胰岛素抵抗指标TyG对心肌梗死后残余风险的增量效应
Incremental Effect of TyG, an Indicator of Insulin Resistance, on Residual Risk after Myocardial Infarction
摘要: 目的:本研究的目的是为了研究TyG与心肌梗死患者残余风险之间的关系。方法:选取712名急性心肌梗的患者进行5年随访,采集患者基本信息、体格检查等资料,检测实验室相关指标。绘制ROC曲线评估TyG对残余风险的预测能力,使用R语言计算分析净重分类指数(NRI)和综合判别改善指数(IDI),以进一步评估TyG在心肌梗死后残余风险传统危险因素之上的额外预测价值。结果:ROC曲线显示,TyG指数曲线下面积0.554 (95%CI: 0.503~0.604, P = 0.042),在基线风险模型中纳入TyG的综合判别改善指数[IDI]:0.0082,P = 0.022;纳入TyG的净重新分类指数[NRI]:0.2169,P = 0.017。在基线风险模型中纳入TyG对基线模型对MACE的预测能力有增量效应。结论:TyG对心血管残余风险具有一定的预测能力,在控制传统危险因素的同时,TyG可以指导急性心梗患者的进一步强化治疗。
Abstract: Objective: The purpose of this study was to investigate the relationship between TyG and residual risk in patients with myocardial infarction. Methods: 712 patients with acute myocardial infarction were selected for 5-year follow-up, and basic information, physical examination and other data were collected, and laboratory related indexes were tested. ROC curves were plotted to assess the predictive ability of TyG on residual risk. The net reclassification index (NRI) and integrated discriminant improvement index (IDI) were calculated and analyzed using the R language to further assess the additional predictive value of TyG over and above the traditional risk factors for residual risk after myocardial infarction. Results: ROC curves showed an area under the curve of the TyG index of 0.554 (95% CI: 0.503 to 0.604, P = 0.042), a composite discriminant improvement index [IDI] incorporating TyG in the baseline risk model: 0.0082, P = 0.022, and a net reclassification index [NRI] incorporating TyG: 0.2169, P = 0.017. In the baseline risk model, the inclusion of TyG had an incremental effect on the predictive power of the baseline model for MACE. Conclusion: TyG has a predictive ability for residual cardiovascular risk, and while controlling traditional risk factors, TyG may guide further intensive treatment for patients with acute myocardial infarction.
文章引用:汪园园, 李鹏. 胰岛素抵抗指标TyG对心肌梗死后残余风险的增量效应[J]. 临床医学进展, 2025, 15(4): 1631-1636. https://doi.org/10.12677/acm.2025.1541101

1. 引言

心血管疾病是全球死亡的主要原因[1]。已确定的动脉粥样硬化性心血管疾病(ASCVD)危险因素包括年龄、男性、ASCVD家族史、肥胖、高血压、高胆固醇血症和糖尿病[2] [3]。然而在控制了这些危险因素以后,仍然存在持续的残余心血管风险[4] [5]。从而强调了在一般人群中识别ASCVD新危险因素的重要性。先前的研究表明,胰岛素抵抗不仅普遍存在于2型糖尿病患者中,也普遍存在于肥胖或代谢综合征患者中,也可能与ASCVD的发病机制有关,因为胰岛素抵抗会导致动脉硬化和小血管的病变[6]-[8]。甘油三酯–葡萄糖(TyG)指数是一个来自空腹血糖和甘油三酯水平的参数,已被提议作为胰岛素抵抗的可靠替代指标[9]。现有的研究表明,在一般人群中,较高TyG指数水平与ASCVD的患病率相关,有助于早期识别心血管风险事件发生[10]-[16]。本研究的目的是为了研究TyG与心肌梗死患者残余风险之间的关系。

2. 研究对象与方法

2.1. 研究对象

选取2016.08~2019.2期间我院数据库中急性心肌梗死的3150名患者,并按照纳入及排除标准进行筛选,对符合标准的研究对象进行5年随访。最终纳入研究的受试者共有712名。纳入标准如下:(1) 入院诊断为急性心肌梗死的患者,根据WHO标准诊断心肌梗死:典型症状加上心电图改变或心肌酶升高。(2) 于我院接受CAG术。(3) 能够提供完整的临床资料。排除标准:(1) 在基线时患有严重肝功能和/或肾功能不全。(2) 恶性肿瘤。(3) 既往心肌梗死。(4) 既往冠状动脉支架植入术后。(5) 既往冠状动脉搭桥术后。(6) 基线时数据缺失。(7) 以及随访期间失访。本研究获得医院伦理委员会批准。

