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《JACC: Cardiovascular Interventions》2023,16(2):156-165
BackgroundThe recent morphologic classification of tricuspid regurgitation (TR) (ie, atrial functional, ventricular functional, lead related, and primary) does not capture underlying comorbidities and clinical characteristics.ObjectivesThis 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.MethodsWe 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.ResultsThe 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).ConclusionsCluster 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. 相似文献