Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Helmholtz Zentrum München GmbH - German Research Center for Environmental Health, Institute of Computational Biology, Neuherberg, Germany.
Department of Cardiology, Thoraxcenter, Erasmus MC University Medical Center, Rotterdam, the Netherlands.
Int J Cardiol. 2023 Sep 1;386:83-90. doi: 10.1016/j.ijcard.2023.05.024. Epub 2023 May 16.
Heart failure (HF) is a heterogeneous syndrome, and the specific sub-category HF with mildly reduced ejection fraction (EF) range (HFmrEF; 41-49% EF) is only recently recognised as a distinct entity. Cluster analysis can characterise heterogeneous patient populations and could serve as a stratification tool in clinical trials and for prognostication. The aim of this study was to identify clusters in HFmrEF and compare cluster prognosis.
Latent class analysis to cluster HFmrEF patients based on their characteristics was performed in the Swedish HF registry (n = 7316). Identified clusters were validated in a Dutch cross-sectional HF registry-based dataset CHECK-HF (n = 1536). In Sweden, mortality and hospitalisation across the clusters were compared using a Cox proportional hazard model, with a Fine-Gray sub-distribution for competing risks and adjustment for age and sex. Six clusters were discovered with the following prevalence and hazard ratio with 95% confidence intervals (HR [95%CI]) vs. cluster 1: 1) low-comorbidity (17%, reference), 2) ischaemic-male (13%, HR 0.9 [95% CI 0.7-1.1]), 3) atrial fibrillation (20%, HR 1.5 [95% CI 1.2-1.9]), 4) device/wide QRS (9%, HR 2.7 [95% CI 2.2-3.4]), 5) metabolic (19%, HR 3.1 [95% CI 2.5-3.7]) and 6) cardio-renal phenotype (22%, HR 2.8 [95% CI 2.2-3.6]). The cluster model was robust between both datasets.
We found robust clusters with potential clinical meaning and differences in mortality and hospitalisation. Our clustering model could be valuable as a clinical differentiation support and prognostic tool in clinical trial design.
心力衰竭（HF）是一种异质性综合征，射血分数轻度降低的心力衰竭（HFmrEF；EF 范围 41-49%）这一特定亚类最近才被认为是一种独特的实体。聚类分析可以描述异质患者人群，并可作为临床试验中的分层工具和预后预测。本研究的目的是确定 HFmrEF 中的聚类并比较聚类预后。
基于特征对 HFmrEF 患者进行潜在类别分析，在瑞典 HF 登记处（n=7316）中进行。在基于荷兰横断面 HF 登记处的数据集 CHECK-HF（n=1536）中验证了确定的聚类。在瑞典，使用 Cox 比例风险模型比较了各聚类之间的死亡率和住院率，使用 Fine-Gray 亚分布进行竞争风险，并根据年龄和性别进行调整。在瑞典发现了六个聚类，以下是其患病率和 95%置信区间（HR [95%CI]）与聚类 1的比值：1）低合并症（17%，参考），2）缺血性男性（13%，HR 0.9 [95%CI 0.7-1.1]），3）心房颤动（20%，HR 1.5 [95%CI 1.2-1.9]），4）器械/宽 QRS（9%，HR 2.7 [95%CI 2.2-3.4]），5）代谢（19%，HR 3.1 [95%CI 2.5-3.7]）和 6）心脏-肾脏表型（22%，HR 2.8 [95%CI 2.2-3.6]）。该聚类模型在两个数据集之间具有稳健性。
我们发现了具有潜在临床意义且死亡率和住院率存在差异的稳健聚类。我们的聚类模型可作为临床试验设计中的临床区分支持和预后工具，具有重要价值。
