Suppr超能文献

生存分类回归树分析在识别左心室射血分数降低的心力衰竭患者亚组风险中的应用。

Application of survival classification and regression tree analysis for identification of subgroups of risk in patients with heart failure and reduced left ventricular ejection fraction.

机构信息

Nephrology Department, University of Medicine and Pharmacy "Grigore T. Popa", Iasi, Romania.

Dr. C.I. Parhon" University Hospital, Carol I Bld, 700503, Iasi, Romania.

出版信息

Int J Cardiovasc Imaging. 2021 Jun;37(6):1853-1861. doi: 10.1007/s10554-021-02159-6. Epub 2021 Jan 16.

Abstract

The aim of this study was to identify by classification and regression tree (CART) analysis groups of patients with different survival patterns in a population of patients with heart failure and reduced left ventricular ejection fraction (HFrEF) by using standard methods of heart function assessment, as well as well as utilizing non-traditional approaches for determining hydration and nutritional status in HF patients-lung ultrasonography (LUS) and bioimpedance spectroscopy (BIS) analysis. Eligible patients with a left ventricular ejection fraction (LVEF) below 45% were identified via the daily echocardiography assessments. LUS was performed with patients in the supine position, for a total of 28 sites per complete examination. The hydration state and the body composition were assessed using a portable whole-body BIS device. Our study included 151 patients (69.2% males) with a mean age of 67.1 years. During the follow-up 53 (35.1%) patients died. Using the CART algorithm, we identified five groups based on serum sodium, the severity of NYHA class, serum urea and systolic blood pressure. When comparing the two models, the model derived from the CART analysis showed better predictive power than the conventional Cox model (c-index 0.790, 95% CI 0.723-0.857 vs. 0.736, 95%CI 0.664-0.807, p < 0.05). The application of CART analysis allowed us to identify different groups of risk for all-cause mortality in patients with HFrEF. The use of this type of modelling showed better prediction capabilities over that of using more conventional statistical approach.ClinicalTrials.gov Identifier: NCT02764073.

摘要

本研究旨在通过分类回归树(CART)分析,确定心力衰竭和左心室射血分数降低(HFrEF)患者人群中具有不同生存模式的患者群体。采用标准的心脏功能评估方法,以及用于确定心力衰竭患者水合状态和营养状况的非传统方法-肺部超声(LUS)和生物阻抗谱(BIS)分析。通过每日超声心动图评估确定左心室射血分数(LVEF)低于 45%的合格患者。LUS 在患者仰卧位时进行,每次完整检查共进行 28 个部位。使用便携式全身 BIS 设备评估水合状态和身体成分。我们的研究包括 151 名(69.2%为男性)患者,平均年龄为 67.1 岁。在随访期间,有 53 名(35.1%)患者死亡。使用 CART 算法,我们根据血清钠、NYHA 分级严重程度、血清尿素和收缩压确定了五个组。当比较这两种模型时,CART 分析得出的模型比传统 Cox 模型具有更好的预测能力(C 指数为 0.790,95%CI 为 0.723-0.857 比 0.736,95%CI 为 0.664-0.807,p<0.05)。CART 分析的应用使我们能够确定 HFrEF 患者全因死亡率的不同风险组。与使用更传统的统计方法相比,这种类型的建模显示出更好的预测能力。ClinicalTrials.gov 标识符:NCT02764073。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验