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Triglyceride-glucose index as a marker in cardiovascular diseases: landscape and limitations
Cardiovascular Diabetology volume 21, Article number: 68 (2022)
The triglyceride-glucose (TyG) index has been identified as a reliable alternative biomarker of insulin resistance (IR). Recently, a considerable number of studies have provided robust statistical evidence suggesting that the TyG index is associated with the development and prognosis of cardiovascular disease (CVD). Nevertheless, the application of the TyG index as a marker of CVD has not systemically been evaluated, and even less information exists regarding the underlying mechanisms associated with CVD. To this end, in this review, we summarize the history of the use of the TyG index as a surrogate marker for IR. We aimed to highlight the application value of the TyG index for a variety of CVD types and to explore the potential limitations of using this index as a predictor for cardiovascular events to improve its application value for CVD and provide more extensive and precise supporting evidence.
Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide, posing serious public health challenges and placing an economic burden on patients . Although several risk factors for CVD have been established, including age, male sex, obesity, hypertension, hypercholesteraemia, and diabetes, recent studies have demonstrated that some individuals without these risk factors may also develop CVD [2, 3]. Additionally, despite the development of advanced techniques and the popularization of primary and secondary prevention measures, patients with CVD remain at increased risk of recurrent adverse cardiovascular events . Therefore, identifying persons at early risk for CVD will have remarkable clinical significance for improving risk stratification and therapeutic management.
Insulin resistance (IR) is a state of decreased sensitivity and responsiveness to the action of insulin and has bee identified as a hallmark of T2DM, even preceding diabetes for several years . There has been increasing evidence demonstrating that IR and related disorders contribute to the development of CVD in diabetic as well as nondiabetic subjects . It is well known that individuals with IR are predisposed to developing several metabolic disorders, such as hyperglycaemia, dyslipidaemia, and hypertension, all of which are strongly associated with poor outcomes of CVD . Thus, IR has been regarded not only as a pathogenic cause but also as a predictor of CVD in both general populations and subjects with diabetes. Therefore, developing convenient and reliable screening tools to detect IR and predict cardiovascular risks is of particular importance.
Currently, there are no specific methods for the accurate determination of IR. The gold standards of the euglycemic insulin clamp and intravenous glucose tolerance testing are invasive and expensive; although they are used in academic studies, they are not applied in clinical practice . The homeostasis model assessment-estimated insulin resistance (HOMA-IR) index, a means for detecting β-cell function and IR, is widely used at present, but it has limited value in subjects receiving insulin treatment or those who do not have functioning beta cells . To address this limitation, the triglyceride-glucose (TyG) index has been developed and was shown to be superior to HOMA-IR in assessing IR in individuals with and without diabetes . According to previous studies, this simple, convenient, and low-cost surrogate does not require insulin quantification and may be used in all subjects regardless of their insulin treatment status . Furthermore, recent studies have demonstrated that the TyG index is an independent predictor of prognosis in diabetic or nondiabetic patients with CVD, suggesting its potential clinical utility in predicting cardiovascular risk.
In this review, we systemically describe the history of the TyG index as a marker for IR. We will also discuss recently published literature that has helped to shed light on the application value of the TyG index in a variety of CVD settings, as well as its potential underlying mechanisms associated with CVD. Additionally, the limitations of the TyG index in predicting CVD are also discussed.
This systematic review examined the application value of the TyG index in a variety of CVD types. Study selection included cross-sectional, case–control, or retrospective studies involving clinical populations with different CVD phenotypes. There were no language or time restrictions for eligible studies. The electronic databases PubMed and Web of Science were used. The search terms used were “TyG index” OR “triglyceride-glucose index” AND “coronary artery disease” OR “acute coronary syndrome” OR “in-stent restenosis” OR “arterial stiffness” OR “coronary artery calcification” OR “heart failure”. Screening of the retrieved titles and/or abstracts was performed in duplicate using Endnote Software, Version X8, and eligible studies were identified. Two authors (Li-chan Tao and Jia-ni Xu) retrieved the full texts of these studies and assessed them for eligibility. Disagreements were resolved through discussion.
History of the use of the triglyceride-glucose index
The TyG index, calculated as TyG index = ln [Fasting triglyceride (mg/dl) × fasting glucose (mg/dl)]/2, is a composite indicator composed of fasting triglyceride (TG) and fasting glucose (FG) levels. It was first proposed in 2008. In a large cross-sectional study of apparently healthy individuals, the TyG index was found to be a better surrogate (sensitivity 84.0% and specificity 45.0%) to identify IR than the HOMA-IR index . However, its low specificity (45.0%) and potentially high proportion of false-positive tests has limited the widespread use of the TyG index in screening for IR. In 2010, a cross-sectional study involving 99 individuals with various degrees of body weight and glucose tolerance was performed by Guerrero-Romero et al., and they identified the TyG index as an optimal tool for the assessment of IR, showing high sensitivity (96.5%) and specificity (85.0%) compared to the gold standard, the euglycemic-hyperinsulinaemia clamp test . Furthermore, in a cross-sectional study of 82 Brazilian subjects with T2DM or normal glucose tolerance conducted in 2011, the TyG index was confirmed to be a better marker for estimating IR than the HOMA-IR index (area under the ROC curve (AUC): TyG index: 0.79, HOMA-IR index: 0.77) . However, since both studies had small sample sizes, the results were not fully convincing.
Since then, the TyG index has been proven to be a reliable and accessible index for evaluating IR in high-risk individuals by large clinical studies. IR plays a crucial role in the development of impaired glucose tolerance and diabetes mellitus (DM). In 2014, a study by Lee et al. enrolled a total of 5,354 middle-aged nondiabetic Koreans for long-term follow-up to assess diabetes status. They found that the risk of diabetes onset in the highest quartile of the TyG index was more than fourfold higher than that in the lowest quartile (relative risk, 4.095; 95% CI 2.701–6.207), suggesting that the TyG index might be a useful marker for identifying subjects at high risk of developing diabetes. In addition, this study revealed that the predictive power of the TyG index was better than that of the HOMA-IR index for evaluating IR . However, the lack of positive comparisons for diagnosing DM limited their conclusions regarding the reliability of the TyG index in predicting the occurrence of DM. Then, in 2016, a study by David et al. revealed that the TyG index had better predictive power (AUC: 0.75, 95% CI 0.7–0.81) in diagnosing subjects with DM than fasting blood glucose (FBG) measurement (AUC: 0.66, 95% CI 0.60–0.72) and TG levels (AUC: 0.71, 95% CI 0.65–0.77) among 4820 individuals . Thus, the TyG index may help to identify individuals at risk of developing DM in the future so that early interventions can be provided.
In addition to DM, IR is also a significant hallmark of obesity, hypertension, dyslipidaemia (hypertriglyceridaemia and decreased high-density lipoprotein (HDL)), as well as other metabolic syndrome (MetS) symptoms [15, 16]. These metabolism-related components have been proven to be independent risk factors for CVD [17,18,19]. As a useful surrogate of IR, the TyG index has been gradually linked to the development of CVD and poor outcomes. Using a large sample from the Vascular Metabolic CUN cohort (VMCUN cohort) with a median period of 10 years of follow-up, Laura et al. first suggested a positive association between the TyG index (AUC: 0.708, 95% CI 0.68–0.73) and CVD events, including coronary heart failure (CHD), cerebrovascular disease, and peripheral arterial disease, independent of confounding factors. Since then, the relationship between the TyG index and different types of CVD has been consecutively revealed (Fig. 1).
