KM Fundamental Research Division, Korea Institute of Oriental Medicine (KIOM), 1672 Yuseongdaero, Yuseong-gu, Daejeon, Republic of Korea.
Department of Electrical and Electronic Engineering & Institute for IT Convergence, Hankyong National University, 327 Jungang-no, Anseong-si, Gyeonggi-do, Republic of Korea.
Sci Rep. 2018 Jan 12;8(1):648. doi: 10.1038/s41598-017-18913-7.
We investigated segmental phase angles (PAs) in the four limbs using a multi-frequency bioimpedance analysis (MF-BIA) technique for noninvasively diagnosing diabetes mellitus. We conducted a meal tolerance test (MTT) for 45 diabetic and 45 control subjects stratified by age, sex and body mass index (BMI). HbA1c and the waist-to-hip-circumference ratio (WHR) were measured before meal intake, and we measured the glucose levels and MF-BIA PAs 5 times for 2 hours after meal intake. We employed a t-test to examine the statistical significance and the area under the curve (AUC) of the receiver operating characteristics (ROC) to test the classification accuracy using segmental PAs at 5, 50, and 250 kHz. Segmental PAs were independent of the HbA1c or glucose levels, or their changes caused by the MTT. However, the segmental PAs were good indicators for noninvasively screening diabetes In particular, leg PAs in females and arm PAs in males showed best classification accuracy (AUC = 0.827 for males, AUC = 0.845 for females). Lastly, we introduced the PA at maximum reactance (PAmax), which is independent of measurement frequencies and can be obtained from any MF-BIA device using a Cole-Cole model, thus showing potential as a useful biomarker for diabetes.
我们使用多频生物阻抗分析（MF-BIA）技术研究了四肢的节段相位角（PA），以无创诊断糖尿病。我们对 45 名糖尿病患者和 45 名对照者进行了膳食耐量试验（MTT），这些患者按年龄、性别和体重指数（BMI）分层。在餐前测量了 HbA1c 和腰臀比（WHR），并在餐后 2 小时内测量了 5 次血糖水平和 MF-BIA PA。我们采用 t 检验检查统计学意义，使用 5、50 和 250 kHz 的节段 PA 进行受试者工作特征（ROC）曲线下面积（AUC）测试，以测试分类准确性。节段 PA 与 HbA1c 或血糖水平及其 MTT 引起的变化无关。然而，节段 PA 是无创筛查糖尿病的良好指标。特别是女性的腿部 PA 和男性的手臂 PA 显示出最佳的分类准确性（男性 AUC=0.827，女性 AUC=0.845）。最后，我们引入了最大电抗相位角（PAmax），它不依赖于测量频率，可以使用 Cole-Cole 模型从任何 MF-BIA 设备中获得，因此具有成为糖尿病有用生物标志物的潜力。
