Identifying clinical phenotype clusters in patients with coronary artery disease.

IF 5.1 2区医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS

Heart Pub Date : 2025-06-01 DOI:10.1136/heartjnl-2025-325740

Joris Holtrop, Carl-Emil Lim, Alicia Uijl, Peter Ueda, Tomas Jernberg, Manon G van der Meer, Pim van der Harst, Adriaan O Kraaijeveld, Jan-Willem Balder, Steven H J Hageman, Frank L J Visseren, Jannick A N Dorresteijn

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引用次数: 0

Abstract

Background: Guideline recommendations for the prevention of cardiovascular (CV) events in patients with coronary artery disease (CAD) are predominantly one-size-fits-all. Clinically identifiable phenotypes needing specific considerations might exist. The purpose of this study is to identify such clinical phenotypic clusters in patients with CAD and assess their relationship with the risk of recurrent CV events.

Methods: Unsupervised machine learning through latent class analysis was performed in patients with CAD from the Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies (SWEDEHEART) registry (n=88 894) and Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) cohort (n=5506). Characteristics for clustering were based on availability, missingness and clinical relevance. Clustering was performed in SWEDEHEART and validated in UCC-SMART. Association between clusters and the composite of myocardial infarction, stroke or CV death was assessed using Cox proportional hazard models.

Results: Four phenotypes could be distinguished: cluster 1 (38%, n=33 777) of predominantly younger males with increased body mass index, blood pressure and C-reactive protein, cluster 2 (21%, n=18 775) of smokers with few traditional risk factors, cluster 3 (30%, n=26 501) of older patients with few comorbidities and cluster 4 (11%, n=9841) of patients with multimorbidity. Compared with cluster 1, cluster 4 was at the highest risk (HR 4.38 95% CI (4.01 to 4.78)), followed by cluster 3 (HR 1.78 (1.70 to 1.85)), and cluster 2 (HR 0.97 (0.88 to 1.07)). Validation in UCC-SMART yielded similar results.

Conclusion: Four distinct and reproducible phenotypes, with differences in the risk of recurrent CV events, were identified among patients with CAD. These may be relevant in practice and warrant research into specific pathophysiology and differences in treatment effects.

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鉴定冠状动脉疾病患者的临床表型簇。

背景：预防冠状动脉疾病（CAD）患者心血管（CV）事件的指南建议主要是一刀切。可能存在需要特殊考虑的临床可识别表型。本研究的目的是确定CAD患者的这些临床表型簇，并评估它们与复发性心血管事件风险的关系。方法：通过潜在分类分析的无监督机器学习，对来自瑞典心脏病循证护理增强和发展网络系统（SWEDEHEART）注册（n= 88894）和乌得勒支心血管队列-动脉疾病第二表现（UCC-SMART）队列（n=5506）的CAD患者进行研究。聚类的特征是基于可用性、缺失性和临床相关性。在SWEDEHEART中进行聚类，并在UCC-SMART中进行验证。使用Cox比例风险模型评估聚类与心肌梗死、卒中或CV死亡组合之间的关联。结果：可以区分出四种表型：第1类（38%,n=33 777）以年轻男性为主，体重指数、血压和c反应蛋白升高；第2类（21%,n=18 775）为吸烟者，传统危险因素较少；第3类（30%,n=26 501）为老年患者，合共病较少；第4类（11%,n=9841）为多病患者。与集群1相比，集群4的风险最高（HR 4.38 95% CI(4.01 ~ 4.78)），其次是集群3 （HR 1.78(1.70 ~ 1.85)）和集群2 （HR 0.97(0.88 ~ 1.07)）。在UCC-SMART中验证也得到了类似的结果。结论：在CAD患者中发现了四种不同且可重复的表型，它们具有复发性CV事件的风险差异。这些可能在实践中是相关的，需要对具体的病理生理学和治疗效果的差异进行研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Heart 医学-心血管系统

CiteScore

10.30

自引率

5.30%

发文量

320

审稿时长

3-6 weeks

期刊介绍： Heart is an international peer reviewed journal that keeps cardiologists up to date with important research advances in cardiovascular disease. New scientific developments are highlighted in editorials and put in context with concise review articles. There is one free Editor’s Choice article in each issue, with open access options available to authors for all articles. Education in Heart articles provide a comprehensive, continuously updated, cardiology curriculum.