心率变化作为心力衰竭死亡率的预测因素:系统性审查和元分析
Indresh Yadav1, Raja Waqas2, Ahmad Mohammad3
1Internal Medicine, Zucker School of Medicine at Hofstra/Northwell Health at Vassar Brothers Medical Center, Poughkeepsie, USA.
Cureus
|January 14, 2026
概括
心率变化障碍 (HRV) 显著预测心力衰竭 (HF) 患者的死亡率. NN间隔的标准偏差 (SDNN) 是评估风险的最可靠的HRV测量方法.
科学领域:
- 心脏病学 心脏病学
- 自主神经科学 自主神经科学
背景情况:
- 心率变化 (HRV) 是自主神经系统功能的关键指标,越来越多地被认为是心力衰竭 (HF) 的预后潜力.
- 关于HRV对HF患者死亡率的预测能力的现有证据是分散的,需要进行全面的综合分析.
研究的目的:
- 系统地评估和综合有关HRV对心力衰竭患者死亡率预测价值的现有证据.
- 确定特定的HRV参数和HF患者的子组,其中HRV显示出最强的预测能力.
主要方法:
- 从2000年到2024年,在主要数据库 (PubMed,Embase,Cochrane) 进行了系统的文献搜索,遵守PRISMA指南.
- 对十项研究的数据进行了随机效应元分析,包括10544名高压患者,以确定HRV-死亡率关联的综合效应大小 (ES).
- 对心力衰竭进行了小组分析,其中包括心力衰竭的减少喷射分数 (HFrEF) 和混合HF群体,并评估了HRV的增量预测值与已建立的标记器 (如喷射分数和NYHA类) 相比.
主要成果:
- 分析显示,HRV受损与HF患者死亡风险增加之间存在显著的关联 (ES=1.99).
- 时间域HRV测量,特别是NN间隔的标准偏差 (SDNN),显示出最强的预测能力 (ES = 1.75).
- HRV提供了除了射出分数和NYHA类之外的显著预后信息,特别是在预测突然心脏死亡时 (HR: 2.1-3.2). 在子组分析中发现了很高的异质性.
结论:
- 降低HRV是心力衰竭死亡率的强大和显著预测因素.
- SDNN成为HF风险分层中最可靠的HRV参数.
- 进一步的研究侧重于HRV测量的标准化和HRV导向治疗策略的实施,对于提高HF管理的临床效用至关重要.
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