Cited 8 times in 
Cited 0 times in 
Advanced echocardiography and cluster analysis to identify secondary tricuspid regurgitation phenogroups at different risk
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Badano, Luigi P. | - |
| dc.contributor.author | Penso, Marco | - |
| dc.contributor.author | Tomaselli, Michele | - |
| dc.contributor.author | Kim, Kyu | - |
| dc.contributor.author | Clement, Alexandra | - |
| dc.contributor.author | Radu, Noela | - |
| dc.contributor.author | Hong, Geu-Ru | - |
| dc.contributor.author | Hadareanu, Diana R. | - |
| dc.contributor.author | Buta, Alexandra | - |
| dc.contributor.author | Delcea, Caterina | - |
| dc.contributor.author | Fisicaro, Samantha | - |
| dc.contributor.author | Parati, Gianfranco | - |
| dc.contributor.author | Shim, Chi Young | - |
| dc.contributor.author | Murarua, Denisa | - |
| dc.date.accessioned | 2025-12-02T06:33:04Z | - |
| dc.date.available | 2025-12-02T06:33:04Z | - |
| dc.date.created | 2026-01-02 | - |
| dc.date.issued | 2025-10 | - |
| dc.identifier.issn | 0300-8932 | - |
| dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/209240 | - |
| dc.description.abstract | Introduction and objectives: Significant secondary tricuspid regurgitation (STR) is associated with poor prognosis, but its heterogeneity makes predicting patient outcomes challenging. Our objective was to identify STR prognostic phenogroups. Methods: We analyzed 758 patients with moderate-to-severe STR: 558 (74 +/- 14 years, 55% women) in the derivation cohort and 200 (73 +/- 12 years, 60% women) in the external validation cohort. The primary endpoint was a composite of heart failure hospitalization and all-cause mortality. Results: We identified 3 phenogroups. The low-risk phenogroup (2-year event-free survival 80%, 95%CI, 74%-87%) had moderate STR, preserved right ventricular (RV) size and function, and a moderately dilated but normally functioning right atrium. The intermediate-risk phenogroup (HR, 2.20; 95%CI, 1.44-3.37; P < .001) included older patients with severe STR, and a mildly dilated but uncoupled RV. The high-risk phenogroup (HR, 4.67; 95%CI, 3.20-6.82; P < .001) included younger patients with massive-to-torrential tricuspid regurgitation, as well as severely dilated and dysfunctional RV and right atrium. Multivariable analysis confirmed the clustering as independently associated with the composite endpoint (HR, 1.40; 95%CI, 1.13-1.70; P = .002). A supervised machine learning model, developed to assist clinicians in assigning patients to the 3 phenogroups, demonstrated excellent performance both in the derivation cohort (accuracy = 0.91, precision = 0.91, recall = 0.91, and F1 score = 0.91) and in the validation cohort (accuracy = 0.80, precision = 0.78, recall = 0.78, and F1 score = 0.77). Conclusions: The unsupervised cluster analysis identified 3 risk phenogroups, which could assist clinicians in developing more personalized treatment and follow-up strategies for STR patients. (c) 2025 Sociedad Espa & ntilde;ola de Cardiologia. Published by Elsevier Espa & ntilde;a, S.L.U. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | - |
| dc.description.statementOfResponsibility | open | - |
| dc.language | Spanish, English(Summary) | - |
| dc.publisher | Elsevier España | - |
| dc.relation.isPartOf | REVISTA ESPANOLA DE CARDIOLOGIA | - |
| dc.relation.isPartOf | REVISTA ESPANOLA DE CARDIOLOGIA | - |
| dc.rights | CC BY-NC-ND 2.0 KR | - |
| dc.subject.MESH | Aged | - |
| dc.subject.MESH | Cluster Analysis | - |
| dc.subject.MESH | Echocardiography* / methods | - |
| dc.subject.MESH | Female | - |
| dc.subject.MESH | Follow-Up Studies | - |
| dc.subject.MESH | Humans | - |
