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三尖瓣反流的 5 种表型:聚类分析临床和超声心动图变量的见解。

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

机构信息

Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.

Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA; Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA.

出版信息

JACC Cardiovasc Interv. 2023 Jan 23;16(2):156-165. doi: 10.1016/j.jcin.2022.10.055.

Abstract

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.

摘要

背景

最近的三尖瓣反流(TR)形态学分类(即心房功能、心室功能、导联相关和原发性)并未捕捉到潜在的合并症和临床特征。

目的

本研究旨在使用无监督聚类分析确定 TR 的不同表型,并确定临床结局的差异是否与这些表型相关。

方法

我们最终分析纳入了 2004 年 1 月至 2019 年 4 月期间 13611 例≥中度 TR 的患者。基线人口统计学、临床和超声心动图数据来自电子病历和超声心动图报告。基于 38 个变量,采用 Ward 最小方差法对患者进行聚类。使用 Kaplan-Meier 方法分析全因死亡率,并使用对数秩检验比较组间差异。

结果

患者的平均年龄为 72±13 岁,其中 56%为女性。聚类分析确定了 5 种不同的表型:第 1 组代表“低危 TR”,表现为 TR 程度较轻、右心室扩大、心房颤动和合并症发生率较低;第 2 组代表“高危 TR”;第 3、4 和 5 组分别代表与肺部疾病、冠状动脉疾病和慢性肾脏病相关的 TR。第 1 组死亡率最低,其次是第 2 组(HR:2.22[95%CI:2.1-2.35];P<0.0001)和第 4 组(HR:2.19[95%CI:2.04-2.35];P<0.0001);第 3 组(HR:2.45[95%CI:2.27-2.65];P<0.0001);最后是第 5 组(HR:3.48[95%CI:3.07-3.95];P<0.0001)。

结论

聚类分析确定了 TR 的 5 种不同的新型亚组,其全因死亡率存在差异。这种基于表型的分类提高了我们对合并症与这种复杂瓣膜病变相互作用的认识,并能为临床决策提供信息。

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