Stable coronary artery disease
Coronary artery disease (CAD) is one of the main causes of cardiovascular-related death. Although advanced therapeutics, including optimal drug strategies and revascularization, have effectively decreased the incidence of chest pain, patients with CAD still have an increased risk of experiencing major adverse cardiovascular events (MACEs) . Consistent clinical data have suggested that an elevated TyG index is positively associated with poor outcomes in patients with CAD. A nested case–control study enrolled 1282 T2DM patients with new-onset stable CAD and revealed that an increased TyG index was associated with an increased risk of major adverse cardiovascular and cerebral events (MACCEs) after adjusting for confounding risk factors (HR: 1.693, 95% CI 1.238–2.316). Moreover, the addition of the TyG index to a Cox model containing glycated haemoglobin (HbA1c) was found to increase the predictive value for MACCEs . A study by Jin et al. further confirmed the prognostic value of the TyG index in patients with stable CAD . In addition, a single-centre observational study conducted by Gao et al. with a relatively large number of patients revealed the value of determining the TyG index (ORs: 1.59 and 5.72 in the T2 and T3 groups compared with the first tertile group) in patients with totally occluded coronary vessels over 3 months, namely, CTO lesions. Particularly, the improvement in the AUC value for the evaluation of less developed collateralization was most significant after adding the TyG index to the baseline model , providing novel information regarding the relation of TyG to clinical outcomes in patients with CAD (see Table 1).
In addition to the association with prognosis in patients with established CAD, the TyG index has also been used to identify asymptomatic patients with a high risk of atherosclerosis. Lee et al. enrolled a total of 888 asymptomatic adults with T2DM but without previous CAD to evaluate coronary artery stenosis (CAS) by coronary computed tomographic (CT) angiography and found that a higher TyG index was associated with an increased risk of CAS, similar to old age, male sex, poor glycaemic control, a longer duration of diabetes, and no statin use. Moreover, a higher TyG index was identified as an independent risk factor for CAD (OR: 3.19, 95% CI 1.371–7.424) . A study by Thai et al. confirmed the role of the TyG index in identifying diabetic subjects at high risk of CAD in Vietnam. They found that the number of narrowed coronary arteries and the degree of coronary stenosis were also associated with a higher TyG index . Nevertheless, the current guidelines for the primary prevention of CVD indicate that asymptomatic individuals without cardiovascular risk factors (CVRFs) are not considered candidates for preventive treatments . Recently, a study by the Progression of Early Subclinical Atherosclerosis (PESA) indicated that in middle-aged populations without CVRF, the prevalence of subclinical atherosclerosis is approximately 50% ; therefore, identifying patients in this population who are at early risk for subclinical atherosclerosis is of great importance. In a retrospective observational study, Park et al. included 1250 asymptomatic Korean individuals without traditional CVRFs to evaluate coronary stenosis by coronary CT angiography. They found that the TyG index was associated with an increased risk of CAD (OR: 1.473, 95% CI 1.026–2.166), especially in patients with noncalcified and mixed plaques . These studies support the notion that the TyG index is an independent marker that can be used to predict subclinical CAD both in general populations and individuals with established risk factors.
Acute coronary syndrome (ACS)
ACS is the most severe type of ischaemic heart disease and describes a range of myocardial ischaemic conditions, including unstable angina (UA), non-ST elevated myocardial infarction (NSTEMI), and ST-elevated myocardial infarction (STEMI) . Despite the use of current guideline-recommended therapeutics, including coronary artery revascularization techniques such as percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) and optimal drug treatments, some patients with ACS remain at high risk for recurrent cardiovascular events (CVEs) . Thus, it is critical to identify ACS patients who are at a high risk of CVEs so that intense strategies can be provided. Studies have suggested that the TyG index might be a useful marker for risk stratification and for predicting the prognosis of ACS patients with or without diabetes. A retrospective cohort study enrolled a total of 2531 consecutive patients with established diabetes. These patients received coronary angiography (CAG) due to ACS and completed 3 years of clinical follow-up. The authors found that the incidence of MACEs increased along with the TyG index tertiles and that the TyG index was an independent predictor of MACEs (HR: 1.455, 95% CI 1.208–1.753) after adjusting for traditional CVRFs, irrespective of whether non-invasive or invasive treatments were administered . However, in this study, subgroup analysis showed that the prognostic value of the TyG index was only significant in patients with UAP (adjusted HR: 1.604, 95% CI 1.270–2.027). One explanation for this result may be the small sample size. Subsequently, Luo et al. included 1092 STEMI patients who underwent PCI and found that the TyG index was positively associated with an increased risk of MACCEs in STEMI patients within 1 year following PCI after adjusting for confounding factors (HR: 1.529, 95% CI 1.001–2.061) . Additionally, Mao et al. evaluated 438 patients with NSTE-ACS and followed them for 12 months after admission to assess the risk of MACEs. The results indicated that the TyG index presented strong diagnostic power for CVRFs, including glucose metabolism disorder and metabolic syndrome . Furthermore, the TyG index was found to be an independent predictor of a high SYNTAX score (OR: 6.055, 95% CI 2.915–12.579) and the occurrence of MACEs (HR: 1.878, 95% CI 1.130–3.121). These two studies supported the potential value of using the TyG index for predicting clinical outcomes in patients with different groups of ACS. However, these previous studies were carried out only with patients who had an established DM diagnosis or impaired glucose tolerance. Is the TyG index also useful for predicting the prognosis of patients without glucose metabolic disorders? As discussed above, the TyG index has been reported to be useful for the early identification of apparently healthy individuals at high risk of developing CVD. Therefore, whether the TyG index can predict the clinical outcome of ACS patients without established risk factors may be of clinical interest. In an analysis of 1655 ACS patients without diabetes and low-density lipoprotein cholesterol (LDL-C) levels less than 1.8 mmol/L, Zhang et al. found that a high TyG index level was associated with a higher incidence of AMI (21.2% vs. 15.2%), larger infarct size and higher incidence of revascularization (8.9% vs. 5.0%) compared with ACS patients with LDL-C levels below 1.8 mmol/L. Interestingly, patients with a high TyG index were prone to develop DM during follow-up, indicating that they might be more likely to develop multivessel CAD, which would be a potential contributor to the increased incidence of revascularization . The results of this study suggested that a high TyG index level might be a valid predictor for early stratification in ACS patients with relatively low risk.
In addition to obstructive ACS, an elevated TyG index is also independently associated with a poor prognosis in MI patients with nonobstructive coronary arteries (MINOCA). MINOCA is a distinct clinical entity and presents a heterogenous diagnosis of multiple causes, including plaque rupture or erosion, coronary spasm, thromboembolism, spontaneous dissection, microvascular dysfunction and supply/demand mismatch, accounting for 5–10% of all MI cases. Gao et al. recruited a total of 1179 MINOCA patients who completed a median follow-up of 41.7 months and found that the patients in the higher TyG index tertiles had an increased risk of MACEs (HR: 1.33, 95% CI 1.04–1.69) after adjusting for multivariate risk factors. Of note, the TyG index remained a robust risk factor in overall MINOCA patients or subgroups, including DM or non-DM patients and those with LDL-C levels higher or lower than 1.8 mmol/l, suggesting that the TyG was a reliable marker for predicting outcomes independent of glucose-lipid metabolic status in patients with MINOCA .