2.2. 资料收集

收集研究者入院基线资料。一般资料收集包括性别、年龄、身高、体重、BMI、高血压病史、糖尿病病史、吸烟史、饮酒史;实验室指标收集包括空腹血糖、载脂蛋白B (ApoB)、总胆固醇(TC)、低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇(HDL-C)、甘油三酯(TG)、脂蛋白a(Lp(a))。甘油三酯葡萄糖(TyG)指数:计算公式:TyG = ln[甘油三酯(mg/dl)*血浆葡萄糖(mg/dl)/2]。对随访的患者进行门诊随访。以发生主要不良心血管事件MACE为终点事件或是随访时间结束未发生MACE。MACE包括全因死亡、复发性心肌梗死、缺血性脑卒中、心力衰竭再入院、支架内再狭窄或血栓形成。全因死亡定义为心脏或非心脏原因导致的死亡,且只收集随访期间的死亡信息。

2.3. 统计学方法

使用SPSS 26.0版和R版本4.4.1进行统计分析。P < 0.05,差异被认为是显著的。所有分析均为双尾。TyG水平的分组基于三分位法。均数±标准差用于描述具有正态分布的连续变量,分类变量用百分比来描述。符合正态分布的连续变量的组间的比较用方差分析进行,对于不符合正态分布的连续变量之间用Kruskal-Wallis秩和检验来分析组间差异。使用卡方检验对分类变量进行三组间比较。使用受试者工作特征(ROC)曲线评估TyG对心肌梗死后残余风险的预测能力,此外,进一步计算了净重分类指数(NRI)和综合判别改善指数(IDI),以进一步评估TyG在心肌梗死后残余风险因素之上的额外预测价值。

3. 结果

3.1. 符合标准的研究对象的基线特征

根据三分位将TyG分为低水平组(≤1.11)、中水平组(1.12~1.68)、高水平组(≥1.69)。三组间一般资料和临床指标的比较。本研究共纳入712名接受PCI的AMI患者(平均年龄59.6岁,其中男性占比63.06%),基线TyG的平均值为1.49 ± 0.74。根据TyG水平将研究参与者分低、中、高水平组,其分组的基线特征显示在表1。根据TyG水平,其基线特征,即性别、高血压、吸烟史、体重指数方面没有发现统计学差异;在年龄、胆固醇、甘油三酯、脂蛋白a、低密度脂蛋白胆固醇、高密度脂蛋白胆固醇、以及ApoB方面,不同水平的TyG分组间存在显著统计学差异。并且,高水平TyG组的MACE的发生率要高于低水平组的。

Table 1. Baseline characteristics of participants grouped according to TyG level

1. 根据TyG水平分组的参与者的基线特征

TyG水平

Total

≤1.11

1.12~1.68

≥1.69

P

基线特征

年龄(岁)

59.59 ± 11.34

62.16 ± 10.22

60.31 ± 11.53

56.30 ± 11.47

<0.001

性别

0.208

女性

263 (36.9%)

95 (39.9%)

91 (38.4%)

77 (32.5%)

男性

449 (63.1%)

143 (60.1%)

146 (61.6%)

160 (67.5%)

糖尿病史

<0.001

166 (23.3%)

19 (8%)

50 (21.1%)

97 (40.9%)

546 (76.7%)

219 (92%)

187 (78.9%)

140 (59.1%)

高血压病史

0.458

403 (56.6%)

127 (53.4%)

137 (57.8%)

139 (58.6%)

309 (43.4%)

111 (46.6%)

100 (42.2%)

98 (41.4%)

吸烟史

0.361

361 (50.7%)

128 (53.8%)

121 (51.1%)

112 (47.3%)

351 (49.3%)

110 (46.2%)

116 (48.9%)

125 (52.7%)

是否超重

0.591

475 (66.7%)

