Kiyono Ken, Hayano Junichiro, Watanabe Eiichi, Struzik Zbigniew R, Yamamoto Yoshiharu
College of Engineering, Nihon University, Koriyama, Japan.
Heart Rhythm. 2008 Feb;5(2):261-8. doi: 10.1016/j.hrthm.2007.10.030. Epub 2007 Oct 18.
Morbidity and mortality due to chronic heart failure remain unacceptably high despite effective drug therapies, and the search for a better risk predictor is ongoing. Statistics derived from beat-to-beat fluctuations in heart rate or heart rate variability (HRV) have been used for this purpose, but the current predictability level is low or moderate at best.
The purpose of this study was to evaluate whether a recently proposed non-Gaussian index of HRV is a significant and independent mortality predictor in patients with congestive heart failure (CHF).
Twenty-four-hour Holter ECGs from 108 CHF patients were evaluated. Thirty-nine (36.1%) of the patients died during the follow-up period of 33 +/- 17 months. Cox proportional hazards regression analysis was performed to determine factors related to all-cause mortality. The factors evaluated derived from clinical information, including plasma brain natriuretic peptide, conventional time- and frequency-domain and fractal HRV measures, and a recently proposed non-Gaussian index lambda of HRV.
The short-term (<40 beats) non-Gaussian index lambda(40) (hazard ratio per increment of unit standard deviation 1.64, 95% confidence interval [1.23, 2.18], P <.001) and the long-term (<1,000 beats) index lambda(1000) (hazard ratio 1.42, 95% confidence interval [1.07, 2.18], P <.02), together with brain natriuretic peptide (hazard ratio 2.26, 95% confidence interval [1.45, 3.53], P <.001), are significant univariate risk predictors of mortality. In a multivariate model, lambda(40) (1.49, [1.13, 1.96], P <.005) and brain natriuretic peptide (2.39, [1.53, 3.75], P <.001) are independent predictors of the survival statistics of patients. None of the conventional HRV measures have predicted the mortality of patients in a significant and independent manner.
The results of this study indicate the usefulness of the short-term non-Gaussian index of HRV for risk prediction in patients with CHF.
尽管有有效的药物治疗,但慢性心力衰竭导致的发病率和死亡率仍然高得令人无法接受,目前仍在寻找更好的风险预测指标。为此,人们使用了源自心率逐搏波动或心率变异性(HRV)的统计数据,但目前的预测水平充其量也只是低或中等。
本研究旨在评估最近提出的一种非高斯HRV指标是否是充血性心力衰竭(CHF)患者死亡率的显著且独立的预测指标。
对108例CHF患者的24小时动态心电图进行评估。在33±17个月的随访期内,39例(36.1%)患者死亡。进行Cox比例风险回归分析以确定与全因死亡率相关的因素。评估的因素来自临床信息,包括血浆脑钠肽、传统的时域和频域以及分形HRV测量指标,以及最近提出的非高斯HRV指标λ。
短期(<40次搏动)非高斯指标λ(40)(单位标准差每增加一个单位的风险比为1.64,95%置信区间[1.23, 2.18],P<.001)和长期(<1000次搏动)指标λ(1000)(风险比为1.42,95%置信区间[1.07, 2.18],P<.02),与脑钠肽(风险比为2.26,95%置信区间[1.45, 3.53],P<.001)一起,是死亡率的显著单变量风险预测指标。在多变量模型中,λ(40)(1.49,[1.13, 1.96],P<.005)和脑钠肽(2.39,[1.53, 3.75],P<.001)是患者生存统计的独立预测指标。没有任何传统的HRV测量指标能够以显著且独立的方式预测患者的死亡率。
本研究结果表明,HRV的短期非高斯指标对CHF患者的风险预测有用。