PCI is currently the most common revascularization strategy in Chinese patients with CAD, even those with diabetes. However, despite considerable improvements in outcomes due to the widespread use of drug-eluting stents, in-stent restenosis (ISR) remains one of the major challenges after PCI, occurring in 3–20% of patients [37, 38]. Therefore, the early identification of patients with a high risk of ISR may have great clinical importance. Zhu et al. retrospectively recruited 1574 patients who were admitted for ACS and underwent successful drug-eluting stent (DES)-based PCI. They found that an elevated TyG index was independently and positively associated with the occurrence of DES-ISR . However, the incremental predictive value of the TyG index for DES-ISR was slight; thus, multicentre, large-scale clinical studies are necessary to clarify the relationship between the TyG index and ISR.
Atrial stiffness (AS) is one of the earliest types of functional damage that occurs during the vascular ageing process, during which the arterial elasticity decreases and pulse pressure increases [40, 41]. Mounting evidence has suggested that AS is a powerful predictor for the future risk of CVDs such as ACS, heart failure (HF), and ischaemic or haemorrhagic stroke [42, 43]. Considering that patients with AS suffer from long-term pathological progression, there is an urgent need for reliable biomarkers to identify patients in the early stage and to develop preventive therapeutics. In an analysis of 473 postmenopausal women without diabetes, Lambrinoudaki et al. showed a positive association between the TyG index and AS by measuring brachial ankle pulse wave velocity (baPWV). Nonetheless, this study was limited by its small size, and it included only postmenopausal women . Subsequently, a Korean study enrolling 3587 healthy adults found that compared to the HOMA-IR index, the TyG index was independently associated with increased baPWV . Won et al.  and Su et al.  provided further evidence to support the predictive value of the TyG index in identifying AS among healthy Korean adults and Chinese community-dwelling elderly individuals. Furthermore, mounting evidence has revealed that elevated baPWV is associated with an increased risk of hypertension  and diabetes , which are major risk factors for AS. Thus, it is of great importance to focus on the link between the TyG index and AS in different populations. Li et al. performed a study involving a large number of hypertensive adults and revealed that there was a significant positive association between the TyG index and baPWV (OR: 1.02, 95% CI 0.83–1.20), especially in men . In contrast, Nakagomi et al. found that the association between the TyG index and increased levels of baPWV was stronger in women . This discrepancy might be due to differences in the age distribution between these two studies; the mean age of individuals in Nakagomi et al. was 38.8 years old, while it was 64.41 in the study by Li et al. Therefore, further studies are needed to examine the relationship among IR, AS, sex and age. Recently, Wu et al. added more data to support the association of the TyG index with the progression of AS in hypertensive individuals. In their study, 1895 prehypertensive and hypertensive patients were followed up for a median of 4.71 years, and their results indicated that there was a linear and positive association between the TyG index and three baPWV parameters (baPWV change, baPWV change rate and baPWV slope) in hypertensive populations rather than in prehypertensive populations . These results suggest that the interaction between IR and hypertensive status may contribute to AS development and progression; therefore, more attention should be given to IR indexes in patients with hypertension. In addition to hypertension, patients with diabetes can also develop AS. In a study involving 3185 patients with T2DM, Wang et al. showed a positive and dose–response relationship between the TyG index and AS, assessed by baPWV after adjusting for confounding factors (OR: 1.40, 95% CI 1.16–1.70). Moreover, compared to the HOMA-IR index, the TyG index was better at predicting an increased incidence of AS in T2DM patients , providing evidence to support that the TyG index can serve as a simple but reliable biomarker to evaluate AS in diabetic patients. Additionally, Guo et al. further demonstrated a positive association between the TyG index and 10-year CVD risk among a large number of patients with AS in China . The results of all these studies reflect the potential value of the TyG index in predicting AS and in providing guidance to clinicians regarding appropriate treatment strategies.
Coronary artery calcification
Coronary artery calcification (CAC), defined as an Agatston score > 0 by a multidetector CT scanner, is a sensitive marker for detecting the existence of early atherosclerosis. Additionally, CAC plays an important role in predicting adverse CVEs [55, 56]. Therefore, the identification of patients who have a high risk of CAC may have significant clinical relevance. A Korean study performed in 2016 was the first to explore the relationship between the TyG index and CAC in 4319 apparently healthy adults. The data showed that the TyG index was independently associated with the presence of CAC after adjusting for multiple risk factors (OR: 1.95, 95% CI: 1.23–3.11) . In addition, Won et al.  enrolled a large number of asymptomatic healthy adults without severe CAC at baseline and demonstrated that a high TyG index was significantly associated with CAC progression, which was defined as a difference ≥ 2.5 between the square roots of the baseline and follow-up CAC scores (Δ√ transformed CACS) . Notably, these two studies on the relationship between the TyG index and CAC were based on Korean healthy populations, which does not represent the characteristics of all patients with CAC. Thus, the significance of the TyG index for predicting CAC progression in individuals who have CAD still needs to be clarified.
Epidemiological studies have demonstrated that heart failure (HF) is a growing health burden, with a prevalence of up to 1–2% in adult populations . Recent studies have indicated that IR was the main cause for the poor prognosis of patients with HF . Thus, the identification of IR surrogate markers would play a vital role in the prevention and treatment of HF. Guo et al. showed that the TyG index was positively related to the prognosis of patients with chronic HF and DM. They revealed that the higher the TyG index is, the higher the risk of cardiovascular death or rehospitalization caused by HF . In addition to predicting the prognosis of patients with HF, the TyG index was also identified as a novel biomarker of cardiac fibrosis in these patients. The myocardial fibrosis estimated by cardiovascular magnetic resonance (CMR) can provide important prognostic information on the cardiovascular risk of HF . Yang et al. analysed 103 hospitalized HF patients and found that myocardial fibrosis could quantified by the extracellular volume (ECV) fraction using CMR. Multivariate regression linear analysis showed that the TyG index was a significant determinator for the ECV fraction (rpartial = 0.36) in patients with HF. Additionally, during a median follow-up of 12.3 months, the TyG index was identified as an independent risk factor for all-cause mortality and HF hospitalization (HR: 2.01, 95% CI 1.03–4.01), supporting the utility of the TyG index in stratification metrics during the management of HF .
Potential explanations of the TyG index as a marker for predicting cardiovascular disease
The exact mechanism underlying the relationship between the TyG index and CVD remains unknown. It is very clear that TyG is an index consisting of two risk factors for CVD, lipid-related and glucose-related factors, which are reflective of IR in the human body. Recent studies have identified the TyG index as a reliable marker of IR, which may be one of the explanations for this association . IR is a risk factor for CVD, which not only leads to the development of CVD in both the general population and patients with diabetes but also predicts the cardiovascular prognosis of patients with CVD . The potential mechanisms underlying IR and CVD are described as follows (Fig. 3).