131 (55%)

169 (71.3%)

175 (73.8%)

237 (33.3%)

107 (45%)

68 (28.7%)

62 (26.2%)

脂质指标

TC (mmol/L)

4.72 ± 1.18

4.44 ± 1.21

4.70 ± 1.06

5.02 ± 1.20

<0.001

TG (mmol/L)

1.80 ± 1.57

0.90 ± 0.25

1.47 ± 0.39

3.04 ± 2.18

<0.001

HDL-C (mmol/L)

1.14 ± 0.26

1.22 ± 0.26

1.13 ± 0.25

1.07 ± 0.26

<0.001

Lp(a) (mg/L)

241.009 ± 248.87

255.45 ± 251.65

268.66 ± 274.32

199.10 ± 212.15

0.001

LDL-C (mmol/L)

2.85 ± 0.93

2.66 ± 0.99

2.91 ± 0.87

2.96 ± 0.91

<0.001

ApoB (g/L)

0.95 ± 0.27

0.86 ± 0.27

0.96 ± 0.24

1.04 ± 0.27

<0.001

MACE

0.134

153 (21.5%)

44 (18.5%)

48 (20.3%)

61 (25.7%)

559 (78.5%)

194 (81.5%)

189 (79.7%)

176 (74.3%)

数据以平均值 ± 标准差、百分率表示。TyG水平分为低水平组(≤1.11)、中水平组(1.12~1.68)、高水平组(≥1.69)。BMI为体重指数(kg/m2)。

3.2. TyG、TG/HDL-C指数对急性心肌梗死患者心血管残余风险的预测价值

ROC曲线显示,TyG指数曲线下面积0.554 (95%CI: 0.503~0.604, P = 0.042),TG/HDL-C曲线下面积为0.501 (95%CI: 0.450~0.552, P = 0.975) (图1)。TyG水平对急性心肌梗死后发生不良心血管事件具有一定的预测价值,且有统计学差异。TG/HDL-C对发生不良心血管事件的预测能力不如TyG。

Figure 1. ROC curves of TyG, TG/HDL-C for predicting residual risk after infarction

1. TyG、TG/HDL-C预测心梗后残余风险的ROC曲线

3.3. 基线风险模型加入TyG指数后对预测心肌梗死后心血管不良事件的增量效应

在急性心肌梗死患者残余风险分析中,构建基线风险模型和基线风险模型加上LDL-C、TyG对心肌梗死后残余风险的预测能力(表2))。在纳入研究的患者中,通过在基线风险模型中纳入LDL-C以及TyG指数,观察到基线风险模型的预测能力都有所改善(表2)。纳入LDL-C的净重新分类指数[NRI]:0.3218,P < 0.001;纳入LDL-C的综合判别改善指数[IDI]:0.0263,P < 0.001;纳入TyG的净重新分类指数[NRI]:0.2169,P = 0.017;纳入TyG的综合判别改善指数[IDI]:0.0082,P = 0.022,在基线风险模型中纳入TyG对基线模型对MACE的预测能力有增量效应(表2)。

Table 2. Incremental effect of the addition of the TyG index to the baseline risk model for predicting adverse cardiovascular events after myocardial infarction

2. 基线风险模型加入TyG指数后对预测心肌梗死后心血管不良事件的增量效应

NRI (95%CI)

P-value

IDI (95%CI)

P-value

Baseline Model

Ref

Ref

+LDL-C

0.3218 (0.1445~0.499)

<0.001

0.0263 (0.0119~0.0406)

<0.001

+TyG index

0.2169(0.0388~0.395)

0.017

0.0082 (0.0012~0.0152)