| dc.subject.MESH | Male | - |
| dc.subject.MESH | Middle Aged | - |
| dc.subject.MESH | Prognosis | - |
| dc.subject.MESH | Retrospective Studies | - |
| dc.subject.MESH | Risk Assessment / methods | - |
| dc.subject.MESH | Risk Factors | - |
| dc.subject.MESH | Severity of Illness Index | - |
| dc.subject.MESH | Tricuspid Valve Insufficiency* / diagnosis | - |
| dc.subject.MESH | Tricuspid Valve Insufficiency* / diagnostic imaging | - |
| dc.subject.MESH | Tricuspid Valve Insufficiency* / etiology | - |
| dc.subject.MESH | Tricuspid Valve Insufficiency* / mortality | - |
| dc.subject.MESH | Tricuspid Valve Insufficiency* / physiopathology | - |
| dc.title | Advanced echocardiography and cluster analysis to identify secondary tricuspid regurgitation phenogroups at different risk | - |
| dc.type | Article | - |
| dc.contributor.college | College of Medicine (의과대학) | - |
| dc.contributor.department | Dept. of Internal Medicine (내과학교실) | - |
| dc.contributor.googleauthor | Badano, Luigi P. | - |
| dc.contributor.googleauthor | Penso, Marco | - |
| dc.contributor.googleauthor | Tomaselli, Michele | - |
| dc.contributor.googleauthor | Kim, Kyu | - |
| dc.contributor.googleauthor | Clement, Alexandra | - |
| dc.contributor.googleauthor | Radu, Noela | - |
| dc.contributor.googleauthor | Hong, Geu-Ru | - |
| dc.contributor.googleauthor | Hadareanu, Diana R. | - |
| dc.contributor.googleauthor | Buta, Alexandra | - |
| dc.contributor.googleauthor | Delcea, Caterina | - |
| dc.contributor.googleauthor | Fisicaro, Samantha | - |
| dc.contributor.googleauthor | Parati, Gianfranco | - |
| dc.contributor.googleauthor | Shim, Chi Young | - |
| dc.contributor.googleauthor | Murarua, Denisa | - |
| dc.identifier.doi | 10.1016/j.rec.2025.02.004 | - |
| dc.relation.journalcode | J02623 | - |
| dc.identifier.eissn | 1579-2242 | - |
| dc.identifier.pmid | 39988031 | - |
| dc.subject.keyword | Secondary tricuspid regurgitation | - |
| dc.subject.keyword | Unsupervised cluster analysis | - |
| dc.subject.keyword | Phenogroups | - |
| dc.subject.keyword | Outcomes | - |
| dc.subject.keyword | Machine learning | - |
| dc.subject.keyword | 3-dimensional echocardiography | - |
| dc.subject.keyword | Speckle-tracking echocardiography | - |
| dc.contributor.alternativeName | Shim, Chi Young | - |
| dc.contributor.affiliatedAuthor | Kim, Kyu | - |
| dc.contributor.affiliatedAuthor | Hong, Geu-Ru | - |
| dc.contributor.affiliatedAuthor | Shim, Chi Young | - |
| dc.identifier.wosid | 001589504100001 | - |
| dc.citation.volume | 78 | - |
| dc.citation.number | 10 | - |
| dc.citation.startPage | 838 | - |
| dc.citation.endPage | 847 | - |
| dc.identifier.bibliographicCitation | REVISTA ESPANOLA DE CARDIOLOGIA, Vol.78(10) : 838-847, 2025-10 | - |
| dc.identifier.rimsid | 90634 | - |
| dc.type.rims | ART | - |
| dc.description.journalClass | 1 | - |
| dc.description.journalClass | 1 | - |
| dc.subject.keywordAuthor | Secondary tricuspid regurgitation | - |
| dc.subject.keywordAuthor | Unsupervised cluster analysis | - |
| dc.subject.keywordAuthor | Phenogroups | - |
| dc.subject.keywordAuthor | Outcomes | - |
| dc.subject.keywordAuthor | Machine learning | - |
| dc.subject.keywordAuthor | 3-dimensional echocardiography | - |
| dc.subject.keywordAuthor | Speckle-tracking echocardiography | - |
| dc.subject.keywordPlus | PROGNOSTIC IMPACT | - |
| dc.subject.keywordPlus | PHENOTYPES | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.relation.journalWebOfScienceCategory | Cardiac & Cardiovascular Systems | - |
| dc.relation.journalResearchArea | Cardiovascular System & Cardiology | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.