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山东大学学报 (医学版) ›› 2022, Vol. 60 ›› Issue (12): 44-51.doi: 10.6040/j.issn.1671-7554.0.2022.0575

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简易胰岛素抵抗指标与698例2型糖尿病患者发生高尿酸血症风险的关联

赵美茹1,2,3,4,朱迪2,3,4,刘淋2,3,4,管庆波1,2,3,4,张栩2,3,4   

  1. 1.山东大学, 山东 济南 250012;2.山东第一医科大学附属省立医院内分泌代谢病科, 山东 济南 250021;3.山东省内分泌与脂代谢重点实验室, 山东 济南 250021;4.山东省糖尿病与代谢疾病临床医学研究中心, 山东 济南 250021
  • 发布日期:2022-12-01
  • 通讯作者: 张栩. E-mail:zhangxu@medmail.com.cn

Association of 4 simple insulin resistance indicators with the risk of hyperuricemia in 698 patients with type 2 diabetes mellitus

ZHAO Meiru1,2,3,4, ZHU Di2,3,4, LIU Lin2,3,4, GUAN Qingbo1,2,3,4, ZHANG Xu2,3,4   

  1. 1. Shandong University, Jinan 250012, Shandong, China;
    2. Department of Endocrine and Metabolic Diseases, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China;
    3. Shandong Key Laboratory of Endocrinology and Lipid Metabolism, Jinan 250021, Shandong, China;
    4. Shandong Clinical Research Center of Diabetes and Metabolic Diseases, Jinan 250021, Shandong, China
  • Published:2022-12-01

摘要: 目的 旨在探讨甘油三酯葡萄糖(TyG)指数、甘油三酯葡萄糖体质量(TyG-BMI)指数、甘油三酯/高密度脂蛋白胆固醇(TG/HDL-C)比值和胰岛素抵抗代谢(METS-IR)指数对中老年男性2型糖尿病(T2DM)患者发生高尿酸血症(HUA)风险的影响。 方法 选取2016年1月至2019年12月山东省立医院内分泌科住院的中老年男性2型糖尿病患者698例。根据血尿酸值(SUA)将698例中老年男性T2DM患者分为非高尿酸血症组(SUA<420 μmol/L,NUA组)和HUA组(SUA≥420 μmol/L)。采用多因素Logistics回归评估简易胰岛素抵抗指标及其四分位数对中老年男性T2DM患者发生HUA的影响。采用ROC曲线评估4种简易胰岛素抵抗(IR)指标对中老年男性T2DM患者发生HUA的预测价值。 结果 HUA组的TyG指数、TyG-BMI指数、TG/HDL-C比值、METS-IR指数较NUA组升高,差异有统计学意义(P<0.05)。以T2DM患者是否发生HUA(赋值:0=否,1=是)为因变量,以单因素回归分析中有统计学意义的指标为自变量进行多因素二分类Logistic回归分析,结果显示,血清肌酐(Scr)、维生素A结合蛋白(RBP)、TyG指数、TyG-BMI、TG/HDL-C和METS-IR是中老年男性T2DM患者发生HUA的独立影响因素(P<0.05)。ROC曲线显示,TyG指数对T2DM患者发生HUA的参考价值最高,AUC为0.73(95%CI:0.68~0.77),灵敏度为76.6 %,特异度为57.8%,约登指数为0.34;其次是TyG-BMI、TG/HDL-C、METS-IR。 结论 TyG指数、TyG-BMI、TG/HDL-C和METS-IR对中老年男性2型糖尿病患者发生HUA具有参考意义。

