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European Journal of Medical Research
Published in: European Journal of Medical Research 1/2023

Open Access 01-12-2023 | Arterial Diseases | Research

Association of triglyceride–glucose index with coronary severity and mortality in patients on dialysis with coronary artery disease

Authors: Enmin Xie, Zixiang Ye, Yaxin Wu, Xuecheng Zhao, Yike Li, Nan Shen, Xiaochun Guo, Yanxiang Gao, Jingang Zheng

Published in: European Journal of Medical Research | Issue 1/2023

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Abstract

Background

The triglyceride–glucose (TyG) index is validated as a reliable biomarker of insulin resistance and an independent predictor of cardiovascular prognosis. However, the prognostic value of the TyG index in patients on dialysis with coronary artery disease (CAD) remained unexplored. This study aimed to determine the association between the TyG index and CAD severity and mortality in these patients.

Methods

A total of 1061 dialysis patients with CAD were enrolled in this multi-center cohort study from January 2015 to June 2021. The extent and severity of CAD were evaluated using the multivessel disease and Gensini score (GS). Patients were followed up for all-cause death and cardiovascular death.

Results

The multivariable logistic regression model indicated that the TyG index was significantly associated with multivessel disease (odds ratio [OR] 1.51, 95% confidence interval [CI] 1.18–1.94, P = 0.001), and high GS (OR 1.33, 95% CI 1.10–1.61, P = 0.003). After adjusting for baseline risk factors, the hazards of all-cause death and cardiovascular death were 1.23 (95% CI 1.06–1.43, P = 0.007), and 1.33 (95% CI 1.11–1.59, P = 0.002), independent of CAD severity. Restricted cubic spline analysis identified a dose–response association between the TyG index and both CAD severity and mortality (all P for nonlinearity > 0.05). When modeling the TyG index as a categorical variable, these independent associations remained. Subgroup analyses did not substantially modify the results. Furthermore, incorporating the TyG index into the existing risk prediction model improved the predictive accuracy for all-cause death and cardiovascular death, as evaluated by C-statistic, continuous net reclassification improvement, and integrated discrimination improvement.

