Aims Although several treatment options are available for patients with severe mitral regurgitation (MR), a significant proportion of patients remain ineligible for any mitral valve (MV) intervention. We aimed to analyse the phenotypic characteristics of surgical high-risk patients ineligible for MV interventions using an unsupervised phenotypic clustering approach. Methods and results Between 2014 and 2022, the CHOICE-MI registry included 984 patients with MR undergoing screening for transcatheter MV replacement at 33 international sites. For this study, only patients with screening failure receiving medical therapy alone were included. Patients receiving transcatheter or surgical treatment were excluded. A cluster analysis using K-means was performed on baseline clinical, demographic, and imaging variables to identify different patient phenotypes. Among 284 patients with MR (77.4 ± 8.82 years, 56.0% female, EuroSCORE II: 6.6 ± 5.8%) considered ineligible for any MV intervention, two clinically distinct phenogroups (PGs) were identified using unsupervised hierarchical clustering of principal components: PG1, elderly women with primary MR, preserved left ventricular function, and annular calcification; and PG2, patients with secondary MR, advanced heart failure, and high prevalence of comorbidities. One-year all-cause mortality did not differ between the PGs (PG1: 21.4%, PG2: 23.4%, P = 0.89). Predictors of mortality were albumin, renal function, and extracardiac arteriopathy for PG1 and albumin, coronary artery disease, and prior myocardial infarction for PG2. Conclusion This study identified two major subgroups among patients ineligible for mitral interventions showing profound differences in clinical and anatomical profiles. Identifying these factors may drive technological evolution to address the unmet clinical need for therapeutic options in MR patients. ClinicalTrials.gov identifier NCT04688190 (CHOICE-MI Registry).

Phenotypic clustering analysis of patients rejected for mitral valve interventions: implications for future transcatheter technologies / Ludwig, S.; Coisne, A.; Hamzi, K.; Ben Ali, W.; Scotti, A.; Koell, B.; Duncan, A.; Makkar, R.; Akodad, M.; Bleiziffer, S.; Nickenig, G.; Kaneko, T.; Ruge, H.; Adam, M.; Sondergaard, L.; Dahle, G.; Taramasso, M.; Walther, T.; Kempfert, J.; Obadia, J. -F.; Chehab, O.; Tang, G. H. L.; Goel, S.; Fam, N.; Denti, P.; Praz, F.; Von Bardeleben, R. S.; Hausleiter, J.; Latib, A.; Conradi, L.; Modine, T.; Pezel, T.; Granada, J. F.; Maisano, F.; Metra, M.. - In: EUROPEAN HEART JOURNAL. CARDIOVASCULAR IMAGING. - ISSN 2047-2404. - 26:8(2025), pp. 1452-1463. [10.1093/ehjci/jeaf141]

Phenotypic clustering analysis of patients rejected for mitral valve interventions: implications for future transcatheter technologies

Maisano F.
Membro del Collaboration Group
;
Metra M.
Membro del Collaboration Group
2025-01-01

Abstract

Aims Although several treatment options are available for patients with severe mitral regurgitation (MR), a significant proportion of patients remain ineligible for any mitral valve (MV) intervention. We aimed to analyse the phenotypic characteristics of surgical high-risk patients ineligible for MV interventions using an unsupervised phenotypic clustering approach. Methods and results Between 2014 and 2022, the CHOICE-MI registry included 984 patients with MR undergoing screening for transcatheter MV replacement at 33 international sites. For this study, only patients with screening failure receiving medical therapy alone were included. Patients receiving transcatheter or surgical treatment were excluded. A cluster analysis using K-means was performed on baseline clinical, demographic, and imaging variables to identify different patient phenotypes. Among 284 patients with MR (77.4 ± 8.82 years, 56.0% female, EuroSCORE II: 6.6 ± 5.8%) considered ineligible for any MV intervention, two clinically distinct phenogroups (PGs) were identified using unsupervised hierarchical clustering of principal components: PG1, elderly women with primary MR, preserved left ventricular function, and annular calcification; and PG2, patients with secondary MR, advanced heart failure, and high prevalence of comorbidities. One-year all-cause mortality did not differ between the PGs (PG1: 21.4%, PG2: 23.4%, P = 0.89). Predictors of mortality were albumin, renal function, and extracardiac arteriopathy for PG1 and albumin, coronary artery disease, and prior myocardial infarction for PG2. Conclusion This study identified two major subgroups among patients ineligible for mitral interventions showing profound differences in clinical and anatomical profiles. Identifying these factors may drive technological evolution to address the unmet clinical need for therapeutic options in MR patients. ClinicalTrials.gov identifier NCT04688190 (CHOICE-MI Registry).
2025
clustering
medical therapy
mitral regurgitation
non-supervised machine learning
transcatheter mitral valve replacement
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/190565
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