关键词: 甘油三酯葡萄糖指数, 甘油三酯葡萄糖体质量指数, 甘油三酯/高密度脂蛋白胆固醇比值, 胰岛素抵抗代谢指数, 高尿酸血症, 2型糖尿病, 胰岛素抵抗

Abstract: Objective To investigate the effects of triglyceride-glucose(TyG), triglyceride-glucose body mass index(TyG-BMI), triglyceride/high-density lipoprotein cholesterol ratio(TG/HDL-C)and metabolic score for insulin resistance(METS-IR)on the risk of hyperuricemia(HUA)in 698 patients with type 2 diabetes mellitus(T2DM). Methods A total of 698 patients with T2DM hospitalized in the Department of Endocrinology of Shandong Provincial Hospital during Jan. 2016 and Dec. 2019 were selected. According to the serum uric acid value(SUA), the patients were divided into the non-hyperuricemia group(SUA<420 μmol/L, NUA group)and HUA group(SUA≥420 μmol/L, HUA group). The reference value of TyG, TyG-BMI, TG/HDL-C and METS-IR for HUA was analyzed with multivariate Logistic regression and receiver operator characteristic(ROC)curve. Results TyG, TyG-BMI, TG/HDL-C and METS-IR were higher in HUA group than in NUA group(P<0.05). With the occurrence of HUA(assignment: 0=no, 1=yes)as the dependent variable, and the indicators with statistical significance in the univariate regression analysis as the independent variables, the multivariate binary Logistic regression analysis showed that, serum creatinine(Scr), retinol binging protein(RBP), TyG, TyG-BMI, TG/HDL-C and METS-IR were independent influencing factors of HUA in T2DM patients(P<0.05). The ROC curve showed that TyG had the highest reference value on the occurrence of HUA, with the area under the curve(AUC)of 0.73(95%CI: 0.68-0.77), sensitivity of 76.6%, specificity of 57.8 %, and Youden index of 0.34, followed by TyG-BMI, TG/HDL-C and METS-IR. Conclusion TyG, TyG-BMI, TG/HDL-C and METS-IR have reference significance for the occurrence of HUA in middle-aged and elderly male patients with T2DM.

Key words: Triglyceride-glucose index, Triglyceride glucose-body mass index, Triglyceride/high-density lipoprotein cholesterol ratio, Metabolic score for insulin resistance, Hyperuricemia, Type 2 diabetes, Insulin resistance

中图分类号: 

