甘油三酯葡萄糖乘积指数与BMI对2型糖尿病合并非酒精性脂肪性肝病的预测价值

王东旭; 南楠; 邴浩; 林连捷

doi:10.3969/j.issn.1001-5256.2022.05.017

甘油三酯葡萄糖乘积指数与BMI对2型糖尿病合并非酒精性脂肪性肝病的预测价值

DOI: 10.3969/j.issn.1001-5256.2022.05.017

中国医科大学附属盛京医院消化内科，沈阳 110134

基金项目:

辽宁省自然科学基金 (2014021083)

伦理学声明：本研究方案于2021年9月10日经由中国医科大学附属盛京医院医学伦理委员会审查，批号：2021PS694K。

利益冲突声明：本研究不存在研究者、伦理委员会、受试者及公开研究成果有关的利益冲突。

作者贡献声明：王东旭负责文章的构思与设计，数据收集与整理、统计学分析和撰写论文；南楠、邴浩参与数据的收集与整理；林连捷负责选题，指导撰写文章并最后定稿。

详细信息

通信作者:
林连捷，leanlj13@yeah.net

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出版历程
- 收稿日期: 2021-09-15
- 录用日期: 2021-10-29
- 出版日期: 2022-05-20

Value of triglyceride-glucose index and body mass index in predicting nonalcoholic fatty liver disease in patients with type 2 diabetes mellitus

Department of Gastroenterology, Shengjing Hospital of China Medical University, Shenyang 110134, China

Research funding:

Natural Science Foundation of Liaoning Province (2014021083)

More Information

Corresponding author: LIN Lianjie, leanlj13@yeah.net(ORCID: 0000-0002-5624-4958)

摘要

摘要: 目的探讨甘油三酯葡萄糖乘积指数(TyG)与BMI对2型糖尿病(T2DM)合并非酒精性脂肪性肝病(NAFLD)的预测价值。方法回顾性分析2020年5月—2021年7月中国医科大学附属盛京医院诊治349例T2DM患者的临床资料，按照有无NAFLD分为T2DM合并NAFLD组(n=213)和单纯T2DM组(n=136)。计量资料两组间比较采用t检验或Mann-Whitney U检验；计数资料两组间比较采用χ²检验。采用logistic回归分析TyG及BMI与T2DM合并NAFLD的关系，受试者工作特征曲线(ROC曲线)评价TyG、BMI及TyG联合BMI对T2DM合并NAFLD的预测效能。采用Kappa系数分析预测结果的一致性。结果 T2DM合并NAFLD组的BMI、舒张压、空腹血糖、糖化血红蛋白、ALT、AST、GGT、TG、TC、LDL-C、TyG均高于单纯T2DM组(P值均＜0.05)，T2DM合并NAFLD组的HDL-C低于单纯T2DM组(P＜0.05)，两组在收缩压、总胆红素、直接胆红素、间接胆红素间的差异均无统计学意义(P值均＞0.05)。Logistic分析显示TyG(OR=6.513，95%CI：1.884~22.517，P=0.003)和BMI(OR=1.369，95%CI：1.191~1.575，P＜0.001)为T2DM合并NAFLD的独立危险因素。ROC曲线显示，TyG预测T2DM合并NAFLD的曲线下面积(AUC)为0.875，最佳截断点9.41，敏感度、特异度、阳性预测值和阴性预测值分别为80.3%、80.1%、86.36%、72.19%；BMI预测T2DM合并NAFLD的AUC为0.787，最佳截断点24.22，敏感度、特异度、阳性预测值和阴性预测值分别为78.9%、64.0%、77.36%、64.23%；TyG联合BMI预测T2DM合并NAFLD的AUC、敏感度、特异度、阳性预测值和阴性预测值分别为0.910、81.2%、88.2%、91.53%、75.00%。TyG、BMI及TyG联合BMI预测T2DM合并NAFLD的Kappa系数分别为0.592、0.416、0.673。结论 TyG和BMI可用来预测T2DM合并NAFLD的发生，二者联合可提高预测价值。
- 非酒精性脂肪性肝病 /
- 糖尿病, 2型 /
- 甘油三酯葡萄糖乘积指数 /
- 人体质量指数
Abstract: Objective To investigate the value of triglyceride-glucose index (TyG) and body mass index (BMI) in predicting nonalcoholic fatty liver disease (NAFLD) in type 2 diabetes mellitus (T2DM). Methods A retrospective analysis was performed for the clinical data of 349 patients with T2DM who were treated in Shengjing Hospital of China Medical University from May 2020 to July 2021, and according to the presence or absence of NAFLD, they were divided into T2DM+NAFLD group with 213 patients and simple T2DM group with 136 patients. The t-test or the Mann Whitney U test was used for comparison of continuous data between two groups, and the chi-square test was used for comparison of categorical data between two groups. A logistic regression analysis was used to investigate the association of TyG and BMI with T2DM+NAFLD, and the receiver operating characteristic (ROC) curve was plotted to evaluate the prediction efficiency of TyG alone, BMI alone, and TYG combined with BMI for NAFLD in T2DM. The Kappa coefficient was used to analyze the consistency of prediction results. Results Compared with the simple T2DM group, the T2DM+NAFLD group had significantly higher BMI, diastolic pressure, fasting blood glucose, HbA1c, alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transpeptidase, triglyceride, total cholesterol, low-density lipoprotein cholesterol, and TyG (all P < 0.05) and a significantly lower high-density lipoprotein cholesterol (P < 0.05), while there were no significant differences between the two groups in systolic pressure, total bilirubin, direct bilirubin, and indirect bilirubin (all P > 0.05). The logistic regression analysis showed that TyG (odds ratio [OR]=6.513, 95% confidence interval [CI]: 1.884-22.517, P < 0.001) and BMI (OR=1.369, 95% CI: 1.191-1.575, P < 0.001) were independent risk factors for NAFLD in T2DM. The ROC curve analysis showed that TyG had an area under the ROC curve (AUC) of 0.875 in predicting NAFLD in T2DM, with a sensitivity of 80.3%, a specificity of 80.1%, a positive predictive value of 86.36%, and a negative predictive value of 72.19% at the optimal cut-off value of 9.41; BMI had an AUC of 0.787, with a sensitivity of 78.9%, a specificity of 64.0%, a positive predictive value of 77.36%, and a negative predictive value of 64.23% at the optimal cut-off value of 24.22; TyG combined with BMI had an AUC of 0.910, a sensitivity of 81.2%, a specificity of 88.2%, a positive predictive value of 91.53%, and a negative predictive value of 75.00% in predicting NAFLD in T2DM. TyG alone, BMI alone, and TyG combined with BMI had a Kappa coefficient of 0.592, 0.416, and 0.673, respectively, in predicting NAFLD in T2DM. Conclusion TyG and BMI can be used to predict the onset of NAFLD in T2DM, and the combination of TyG and BMI can improve the predictive value.
- Non-alcoholic Fatty Liver Disease /
- Diabetes Mellitus, Type 2 /
- Triglyceride-Glucose Index /
- Body Mass Index

