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首页> 外文期刊>Circulation journal >Breakdown of the intermediate-term fractal scaling exponent in sinus node dysfunction. New method for non-invasive evaluation of sinus node function.
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Breakdown of the intermediate-term fractal scaling exponent in sinus node dysfunction. New method for non-invasive evaluation of sinus node function.

机译:窦房结功能障碍中期分形标度指数的分解。窦房结功能非侵入性评估的新方法。

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BACKGROUND: The aim of the present study was to characterize the heart rate dynamics of sinus bradycardia (SB) from sinus node dysfunction (SND) using non-linear dynamical system analysis. No data are yet available on how the dynamics change in the presence of SND. METHODS AND RESULTS: Conventional time and frequency domain analysis, the short- (DFAalpha(1)) and intermediate-term fractal scaling exponent (DFAalpha(2)), approximate entropy (ApEn) and sample entropy (SampEn) were calculated in 60-min sinus RR interval data of SB from 24-h ambulatory electrocardiograms of 110 patients: 44 SND patients, 44 age-matched controls, and 22 younger controls. All of the time and frequency domain parameters, ApEn and SampEn, were significantly reduced in the age-matched control group, compared with the young control group. DFAalpha(1) and DFAalpha(2) increased with aging. Both the DFAalpha(1) and DFAalpha(2) of SND patients were paradoxically reduced, which was not appropriate for their age. Only the percentage of consecutive RR intervals with absolute differences >50ms (pNN(50)), low-frequency power, and DFAalpha(2) made a significant contribution to prediction of SND on logistic regression analysis. Among them, DFAalpha(2) was the most significant variable for prediction of SND (odds ratio, 0.927; 95% confidence interval: 0.888-0.969, P=0.001). DFAalpha(2) remained as a significant variable for prediction of SND, when compared with overall control patients, combining the 2 control groups. CONCLUSIONS: Inappropriate reduction of DFAalpha(2) is a robust measure and could be an adjunctive tool for improvement of diagnostic performance in detection of SND.
机译:背景:本研究的目的是利用非线性动力系统分析从窦房结功能障碍(SND)来表征窦性心动过缓(SB)的心率动力学。尚无关于SND存在时动态变化的数据。方法和结果:常规时域和频域分析,短期(DFAalpha(1))和中期分形标度指数(DFAalpha(2)),近似熵(ApEn)和样本熵(SampEn)在60-来自110例患者的24小时动态心电图的SB的最小窦性RR间隔数据:44例SND患者,44例年龄匹配的对照和22例年轻对照。与年轻对照组相比,年龄匹配对照组的所有时域和频域参数ApEn和SampEn均显着降低。 DFAalpha(1)和DFAalpha(2)随着老化而增加。 SND患者的DFAalpha(1)和DFAalpha(2)均自相矛盾地降低,这不适合其年龄。只有绝对差异> 50ms(pNN(50)),低频功率和DFAalpha(2)的连续RR间隔百分比对logistic回归分析的SND预测做出了重大贡献。其中,DFAalpha(2)是预测SND的最显着变量(赔率为0.927; 95%置信区间:0.888-0.969,P = 0.001)。与将两个对照组相结合的总体对照组相比,DFAalpha(2)仍是预测SND的重要变量。结论:DFAalpha(2)的不当降低是一种可靠的措施,并且可能是改善SND诊断性能的辅助工具。

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