Metabolic clustering of risk factors: evaluation of Triglyceride-glucose index (TyG index) for evaluation of insulin resistance.
Metabolic clustering of risk factors: evaluation of Triglyceride-glucose index (TyG index) for evaluation of insulin resistance.
复制标题
DOI：
10.1186/s13098-018-0376-8
复制
发表时间：
2018
影响因子：
4.8
通讯作者：
Ahmad F
中科院分区：
文献类型：
--
作者：
Khan SH;Sobia F;Niazi NK;Manzoor SM;Fazal N;Ahmad F
多年来，代谢综合征有结构化的定义来对患有该疾病的个体进行分类。文献综述表明胰岛素抵抗是这些代谢聚集的标志。虽然在一般实践中直接或间接测量胰岛素抵抗在技术上仍然存在困难，而且胰岛素存在多种稳定性问题，但当局已建议采取各种间接措施。空腹甘油三酯-葡萄糖 (TyG) 指数就是这样一种标记物，最近被建议作为预测代谢综合征的有用诊断标记物。然而，关于该主题的可用数据有限，我们地区几乎没有关于该主题的文献。 1. 将 TyG 指数与胰岛素抵抗、人体测量指数、小密度 LDLc、HbA1c 和肾病相关联。 2. 与其他可用标记物相比，评估 TyG 指数作为诊断代谢综合征的标记物。学习地点和持续时间 - 2016 年 6 月至 2017 年 7 月在伊斯兰堡 PSS HAFEEZ 医院。从最终选定的 227 名男性和女性受试者样本中，我们评估了他们的人体测量数据、HbA1c、血脂谱（包括计算出的 sdLDLc）、尿白蛋白肌酸酐 (UACR) 和胰岛素抵抗 (HOMAIR)。 TyG指数使用Simental-Mendía LE等人的公式计算。上述参数与TyG指数相关，使用独立样本t检验计算患有和不患有代谢综合征受试者之间的差异。最后进行ROC曲线分析，测量包括TyG指数在内的候选参数的AUC，以进行比较。与空腹甘油三酯、HOMAIR、HDLc 和非 HDLc 等其他标志物相比，TyG 指数与 BMI、致动脉粥样硬化血脂异常 (sdLDLc)、肾病 (UACR)、HbA1c 和胰岛素抵抗呈更高的正线性相关。根据 IDF 标准，TyG 指数显示患有和不患有代谢综合征的受试者中各种标记物之间存在显着差异。 AUC（曲线下面积）显示 TyG 的最高 AUC 为 [(0.764，95% CI 0.700–0.828，p 值 ≤ 0.001)]，其次是空腹甘油三酯 [(0.724，95% CI 0.656–0.791，p 值 ≤ 0.001)]， sdLDLc [(0.695, 95% CI 0.626–0.763，p值 ≤ 0.001)]，空腹血糖[(0.686，95% CI 0.616–0.756，p值 ≤ 0.001)]，非HDLc [(0.640，95% CI 0.626–0.763， p 值 ≤ 0.001)] 和 HOMAIR [(0.619, 95% CI 0.545–0.694，p 值 ≤ 0.001)]。与空腹血糖、甘油三酯、sdLDLc、非 HDLc 和 HOMAIR 相比，TyG 指数具有最高的 AUC，可以作为诊断代谢综合征的更好标志物。
Metabolic syndrome over the years have structured definitions to classify an individual with the disease. Literature review suggests insulin résistance is hallmark of these metabolic clustering. While measuring insulin resistance directly or indirectly remains technically difficult in general practice, along with multiple stability issues for insulin, various indirect measures have been suggested by authorities. Fasting triglycerides-glucose (TyG) index is one such marker, which is recently been suggested as a useful diagnostic marker to predict metabolic syndrome. However, limited data is available on the subject with almost no literature from our region on the subject. 1. To correlate TyG index with insulin resistance, anthropometric indices, small dense LDLc, HbA1c and nephropathy. 2. To evaluate TyG index as a marker to diagnose metabolic syndrome in comparison to other available markers. Place and duration of study-From Jun-2016 to July-2017 at PSS HAFEEZ hospital Islamabad. From a finally selected sample size of 227 male and female subjects we evaluated their anthropometric data, HbA1c, lipid profile including calculated sdLDLc, urine albumin creatinine raito(UACR) and insulin resistance (HOMAIR). TyG index was calculated using formula of Simental-Mendía LE et al. Aforementioned parameters were correlated with TyG index, differences between subjects with and without metabolic syndrome were calculated using Independent sample t-test. Finally ROC curve analysis was carried out to measure AUC for candidate parameters including TyG Index for comparison. TyG index in comparison to other markers like fasting triglycerides, HOMAIR, HDLc and non-HDLc demonstrated higher positive linear correlation with BMI, atherogenic dyslipidemia (sdLDLc), nephropathy (UACR), HbA1c and insulin resistance. TyG index showed significant differences between various markers among subjects with and without metabolic syndrome as per IDF criteria. AUC (Area Under Curve) demonstrated highest AUC for TyG as [(0.764, 95% CI 0.700–0.828, p-value ≤ 0.001)] followed by fasting triglycerides [(0.724, 95% CI 0.656–0.791, p-value ≤ 0.001)], sdLDLc [(0.695, 95% CI 0.626–0.763, p-value ≤ 0.001)], fasting plasma glucose [(0.686, 95% CI 0.616–0.756, p-value ≤ 0.001)], Non-HDLc [(0.640, 95% CI 0.626–0.763, p-value ≤ 0.001)] and HOMAIR [(0.619, 95% CI 0.545–0.694, p-value ≤ 0.001)]. TyG index, having the highest AUC in comparison to fasting glucose, triglycerides, sdLDLc, non-HDLc and HOMAIR can act as better marker for diagnosing metabolic syndrome.
登录
查看更多内容
影响因子：
5.9
作者：
Song YS;Hwang YC;Ahn HY;Park CY
通讯作者：
Park CY
影响因子：
4.8
作者：
Yin J;Li M;Xu L;Wang Y;Cheng H;Zhao X;Mi J
通讯作者：
Mi J
DOI：
10.1080/00365513.2018.1469787
发表时间：
2018-01-01
影响因子：
2.1
作者：
Placzkowska, Sylwia;Pawlik-Sobecka, Lilla;Piwowar, Agnieszka
通讯作者：
Piwowar, Agnieszka
DOI：
10.3265/nefrologia.pre2012.nov.11430
发表时间：
2013-01-01
期刊：
Nefrología (Madrid)
影响因子：
--
作者：
Sánchez-Villanueva, Rafael;Estrada, Patricia;Bajo, M. Auxiliadora
通讯作者：
Bajo, M. Auxiliadora
影响因子：
5.1
作者：
Junqueira Vasques, Ana Carolina;Novaes, Fernanda Satake;Geloneze, Bruno
通讯作者：
Geloneze, Bruno