A Novel and Effective Method for Congestive Heart Failure Detection and Quantification Using Dynamic Heart Rate Variability Measurement.
A Novel and Effective Method for Congestive Heart Failure Detection and Quantification Using Dynamic Heart Rate Variability Measurement.
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使用动态心率变异性测量进行充血性心力衰竭检测和量化的新颖有效方法
DOI：
10.1371/journal.pone.0165304
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Jiang Q
中科院分区：
文献类型：
--
作者：
Chen W;Zheng L;Li K;Wang Q;Liu G;Jiang Q
充血性心力衰竭（CHF）的风险评估对于检测至关重要，特别是帮助患者对药物，设备，移植和临终关怀做出明智的决定。大多数研究都集中在CHF患者和正常受试者之间的疾病检测使用短期/长期心率变异性（HRV）的措施，但不太量化。我们从MIT/BIH数据库中下载了116个标称24小时RR间期记录，包括72名正常人和44名CHF患者。根据4级风险评估模型分析这些记录：无风险（正常人，N）、轻度风险（纽约心脏协会（NYHA）I-II级，P1）、中度风险（NYHA III级，P2）和重度风险（NYHA III-IV级，P3）。提出了一种基于非平衡决策树的支持向量机多阶段分类方法，用于CHF风险评估和评级。我们提出动态指标的心率变异性捕捉动态的5分钟短期心率变异性测量量化自主活动的变化，CHF。我们提取了54个经典的措施和126个动态指标，并从这些使用向后消除检测和量化CHF患者。实验结果表明，该多阶段风险评估模型可以实现CHF的检测和定量分析，总的准确率为96.61%。多阶段模型在预测和实际评级之间提供了一个强有力的预测因子，它可以作为一个有临床意义的结局，为CHF患者提供早期评估和预后标志物。
Risk assessment of congestive heart failure (CHF) is essential for detection, especially helping patients make informed decisions about medications, devices, transplantation, and end-of-life care. The majority of studies have focused on disease detection between CHF patients and normal subjects using short-/long-term heart rate variability (HRV) measures but not much on quantification. We downloaded 116 nominal 24-hour RR interval records from the MIT/BIH database, including 72 normal people and 44 CHF patients. These records were analyzed under a 4-level risk assessment model: no risk (normal people, N), mild risk (patients with New York Heart Association (NYHA) class I-II, P1), moderate risk (patients with NYHA III, P2), and severe risk (patients with NYHA III-IV, P3). A novel multistage classification approach is proposed for risk assessment and rating CHF using the non-equilibrium decision-tree–based support vector machine classifier. We propose dynamic indices of HRV to capture the dynamics of 5-minute short term HRV measurements for quantifying autonomic activity changes of CHF. We extracted 54 classical measures and 126 dynamic indices and selected from these using backward elimination to detect and quantify CHF patients. Experimental results show that the multistage risk assessment model can realize CHF detection and quantification analysis with total accuracy of 96.61%. The multistage model provides a powerful predictor between predicted and actual ratings, and it could serve as a clinically meaningful outcome providing an early assessment and a prognostic marker for CHF patients.
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影响因子：
7.7
作者：
Isler, Yalcin;Kuntalp, Mehmet
通讯作者：
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影响因子：
37.8
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影响因子：
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DOI：
10.1109/titb.2010.2091647
发表时间：
2011-01-01
影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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