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多重分形心率值分析:一种用于糖尿病神经病变诊断的新方法。

Multifractal Heart Rate Value Analysis: A Novel Approach for Diabetic Neuropathy Diagnosis.

作者信息

Coppola Andrea, Conte Sergio, Pastore Donatella, Chiereghin Francesca, Donadel Giulia

机构信息

Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy.

Faculty of Medicine and Surgery, Catholic University "Our Lady of Good Counsel", 1000 Tirana, Albania.

出版信息

Healthcare (Basel). 2024 Jan 17;12(2):234. doi: 10.3390/healthcare12020234.

Abstract

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.

摘要

2型糖尿病(T2DM)具有多种并发症,如视网膜病变、肾衰竭、心血管疾病和糖尿病神经病变。其中,神经病变是最严重的并发症,因为其早期检测具有挑战性。线性心率变异性(HRV)分析是糖尿病神经病变最常用的诊断技术,其特点是通过对使用光电容积脉搏波描记法获得的心动周期图进行线性分析来确定外周神经的交感-副交感平衡。我们旨在进行多重分形分析以识别尚未显现且线性HRV分析无法检测到的自主神经病变。我们招募了10名健康对照者、10名被诊断为T2DM但未出现完全性神经病变的患者以及10名被诊断为T2DM且出现完全性神经病变的患者。使用手指光电容积脉搏波描记法获取用于HRV分析的心动周期图,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患有完全性神经病变的T2DM患者;然而,比较患有完全性神经病变和未出现完全性神经病变的糖尿病神经病变患者时未发现差异。相反,多重分形HRV分析对于区分患有完全性神经病变和未出现完全性神经病变的T₂DM患者有效。即使没有临床诊断证据,多重分形分析也可能是确定神经病变发病的有力策略。

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