TyG、SII与急性冠脉综合征患者冠脉狭窄程度的相关性分析
Correlation Analysis of TyG, SII and the Degree of Coronary Artery Stenosis in Patients with Acute Coronary Syndrome
摘要: 目的:探讨ACS患者TyG、SII与冠状动脉狭窄程度的关系,从而为预测ACS患者冠脉狭窄程度提供一定参考价值。方法:纳入2022年2月~2024年2月于安徽某三甲医院接受冠脉造影发现冠脉狭窄的ACS患者200例,根据Gensini评分进行分组,分为冠脉轻度狭窄组(<60分,n = 65)、冠脉中度狭窄组(60~90分,n = 67)、冠脉重度狭窄组(>90分,n = 68);另选取同期行冠脉造影未见狭窄的100例ACS患者作为对照。收集患者性别、年龄、BMI、血小板计数、淋巴细胞计数、中性粒细胞计数、空腹血糖、血脂、超敏肌钙蛋白、射血分数等指标。比较狭窄组与对照组的数据资料。采用Spearman相关性分析探究SII、TyG与冠状动脉病变程度的相关性。绘制受试者工作特征(Receiver operating characteristic, ROC)曲线分析TyG、SII对冠状动脉病变程度的预测价值。结果:1. ACS患者FBG、TC、TG、LC、NC、PLT、hs-cTnI高于对照患者,差异有统计学意义(P < 0.05)。2. 冠脉狭窄组SII和TyG高于对照组,差异有统计学意义(P < 0.05)。3. SII与冠状动脉中度狭窄的相关性(r = 0.310, P < 0.05),SII与重度冠脉狭窄的相关性(r = 0.288, P < 0.01);TyG指数与中度冠状动脉狭窄程度的相关性(r = 0.379, P < 0.001);TyG指数与重度冠脉狭窄的相关性(r = 0.579, P < 0.017)。4. SII、TyG指数预测冠状动脉狭窄程度的ROC曲线下面积(AUC)分别为0.770、0.791。95%CI:(0.739, 0.844)、(0.717, 0.823)灵敏度分别为0.595、0.655,特异度分别为0.83、0.84,预测冠状动脉狭窄的截断值分别为655.67、1.772。SII联合TyG的ROC曲线下面积为0.833。95%CI:(0.788, 0.877),灵敏度为0.665,特异度为0.900。结论:SII和TyG可作为预测冠状动脉狭窄的指标,两者联合预测价值更高。
Abstract: Objective: This study aims to explore the association between the Triglyceride-Glucose Index (TyG), Systemic Immune-Inflammation Index (SII), and the extent of coronary artery stenosis in individuals diagnosed with acute coronary syndrome (ACS). Methods: A total of 200 ACS patients with coronary artery stenosis confirmed by coronary angiography at a tertiary hospital in Anhui Province from February 2022 to February 2024 were enrolled. They were divided into three groups based on Gensini scores: mild stenosis group (<60 points, n = 65), moderate stenosis group (60~90 points, n = 67), and severe stenosis group (>90 points, n = 68). Additionally, 100 ACS Individuals who underwent coronary angiography during the same timeframe and showed no evidence of stenosis were designated as the control group. Data on gender, age, BMI, platelet count, lymphocyte count, neutrophil count, fasting blood glucose, blood lipids, high-sensitivity troponin, and ejection fraction were collected. A comparative analysis was conducted between the stenosis group and the control group. To assess the association between SII, TyG, and the extent of coronary artery disease, Spearman correlation analysis was employed. Additionally, receiver operating characteristic (ROC) curves were constructed to evaluate the predictive performance of TyG and SII in determining the severity of coronary artery disease. Results: 1. The levels of FBG, TC, TG, LC, NC, PLT, and hs-cTnI were significantly higher in patients with coronary artery stenosis compared to the control group, with statistically significant differences (P < 0.05). 2. The levels of SII and TyG were markedly elevated in the coronary stenosis group compared to the control group, with the differences reaching statistical significance (P < 0.05). 3. SII showed a correlation with moderate coronary stenosis (r = 0.310, P < 0.05) and severe coronary stenosis (r = 0.288, P < 0.01). TyG index was correlated with moderate coronary stenosis (r = 0.379, P < 0.001) and severe coronary stenosis (r = 0.579, P < 0.017). 4. The areas under the ROC curve (AUC) for SII and TyG in predicting multi-vessel coronary disease were 0.770 and 0.791, respectively. The 95% confidence intervals (CI) were (0.739, 0.844) and (0.717, 0.823), with sensitivities of 0.595 and 0.655, and specificities of 0.83 and 0.84, respectively. The cutoff values for predicting coronary stenosis were 655.67 and 1.772, respectively. The AUC for the combination of SII and TyG was 0.833, with a 95% CI of (0.788, 0.877), a sensitivity of 0.665, and a specificity of 0.900. Conclusion: 1. SII and TyG index are positively correlated with the degree of coronary artery stenosis. 2. SII and TyG can serve as indicators for predicting coronary artery stenosis, and their combined use has higher predictive value.
