Andreas Voss, R. Schroeder, M. Vallverdú, I. Cygankiewicz, Rafael Vázquez, A. B. D. Luna, P. Caminal
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引用次数: 25
摘要
慢性心力衰竭(CHF)是一个日益严重的重大公共卫生问题(全世界约有2300万人)，男性5年生存率为25%，女性为38%。本研究的目的是探讨线性和非线性心率变异性(HRV)指标是否能增强心力衰竭患者的风险预测。为了区分低危(病情稳定，N = 459)和高危(心源性死亡，N = 50) CHF患者组，从24 h动态心电图记录中计算压缩熵(CE)、去趋势波动分析(DFA)、符号动力学(SD)和标准线性HRV分析的非线性指标。非线性动力学指标(CE、DFA、SD: p < 0.001)与临床参数NYHA和LVEF一起有助于增强CHF患者的风险分层。
Linear and nonlinear heart rate variability risk stratification in heart failure patients
Chronic heart failure (CHF) is a major and growing public health concern (~23 million people worldwide) with five-year survival rates of 25% in men and 38% in women. Objective of this study was to investigate whether linear and nonlinear heart rate variability (HRV) indices enhance risk prediction in patients with CHF. To discriminate between low risk (stable condition, N = 459) and high risk (cardiac death, N = 50) CHF patient groups, nonlinear indices from compression entropy (CE), detrended fluctuation analysis (DFA), symbolic dynamics (SD) and standard linear HRV analysis were calculated from 24 h Holter ECG recordings. Indices from nonlinear dynamics (CE, DFA, SD: p < 0.001) contribute together with clinical parameters NYHA and LVEF to an enhanced risk stratification in CHF patients.
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