目的:口服葡萄糖耐量试验(OGTT)将受试者分类为正常,葡萄糖不耐受或糖尿病,取决于测试后120分钟(T120)的血糖。在OGTT之后,先前描述了与10年糖尿病不同发病率相关的五个胰岛素谱。然而,胰岛素测量对溶血敏感,并且可以通过对溶血样品的C肽测定来代替。然而,对C肽对OGTT的反应模式知之甚少。
方法:总共,包括128名患者,建立初步基线C肽值,并与胰岛素反应相比,评估对OGTT的C肽反应,使用LiaisonXL免疫分析仪。
结果:百例患者血糖反应正常,19个被归类为葡萄糖不耐受,9个被归类为糖尿病。在正常受试者中,中值C肽(nmol/L,5-95百分位数)在基线时为0.53(0.23-1.37),在T60时达到2.36(0.94-1.83)的峰值,在T120时下降到2.09(1.13-4.36)。由于不同的分解代谢途径,C肽反应模式与胰岛素模式相似但更平坦。然而,只有9.4%的病例中C肽和胰岛素反应谱不一致。曲线3(C肽在T60峰值)在正常患者中最普遍,而曲线4(在120分钟达到峰值,在T30低于T60水平)在葡萄糖不耐受和糖尿病患者中最普遍。
结论:在OGTT中,C肽可以代替溶血血液样本的胰岛素测定来预测2型糖尿病的风险。
OBJECTIVE: The oral glucose tolerance test (OGTT) classifies subjects as normal, glucose intolerant or diabetic depending on glycemia at 120 min (T120) post-test. Five insulin profiles associated with different incidences of diabetes over 10 years\' follow-up were previously described following OGTT. However, insulin measurement is sensitive to hemolysis, and can be replaced by C-peptide assay on hemolyzed samples. However, little is known about patterns of C-peptide response to OGTT.
METHODS: In total, 128 patients were included, to establish preliminary baseline C-peptide values and to evaluate C-peptide response to OGTT in comparison to insulin response, using the Liaison XL immunoanalyzer.
RESULTS: Hundred patients had a normal glycemic response, 19 were classified as glucose intolerant and 9 as diabetic. In normal subjects, median C-peptide values (nmol/L, with 5-95 percentiles) were 0.53 (0.23-1.37) at baseline, peaking at 2.36 (0.94-1.83) at T60, and decreasing to 2.09 (1.13-4.36) at T120. The C-peptide response pattern was similar but flatter than the insulin pattern because of different catabolism pathways. Nevertheless, C-peptide and insulin response profiles were discordant in only 9.4% of cases. Profile 3 (C-peptide peaking at T60) was the most prevalent in normal patients whereas profile 4 (peak at 120 min and lower level at T30 than at T60) was the most prevalent in glucose intolerant and diabetic patients.
CONCLUSIONS: In OGTT, C-peptide could replace insulin determination on hemolyzed blood samples to predict the risk of type 2 diabetes.