Conclusions

In patients on dialysis with CAD, the TyG index was significantly associated with more severe CAD as well as mortality. These results highlight the clinical importance of the TyG index for assessing CAD severity and risk stratification in patients on dialysis with CAD.
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Literature
1.
Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, et al. Heart disease and stroke statistics-2020 update: a report from the American Heart Association. Circulation. 2020;141:e139-596.PubMed
2.
Lai AC, Bienstock SW, Sharma R, Skorecki K, Beerkens F, Samtani R, et al. A personalized approach to chronic kidney disease and cardiovascular disease: JACC review topic of the week. J Am Coll Cardiol. 2021;77:1470–9.PubMed
3.
Bello AK, Okpechi IG, Osman MA, Cho Y, Htay H, Jha V, et al. Epidemiology of haemodialysis outcomes. Nat Rev Nephrol. 2022;18:378–95.PubMedPubMedCentral
4.
Herzog CA, Littrell K, Arko C, Frederick PD, Blaney M. Clinical characteristics of dialysis patients with acute myocardial infarction in the United States: a collaborative project of the United States Renal Data System and the National Registry of Myocardial Infarction. Circulation. 2007;116:1465–72.PubMed
5.
Fox CS, Muntner P, Chen AY, Alexander KP, Roe MT, Cannon CP, et al. Use of evidence-based therapies in short-term outcomes of ST-segment elevation myocardial infarction and non-ST-segment elevation myocardial infarction in patients with chronic kidney disease: a report from the National Cardiovascular Data Acute Coronary Treatment and Intervention Outcomes Network registry. Circulation. 2010;121:357–65.PubMedPubMedCentral
6.
Wanner C, Amann K, Shoji T. The heart and vascular system in dialysis. Lancet. 2016;388:276–84.PubMed
7.
Kalantar-Zadeh K, Block G, Humphreys MH, Kopple JD. Reverse epidemiology of cardiovascular risk factors in maintenance dialysis patients. Kidney Int. 2003;63:793–808.PubMed
8.
Malatino LS, Benedetto FA, Mallamaci F, Tripepi G, Zoccali C, Parlongo S, et al. Smoking, blood pressure and serum albumin are major determinants of carotid atherosclerosis in dialysis patients. CREED Investigators. Cardiovascular Risk Extended Evaluation in Dialysis patients. J Nephrol. 1999;12:256–60.PubMed
9.
Reiss AB, Voloshyna I, De Leon J, Miyawaki N, Mattana J. Cholesterol metabolism in CKD. Am J Kidney Dis. 2015;66:1071–82.PubMedPubMedCentral
10.
Shroff R, Speer T, Colin S, Charakida M, Zewinger S, Staels B, et al. HDL in children with CKD promotes endothelial dysfunction and an abnormal vascular phenotype. J Am Soc Nephrol. 2014;25:2658–68.PubMedPubMedCentral
11.
Zanoli L, Lentini P, Briet M, Castellino P, House AA, London GM, et al. Arterial stiffness in the heart disease of CKD. J Am Soc Nephrol. 2019;30:918–28.PubMedPubMedCentral
12.
Zoccali C, Bode-Böger S, Mallamaci F, Benedetto F, Tripepi G, Malatino L, et al. Plasma concentration of asymmetrical dimethylarginine and mortality in patients with end-stage renal disease: a prospective study. Lancet. 2001;358:2113–7.PubMed
13.
Zoccali C, Mallamaci F, Maas R, Benedetto FA, Tripepi G, Malatino LS, et al. Left ventricular hypertrophy, cardiac remodeling and asymmetric dimethylarginine (ADMA) in hemodialysis patients. Kidney Int. 2002;62:339–45.PubMed
14.
Testa A, Spoto B, Tripepi G, Mallamaci F, Malatino L, Fatuzzo P, et al. The GLU298ASP variant of nitric oxide synthase interacts with asymmetric dimethyl arginine in determining cardiovascular mortality in patients with end-stage renal disease. J Hypertens. 2005;23:1825–30.PubMed
15.
Krediet RT, Balafa O. Cardiovascular risk in the peritoneal dialysis patient. Nat Rev Nephrol. 2010;6:451–60.PubMed
16.
Bernardo AP, Oliveira JC, Santos O, Carvalho MJ, Cabrita A, Rodrigues A. Insulin resistance in nondiabetic peritoneal dialysis patients: associations with body composition, peritoneal transport, and peritoneal glucose absorption. Clin J Am Soc Nephrol. 2015;10:2205–12.PubMedPubMedCentral
17.
Nishimura M, Tsukamoto K, Tamaki N, Kikuchi K, Iwamoto N, Ono T. Risk stratification for cardiac death in hemodialysis patients without obstructive coronary artery disease. Kidney Int. 2011;79:363–71.PubMed
18.
Radcliffe NJ, Seah J-M, Clarke M, MacIsaac RJ, Jerums G, Ekinci EI. Clinical predictive factors in diabetic kidney disease progression. J Diabetes Investig. 2017;8:6–18.PubMed
19.
Nakashima A, Kato K, Ohkido I, Yokoo T. Role and treatment of insulin resistance in patients with chronic kidney disease: a review. Nutrients. 2021;13:4349.PubMedPubMedCentral
20.
Mancusi C, de Simone G, Best LG, Wang W, Zhang Y, Roman MJ, et al. Myocardial mechano-energetic efficiency and insulin resistance in non-diabetic members of the Strong Heart Study cohort. Cardiovasc Diabetol. 2019;18:56.PubMedPubMedCentral
21.
Hill MA, Yang Y, Zhang L, Sun Z, Jia G, Parrish AR, et al. Insulin resistance, cardiovascular stiffening and cardiovascular disease. Metabolism. 2021;119:154766.PubMed
22.
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. Metab Syndr Relat Disord. 2008;6:299–304.PubMed
23.
Demirci I, Haymana C, Candemir B, Meric C, Yuksel B, Eser M, et al. Triglyceride-glucose index levels in patients with congenital hypogonadotropic hypogonadism and the relationship with endothelial dysfunction and insulin resistance. Endokrynol Pol. 2021;72:232–7.PubMed
24.