First, IR can induce glucose metabolism imbalance, contributing to hyperglycaemia, which in turn triggers inflammation and oxidative stress. Additionally, systemic lipid disturbances have also been reported, including elevated TG, small dense LDL, and postprandial lipaemia levels and reduced high-density lipoprotein (HDL) levels, which may cause the initiation of atherosclerosis . Moreover, in established ischaemic myocardium, reduced insulin activity limits glucose bioavailability and causes a shift to fatty acid metabolism, ultimately leading to increased myocardial oxygen consumption and a reduction in the compensatory capacity of non-infarcted myocardium . These pathological metabolic disorders further aggravate CAD progression.
Second, studies have shown that IR can induce an increased production of glycosylated products and free radicals, leading to nitric oxide (NO) inactivation. The abnormal secretion of NO related to IR damages the vascular endothelium and causes endothelium-dependent vasodilation . Furthermore, IR also activates the mitochondrial electron-transport chain and induces overproduction of reactive oxidative stress (ROS), which is another cause of impaired endothelial function . The abnormal endothelial function observed in patients with diabetes extends to the coronary microcirculation and myocardial energy metabolism. In patients with cardiac ischaemia, IR is inversely associated with median colony forming unit endothelial cells, contributing to a reduced density of collaterals in response to cardiac ischaemia .
Moreover, many experimental studies have clearly established that the insulin receptor can mediate related signalling to sensitize platelets to the antiaggregating actions of prostaglandin I2 (PGI2) and NO. On the one hand, IR may contribute to platelet hyperactivity. On the other hand, it can increase adhesion-induced and thromboxane A2 (TxA2)-dependent tissue factor expression in platelets. These events have been implicated in both thrombosis and inflammation , which may partly explain the obstructive ACS or nonobstructive coronary thromboembolism observed in some patients.
In addition, previous studies have demonstrated that IR, which is usually accompanied by hyperglycaemia, induces excessive glycosylation, which can promote smooth muscle cell proliferation, collagen crosslinking, and collagen deposition. These pathological events then contribute to increased diastolic left ventricular stiffness, cardiac fibrosis and, ultimately, heart failure .
Finally, in addition to its role in hyperglycaemia, IR plays an important role in hyperlipidaemia. Studies have suggested that increased TG levels can induce elevated free fatty acid (FFA) levels and promote the increased flux of FFAs from adipose tissue to non-adipose tissue, which may accompany IR . More importantly, the retention of cholesterol-rich and TG-rich ApoB-containing remnants within the coronary wall may be considered related to the pathogenesis of atherosclerosis . Thus, lowering TG levels appears to be an additional target in patients with a high CVD risk. Additionally, activation of the renin-angiotensin system  and impaired cardiac calcium processing capacity  may also be contributors.
Limitations of the TyG index as a marker in cardiovascular diseases
The TyG index is a composite indicator composed of fasting TG and FG, which could be used as an alternative test for recognizing IR in large-scale studies or for evaluating populations at high risk of developing diabetes. Notably, several studies have suggested that the TyG index was better than the HOMA-IR index in predicting the development of atherosclerosis and poor outcomes such as the increased occurrence of carotid atherosclerosis  and CAC progression as evaluated by the CAC score . Moreover, according to previous studies, the direct qualification of serum insulin levels is expensive and is not available in most cities in developing counties; an alternative test derived from fasting TG and FBG is less costly and universally available. In addition, due to the need for quantitation, exogenous insulin may interfere with the value of the HOMA-IR index. Therefore, the current evaluation of IR by the HOMA-IR index may not be applicable to diabetic patients who are treated with insulin. Since the TyG index is a formula composed of fasting TG and FG, it does require the quantification of insulin and thus may be widely applicable in all diabetic patients treated with insulin. In summary, TyG is regarded as an accessible and reliable index for IR in individuals with a high risk of CVD, especially in developing counties.
However, there are still several observations that have failed to support the association between the TyG index and CVEs. First, the rationale for the first use of the TyG index in 2008 was that IR is a common cause of the increase in TG and glucose levels in healthy individuals . Therefore, the application of the TyG index in CVD patients can be affected by hyperlipidaemia and diabetes. To justify the value of the TyG index as a biomarker, hypertriglyceridaemia and glucose metabolic disorder should be well controlled. Nevertheless, several patients with extremely high TGs or FBSs were still enrolled in previous clinical studies, which could not explore reverse causality in the application of the TyG index in these CVD patients. For example, Laura et al. did not find an association between the TyG index and CVD in subjects with T2DM or hypertension at baseline. Their outcomes could be explained by the hypothesis that patients previously diagnosed with diabetes or hypertension were under treatment or had adopted healthier habits, so their analytical parameters might be well controlled . Cho et al. also failed to find an independent association between the TyG index and the presence of CAD or obstructive CAD in 996 patients with established diabetes after adjusting for traditional CVRFs . Unfortunately, in this study, detailed information regarding the doses used, classes of patients enrolled and eventual changes in related drugs was unavailable. Hence, the potential influence of medications taken for hyperlipidaemia, diabetes and hypertension could not be excluded in these studies. Finally, other important information, including physical activity, alcohol consumption, and family history of diseases, was also lacking in many clinical studies.
Second, medical doctors involved in clinical work usually first pay attention to FBG and TG levels when screening patients with a high risk of CVD. However, the question of how the TyG index can add to the predictive value of TG and FBG levels remains. The comparison of the predictive values between the TyG index and TG and FBG (and may be the combination) is also missing in some studies. In addition, CVD is a series of dynamic and progressive disturbances, and the development of acute diseases such as MI may lead to stress hyperglycaemia, which may affect the diagnostic or predictive value of the TyG index based on the TyG formula. In most studies, TG and FBG were examined only at baseline, regardless of their changes over time, which may lead to potential regression dilution bias. Therefore, the measurement of the TyG index at baseline alone does not reflect the longitudinal association between the TyG index and CVD risk over time. Recently, Cui et al. showed that the risk of CVD development increased along with the quartile of the cumulative TyG index (defined as the summation of average TyG index for each pair of consecutive evaluations multiplied by the time between these two consecutive visits in years), showing a multivariate-adjusted HR of 1.39 (95% CI 1.21–1.61) . These authors found that the cumulative effect of the TyG index seemed to be independent and better than the TyG index at baseline in predicting CVD. Therefore, the use of the TyG index at baseline as a biomarker to predict outcomes of CVD may be less robust. Evaluating the mean changes in the TyG index in CVD progression and follow-up is warranted in future studies.
Moreover, most studies regarding the use of TyG in CVD have been performed in middle-aged or elderly individuals, and no data are currently available concerning the value of TyG in young subjects. Dikaiakou et al. found that the TyG index showed a positive correlation with IR among both children and adolescents ; however, data regarding the predictive ability of the TyG index in identifying the presence of future CVD in these younger individuals are limited. In addition to the lack of information on different age groups, differences in the TyG index between the sexes are also still uncertain. Compared to women, men have more risk factors for metabolic diseases. For example, men are more likely to smoke and drink and have higher serum uric acid and serum homocysteine levels and a lower estimated glomerular filtration rate (eGFR) . Therefore, further sex-related studies are warranted to explore the relationship between the TyG index and CVD. Finally, dietary habits can dramatically affect TG levels. However, nutrition data are missing from most studies, so we were unable to adjust for dietary habits when evaluating the diagnostic or predictive value of the TyG index in CVD.
