Artificial intelligence-derived risk score for mortality in secondary mitral regurgitation treated by transcatheter edge-to-edge repair: the EuroSMR risk score
Authors: Hausleiter Jörg , Lachmann Mark , Stolz Lukas , Bedogni Francesco , Rubbio Antonio P , Estévez-Loureiro Rodrigo , Raposeiras-Roubin Sergio , Boekstegers Peter , Karam Nicole , Rudolph Volker ,   the EuroSMR Investigators, Stocker Thomas , Orban Mathias , Braun Daniel , Näbauer Michael , Massberg Steffen , Popescu Aniela , Ruf Tobias , von Bardeleben Ralph Stephan , Iliadis Christos , Pfister Roman , Baldus Stephan , Besler Christian , Kister Tobias , Kresoja Karl , Lurz Philipp , Thiele Holger , Koell Benedikt , Schofer Niklas , Kalbacher Daniel , Neuss Michael , Butter Christian , Laugwitz Karl-Ludwig , Trenkwalder Teresa , Xhepa Eroion , Joner Michael , Omran Hazem , Fortmeier Vera , Gerçek Muhammed , Beucher Harald , Schmitz Thomas , Bufe Alexander , Rothe Jürgen , Seyfarth Melchior , Schmidt Tobias , Frerker Christian , Rottländer Dennis , Horn Patrick , Spieker Maximilian , Zweck Elric , Kassar Mohammad , Praz Fabien , Windecker Stephan , Puscas Tania , Adamo Marianna , Lupi Laura , Metra Marco , Villa Emmanuel , Zoccai Giuseppe Biondi , Tamburino Corrado , Grasso Carmelo , Catriota Fausto , Testa Luca , Tusa Maurizio , Godino Cosmo , Galasso Michele , Montorfano Matteo , Agricola Eustachio , Denti Paolo , De Marco Federico , Tarantini Giuseppe , Masiero Giulia , Crimi Gabriele , Munafò Andrea Raffaele , Giannini Christina , Petronio Anna , Pidello Stefano , Boretto Paolo , Montefusco Antonio , Frea Simone , Angelini Filippo , Bocchino Pier Paolo , De Felice Francesco , Citro Rodolfo , Caneiro-Queija Berenice , Freixa Xavier , Regueiro Ander , Sanchís Laura , Sabaté Manel , Arzamendi Dabit , Asmarats Lluís , Peregrina Estefanía Fernández , Benito-González Tomas , Fernández-Vázquez Felipe , Pascual Isaac , Avanzas Pablo , Nombela-Franco Luis , Tirado-Conte Gabriela , Pozo Eduardo , Portolés-Hernández Antonio , Palomero Vanessa Moñivas , Sampaio Francisco , Melica Bruno , Rodes-Cabau Josep , Paradis Jean-Michel , Alperi Alberto , Shuvy Mony , Haberman Dan 
Published: January 2024

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 &lt; .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 &lt;5% to &gt;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 &lt; .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.