AU - Kassar, Mohammad
AU - Gerçek, Muhammed
AU - Schöber, Anne R.
AU - Stocker, Thomas J.
AU - Omran, Hazem
AU - Fett, Michelle
AU - Tervooren, Jule
AU - Körber, Maria I.
AU - Hesse, Amelie
AU - Harmsen, Gerhard
AU - Friedrichs, Kai Peter
AU - Yuasa, Shinsuke
AU - Rudolph, Tanja K.
AU - Joner, Michael
AU - Pfister, Roman
AU - Baldus, Stephan
AU - Laugwitz, Karl Ludwig
AU - Windecker, Stephan
AU - Praz, Fabien
AU - Lurz, Philipp
AU - Hausleiter, Jörg
AU - Rudolph, Volker
N1 - Publisher Copyright:
© 2025 The Authors
PY - 2025/2
Y1 - 2025/2
N2 - 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 was to create a survival tree-based model to determine the cardiac and extra-cardiac features associated with 2-year survival after TTVI. Methods: The study included 918 patients (derivation set, n = 631; validation set, n = 287) undergoing TTVI for severe TR. Supervised machine learning-derived survival tree-based modelling was applied to preprocedural clinical, laboratory, echocardiographic, and hemodynamic data. Results: Following univariate regression analysis to pre-select candidate variables for 2-year mortality prediction, a survival tree-based model was constructed using 4 key parameters. Three distinct cluster-related risk categories were identified, which differed significantly in survival after TTVI. Patients from the low-risk category (n = 261) were defined by mean pulmonary artery pressure ≤28 mm Hg and N-terminal pro–B-type natriuretic peptide ≤2,728 pg/mL, and they exhibited a 2-year survival rate of 85.5%. Patients from the high-risk category (n = 190) were defined by mean pulmonary artery pressure >28 mm Hg, right atrial area >32.5 cm2, and estimated glomerular filtration rate ≤51 mL/min, and they showed a significantly worse 2-year survival of only 52.6% (HR for 2-year mortality: 4.3, P < 0.001). Net re-classification improvement analysis demonstrated that this model was comparable to the TRI-Score and outperformed the EuroScore II in identifying high-risk patients. The prognostic value of risk phenotypes was confirmed by external validation. Conclusions: This simple survival tree-based model effectively stratifies patients with severe TR into distinct risk categories, demonstrating significant differences in 2-year survival after TTVI.
AB - 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 was to create a survival tree-based model to determine the cardiac and extra-cardiac features associated with 2-year survival after TTVI. Methods: The study included 918 patients (derivation set, n = 631; validation set, n = 287) undergoing TTVI for severe TR. Supervised machine learning-derived survival tree-based modelling was applied to preprocedural clinical, laboratory, echocardiographic, and hemodynamic data. Results: Following univariate regression analysis to pre-select candidate variables for 2-year mortality prediction, a survival tree-based model was constructed using 4 key parameters. Three distinct cluster-related risk categories were identified, which differed significantly in survival after TTVI. Patients from the low-risk category (n = 261) were defined by mean pulmonary artery pressure ≤28 mm Hg and N-terminal pro–B-type natriuretic peptide ≤2,728 pg/mL, and they exhibited a 2-year survival rate of 85.5%. Patients from the high-risk category (n = 190) were defined by mean pulmonary artery pressure >28 mm Hg, right atrial area >32.5 cm2, and estimated glomerular filtration rate ≤51 mL/min, and they showed a significantly worse 2-year survival of only 52.6% (HR for 2-year mortality: 4.3, P < 0.001). Net re-classification improvement analysis demonstrated that this model was comparable to the TRI-Score and outperformed the EuroScore II in identifying high-risk patients. The prognostic value of risk phenotypes was confirmed by external validation. Conclusions: This simple survival tree-based model effectively stratifies patients with severe TR into distinct risk categories, demonstrating significant differences in 2-year survival after TTVI.
KW - machine learning
KW - transcatheter tricuspid valve intervention
KW - tricuspid regurgitation
UR - https://www.scopus.com/pages/publications/85215231097
U2 - 10.1016/j.jacadv.2024.101575
DO - 10.1016/j.jacadv.2024.101575
M3 - Article
AN - SCOPUS:85215231097
SN - 2772-963X
VL - 4
JO - JACC: Advances
JF - JACC: Advances
IS - 2
M1 - 101575
ER -