文章引用:李毛毛, 李洁华. TyG、SII与急性冠脉综合征患者冠脉狭窄程度的相关性分析[J]. 临床医学进展, 2025, 15(4): 3563-3570. https://doi.org/10.12677/acm.2025.1541329

参考文献

[1] Vaduganathan, M., Mensah, G.A., Turco, J.V., Fuster, V. and Roth, G.A. (2022) The Global Burden of Cardiovascular Diseases and Risk: A Compass for Future Health. Journal of the American College of Cardiology, 80, 2361-2371. [Google Scholar] [CrossRef] [PubMed]
[2] Björkegren, J.L.M. and Lusis, A.J. (2022) Atherosclerosis: Recent Developments. Cell, 185, 1630-1645. [Google Scholar] [CrossRef] [PubMed]
[3] Libby, P. and Hansson, G.K. (2019) From Focal Lipid Storage to Systemic Inflammation. Journal of the American College of Cardiology, 74, 1594-1607. [Google Scholar] [CrossRef] [PubMed]
[4] Wang, H., Huang, Z., Wang, J., Yue, S., Hou, Y., Ren, R., et al. (2024) Predictive Value of System Immune-Inflammation Index for the Severity of Coronary Stenosis in Patients with Coronary Heart Disease and Diabetes Mellitus. Scientific Reports, 14, Article No. 31370. [Google Scholar] [CrossRef] [PubMed]
[5] Pant, S., Deshmukh, A., GuruMurthy, G.S., Pothineni, N.V., Watts, T.E., Romeo, F., et al. (2013) Inflammation and Atherosclerosis—Revisited. Journal of Cardiovascular Pharmacology and Therapeutics, 19, 170-178. [Google Scholar] [CrossRef] [PubMed]
[6] Lee, J., Kim, B., Kim, W., Ahn, C., Choi, H.Y., Kim, J.G., et al. (2021) Lipid Indices as Simple and Clinically Useful Surrogate Markers for Insulin Resistance in the U.S. Population. Scientific Reports, 11, Article No. 2366. [Google Scholar] [CrossRef] [PubMed]
[7] Bornfeldt, K.E. and Tabas, I. (2011) Insulin Resistance, Hyperglycemia, and Atherosclerosis. Cell Metabolism, 14, 575-585. [Google Scholar] [CrossRef] [PubMed]
[8] Ding, X., Wang, X., Wu, J., Zhang, M. and Cui, M. (2021) Triglyceride-Glucose Index and the Incidence of Atherosclerotic Cardiovascular Diseases: A Meta-Analysis of Cohort Studies. Cardiovascular Diabetology, 20, Article No. 76. [Google Scholar] [CrossRef] [PubMed]
[9] 盛春梅, 陈厚良, 程小兵. Gensini评分、全身炎症指数对急性心肌梗死患者死亡事件的预测价值[J]. 中国急救复苏与灾害医学杂志, 2024, 19(5): 569-572, 615.
[10] Wang, L., Cong, H., Zhang, J., Hu, Y., Wei, A., Zhang, Y., et al. (2020) Triglyceride-Glucose Index Predicts Adverse Cardiovascular Events in Patients with Diabetes and Acute Coronary Syndrome. Cardiovascular Diabetology, 19, Article No. 80. [Google Scholar] [CrossRef] [PubMed]
[11] Liang, S., Wang, C., Zhang, J., Liu, Z., Bai, Y., Chen, Z., et al. (2023) Triglyceride-Glucose Index and Coronary Artery Disease: A Systematic Review and Meta-Analysis of Risk, Severity, and Prognosis. Cardiovascular Diabetology, 22, Article No. 170. [Google Scholar] [CrossRef] [PubMed]
[12] Yang, X., Li, K., Wen, J., Yang, C., Li, Y., Xu, G., et al. (2024) Association of the Triglyceride Glucose-Body Mass Index with the Extent of Coronary Artery Disease in Patients with Acute Coronary Syndromes. Cardiovascular Diabetology, 23, Article No. 24. [Google Scholar] [CrossRef] [PubMed]
[13] Wang, H., Liu, Z., Shao, J., Lin, L., Jiang, M., Wang, L., et al. (2020) Immune and Inflammation in Acute Coronary Syndrome: Molecular Mechanisms and Therapeutic Implications. Journal of Immunology Research, 2020, Article ID: 4904217. [Google Scholar] [CrossRef] [PubMed]
[14] Kim, J.H., Lim, S., Park, K.S., Jang, H.C. and Choi, S.H. (2017) Total and Differential WBC Counts Are Related with Coronary Artery Atherosclerosis and Increase the Risk for Cardiovascular Disease in Koreans. PLOS ONE, 12, e0180332. [Google Scholar] [CrossRef] [PubMed]
[15] Guo, J., Huang, Y., Pang, L., Zhou, Y., Yuan, J., Zhou, B., et al. (2024) Association of Systemic Inflammatory Response Index with ST Segment Elevation Myocardial Infarction and Degree of Coronary Stenosis: A Cross-Sectional Study. BMC Cardiovascular Disorders, 24, Article No. 98. [Google Scholar] [CrossRef] [PubMed]