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Advanced echocardiography and cluster analysis to identify secondary tricuspid regurgitation phenogroups at different risk

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dc.contributor.authorBadano, Luigi P.-
dc.contributor.authorPenso, Marco-
dc.contributor.authorTomaselli, Michele-
dc.contributor.authorKim, Kyu-
dc.contributor.authorClement, Alexandra-
dc.contributor.authorRadu, Noela-
dc.contributor.authorHong, Geu-Ru-
dc.contributor.authorHadareanu, Diana R.-
dc.contributor.authorButa, Alexandra-
dc.contributor.authorDelcea, Caterina-
dc.contributor.authorFisicaro, Samantha-
dc.contributor.authorParati, Gianfranco-
dc.contributor.authorShim, Chi Young-
dc.contributor.authorMurarua, Denisa-
dc.date.accessioned2025-12-02T06:33:04Z-
dc.date.available2025-12-02T06:33:04Z-
dc.date.created2026-01-02-
dc.date.issued2025-10-
dc.identifier.issn0300-8932-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/209240-
dc.description.abstractIntroduction 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.statementOfResponsibilityopen-
dc.languageSpanish, English(Summary)-
dc.publisherElsevier España-
dc.relation.isPartOfREVISTA ESPANOLA DE CARDIOLOGIA-
dc.relation.isPartOfREVISTA ESPANOLA DE CARDIOLOGIA-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAged-
dc.subject.MESHCluster Analysis-
dc.subject.MESHEchocardiography* / methods-
dc.subject.MESHFemale-
dc.subject.MESHFollow-Up Studies-
dc.subject.MESHHumans-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHPrognosis-
dc.subject.MESHRetrospective Studies-
dc.subject.MESHRisk Assessment / methods-
dc.subject.MESHRisk Factors-
dc.subject.MESHSeverity of Illness Index-
dc.subject.MESHTricuspid Valve Insufficiency* / diagnosis-
dc.subject.MESHTricuspid Valve Insufficiency* / diagnostic imaging-
dc.subject.MESHTricuspid Valve Insufficiency* / etiology-
dc.subject.MESHTricuspid Valve Insufficiency* / mortality-
dc.subject.MESHTricuspid Valve Insufficiency* / physiopathology-
dc.titleAdvanced echocardiography and cluster analysis to identify secondary tricuspid regurgitation phenogroups at different risk-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Internal Medicine (내과학교실)-
dc.contributor.googleauthorBadano, Luigi P.-
dc.contributor.googleauthorPenso, Marco-
dc.contributor.googleauthorTomaselli, Michele-
dc.contributor.googleauthorKim, Kyu-
dc.contributor.googleauthorClement, Alexandra-
dc.contributor.googleauthorRadu, Noela-
dc.contributor.googleauthorHong, Geu-Ru-
dc.contributor.googleauthorHadareanu, Diana R.-
dc.contributor.googleauthorButa, Alexandra-
dc.contributor.googleauthorDelcea, Caterina-
dc.contributor.googleauthorFisicaro, Samantha-
dc.contributor.googleauthorParati, Gianfranco-
dc.contributor.googleauthorShim, Chi Young-
dc.contributor.googleauthorMurarua, Denisa-
dc.identifier.doi10.1016/j.rec.2025.02.004-
dc.relation.journalcodeJ02623-
dc.identifier.eissn1579-2242-
dc.identifier.pmid39988031-
dc.subject.keywordSecondary tricuspid regurgitation-
dc.subject.keywordUnsupervised cluster analysis-
dc.subject.keywordPhenogroups-
dc.subject.keywordOutcomes-
dc.subject.keywordMachine learning-
dc.subject.keyword3-dimensional echocardiography-
dc.subject.keywordSpeckle-tracking echocardiography-
dc.contributor.alternativeNameShim, Chi Young-
dc.contributor.affiliatedAuthorKim, Kyu-
dc.contributor.affiliatedAuthorHong, Geu-Ru-
dc.contributor.affiliatedAuthorShim, Chi Young-
dc.identifier.wosid001589504100001-
dc.citation.volume78-
dc.citation.number10-
dc.citation.startPage838-
dc.citation.endPage847-
dc.identifier.bibliographicCitationREVISTA ESPANOLA DE CARDIOLOGIA, Vol.78(10) : 838-847, 2025-10-
dc.identifier.rimsid90634-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordAuthorSecondary tricuspid regurgitation-
dc.subject.keywordAuthorUnsupervised cluster analysis-
dc.subject.keywordAuthorPhenogroups-
dc.subject.keywordAuthorOutcomes-
dc.subject.keywordAuthorMachine learning-
dc.subject.keywordAuthor3-dimensional echocardiography-
dc.subject.keywordAuthorSpeckle-tracking echocardiography-
dc.subject.keywordPlusPROGNOSTIC IMPACT-
dc.subject.keywordPlusPHENOTYPES-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.relation.journalWebOfScienceCategoryCardiac & Cardiovascular Systems-
dc.relation.journalResearchAreaCardiovascular System & Cardiology-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers

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