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图 1 TyG、BMI及TyG联合BMI预测T2DM合并NAFLD的ROC曲线

Figure 1. ROC curve of TyG, BMI and TyG combined with BMI for predicting T2DM combined with NAFLD

下载: 全尺寸图片幻灯片

表 1 两组一般资料的比较

Table 1. Comparison of general data between two groups

指标	T2DM合并NAFLD组(n=213)	单纯T2DM组(n=136)	统计值	P值
BMI(kg/m²)	26.33(24.52~29.37)	23.23(21.92~25.39)	Z=-9.044	＜0.001
收缩压(mmHg)	130.00(120.00~140.00)	130.00(120.00~140.00)	Z=-1.729	0.084
舒张压(mmHg)	80.00(80.00~90.00)	80.00(75.00~84.00)	Z=-3.251	0.001
FBG(mmol/L)	9.85(8.20~12.29)	7.96(6.36~9.68)	Z=-6.126	＜0.001
HbA1c(%)	8.90(7.45~10.25)	7.35(6.50~9.05)	Z=-5.075	＜0.001
ALT(U/L)	31.00(22.00~44.00)	21.00(13.00~26.00)	Z=-7.820	＜0.001
AST(U/L)	22.00(17.00~29.00)	18.00(15.00~21.00)	Z=-5.447	＜0.001
GGT(U/L)	36.00(24.00~56.00)	18.00(13.00~25.25)	Z=-9.402	＜0.001
TBil(μmol/L)	10.25(8.30~13.40)	10.40(7.80~13.20)	Z=-0.098	0.922
DBil(μmol/L)	3.20(2.50~4.18)	3.30(2.53~4.38)	Z=-1.129	0.259
IBil(μmol/L)	7.25(5.40~9.20)	7.05(5.25~9.00)	Z=-0.226	0.821
TG(mmol/L)	2.42(1.74~3.63)	1.07(0.81~1.50)	Z=-11.831	＜0.001
TC(mmol/L)	5.04(4.28~5.96)	4.21(3.86~4.70)	Z=-7.188	＜0.001
HDL-C(mmol/L)	1.02(0.88~1.25)	1.16(1.02~1.37)	Z=-4.897	＜0.001
LDL-C(mmol/L)	3.28(2.63~3.97)	2.87(2.63~3.87)	Z=-4.042	＜0.001
TyG	9.98±0.79	8.87±0.61	t=13.832	＜0.001

