Department of Neurology, University of Utah, Salt Lake City, UT, USA.
J Diabetes Complications. 2013 Sep-Oct;27(5):436-42. doi: 10.1016/j.jdiacomp.2013.04.003. Epub 2013 Jun 2.
The Utah Diabetic Neuropathy Study (UDNS) examined 218 type 2 diabetic subjects without neuropathy symptoms, or with symptoms of<5 years, in order to evaluate risk factors for neuropathy development. Each subject completed symptom questionnaires, the Utah Early Neuropathy Scale (UENS), nerve conduction studies (NCS), quantitative sensory testing (QST) for vibration and cold detection, quantitative sudomotor axon reflex testing (QSART), and skin biopsy with measurement of intraepidermal nerve fiber density (IENFD). Those with abnormalities of≥3 were classified as having probable, and those with 1-2 as possible neuropathy. The relationship between glycemic control, lipid parameters (high density lipoprotein and triglyceride levels), blood pressure, and obesity, and neuropathy risk was examined. There was a significant relationship between the number of abnormalities among these features and neuropathy status (p<0.01). Hypertriglyceridemia, obesity and 3 or more abnormalities increased neuropathy risk (risk ratios 2.1 p<0.03, 2.9 p>0.02 and 3.0 p<0.004 respectively). Multivariate analysis found obesity and triglycerides were related to loss of small unmyelinated axons based on IENFD whereas elevated hemoglobin A1c was related to large myelinated fiber loss (motor conduction velocity). These findings indicate obesity and hypertriglyceridemia significantly increase risk for peripheral neuropathy, independent of glucose control. Obesity/hypertriglyceridemia and hyperglycemia may have differential effects on small versus large fibers.
犹他州糖尿病神经病变研究(UDNS)检查了 218 名无神经病变症状或症状持续时间<5 年的 2 型糖尿病患者,以评估神经病变发展的危险因素。每位患者都完成了症状问卷、犹他早期神经病变量表(UENS)、神经传导研究(NCS)、振动和冷觉定量感觉测试(QST)、定量自主神经反射测试(QSART)以及皮肤活检,测量表皮内神经纤维密度(IENFD)。具有≥3 项异常的患者被归类为可能有神经病变,具有 1-2 项异常的患者被归类为可能有神经病变。研究了血糖控制、血脂参数(高密度脂蛋白和甘油三酯水平)、血压和肥胖与神经病变风险之间的关系。这些特征中异常数量与神经病变状态之间存在显著关系(p<0.01)。高甘油三酯血症、肥胖和 3 项或更多异常增加了神经病变风险(风险比分别为 2.1,p<0.03、2.9,p>0.02 和 3.0,p<0.004)。多变量分析发现,肥胖和甘油三酯与基于 IENFD 的小无髓鞘轴突丧失有关,而升高的血红蛋白 A1c 与大髓鞘纤维丧失(运动传导速度)有关。这些发现表明,肥胖和高甘油三酯血症显著增加了周围神经病变的风险,与血糖控制无关。肥胖/高甘油三酯血症和高血糖可能对小纤维和大纤维有不同的影响。