Artificial intelligence-derived risk score for mortality in secondary mitral regurgitation treated by transcatheter edge-to-edge repair: The EuroSMR risk score

Unidades de investigação

• Cirurgia e Fisiologia

• Laboratório Associado RISE- Rede de Investigação em Saúde

  

  Investigador

  Fernando Carlos De Landér Schmitt

• RISE-Health

  

  Investigador

  Fernando Carlos De Landér Schmitt

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. © 2024 The Author(s). Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved.

Keywords

• Artificial Intelligence; Echocardiography; Heart; Heart Valve Prosthesis Implantation; Humans; Mitral Valve Insufficiency; Risk Factors; Treatment Outcome; beta adrenergic receptor blocking agent; brain natriuretic peptide; enkephalinase inhibitor; mineralocorticoid antagonist; aged; area under the curve; Article; artificial intelligence; atrial fibrillation; body mass; cardiac resynchronization therapy; chronic obstructive lung disease; cohort analysis; coronary artery disease; echocardiography; estimated glomerular filtration rate; EuroSCORE; female; follow up; heart failure; heart left ventricle ejection fraction; heart left ventricle enddiastolic volume; hospital mortality; hospitalization; human; major clinical study; male; mitral valve regurgitation; mortality; New York Heart Association class; receiver operating characteristic; renin angiotensin aldosterone system; retrospective study; transcatheter edge to edge mitral valve repair; tricuspid annular plane systolic excursion; ar