Shanglin Yang , Xuwei Liao , Yuyang Lin , Jianjung Chen , Hsientsai Wu
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引用次数: 0
摘要
本研究旨在介绍和评估气压反射熵指数(BEI),这是一种从标准二导联心电图(EKG)中提取的新型工具,用于评估 2 型糖尿病(T2DM)患者的自律神经功能(AF)。分工不同(分析和数据准备)的研究人员分析了健康对照组和两个 T2DM 患者组(控制良好和控制不佳)的匿名心电图数据。对各组之间的 BEI 进行了比较,并研究了其与血糖指标(HbA1c、空腹血糖)之间的相关性。逻辑回归用于评估 BEI 与 T2DM 风险之间的关联。BEI 显示出良好的重复性和组间差异。值得注意的是,它只需要单导联心电图。BEI 与血糖指标呈反向相关,这表明血糖控制得好,气压反射调节也会改善。在组别区分方面,BEI 的表现也优于小规模多尺度熵。逻辑回归确定 BEI 是 T2DM 的保护因素。BEI 是监测心房颤动、评估血糖控制和潜在的 T2DM 风险分层的一种有前途的工具。有必要在更大规模的纵向研究中进行进一步验证,并探索 BEI 对其他疾病的适用性。
Lead II electrocardiograph-derived entropy index for autonomic function assessment in type 2 diabetes mellitus
The aim of this study was to introduce and evaluate the baroreflex entropy index (BEI), a novel tool derived from standard lead II electrocardiograph (EKG) for autonomic function (AF) assessment in type 2 diabetes mellitus (T2DM). Researchers with distinct roles (analysis and data preparation) analyzed anonymized EKG data from healthy controls and two patient groups with T2DM (well controlled and poorly controlled). BEI was compared between groups, and correlations with glycemic markers (HbA1c, fasting glucose) were investigated. Logistic regression was used to assess the association between BEI and T2DM risk. BEI showed good repeatability and differentiation between groups. Notably, it required only single-lead EKG. BEI was inversely correlated with glycemic markers, suggesting improved baroreflex regulation with better glycemic control. BEI also outperformed small-scale multiscale entropy in group discrimination. Logistic regression identified BEI as a protective factor for T2DM. BEI represents a promising tool for monitoring AF, assessing glycemic control, and potentially stratifying T2DM risk. Further validation in larger longitudinal studies and an exploration of the applicability of BEI to other diseases are warranted.
期刊介绍:
Biocybernetics and Biomedical Engineering is a quarterly journal, founded in 1981, devoted to publishing the results of original, innovative and creative research investigations in the field of Biocybernetics and biomedical engineering, which bridges mathematical, physical, chemical and engineering methods and technology to analyse physiological processes in living organisms as well as to develop methods, devices and systems used in biology and medicine, mainly in medical diagnosis, monitoring systems and therapy. The Journal''s mission is to advance scientific discovery into new or improved standards of care, and promotion a wide-ranging exchange between science and its application to humans.