下载: 导出CSV

表 2 TyG、BMI与T2DM合并NAFLD的logistic回归分析

Table 2. Logistic regression analysis of TyG, BMI in T2DM combined with NAFLD

指标	β值	标准误	Wald值	OR值	95%CI	P值
校正前BMI	0.392	0.051	59.377	1.479	1.339~1.634	＜0.001
校正前TyG	2.439	0.269	82.237	11.459	6.764~19.411	＜0.001
校正后BMI	0.314	0.071	19.390	1.369	1.191~1.575	＜0.001
校正后TyG	1.874	0.633	8.766	6.513	1.884~22.517	0.003

下载: 导出CSV

表 3 TyG、BMI及TyG联合BMI对T2DM合并NAFLD的预测价值

Table 3. Predictive value of TyG, BMI and TyG combined BMI for T2DM combined with NAFLD

指标	最佳截断点	AUC	95%CI	敏感度(%)	特异度(%)	阳性预测值(%)	阴性预测值(%)	Kappa系数
BMI	24.22	0.787	0.740~0.834	78.9	64.0	77.36	64.23	0.416
TyG	9.41	0.875	0.839~0.911	80.3	80.1	86.36	72.19	0.592
TyG联合BMI		0.910	0.881~0.940	81.2	88.2	91.53	75.00	0.673

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参考文献(19)