Overall, IR, a well-established hallmark of metabolic disorders and systemic inflammation, is not only a substantial risk factor for CVD but also contributes to a worse prognosis. Current studies have confirmed that the TyG index can be used as a reliable and convenient surrogate for IR, which may be optimized for risk stratification as well as outcome prediction for CVD. Nevertheless, based on current studies, there are some knowledge gaps that need to be addressed. First, some investigators have proposed that it would be interesting to explore whether a postprandial TyG index might have clinical significance. Because increased postprandial levels of TG and glucose are metabolically abnormal responses to IR, an elevated postprandial TyG index may be associated with a higher risk of diabetes or CVEs, which remains to be clarified. Second, regarding the predictive power of the TyG index in CVD, especially in CAD, accumulating studies have shown that the predictive value of the TyG index for CAD is mild to moderate, suggesting that it is difficult to predict severe CVEs based on the TyG index alone. Nevertheless, Wang et al. and Zhu et al. demonstrated that when introducing the TyG index into an established risk model, TyG could significantly improve the predictive accuracy for MACEs in patients with ACS [32, 39]. Thus, routinely adding the TyG index into clinical diagnostic models might help to refine cardiovascular risk stratification and enable the administration of more targeted therapeutics or prevention measures. Finally, the pathological role of the TyG index in different types of CVD still warrants further research. The potential benefits of TyG index-targeted treatments in CVD patients also require more in-depth validation.
Availability of data and materials
Sacco RL, Roth GA, Reddy KS, Arnett DK, Bonita R, Gaziano TA, Heidenreich PA, Huffman MD, Mayosi BM, Mendis S, et al. The heart of 25 by 25: achieving the goal of reducing global and regional premature deaths from cardiovascular diseases and stroke: a modeling study from the American Heart Association and World Heart Federation. Circulation. 2016;133(23):e674-690.
Rosenblit PD. Extreme atherosclerotic cardiovascular disease (ASCVD) risk recognition. Curr Diab Rep. 2019;19(8):61.
Choi S. The potential role of biomarkers associated with ASCVD risk: risk-enhancing biomarkers. J Lipid Atheroscler. 2019;8(2):173–82.
Zhao D, Liu J, Wang M, Zhang X, Zhou M. Epidemiology of cardiovascular disease in China: current features and implications. Nat Rev Cardiol. 2019;16(4):203–12.
Defronzo RA. Banting lecture. From the triumvirate to the ominous octet: a new paradigm for the treatment of type 2 diabetes mellitus. Diabetes. 2009;58(4):773–95.
Mancusi C, de Simone G, Best LG, Wang W, Zhang Y, Roman MJ, Lee ET, Howard BV, Devereux RB. Myocardial mechano-energetic efficiency and insulin resistance in non-diabetic members of the strong heart study cohort. Cardiovasc Diabetol. 2019;18(1):56.
Hill MA, Yang Y, Zhang L, Sun Z, Jia G, Parrish AR, Sowers JR. Insulin resistance, cardiovascular stiffening and cardiovascular disease. Metabolism. 2021;119: 154766.
Minh HV, Tien HA, Sinh CT, Thang DC, Chen CH, Tay JC, Siddique S, Wang TD, Sogunuru GP, Chia YC, et al. Assessment of preferred methods to measure insulin resistance in Asian patients with hypertension. J Clin Hypertens (Greenwich). 2021;23(3):529–37.
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(4):299–304.
Placzkowska S, Pawlik-Sobecka L, Kokot I, Piwowar A. Indirect insulin resistance detection: current clinical trends and laboratory limitations. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2019;163(3):187–99.
Guerrero-Romero F, Simental-Mendía LE, González-Ortiz M, Martínez-Abundis E, Ramos-Zavala MG, Hernández-González SO, Jacques-Camarena O, Rodríguez-Morán M. The product of triglycerides and glucose, a simple measure of insulin sensitivity. Comparison with the euglycemic-hyperinsulinemic clamp. J Clin Endocrinol Metab. 2010;95(7):3347–51.
Vasques AC, Novaes FS, de Oliveira MS, Souza JR, Yamanaka A, Pareja JC, Tambascia MA, Saad MJ, Geloneze B. TyG index performs better than HOMA in a Brazilian population: a hyperglycemic clamp validated study. Diabetes Res Clin Pract. 2011;93(3):e98–100.
Lee SH, Kwon HS, Park YM, Ha HS, Jeong SH, Yang HK, Lee JH, Yim HW, Kang MI, Lee WC, et al. Predicting the development of diabetes using the product of triglycerides and glucose: the Chungju Metabolic Disease Cohort (CMC) study. PLoS ONE. 2014;9(2): e90430.
Navarro-González D, Sánchez-Íñigo L, Pastrana-Delgado J, Fernández-Montero A, Martinez JA. Triglyceride-glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: the Vascular-Metabolic CUN cohort. Prev Med. 2016;86:99–105.
Khan SH, Sobia F, Niazi NK, Manzoor SM, Fazal N, Ahmad F. Metabolic clustering of risk factors: evaluation of Triglyceride-glucose index (TyG index) for evaluation of insulin resistance. Diabetol Metab Syndr. 2018;10:74.
Moon S, Park JS, Ahn Y. The Cut-off Values of Triglycerides and Glucose Index for metabolic syndrome in American and Korean Adolescents. J Korean Med Sci. 2017;32(3):427–33.
Katta N, Loethen T, Lavie CJ, Alpert MA. Obesity and coronary heart disease: epidemiology, pathology, and coronary artery imaging. Curr Probl Cardiol. 2021;46(3): 100655.
Bozkurt B, Aguilar D, Deswal A, Dunbar SB, Francis GS, Horwich T, Jessup M, Kosiborod M, Pritchett AM, Ramasubbu K, et al. Contributory risk and management of comorbidities of hypertension, obesity, diabetes mellitus, hyperlipidemia, and metabolic syndrome in chronic heart failure: a scientific statement from the American Heart Association. Circulation. 2016;134(23):e535–78.
ESC/EAS guidelines for the management of dyslipidaemias. Lipid modification to reduce cardiovascular risk. Atherosclerosis. 2019;290:140–205.
Sánchez-Íñigo L, Navarro-González D, Fernández-Montero A, Pastrana-Delgado J, Martínez JA. The TyG index may predict the development of cardiovascular events. Eur J Clin Invest. 2016;46(2):189–97.
Piironen M, Ukkola O, Huikuri H, Havulinna AS, Koukkunen H, Mustonen J, Ketonen M, Lehto S, Airaksinen J, Antero Kesäniemi Y, et al. Trends in long-term prognosis after acute coronary syndrome. Eur J Prev Cardiol. 2017;24(3):274–80.
Jin JL, Sun D, Cao YX, Guo YL, Wu NQ, Zhu CG, Gao Y, Dong QT, Zhang HW, Liu G, et al. Triglyceride glucose and haemoglobin glycation index for predicting outcomes in diabetes patients with new-onset, stable coronary artery disease: a nested case-control study. Ann Med. 2018;50(7):576–86.