  • R587.1
[1] 李静. 高尿酸血症的流行病学研究[J]. 中国心血管杂志, 2016, 21(2): 83-86. LI Jing. Epidemiologic studies of hyperuricemia[J]. Chinese Journal of Cardiovascular Medicine, 2016, 21(2): 83-86.
[2] Hu X, Rong S, Wang Q, et al. Association between plasma uric acid and insulin resistance in type 2 diabetes: a mendelian randomization analysis [J]. Diabetes Res Clin Pract, 2021, 171: 108542. doi: 10.1016/j.diabres.2020.108542.
[3] Bonora E, Capaldo B, Perin PC, et al. Hyperinsulinemia and insulin resistance are independently associated with plasma lipids, uric acid and blood pressure in non-diabetic subjects. The GISIR database [J]. Nutr Metab Cardiovasc Dis, 2008, 18(9): 624-631.
[4] Sánchez-García A, Rodríguez-Gutiérrez R, Mancillas-Adame L, et al. Diagnostic accuracy of the triglyceride and glucose index for insulin resistance: a systematic review [J]. Int J Endocrinol, 2020, 2020: 4678526. doi:10.1155/2020/4678526.
[5] 李融融, 时小东, 陈伟. 新型简化胰岛素抵抗评价指标对糖代谢紊乱预测价值的比较研究[J]. 中华糖尿病杂志, 2022, 14(1): 56-62. LI Rongrong, SHI Xiaodong, CHEN Wei. A comparative study on the predictive value of new simplified insulin resistance assessment indicators in identifying glucose metabolism disturbance [J]. Chinese Journal of Diabetes, 2022, 14(1): 56-62.
[6] 孙琳, 王桂侠, 郭蔚莹. 高尿酸血症研究进展[J]. 中国老年学杂志, 2017, 37(4): 1034-1038. SUN Lin, WANG Guixia, GUO Weiying. Research progress of hyperuricemia [J]. Chinese Journal of Gerontology, 2017, 37(4): 1034-1038.
[7] 李林, 朱小霞, 戴宇翔, 等. 中国高尿酸血症相关疾病诊疗多学科专家共识[J]. 中华内科杂志, 2017, 56(3): 235-248. LI Lin, ZHU Xiaoxia, DAI Yuxiang, et al. Chinese multi-disciplinary consensus on the diagnosis and treatment of hyperuricemia and its related diseases [J]. Chinese Journal of Internal Medicine, 2017, 56(3): 235-248.
[8] Liu R, Han C, Wu D, et al. Prevalence of hyperuricemia and gout in mainland China from 2000 to 2014: a systematic review and meta-analysis [J]. Biomed Res Int, 2015, 2015: 762820. doi: 10.1155/2015/762820.
[9] Cibi cková, Langová L, Vaverková H, et al. Correlation of uric acid levels and parameters of metabolic syndrome [J]. Physiol Res, 2017, 66(3): 481-487.
[10] Adachi SI, Yoshizawa F, Yagasaki K. Hyperuricemia in type 2 diabetic model KK-Ay/Ta mice: a potent animal model with positive correlation between insulin resistance and plasma high uric acid levels [J]. BMC Res Notes, 2017, 10(1): 577.
[11] Wang Y, Yang W, Jiang X. Association between triglyceride-glucose index and hypertension: a meta-analysis [J]. Frontiers in cardiovascular medicine, 2021, 8: 644035. doi: 10.3389/fcvm.2021.644035.
[12] Zheng R, Mao Y. Triglyceride and glucose(TyG)index as a predictor of incident hypertension: a 9-year longitudinal population-based study [J]. Lipids in health and disease, 2017, 16(1): 175.
[13] Li J, Ren L, Chang C, et al. Triglyceride-glukose index predicts adverse events in patients with acute coronary syndrome: a meta-analysis of cohort studies [J]. Horm Metab Res, 2021, 53(9): 594-601.
[14] Duran Karaduman B, Ayhan H, Kele?瘙塂 T, et al. The triglyceride-glucose index predicts peripheral artery disease complexity [J]. Turkish journal of medical sciences, 2020, 50(5): 1217-1222.
[15] Sheng GT, Lu S, Xie QY, et al. The usefulness of obesity and lipid-related indices to predict the presence of Non-alcoholic fatty liver disease [J]. Lipids Heal Dis, 2021, 20(1): 134.
[16] 邹筱芳, 巫冠中. 尿酸肾损伤的分子机制研究进展[J]. 安徽医药, 2015, 19(1): 5-9. ZOU Xiaofang, WU Guanzhong. Molecular mechanism of uric acid in renal injury [J]. Anhui Medical and Pharmaceutical Journal, 2015, 19(1): 5-9.
[17] Salihefendic D, Zildzic M, Masic I. The importance of the quantity and the distribution assessment of fat tissue in a diagnosis of insulin resistance [J]. Med Arch Sarajevo Bosnia Herzegovina, 2020, 74(6): 439-443.
[18] Yamada A, Sato KK, Kinuhata S, et al. Association of visceral fat and liver fat with hyperuricemia [J]. Arthritis Care Res, 2016, 68(4): 553-561.
[19] Zong J, Sun Y, Zhang Y, et al. Correlation between serum uric acid level and central body fat distribution in patients with Type 2 diabetes [J]. Diabetes Metab Syndr Obes, 2020, 13: 2521-2531. doi: 10.2147/DMSO.S260891.
[20] 费晶, 陆昀, 黄阳, 等. 中年男性人群吸烟与血尿酸的关系探讨[J]. 中华老年医学杂志, 2020, 39(2): 151-154. FEI Jing, LU Yun, HUANG Yang, et al. The correlation between different smoking status and serum uric acid in a middle-aged male population [J]. Chinese Journal of Gerontology, 2020, 39(2): 151-154.
[21] Gu Q, Hu X, Meng J, et al. Associations of triglyceride-glucose index and its derivatives with hyperuricemia risk: a cohort study in Chinese general population [J]. Int J Endocrinol, 2020, 2020: 3214716. doi: 10.1155/2020/3214716.
[22] Mazidi M, Katsiki N, Mikhailidis DP, et al. The link between insulin resistance parameters and serum uric acid is mediated by adiposity [J]. Atherosclerosis, 2018, 270: 180-186. doi: 10.1016/j.atherosclerosis.
[23] Kim TH, Lee SS, Yoo JH, et al. The relationship between the regional abdominal adipose tissue distribution and the serum uric acid levels in people with type 2 diabetes mellitus [J]. Diabetol Metab Syndr, 2012, 4(1): 3.
[24] Huang XL, Jiang XH, Wang L, et al. Visceral adipose accumulation increased the risk of hyperuricemia among middle-aged and elderly adults: a population-based study [J]. J Transl Med, 2019, 17(1): 341.
[25] Yang L, He Z, Gu X, et al. Dose-response relationship between BMI and hyperuricemia [J]. Int J Gen Med, 2021, 14: 8065-8071. doi: 10.2147/IJGM.S341622.
[26] 杨曦, 柳怡莹, 万沁. TG/HDL-C、TyG指数对T2DM患者高尿酸血症的预测价值[J]. 天津医药, 2021, 49(6): 603-608. YANG Xi, LIU Yiying, WAN Qin. The predictive value of TG/HDL-C and TyG index for hyperuricemia in T2DM patients [J]. Tianjin Medical Journal, 2021, 49(6): 603-608.
[27] Liu XY, Wu QY, Chen ZH, et al. Elevated triglyceride to high-density lipoprotein cholesterol(TG/HDL-C)ratio increased risk of hyperuricemia: a 4-year cohort study in China [J]. Endocrine, 2020, 68(1): 71-80.
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