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对左心室射血分数恢复的患者进行无监督聚类分析可识别出独特的临床表型。

Unsupervised cluster analysis of patients with recovered left ventricular ejection fraction identifies unique clinical phenotypes.

作者信息

Perry Andrew, Loh Francis, Adamo Luigi, Zhang Kathleen W, Deych Elena, Foraker Randi, Mann Douglas L

机构信息

Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, United States of America.

Institute for Informatics, Washington University School of Medicine, St. Louis, Missouri, United States of America.

出版信息

PLoS One. 2021 Mar 18;16(3):e0248317. doi: 10.1371/journal.pone.0248317. eCollection 2021.

Abstract

BACKGROUND

Patients with heart failure (HF) with recovered ejection fraction (HFrecEF) are a recently identified cohort that are phenotypically and biologically different from HFrEF and HFpEF patients. Whether there are unique phenotypes among HFrecEF patients is not known.

METHODS

We studied all patients at a large medical center, who had an improvement in LVEF from ≤ 35% to ≥ 50% (LVrecEF) between January 1, 2005 and December 31, 2013. We identified a set of 11 clinical variables and then performed unsupervised clustering analyses to identify unique clinical phenotypes among patients with LVrecEF, followed by a Kaplan-Meier analysis to identify differences in survival and the proportion of LVrecEF patients who maintained an LVEF ≥ 50% during the study period.

RESULTS

We identified 889 patients with LVrecEF who clustered into 7 unique phenotypes ranging in size from 37 to 420 patients. Kaplan-Meier analysis demonstrated significant differences in mortality across clusters (logrank p<0.0001), with survival ranging from 14% to 87% at 1000 days, as well as significant differences in the proportion of LVrecEF patients who maintained an LVEF ≥ 50%.

CONCLUSION

There is significant clinical heterogeneity among patients with LVrecEF. Clinical outcomes are distinct across phenotype clusters as defined by clinical cardiac characteristics and co-morbidities. Clustering algorithms may identify patients who are at high risk for recurrent HF, and thus be useful for guiding treatment strategies for patients with LVrecEF.

摘要

背景

射血分数恢复的心力衰竭(HFrecEF)患者是最近确认的一个队列,其在表型和生物学上与射血分数降低的心力衰竭(HFrEF)和射血分数保留的心力衰竭(HFpEF)患者不同。目前尚不清楚HFrecEF患者中是否存在独特的表型。

方法

我们研究了一家大型医疗中心在2005年1月1日至2013年12月31日期间左心室射血分数(LVEF)从≤35%改善至≥50%(LVrecEF)的所有患者。我们确定了一组11个临床变量,然后进行无监督聚类分析,以识别LVrecEF患者中的独特临床表型,接着进行Kaplan-Meier分析,以确定生存率差异以及在研究期间维持LVEF≥50%的LVrecEF患者比例。

结果

我们确定了889例LVrecEF患者,他们聚为7种独特的表型,每组人数从37至420人不等。Kaplan-Meier分析显示各聚类之间的死亡率存在显著差异(对数秩检验p<0.0001),1000天时生存率从14%至87%不等,并且维持LVEF≥50%的LVrecEF患者比例也存在显著差异。

结论

LVrecEF患者存在显著的临床异质性。根据临床心脏特征和合并症定义的表型聚类,其临床结局各不相同。聚类算法可能识别出复发性心力衰竭高危患者,因此有助于指导LVrecEF患者的治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a67/7971566/96dad2189574/pone.0248317.g001.jpg

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