Jin JL, Cao YX, Wu LG, You XD, Guo YL, Wu NQ, Zhu CG, Gao Y, Dong QT, Zhang HW, et al. Triglyceride glucose index for predicting cardiovascular outcomes in patients with coronary artery disease. J Thorac Dis. 2018;10(11):6137–46.
Gao A, Liu J, Hu C, Liu Y, Zhu Y, Han H, Zhou Y, Zhao Y. Association between the triglyceride glucose index and coronary collateralization in coronary artery disease patients with chronic total occlusion lesions. Lipids Health Dis. 2021;20(1):140.
Lee EY, Yang HK, Lee J, Kang B, Yang Y, Lee SH, Ko SH, Ahn YB, Cha BY, Yoon KH, et al. Triglyceride glucose index, a marker of insulin resistance, is associated with coronary artery stenosis in asymptomatic subjects with type 2 diabetes. Lipids Health Dis. 2016;15(1):155.
Thai PV, Tien HA, Van Minh H, Valensi P. Triglyceride glucose index for the detection of asymptomatic coronary artery stenosis in patients with type 2 diabetes. Cardiovasc Diabetol. 2020;19(1):137.
Piepoli MF, Hoes AW, Agewall S, Albus C, Brotons C, Catapano AL, Cooney MT, Corrà U, Cosyns B, Deaton C, et al. 2016 European Guidelines on cardiovascular disease prevention in clinical practice: the sixth joint task force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of 10 societies and by invited experts) developed with the special contribution of the European Association for Cardiovascular Prevention and Rehabilitation (EACPR). Eur Heart J. 2016;37(29):2315–81.
Fernández-Friera L, Fuster V, López-Melgar B, Oliva B, García-Ruiz JM, Mendiguren J, Bueno H, Pocock S, Ibáñez B, Fernández-Ortiz A, et al. Normal LDL-cholesterol levels are associated with subclinical atherosclerosis in the absence of risk factors. J Am Coll Cardiol. 2017;70(24):2979–91.
Park GM, Cho YR, Won KB, Yang YJ, Park S, Ann SH, Kim YG, Park EJ, Kim SJ, Lee SG, et al. Triglyceride glucose index is a useful marker for predicting subclinical coronary artery disease in the absence of traditional risk factors. Lipids Health Dis. 2020;19(1):7.
Thygesen K, Alpert JS, Jaffe AS, Simoons ML, Chaitman BR, White HD, Katus HA, Lindahl B, Morrow DA, Clemmensen PM, et al. Third universal definition of myocardial infarction. Circulation. 2012;126(16):2020–35.
Ray KK, Colhoun HM, Szarek M, Baccara-Dinet M, Bhatt DL, Bittner VA, Budaj AJ, Diaz R, Goodman SG, Hanotin C, et al. Effects of alirocumab on cardiovascular and metabolic outcomes after acute coronary syndrome in patients with or without diabetes: a prespecified analysis of the ODYSSEY OUTCOMES randomised controlled trial. Lancet Diabetes Endocrinol. 2019;7(8):618–28.
Wang L, Cong HL, Zhang JX, Hu YC, Wei A, Zhang YY, Yang H, Ren LB, Qi W, Li WY, et al. Triglyceride-glucose index predicts adverse cardiovascular events in patients with diabetes and acute coronary syndrome. Cardiovasc Diabetol. 2020;19(1):80.
Luo E, Wang D, Yan G, Qiao Y, Liu B, Hou J, Tang C. High triglyceride-glucose index is associated with poor prognosis in patients with acute ST-elevation myocardial infarction after percutaneous coronary intervention. Cardiovasc Diabetol. 2019;18(1):150.
Mao Q, Zhou D, Li Y, Wang Y, Xu SC, Zhao XH. 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.
Zhang Y, Ding X, Hua B, Liu Q, Gao H, Chen H, Zhao XQ, Li W, Li H. High Triglyceride-Glucose Index is associated with poor cardiovascular outcomes in nondiabetic patients with ACS with LDL-C below 1.8 mmol/L. J Atheroscler Thromb. 2022;29(2):268–81.
Gao S, Ma W, Huang S, Lin X, Yu M. Impact of triglyceride-glucose index on long-term cardiovascular outcomes in patients with myocardial infarction with nonobstructive coronary arteries. Nutr Metab Cardiovasc Dis. 2021;31(11):3184–92.
Byrne RA, Joner M, Kastrati A. Stent thrombosis and restenosis: what have we learned and where are we going? The Andreas Grüntzig Lecture ESC 2014. Eur Heart J. 2015;36(47):3320–31.
Alfonso F, Byrne RA, Rivero F, Kastrati A. Current treatment of in-stent restenosis. J Am Coll Cardiol. 2014;63(24):2659–73.
Zhu Y, Liu K, Chen M, Liu Y, Gao A, Hu C, Li H, Zhu H, Han H, Zhang J, et al. Triglyceride-glucose index is associated with in-stent restenosis in patients with acute coronary syndrome after percutaneous coronary intervention with drug-eluting stents. Cardiovasc Diabetol. 2021;20(1):137.
Zhang R, Xie J, Yang R, Li R, Chong M, Zhang X, Chen S, Wu S, Yang Y. Association between ideal cardiovascular health score trajectories and arterial stiffness: the Kailuan study. Hypertens Res. 2020;43(2):140–7.
Van Popele NM, Grobbee DE, Bots ML, Asmar R, Topouchian J, Reneman RS, Hoeks AP, Van der Kuip DA, Hofman A, Witteman JC. Association between arterial stiffness and atherosclerosis: the Rotterdam study. Stroke. 2001;32(2):454–60.
Laurent S, Boutouyrie P, Asmar R, Gautier I, Laloux B, Guize L, Ducimetiere P, Benetos A. Aortic stiffness is an independent predictor of all-cause and cardiovascular mortality in hypertensive patients. Hypertension. 2001;37(5):1236–41.
Mitchell GF, Hwang SJ, Vasan RS, Larson MG, Pencina MJ, Hamburg NM, Vita JA, Levy D, Benjamin EJ. Arterial stiffness and cardiovascular events: the Framingham Heart study. Circulation. 2010;121(4):505–11.
Lambrinoudaki I, Kazani MV, Armeni E, Georgiopoulos G, Tampakis K, Rizos D, Augoulea A, Kaparos G, Alexandrou A, Stamatelopoulos K. The TyG Index as a marker of subclinical atherosclerosis and arterial stiffness in lean and overweight postmenopausal women. Heart Lung Circ. 2018;27(6):716–24.
Lee SB, Ahn CW, Lee BK, Kang S, Nam JS, You JH, Kim MJ, Kim MK, Park JS. Association between triglyceride glucose index and arterial stiffness in Korean adults. Cardiovasc Diabetol. 2018;17(1):41.
Won KB, Park GM, Lee SE, Cho IJ, Kim HC, Lee BK, Chang HJ. Relationship of insulin resistance estimated by triglyceride glucose index to arterial stiffness. Lipids Health Dis. 2018;17(1):268.
Su Y, Wang S, Sun J, Zhang Y, Ma S, Li M, Zhang A, Cheng B, Cai S, Bao Q, et al. Triglyceride Glucose Index associated with arterial stiffness in chinese community-dwelling elderly. Front Cardiovasc Med. 2021;8: 737899.