0.022

4. 讨论

通过本研究得出TyG对急性心肌梗死患者残余风险具有一定的预测能力;对于传统风险模型来说,纳入TyG对模型是有增量效应的。甘油三酯–葡萄糖(TyG)指数是一个来自空腹血糖和甘油三酯水平的参数,已被提议作为胰岛素抵抗的令人信服的指标。观察性研究表明,在一般人群中,较高的TyG指数与ASCVD的患病率相关[17]-[19]。越来越多的队列研究发现基线TyG指数水平与普通人群中ASCVD发病率有关[10]-[16]。可能的解释是胰岛素抵抗可能直接导致内皮功能障碍,导致动脉硬化以及小血管的病变,这是动脉粥样硬化发生和发展的关键病理生理过程[20]。TyG指数对检测胰岛素抵抗具有高度敏感性(96.5%)和特异性(85.0%) [21]。然而,TyG与心血管残余风险之间的关系还需要进一步的研究来确定在传统风险模型中加入TyG指数是否可以提高对残余风险的预测效能。本研究发现TyG对心血管残余风险有一定的预测能力,在积极降低低密度脂蛋白、甘油三酯以及胆固醇等脂质指标的条件下,仍需控制TyG水平来进一步降低残余风险。

尽管具有上述优势和潜在的临床意义,但本研究仍存在一些局限性。首先本研究是回顾性队列研究,并不能完全说明TyG与心血管残余风险之间的关系;其次本研究只测量了基线TyG水平,在随访期间并没有进一步采集;最后除了传统危险因素,还可能存在如遗传因素、生活方式等混杂因素未被纳入,这些因素同样可能影响残余风险。

