The 5 Phenotypes of Tricuspid Regurgitation: Insight From Cluster Analysis of Clinical and Echocardiographic Variables.

Autor:	Anand V; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA. Electronic address: anand.vidhu@mayo.edu., Scott CG; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA; Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA., Hyun MC; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA; Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA., Lara-Breitinger K; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA., Nkomo VT; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA., Kane GC; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA., Pislaru C; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA., Kopecky KF; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA., Schulte PJ; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA., Pislaru SV; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Jazyk:	angličtina
Zdroj:	JACC. Cardiovascular interventions [JACC Cardiovasc Interv] 2023 Jan 23; Vol. 16 (2), pp. 156-165.
DOI:	10.1016/j.jcin.2022.10.055
Abstrakt:	Background: The recent morphologic classification of tricuspid regurgitation (TR) (ie, atrial functional, ventricular functional, lead related, and primary) does not capture underlying comorbidities and clinical characteristics. Objectives: This study aimed to identify the different phenotypes of TR using unsupervised cluster analysis and to determine whether differences in clinical outcomes were associated with these phenotypes. Methods: We included 13,611 patients with ≥moderate TR from January 2004 to April 2019 in the final analyses. Baseline demographic, clinical, and echocardiographic data were obtained from electronic medical records and echocardiography reports. Ward's minimum variance method was used to cluster patients based on 38 variables. The analysis of all-cause mortality was performed using the Kaplan-Meier method, and groups were compared using log-rank test. Results: The mean age of patients was 72 ± 13 years, and 56% were women. Cluster analysis identified 5 distinct phenotypes: cluster 1 represented "low-risk TR" with less severe TR, a lower prevalence of right ventricular enlargement, atrial fibrillation, and comorbidities; cluster 2 represented "high-risk TR"; and clusters 3, 4, and 5 represented TR associated with lung disease, coronary artery disease, and chronic kidney disease, respectively. Cluster 1 had the lowest mortality followed by clusters 2 (HR: 2.22 [95% CI: 2.1-2.35]; P < 0.0001) and 4 (HR: 2.19 [95% CI: 2.04-2.35]; P < 0.0001); cluster 3 (HR: 2.45 [95% CI: 2.27-2.65]; P < 0.0001); and, lastly, cluster 5 (HR: 3.48 [95% CI: 3.07-3.95]; P < 0.0001). Conclusions: Cluster analysis identified 5 distinct novel subgroups of TR with differences in all-cause mortality. This phenotype-based classification improves our understanding of the interaction of comorbidities with this complex valve lesion and can inform clinical decision making. Competing Interests: Funding Support and Author Disclosures The authors have reported that they have no relationships relevant to the contents of this paper to disclose. (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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