Lee SJ, Avolio A, Seo DC, Kim BS, Kang JH, Lee MY, Sung KC. Relationship between brachial-ankle pulse wave velocity and incident hypertension according to 2017 ACC/AHA high blood pressure guidelines. J Am Heart Assoc. 2019;8(16): e013019.
Won KB, Chang HJ, Kim HC, Jeon K, Lee H, Shin S, Cho IJ, Park SH, Lee SH, Jang Y. Differential impact of metabolic syndrome on subclinical atherosclerosis according to the presence of diabetes. Cardiovasc Diabetol. 2013;12:41.
Li M, Zhan A, Huang X, Hu L, Zhou W, Wang T, Zhu L, Bao H, Cheng X. Positive association between triglyceride glucose index and arterial stiffness in hypertensive patients: the China H-type hypertension registry study. Cardiovasc Diabetol. 2020;19(1):139.
Nakagomi A, Sunami Y, Kawasaki Y, Fujisawa T, Kobayashi Y. Sex difference in the association between surrogate markers of insulin resistance and arterial stiffness. J Diabetes Complications. 2020;34(6): 107442.
Wu Z, Zhou D, Liu Y, Li Z, Wang J, Han Z, Miao X, Liu X, Li X, Wang W, et al. Association of TyG index and TG/HDL-C ratio with arterial stiffness progression in a non-normotensive population. Cardiovasc Diabetol. 2021;20(1):134.
Wang S, Shi J, Peng Y, Fang Q, Mu Q, Gu W, Hong J, Zhang Y, Wang W. Stronger association of triglyceride glucose index than the HOMA-IR with arterial stiffness in patients with type 2 diabetes: a real-world single-centre study. Cardiovasc Diabetol. 2021;20(1):82.
Guo W, Zhu W, Wu J, Li X, Lu J, Qin P, Zhu C, Xu N, Zhang Q. Triglyceride glucose index is associated with arterial stiffness and 10-year cardiovascular disease risk in a Chinese population. Front Cardiovasc Med. 2021;8: 585776.
Greenland P, LaBree L, Azen SP, Doherty TM, Detrano RC. Coronary artery calcium score combined with Framingham score for risk prediction in asymptomatic individuals. JAMA. 2004;291(2):210–5.
Budoff MJ, Achenbach S, Blumenthal RS, Carr JJ, Goldin JG, Greenland P, Guerci AD, Lima JA, Rader DJ, Rubin GD, et al. Assessment of coronary artery disease by cardiac computed tomography: a scientific statement from the American Heart Association Committee on Cardiovascular Imaging and Intervention, Council on Cardiovascular Radiology and Intervention, and Committee on Cardiac Imaging Council on Clinical Cardiology. Circulation. 2006;114(16):1761–91.
Kim MK, Ahn CW, Kang S, Nam JS, Kim KR, Park JS. Relationship between the triglyceride glucose index and coronary artery calcification in Korean adults. Cardiovasc Diabetol. 2017;16(1):108.
Won KB, Park EJ, Han D, Lee JH, Choi SY, Chun EJ, Park SH, Han HW, Sung J, Jung HO, et al. Triglyceride glucose index is an independent predictor for the progression of coronary artery calcification in the absence of heavy coronary artery calcification at baseline. Cardiovasc Diabetol. 2020;19(1):34.
Ziaeian B, Fonarow GC. Epidemiology and aetiology of heart failure. Nat Rev Cardiol. 2016;13(6):368–78.
Doehner W, Rauchhaus M, Ponikowski P, Godsland IF, von Haehling S, Okonko DO, Leyva F, Proudler AJ, Coats AJ, Anker SD. Impaired insulin sensitivity as an independent risk factor for mortality in patients with stable chronic heart failure. J Am Coll Cardiol. 2005;46(6):1019–26.
Guo W, Zhao L, Mo F, Peng C, Li L, Xu Y, Guo W, Sun A, Yan H, Wang L. The prognostic value of the triglyceride glucose index in patients with chronic heart failure and type 2 diabetes: a retrospective cohort study. Diabetes Res Clin Pract. 2021;177: 108786.
Treibel TA, Fridman Y, Bering P, Sayeed A, Maanja M, Frojdh F, Niklasson L, Olausson E, Wong TC, Kellman P, et al. Extracellular volume associates with outcomes more strongly than native or post-contrast myocardial T1. JACC Cardiovasc Imaging. 2020;13(1 Pt 1):44–54.
Yang S, Du Y, Liu Z, Zhang R, Lin X, Ouyang Y, Chen H. Triglyceride-Glucose Index and extracellular volume fraction in patients with heart failure. Front Cardiovasc Med. 2021;8: 704462.
Yang Q, Vijayakumar A, Kahn BB. Metabolites as regulators of insulin sensitivity and metabolism. Nat Rev Mol Cell Biol. 2018;19(10):654–72.
Riehle C, Abel ED. Insulin signaling and heart failure. Circ Res. 2016;118(7):1151–69.
Molina MN, Ferder L, Manucha W. Emerging role of nitric oxide and heat shock proteins in insulin resistance. Curr Hypertens Rep. 2016;18(1):1.
Nishikawa T, Kukidome D, Sonoda K, Fujisawa K, Matsuhisa T, Motoshima H, Matsumura T, Araki E. Impact of mitochondrial ROS production in the pathogenesis of insulin resistance. Diabetes Res Clin Pract. 2007;77(Suppl 1):S161-164.
Jia G, DeMarco VG, Sowers JR. Insulin resistance and hyperinsulinaemia in diabetic cardiomyopathy. Nat Rev Endocrinol. 2016;12(3):144–53.
Gerrits AJ, Koekman CA, van Haeften TW, Akkerman JW. Platelet tissue factor synthesis in type 2 diabetic patients is resistant to inhibition by insulin. Diabetes. 2010;59(6):1487–95.
Samuel VT, Shulman GI. The pathogenesis of insulin resistance: integrating signaling pathways and substrate flux. J Clin Invest. 2016;126(1):12–22.
Ala-Korpela M. The culprit is the carrier, not the loads: cholesterol, triglycerides and apolipoprotein B in atherosclerosis and coronary heart disease. Int J Epidemiol. 2019;48(5):1389–92.
Zhou MS, Schulman IH, Zeng Q. Link between the renin-angiotensin system and insulin resistance: implications for cardiovascular disease. Vasc Med. 2012;17(5):330–41.
Ozcan L, Tabas I. Calcium signalling and ER stress in insulin resistance and atherosclerosis. J Intern Med. 2016;280(5):457–64.
Irace C, Carallo C, Scavelli FB, De Franceschi MS, Esposito T, Tripolino C, Gnasso A. Markers of insulin resistance and carotid atherosclerosis. A comparison of the homeostasis model assessment and triglyceride glucose index. Int J Clin Pract. 2013;67(7):665–72.
Cho YK, Lee J, Kim HS, Kim EH, Lee MJ, Yang DH, Kang JW, Jung CH, Park JY, Kim HK, et al. Triglyceride glucose-waist circumference better predicts coronary calcium progression compared with other indices of insulin resistance: a longitudinal observational study. J Clin Med. 2020;10(1):92.