[1]	LI Y, TENG D, SHI X, et al. Prevalence of diabetes recorded in mainland China using 2018 diagnostic criteria from the American Diabetes Association: national cross sectional study[J]. BMJ, 2020, 369: m997. DOI: 10.1136/bmj.m99.
[2]	TARIQ T, DESAI AP. Nonalcoholic fatty liver disease: Making the diagnosis[J]. Clin Liver Dis (Hoboken), 2020, 16(2): 53-57. DOI: 10.1002/cld.924.
[3]	YOUNOSSI ZM, GOLABI P, de AVILA L, et al. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: A systematic review and meta-analysis[J]. J Hepatol, 2019, 71(4): 793-801. DOI: 10.1016/j.jhep.2019.06.021.
[4]	ZHOU Q, WANG Y, WANG J, et al. Prevalence and risk factor analysis for the nonalcoholic fatty liver disease in patients with type 2 diabetes mellitus[J]. Medicine (Baltimore), 2021, 100(10): e24940. DOI: 10.1097/MD.0000000000024940.
[5]	Chinese Diabetes Society. Guideline for the prevention and treatment of type 2 diabetes mellitus in China (2020edition)[J]. Chin J Diabetes, 2021, 13(4): 315-409. DOI: 10.3760/cma.j.cn115791-20210221-00095. 中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2020年版)[J]. 中华糖尿病杂志, 2021, 13(4): 315-409. DOI: 10.3760/cma.j.cn115791-20210221-00095.
[6]	National Workshop on Fatty Liver and Alcoholic Liver Disease, Chinese Society of Hepatology, Chinese Medical Association; Fatty Liver Expert Committee, Chinese Medical Doctor Association. Guidelines of prevention and treatment for nonalcoholic fatty liver disease: A 2018 update[J]. J Clin Hepatol, 2018, 34(5): 947-957. DOI: 10.3969/j.issn.1001-5256.2018.05.007. 中华医学会肝病学分会脂肪肝和酒精性肝病学组, 中国医师协会脂肪性肝病专家委员会. 非酒精性脂肪性肝病防治指南(2018更新版)[J]. 临床肝胆病杂志, 2018, 34(5): 947-957. DOI: 10.3969/j.issn.1001-5256.2018.05.007.
[7]	HONG J, SHI YW, WU XN, et al. Application value of imaging diagnosis in nonalcoholic fatty liver disease[J]. J Clin Hepatol, 2018, 34(12): 2698-2701. DOI: 10.3969/j.issn.1001-5256.2018.12.041. 洪佳, 施漪雯, 吴晓宁, 等. 影像学诊断技术在非酒精性脂肪性肝病中的应用价值[J]. 临床肝胆病杂志, 2018, 34(12): 2698-2701. DOI: 10.3969/j.issn.1001-5256.2018.12.041.
[8]	DU J, YANG ZH. Application progress of imaging examination in liver fat quantification[J]. Radiol Pract, 2017, 32(5): 479-482. DOI: 10.13609/.cnki.1000-0213.2017.05.011. 杜婧, 杨正汉. 影像学检查在肝脏脂肪定量中的应用进展[J]. 放射学实践, 2017, 32(5): 479-482. DOI: 10.13609/.cnki.1000-0213.2017.05.011.
[9]	POLYZOS SA, KOUNTOURAS J, MANTZOROS CS. Obesity and nonalcoholic fatty liver disease: From pathophysiology to therapeutics[J]. Metabolism, 2019, 92: 82-97. DOI: 10.1016/j.metabol.2018.11.014.
[10]	APPARI M, CHANNON KM, MCNEILL E. Metabolic regulation of adipose tissue macrophage function in obesity and diabetes[J]. Antioxid Redox Signal, 2018, 29(3): 297-312. DOI: 10.1089/ars.2017.7060.
[11]	POLYZOS SA, KOUNTOURAS J, MANTZOROS CS. Adipose tissue, obesity and non-alcoholic fatty liver disease[J]. Minerva Endocrinol, 2017, 42(2): 92-108. DOI: 10.23736/S0391-1977.16.02563-3.
[12]	SIMENTAL-MENDÍA LE, RODRÍGUEZ-MORÁN M, GUERRERO-ROMERO F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects[J]. Metab Syndr Relat Disord, 2008, 6(4): 299-304. DOI: 10.1089/met.2008.0034.
[13]	TORO-HUAMANCHUMO CJ, URRUNAGA-PASTOR D, GUARNIZO-POMA M, et al. Triglycerides and glucose index as an insulin resistance marker in a sample of healthy adults[J]. Diabetes Metab Syndr, 2019, 13(1): 272-277. DOI: 10.1016/j.dsx.2018.09.010.
[14]	RODRÍGUEZ-MORÁN M, SIMENTAL-MENDÍA LE, GUERRERO-ROMERO F. The triglyceride and glucose index is useful for recognising insulin resistance in children[J]. Acta Paediatr, 2017, 106(6): 979-983. DOI: 10.1111/apa.13789.
[15]	BUZZETTI E, PINZANI M, TSOCHATZIS EA. The multiple-hit pathogenesis of non-alcoholic fatty liver disease (NAFLD)[J]. Metabolism, 2016, 65(8): 1038-1048. DOI: 10.1016/j.metabol.2015.12.012.
[16]	XIE J, YANG M, XING Y. Effects of liraglutide on glucose and lipid metabolism and insulin resistance in type 2 diabetes mellitus patients with non-alcoholic fatty liver disease[J/CD]. Chin J Liver Dis (Electronic Version), 2021, 13(4): 46-53. DOI: 10.3969/j.issn.1674-7380.2021.04.008. 谢晶, 杨淼, 邢英. 利拉鲁肽对2型糖尿病合并非酒精性脂肪性肝病患者糖脂代谢及胰岛素抵抗的影响[J/CD]. 中国肝脏病杂志(电子版), 2021, 13(4): 46-53. DOI: 10.3969/j.issn.1674-7380.2021.04.008.
[17]	LI TT, BAI XP. Two-way relationship and pathogenesis of nonalcoholic fatty liver disease and type 2 diabetes mellitus[J]. Med Recapitulate, 2021, 27(1): 158-162, 168. DOI: 10.3969/j.issn.1006-2084.2021.01.030. 李婷婷, 白秀平. 非酒精性脂肪性肝病与2型糖尿病的双向关系及发病机制[J]. 医学综述, 2021, 27(1): 158-162, 168. DOI: 10.3969/j.issn.1006-2084.2021.01.030.
[18]	LIU J, REN CQ, FENG YL, et al. Relationship between liver fibrosis and insulin resistance in patients with type 2 diabetes and nonalcoholic fatty liver disease[J]. Chin J Clin Res, 2021, 34(4): 443-448. DOI: 10.13429/j.cnki.cjcr.2021.04.003. 刘佼, 任彩琴, 冯亚莉, 等. 2型糖尿病合并非酒精性脂肪性肝病患者肝纤维化与胰岛素抵抗的关系[J]. 中国临床研究, 2021, 34(4): 443-448. DOI: 10.13429/j.cnki.cjcr.2021.04.003.
[19]	HAN L, XIE H, SUN Y, et al. Diagnosis and evaluation of metabolic related fatty liver disease[J]. Chin Hepatol, 2021, 26(2): 205-210. DOI: 10.14000/j.cnki.issn.1008-1704.2021.02.029. 韩琳, 谢欢, 孙颖, 等. 代谢相关脂肪性肝病的诊断与评估现状[J]. 肝脏, 2021, 26(2): 205-210. DOI: 10.14000/j.cnki.issn.1008-1704.2021.02.029.