2型糖尿病(T2DM)的特点是多种并发症,比如视网膜病变,肾功能衰竭,心血管疾病,和糖尿病神经病变。其中,神经病是最严重的并发症,由于其早期检测的挑战性。线性炉表率变异性(HRV)分析是糖尿病神经病变最常见的诊断技术,并且其特征在于通过使用光电体积描记术获得的速度图的线性分析来确定周围神经上的交感神经-副交感神经平衡。我们的目的是进行多重分形分析来识别自主神经病变,线性HRV分析尚未发现,也无法检测到。我们招募了10名健康对照,10名诊断为T2DM的非完全神经病变患者,10名T2DM患者诊断为完全神经病变。使用手指光电体积描记术获得用于HRV分析的速度图,并进行线性和/或多重分形分析。我们的初步结果表明,线性分析可以有效区分健康患者和T2DM患者的全面神经病变;然而,比较全面和不全面的神经性糖尿病患者,没有发现差异.相反,多重分形HRV分析可有效区分完全和非完全神经性T2DM患者.多重分形分析可以代表确定神经病变发作的强大策略,即使没有临床诊断证据.
Type 2 diabetes mellitus (T2DM) is characterized by several complications, such as retinopathy, renal failure, cardiovascular disease, and diabetic neuropathy. Among these, neuropathy is the most severe complication, due to the challenging nature of its early detection. The linear Hearth Rate Variability (HRV) analysis is the most common diagnosis technique for diabetic neuropathy, and it is characterized by the determination of the sympathetic-parasympathetic balance on the peripheral nerves through a linear analysis of the tachogram obtained using photoplethysmography. We aimed to perform a multifractal analysis to identify autonomic neuropathy, which was not yet manifest and not detectable with the linear HRV analysis. We enrolled 10 healthy controls, 10 T2DM-diagnosed patients with not-full-blown neuropathy, and 10 T2DM diagnosed patients with full-blown neuropathy. The tachograms for the HRV analysis were obtained using finger photoplethysmography and a linear and/or multifractal analysis was performed. Our preliminary results showed that the linear analysis could effectively differentiate between healthy patients and T2DM patients with full-blown neuropathy; nevertheless, no differences were revealed comparing the full-blown to not-full-blown neuropathic diabetic patients. Conversely, the multifractal HRV analysis was effective for discriminating between full-blown and not-full-blown neuropathic T2DM patients. The multifractal analysis can represent a powerful strategy to determine neuropathic onset, even without clinical diagnostic evidence.