Cho YR, Ann SH, Won KB, Park GM, Kim YG, Yang DH, Kang JW, Lim TH, Kim HK, Choe J, et al. Association between insulin resistance, hyperglycemia, and coronary artery disease according to the presence of diabetes. Sci Rep. 2019;9(1):6129.
Cui H, Liu Q, Wu Y, Cao L. Cumulative triglyceride-glucose index is a risk for CVD: a prospective cohort study. Cardiovasc Diabetol. 2022;21(1):22.
Dikaiakou E, Vlachopapadopoulou EA, Paschou SA, Athanasouli F, Panagiotopoulos Ι, Kafetzi M, Fotinou A, Michalacos S. Τriglycerides-glucose (TyG) index is a sensitive marker of insulin resistance in Greek children and adolescents. Endocrine. 2020;70(1):58–64.
Si Y, Fan W, Han C, Liu J, Sun L. Atherogenic Index of plasma, triglyceride-glucose index and monocyte-to-lymphocyte ratio for predicting subclinical coronary artery disease. Am J Med Sci. 2021;362(3):285–90.
Da Silva A, Caldas APS, Hermsdorff HHM, Bersch-Ferreira ÂC, Torreglosa CR, Weber B, Bressan J. Triglyceride-glucose index is associated with symptomatic coronary artery disease in patients in secondary care. Cardiovasc Diabetol. 2019;18(1):89.
Yang J, Tang YD, Zheng Y, Li C, Zhou Q, Gao J, Meng X, Zhang K, Wang W, Shao C. The impact of the triglyceride-glucose index on poor prognosis in nondiabetic patients undergoing percutaneous coronary intervention. Front Endocrinol (Lausanne). 2021;12: 710240.
Si Y, Fan W, Shan W, Zhang Y, Liu J, Han C, Sun L. Association between triglyceride glucose index and coronary artery disease with type 2 diabetes mellitus in middle-aged and elderly people. Medicine (Baltimore). 2021;100(9): e25025.
Chen L, Ding XH, Fan KJ, Gao MX, Yu WY, Liu HL, Yu Y. Association Between Triglyceride-Glucose Index and 2-year adverse cardiovascular and cerebrovascular events in patients with type 2 diabetes mellitus who underwent off-pump coronary artery bypass grafting. Diabetes Metab Syndr Obes. 2022;15:439–50.
Drwiła D, Rostoff P, Gajos G, Nessler J, Konduracka E. Prognostic value of the triglyceride-glucose index among non-diabetic patients with acute myocardial infarction at one-year follow-up. Kardiol Pol. 2021;79(10):1116–23.
Guo Q, Feng X, Zhang B, Zhai G, Yang J, Liu Y, Liu Y, Shi D, Zhou Y. Influence of the Triglyceride-Glucose Index on adverse cardiovascular and cerebrovascular events in prediabetic patients with acute coronary syndrome. Front Endocrinol (Lausanne). 2022;13: 843072.
Jiao Y, Su Y, Shen J, Hou X, Li Y, Wang J, Liu B, Qiu D, Sun Z, Chen Y, et al. Evaluation of the long-term prognostic ability of triglyceride-glucose index for elderly acute coronary syndrome patients: a cohort study. Cardiovasc Diabetol. 2022;21(1):3.
Zhao Q, Zhang TY, Cheng YJ, Ma Y, Xu YK, Yang JQ, Zhou YJ. Triglyceride-Glucose Index as a surrogate marker of insulin resistance for predicting cardiovascular outcomes in nondiabetic patients with non-ST-segment elevation acute coronary syndrome undergoing percutaneous coronary intervention. J Atheroscler Thromb. 2021;28(11):1175–94.
Ma X, Dong L, Shao Q, Cheng Y, Lv S, Sun Y, Shen H, Wang Z, Zhou Y, Liu X. Triglyceride glucose index for predicting cardiovascular outcomes after percutaneous coronary intervention in patients with type 2 diabetes mellitus and acute coronary syndrome. Cardiovasc Diabetol. 2020;19(1):31.
Ling Y, Fu C, Fan Q, Liu J, Jiang L, Tang S. Triglyceride-Glucose Index and new-onset atrial fibrillation in ST-segment elevation myocardial infarction patients after percutaneous coronary intervention. Front Cardiovasc Med. 2022;9: 838761.
Zhao X, Wang Y, Chen R, Li J, Zhou J, Liu C, Zhou P, Sheng Z, Chen Y, Song L, et al. Triglyceride glucose index combined with plaque characteristics as a novel biomarker for cardiovascular outcomes after percutaneous coronary intervention in ST-elevated myocardial infarction patients: an intravascular optical coherence tomography study. Cardiovasc Diabetol. 2021;20(1):131.
Zhang Y, Ding X, Hua B, Liu Q, Gao H, Chen H, Zhao XQ, Li W, Li H. Predictive effect of triglyceride-glucose index on clinical events in patients with type 2 diabetes mellitus and acute myocardial infarction: results from an observational cohort study in China. Cardiovasc Diabetol. 2021;20(1):43.
Zhang Y, Ding X, Hua B, Liu Q, Gao H, Chen H, Zhao XQ, Li W, Li H. High triglyceride-glucose index is associated with adverse cardiovascular outcomes in patients with acute myocardial infarction. Nutr Metab Cardiovasc Dis. 2020;30(12):2351–62.
Hu C, Zhang J, Liu J, Liu Y, Gao A, Zhu Y, Zhao Y. 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(1):116.
Zhao Q, Zhang TY, Cheng YJ, Ma Y, Xu YK, Yang JQ, Zhou YJ. Impacts of triglyceride-glucose index on prognosis of patients with type 2 diabetes mellitus and non-ST-segment elevation acute coronary syndrome: results from an observational cohort study in China. Cardiovasc Diabetol. 2020;19(1):108.
Yan Y, Wang D, Sun Y, Ma Q, Wang K, Liao Y, Chen C, Jia H, Chu C, Zheng W, et al. Triglyceride-glucose index trajectory and arterial stiffness: results from Hanzhong adolescent hypertension cohort study. Cardiovasc Diabetol. 2022;21(1):33.
Wu S, Xu L, Wu M, Chen S, Wang Y, Tian Y. Association between triglyceride-glucose index and risk of arterial stiffness: a cohort study. Cardiovasc Diabetol. 2021;20(1):146.
Park K, Ahn CW, Lee SB, Kang S, Nam JS, Lee BK, Kim JH, Park JS. Elevated TyG Index Predicts Progression of Coronary Artery Calcification. Diabetes Care. 2019;42(8):1569–73.
This research was funded by the National Natural Science Foundation of China (NSFC) Grants 82170356, China Postdoctoral Science Foundation grant 2018M642317, Post-Doctoral Foundation of Jiangsu Province Grant 2018K095B, Six Talent Peaks Project of Jiangsu Province grants WSN-202 and WSW-183, Changzhou Sci&Tech Program Grant CJ20210091, Maternal and Child Health Research Project of Jiangsu Province Grant F201803.
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Tao, LC., Xu, Jn., Wang, Tt. et al. Triglyceride-glucose index as a marker in cardiovascular diseases: landscape and limitations. Cardiovasc Diabetol 21, 68 (2022). https://doi.org/10.1186/s12933-022-01511-x
- Triglyceride-glucose index
- Insulin resistance
- Cardiovascular disease