糖尿病自主神经病变的非线性心率变异性分析

目的通过对糖尿病患者进行心率变异性(HRV)分析,研究糖尿病自主神经病变的早期诊断方法。方法随机选择34名糖尿病(包括22例伴有明显的自主神经病变并发症)患者,采用基于LabVIEW的虚拟仪器开发平台,获得5 min相邻R波间期的时间信号,采用非线性动力学研究方法,包括Allan因子、李雅普诺夫指数、近似熵、分形维数、复杂度、小波变换标准差和非线性能量算子进行心率变异性分析,并与对照组进行对比。结果非线性动力学研究方法对糖尿病患者HRV分析的结果表现出很强的特异性,尤其是李雅普诺夫指数、近似熵和非线性能量算子。结论HRV分析的非线性动力学研究方法在评价自主神经状态与诊断自主神经病变方面具有重要价值,能够为临床诊断和治疗自主神经病变提供参考依据,是提高糖尿病自主神经病变早期诊断率的有效途径。

Nonlinear dynamic analysis of heart rate variability in patients with diabetic autonomic neuropathy

Objective To explore earlier detection methods for diabetic autonomic neuropathy (DAN) by heart rate variability (HRV) analysis. Methods Thirty-four diabetic patients (including 22 with explicit clinical DAN symptoms) were randomly selected for this study from the in-patient department of endocrinology. On the basis of Virtual Instrumental WorkBench- LabVIEW and using several nonlinear dynamic analysis measures, including Allan factor, lyapunov exponent, approximate entropy, fractal dimension, complexity, wavelet-transform standard deviation and nonlinear energy operator, the analysis of the HRV in these diabetic patients was performed in comparison with normal subjects. Results The nonlinear indices of both DAN patients and patients without obvious DAN were significantly different from those of the normal subjects, especially in terms of Lyapunov exponent, approximate entropy, and nonlinear energy operator. Conclusion Nonlinear dynamic methods of HRV analysis can provide assistance in assessing the status and impairment of the autonomic system, and can be used to efficiently detect diabetic neuropathy in early stages.