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Comparison of nonlinear methods symbolic dynamics, detrended fluctuation, and Poincare plot analysis in risk stratification in patients with dilated cardiomyopathy

机译:非线性方法符号动力学,去趋势波动和Poincare图分析在扩张型心肌病患者风险分层中的比较

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Dilated cardiomyopathy (DCM) has an incidence of about 20/100 000 new cases per annum and accounts for nearly 10 000 deaths per year in the United States. Approximately 36+ACU- of patients with dilated cardiomyopathy (DCM) suffer from cardiac death within five years after diagnosis. Currently applied methods for an early risk prediction in DCM patients are rather insufficient. The objective of this study was to investigate the suitability of short-term nonlinear methods symbolic dynamics (STSD), detrended fluctuation (DFA), and Poincare plot analysis (PPA) for risk stratification in these patients. From 91 DCM patients and 30 healthy subjects (REF), heart rate and blood pressure variability (HRV, BPV), STSD, DFA, and PPA were analyzed. Measures from BPV analysis, DFA, and PPA revealed highly significant differences (p +ADw- 0.0011) discriminating REF and DCM. For risk stratification in DCM patients, four parameters from BPV analysis, STSD, and PPA revealed significant differences between low and high risk (maximum sensitivity: 90+ACU-, specificity: 90+ACU-). These results suggest that STSD and PPA are useful nonlinear methods for enhanced risk stratification in DCM patients. (c) 2007 American Institute of Physics.
机译:扩张型心肌病(DCM)每年约有20/100 000新病例发生,在美国每年造成近10,000人死亡。诊断后五年内,约有36 + ACU-的扩张型心肌病(DCM)患者患有心源性死亡。当前在DCM患者中用于早期风险预测的方法还远远不够。这项研究的目的是调查短期非线性方法符号动力学(STSD),去趋势波动(DFA)和Poincare图分析(PPA)在这些患者中进行风险分层的适用性。从91位DCM患者和30位健康受试者(REF)中分析了心率和血压变异性(HRV,BPV),STSD,DFA和PPA。来自BPV分析,DFA和PPA的测量结果显示出差异很大(p + ADw- 0.0011),可以区分REF和DCM。对于DCM患者的风险分层,来自BPV分析,STSD和PPA的四个参数显示了低风险和高风险之间的显着差异(最大敏感性:90 + ACU-,特异性:90 + ACU-)。这些结果表明,STSD和PPA是用于增强DCM患者风险分层的有用的非线性方法。 (c)2007年美国物理研究所。

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