Jiang Z-Z, Zhu J-B, Shen H-L, Zhao S-S, Tang Y-Y, Tang S-Q, et al. A high triglyceride-glucose index value is associated with an increased risk of carotid plaque burden in subjects with prediabetes and new-onset type 2 diabetes: a real-world study. Front Cardiovasc Med. 2022;9:832491.PubMedPubMedCentral
25.
Mao Q, Zhou D, Li Y, Wang Y, Xu S-C, Zhao X-H. The triglyceride-glucose index predicts coronary artery disease severity and cardiovascular outcomes in patients with non-ST-segment elevation acute coronary syndrome. Dis Markers. 2019;2019:6891537.PubMedPubMedCentral
26.
Zhao J, Fan H, Wang T, Yu B, Mao S, Wang X, et al. TyG index is positively associated with risk of CHD and coronary atherosclerosis severity among NAFLD patients. Cardiovasc Diabetol. 2022;21:123.PubMedPubMedCentral
27.
Xiong S, Chen Q, Long Y, Su H, Luo Y, Liu H, et al. Association of the triglyceride-glucose index with coronary artery disease complexity in patients with acute coronary syndrome. Cardiovasc Diabetol. 2023;22:56.PubMedPubMedCentral
28.
Zhang Y, Ding X, Hua B, Liu Q, Gao H, Chen H, et al. High triglyceride-glucose index is associated with adverse cardiovascular outcomes in patients with acute myocardial infarction. Nutr Metab Cardiovasc Dis. 2020;30:2351–62.PubMed
29.
Wu Z, Liu L, Wang W, Cui H, Zhang Y, Xu J, et al. Triglyceride-glucose index in the prediction of adverse cardiovascular events in patients with premature coronary artery disease: a retrospective cohort study. Cardiovasc Diabetol. 2022;21:142.PubMedPubMedCentral
30.
Hu C, Zhang J, Liu J, Liu Y, Gao A, Zhu Y, et al. Discordance between the triglyceride glucose index and fasting plasma glucose or HbA1C in patients with acute coronary syndrome undergoing percutaneous coronary intervention predicts cardiovascular events: a cohort study from China. Cardiovasc Diabetol. 2020;19:116.PubMedPubMedCentral
31.
Gensini GG. A more meaningful scoring system for determining the severity of coronary heart disease. Am J Cardiol. 1983;51:606.PubMed
32.
Zoccali C, Benedetto FA, Maas R, Mallamaci F, Tripepi G, Salvatore Malatino L, et al. Asymmetric dimethylarginine, C-reactive protein, and carotid intima-media thickness in end-stage renal disease. J Am Soc Nephrol. 2002;13:490–6.PubMed
33.
Tripepi G, Mattace Raso F, Sijbrands E, Seck MS, Maas R, Boger R, et al. Inflammation and asymmetric dimethylarginine for predicting death and cardiovascular events in ESRD patients. Clin J Am Soc Nephrol. 2011;6:1714–21.PubMed
34.
Reaven G. Insulin resistance and coronary heart disease in nondiabetic individuals. Arterioscler Thromb Vasc Biol. 2012;32:1754–9.PubMed
35.
Nerpin E, Risérus U, Ingelsson E, Sundström J, Jobs M, Larsson A, et al. Insulin sensitivity measured with euglycemic clamp is independently associated with glomerular filtration rate in a community-based cohort. Diabetes Care. 2008;31:1550–5.PubMedPubMedCentral
36.
Dave N, Wu J, Thomas S. Chronic kidney disease-induced insulin resistance: current state of the field. Curr Diab Rep. 2018;18:44.PubMed
37.
Nishikawa T, Kukidome D, Sonoda K, Fujisawa K, Matsuhisa T, Motoshima H, et al. Impact of mitochondrial ROS production in the pathogenesis of insulin resistance. Diabetes Res Clin Pract. 2007;77(Suppl 1):S161-164.PubMed
38.
Yang Q, Vijayakumar A, Kahn BB. Metabolites as regulators of insulin sensitivity and metabolism. Nat Rev Mol Cell Biol. 2018;19:654–72.PubMedPubMedCentral
39.
Tao L-C, Xu J, Wang T, Hua F, Li J-J. Triglyceride-glucose index as a marker in cardiovascular diseases: landscape and limitations. Cardiovasc Diabetol. 2022;21:68.PubMedPubMedCentral
40.
Samuel VT, Shulman GI. The pathogenesis of insulin resistance: integrating signaling pathways and substrate flux. J Clin Invest. 2016;126:12–22.PubMedPubMedCentral
41.
Jia G, DeMarco VG, Sowers JR. Insulin resistance and hyperinsulinaemia in diabetic cardiomyopathy. Nat Rev Endocrinol. 2016;12:144–53.PubMed
42.
Cho Y-R, Ann SH, Won K-B, Park G-M, Kim Y-G, Yang DH, et al. Association between insulin resistance, hyperglycemia, and coronary artery disease according to the presence of diabetes. Sci Rep. 2019;9:6129.PubMedPubMedCentral
43.
Su J, Li Z, Huang M, Wang Y, Yang T, Ma M, et al. Triglyceride glucose index for the detection of the severity of coronary artery disease in different glucose metabolic states in patients with coronary heart disease: a RCSCD-TCM study in China. Cardiovasc Diabetol. 2022;21:96.PubMedPubMedCentral
44.
Wang X, Xu W, Song Q, Zhao Z, Meng X, Xia C, et al. Association between the triglyceride-glucose index and severity of coronary artery disease. Cardiovasc Diabetol. 2022;21:168.PubMedPubMedCentral
45.
Jin J-L, Cao Y-X, Wu L-G, You X-D, Guo Y-L, Wu N-Q, et al. Triglyceride glucose index for predicting cardiovascular outcomes in patients with coronary artery disease. J Thorac Dis. 2018;10:6137–46.PubMedPubMedCentral
Metadata
Title
Association of triglyceride–glucose index with coronary severity and mortality in patients on dialysis with coronary artery disease
Authors
Enmin Xie
Zixiang Ye
Yaxin Wu
Xuecheng Zhao
Yike Li
Nan Shen
Xiaochun Guo
Yanxiang Gao
Jingang Zheng
Publication date
01-12-2023
Publisher
BioMed Central
Published in
European Journal of Medical Research / Issue 1/2023
Electronic ISSN: 2047-783X
DOI
https://doi.org/10.1186/s40001-023-01410-1

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