Artificial intelligence-derived risk score for mortality in secondary mitral regurgitation treated by transcatheter edge-to-edge repair: the EuroSMR risk score
Jörg Hausleiter, Mark Lachmann, Lukas Stolz, Francesco Bedogni, Antonio Popolo Rubbio, Rodrigo Estévez‐Loureiro, Sergio Raposeiras‐Roubín, Peter Boekstegers, Nicole Karam, Volker Rudolph, the EuroSMR Investigators, Thomas J. Stocker, Mathias Orban, Daniel Braun, Michael Näbauer, Steffen Maßberg, Aniela Popescu, T. Ruf, Ralph Stephan von Bardeleben, Christos Iliadis, Roman Pfister, Stephan Baldus, Christian Besler, Tobias Kister, Karl Patrik Kresoja, Philipp Lurz, Hölger Thiele, Benedikt Koell, Niklas Schofer, Daniel Kalbacher, Michael Neuß, Christian Butter, Karl‐Ludwig Laugwitz, Teresa Trenkwalder, Eroion Xhepa, Michael Joner, Hazem Omran, Vera Fortmeier, Muhammed Gerçek, Harald Beucher, Thomas Schmitz, Alexander Bufe, Jürgen Rothe, Melchior Seyfarth, Tobias Schmidt, Christian Frerker, Dennis Rottländer, Patrick Horn, Maximilian Spieker, Elric Zweck, Mohammad Kassar, Fabien Praz, Stephan Windecker, Tania Puscas, Marianna Adamo, Laura Lupi, Marco Metra, Emmanuel Villa, Giuseppe Biondi‐Zoccai, Corrado Tamburino, Carmelo Grasso, Fausto Catriota, Luca Testa, Maurizio Tusa, Cosmo Godino, Michele Galasso, Matteo Montorfano, Eustachio Agricola, Paolo Denti, Federico De Marco, Giuseppe Tarantini, Giulia Masiero, Gabriele Crimi, Andrea Munafò, Christina Giannini, Anna Sonia Petronio, Stefano Pidello, Paolo Boretto, Antonio Montefusco, Simone Frea, Filippo Angelini, Pier Paolo Bocchino, Francesco De Felice, Rodolfo Citro, Berenice Caneiro‐Queija, Xavier Freixa, Ander Regueiro, Laura Sanchís, Manel Sabaté, Dabit Arzamendi, Lluís Asmarats, Estefanıa Fernández‐Peregrina, Tomás Benito‐González, Felipe Fernández‐Vázquez, Isaac Pascual, Pablo Avanzas, Luis Nombela‐Franco, Gabriela Tirado‐Conte, Eduardo Pozo, Antonio Portolés‐Hernández
Abstract
BACKGROUND AND AIMS: Risk stratification for mitral valve transcatheter edge-to-edge repair (M-TEER) is paramount in the decision-making process to appropriately select patients with severe secondary mitral regurgitation (SMR). This study sought to develop and validate an artificial intelligence-derived risk score (EuroSMR score) to predict 1-year outcomes (survival or survival + clinical improvement) in patients with SMR undergoing M-TEER. METHODS: An artificial intelligence-derived risk score was developed from the EuroSMR cohort (4172 and 428 patients treated with M-TEER in the derivation and validation cohorts, respectively). The EuroSMR score was validated and compared with established risk models. RESULTS: The EuroSMR risk score, which is based on 18 clinical, echocardiographic, laboratory, and medication parameters, allowed for an improved discrimination of surviving and non-surviving patients (hazard ratio 4.3, 95% confidence interval 3.7-5.0; P < .001), and outperformed established risk scores in the validation cohort. Prediction for 1-year mortality (area under the curve: 0.789, 95% confidence interval 0.737-0.842) ranged from <5% to >70%, including the identification of an extreme-risk population (2.6% of the entire cohort), which had a very high probability for not surviving beyond 1 year (hazard ratio 6.5, 95% confidence interval 3.0-14; P < .001). The top 5% of patients with the highest EuroSMR risk scores showed event rates of 72.7% for mortality and 83.2% for mortality or lack of clinical improvement at 1-year follow-up. CONCLUSIONS: The EuroSMR risk score may allow for improved prognostication in heart failure patients with severe SMR, who are considered for a M-TEER procedure. The score is expected to facilitate the shared decision-making process with heart team members and patients.