综上所述,TyG指数对心肌梗死后残余风险的发生有一定的预测价值,有望指导急性心梗患者的进一步强化治疗。

声 明

该研究已获得纳入研究患者的知情同意。

NOTES

*通讯作者。

参考文献

[1] Virani, S.S., Alonso, A., Benjamin, E.J., et al. (2020) Heart Disease and Stroke Statistics—2020 Update: A Report from the American Heart Association. Circulation, 141, e139-e596.
[2] Choi, S. (2019) The Potential Role of Biomarkers Associated with ASCVD Risk: Risk-Enhancing Biomarkers. Journal of Lipid and Atherosclerosis, 8, 173-182.
https://doi.org/10.12997/jla.2019.8.2.173
[3] Rosenblit, P.D. (2019) Extreme Atherosclerotic Cardiovascular Disease (ASCVD) Risk Recognition. Current Diabetes Reports, 19, Article No. 61.
https://doi.org/10.1007/s11892-019-1178-6
[4] Cannon, C.P., Blazing, M.A., Giugliano, R.P., McCagg, A., White, J.A., Theroux, P., et al. (2015) Ezetimibe Added to Statin Therapy after Acute Coronary Syndromes. New England Journal of Medicine, 372, 2387-2397.
https://doi.org/10.1056/nejmoa1410489
[5] Sabatine, M.S., Giugliano, R.P., Keech, A.C., Honarpour, N., Wiviott, S.D., Murphy, S.A., et al. (2017) Evolocumab and Clinical Outcomes in Patients with Cardiovascular Disease. New England Journal of Medicine, 376, 1713-1722.
https://doi.org/10.1056/nejmoa1615664
[6] Di Pino, A. and DeFronzo, R.A. (2019) Insulin Resistance and Atherosclerosis: Implications for Insulin-Sensitizing Agents. Endocrine Reviews, 40, 1447-1467.
https://doi.org/10.1210/er.2018-00141
[7] Beverly, J.K. and Budoff, M.J. (2019) Atherosclerosis: Pathophysiology of Insulin Resistance, Hyperglycemia, Hyperlipidemia, and Inflammation. Journal of Diabetes, 12, 102-104.
https://doi.org/10.1111/1753-0407.12970
[8] Bornfeldt, K.E. and Tabas, I. (2011) Insulin Resistance, Hyperglycemia, and Atherosclerosis. Cell Metabolism, 14, 575-585.
https://doi.org/10.1016/j.cmet.2011.07.015
[9] Khan, S.H., Sobia, F., Niazi, N.K., Manzoor, S.M., Fazal, N. and Ahmad, F. (2018) Metabolic Clustering of Risk Factors: Evaluation of Triglyceride-Glucose Index (TyG Index) for Evaluation of Insulin Resistance. Diabetology & Metabolic Syndrome, 10, Article No. 74.
https://doi.org/10.1186/s13098-018-0376-8
[10] Li, S., Guo, B., Chen, H., Shi, Z., Li, Y., Tian, Q., et al. (2019) The Role of the Triglyceride (Triacylglycerol) Glucose Index in the Development of Cardiovascular Events: A Retrospective Cohort Analysis. Scientific Reports, 9, Article No. 7320.
https://doi.org/10.1038/s41598-019-43776-5
[11] Sánchez-Íñigo, L., Navarro-González, D., Fernández-Montero, A., Pastrana-Delgado, J. and Martínez, J.A. (2016) The Tyg Index May Predict the Development of Cardiovascular Events. European Journal of Clinical Investigation, 46, 189-197.
https://doi.org/10.1111/eci.12583
[12] Su, W., Chen, S., Huang, Y., Huang, J., Wu, P., Hsu, W., et al. (2019) Comparison of the Effects of Fasting Glucose, Hemoglobin A1c, and Triglyceride-Glucose Index on Cardiovascular Events in Type 2 Diabetes Mellitus. Nutrients, 11, Article 2838.
https://doi.org/10.3390/nu11112838
[13] Barzegar, N., Tohidi, M., Hasheminia, M., Azizi, F. and Hadaegh, F. (2020) The Impact of Triglyceride-Glucose Index on Incident Cardiovascular Events during 16 Years of Follow-Up: Tehran Lipid and Glucose Study. Cardiovascular Diabetology, 19, Article No. 155.
https://doi.org/10.1186/s12933-020-01121-5
[14] Hong, S., Han, K. and Park, C. (2020) The Triglyceride Glucose Index Is a Simple and Low-Cost Marker Associated with Atherosclerotic Cardiovascular Disease: A Population-Based Study. BMC Medicine, 18, Article No. 361.
https://doi.org/10.1186/s12916-020-01824-2
[15] Park, B., Lee, Y., Lee, H.S. and Jung, D. (2020) The Triglyceride-Glucose Index Predicts Ischemic Heart Disease Risk in Koreans: A Prospective Study Using National Health Insurance Service Data. Cardiovascular Diabetology, 19, Article No. 210.
https://doi.org/10.1186/s12933-020-01186-2
[16] Tian, X., Zuo, Y., Chen, S., Liu, Q., Tao, B., Wu, S., et al. (2021) Triglyceride-Glucose Index Is Associated with the Risk of Myocardial Infarction: An 11-Year Prospective Study in the Kailuan Cohort. Cardiovascular Diabetology, 20, Article No. 19.
https://doi.org/10.1186/s12933-020-01210-5
[17] Alizargar, J., Bai, C., Hsieh, N. and Wu, S.V. (2020) Use of the Triglyceride-Glucose Index (TyG) in Cardiovascular Disease Patients. Cardiovascular Diabetology, 19, Article No. 8.
https://doi.org/10.1186/s12933-019-0982-2
[18] Lee, E.Y., Yang, H.K., Lee, J., Kang, B., Yang, Y., Lee, S., et al. (2016) Triglyceride Glucose Index, a Marker of Insulin Resistance, Is Associated with Coronary Artery Stenosis in Asymptomatic Subjects with Type 2 Diabetes. Lipids in Health and Disease, 15, Article No. 155.
https://doi.org/10.1186/s12944-016-0324-2
[19] Shi, W., Xing, L., Jing, L., Tian, Y., Yan, H., Sun, Q., et al. (2020) Value of Triglyceride-Glucose Index for the Estimation of Ischemic Stroke Risk: Insights from a General Population. Nutrition, Metabolism and Cardiovascular Diseases, 30, 245-253.
https://doi.org/10.1016/j.numecd.2019.09.015
[20] Wheatcroft, S.B., Williams, I.L., Shah, A.M. and Kearney, M.T. (2003) Pathophysiological Implications of Insulin Resistance on Vascular Endothelial Function. Diabetic Medicine, 20, 255-268.
https://doi.org/10.1046/j.1464-5491.2003.00869.x
[21] Guerrero-Romero, F., Simental-Mendía, L.E., González-Ortiz, M., Martínez-Abundis, E., Ramos-Zavala, M.G., Hernández-González, S.O., et al. (2010) The Product of Triglycerides and Glucose, a Simple Measure of Insulin Sensitivity. Comparison with the Euglycemic-Hyperinsulinemic Clamp. The Journal of Clinical Endocrinology & Metabolism, 95, 3347-3351.
https://doi.org/10.1210/jc.2010-0288