Triglyceride-Glucose Index and Major Adverse Cardiovascular Events in Diabetic and Nondiabetic Patients: A Systematic Review and Meta-Analysis

Abstract

Insulin resistance (IR) is increasingly recognized as a significant risk factor for adverse cardiovascular outcomes. The triglyceride-glucose index (TyG) has emerged as a potential proxy for IR, but its role as a predictor of major adverse cardiovascular events (MACE) in diabetic and nondiabetic populations remains unclear. This systematic review and meta-analysis evaluated the association between the TyG index and MACE outcomes. A comprehensive literature search of PubMed, Embase, Scopus, and Web of Science was conducted for studies published up to August 2024. Twenty-five studies involving 105,755 participants were included. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using a random-effects model, treating TyG as both a continuous variable and by comparing the highest versus lowest TyG groups. In diabetic patients, the pooled HR for MACE when comparing the highest and lowest TyG groups was 1.89 (95% CI: 1.42–2.53, P < 0.01), and a 1-unit increase in the TyG index was associated with a 93% higher MACE risk (HR 1.93, 95% CI: 1.36–2.73, P < 0.01). Similar trends were observed for MACE components, including cardiovascular mortality, myocardial infarction, stroke, and revascularization. Among nondiabetic patients, the pooled HR for MACE was 1.78 (95% CI: 1.24–2.56, P < 0.01), with a 1-unit TyG increase linked to a 52% higher MACE risk (HR 1.52, 95% CI: 1.08–2.15, P = 0.02). Component analysis further supported these findings. This study demonstrates that the TyG index is a significant predictor of MACE risk in both diabetic and nondiabetic populations, underscoring its potential clinical utility for early cardiovascular risk stratification. Further research is needed to confirm these findings and explore the practical implications of TyG in routine clinical care.

Introduction

Cardiovascular diseases (CVDs) are among the leading causes of death worldwide.¹ CVDs encompass a wide range of conditions, including heart failure (HF), coronary artery disease (CAD), irregular heart rhythms, and valvular disorders.¹ Major adverse cardiovascular events (MACE) have been frequently addressed in the literature to comprise various cardiac conditions such as unstable angina, acute myocardial infarction (MI), all-cause mortality, HF, and CAD.² Extensive research has examined the effects of MACE, including its impact on life expectancy, quality of life, overall health, economic costs, and mortality.³ MACE also poses a substantial financial burden on patients, their families, and society.³

Researchers have recently focused on a novel and easy-to-use biomarker for insulin resistance (IR) known as the triglyceride-glucose (TyG) index. This index is calculated by this formula—Ln [fasting plasma glucose (mg/dL) × fasting triglycerides (mg/dL)/2]—and has shown better accuracy in estimating IR compared with the homeostatic model assessment of insulin resistance (HOMA-IR).^4–7 Some human studies have found that TyG index is positively correlated with subclinical myocardial injury, coronary plaque progression, and coronary artery calcification suggesting its potential prognostic value in CAD.⁸ The hyperinsulinemic-euglycemic clamp (HIEC) is known as one of the best methods for calculating IR, but it is complex and lengthy, making it impractical for widespread clinical use.⁵ Consequently, the TyG index has been shown to be an easy, cost-effective, and reliable alternative biomarker for IR.⁹

A study in 2022 showed that elderly patients diagnosed with acute coronary syndrome and elevated TyG index levels had a 1.64-fold and 1.36-fold increased risk of all-cause mortality and MACE, respectively.¹⁰ Among nondiabetic individuals and the general public, a cohort study involving 7521 participants in Iran reported that after 3 years of follow-up, higher risks of CVD and CAD were associated with higher TyG index.¹¹ The evidence implies that the TyG index may serve as a predictor for cardiovascular events, distinct from established risk factors.¹² Clinical studies have strongly demonstrated relationship between higher TyG index and higher incidence of CAD.^13–15 However, there is ongoing debate on the accuracy of the TyG index in predicting adverse cardiac events in those with CAD and various glycemic status.^16,17 Yang et al. concluded that the TyG index was not a proper predictor of adverse cardiovascular outcomes in nondiabetic patients following PCI.¹⁷ Similarly, Drwiła et al. found that the TyG index did not demonstrate significant predictive value for all-cause mortality and MACE during a 1-year follow-up period after MI in non-diabetic population.¹⁶ In contrast, the TyG index was found as an effective predictor of various MACE outcomes among both diabetic and nondiabetic patients in several other studies.^18–20 Thus, this study seeks to evaluate the relation between the TyG index and MACE, especially focusing on differentiating various diabetic status populations.

Materials and Methods

The study protocol has been registered with the International Platform of Registered Systematic Review and Meta-analysis Protocols under registration number (CRD42024590212). We conducted this meta-analysis following the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).²¹ PRISMA checklist is included in Supplementary Table S1.

Search strategy

We extensively searched through major databases, including Embase, Scopus, Web of Science, and PubMed to find pertinent studies from inception until August 2024. The keywords for the search were “TyG,” “MACE,” and “diabetes mellitus.” The detailed search strategy and results for each database are presented in Supplementary Table S2.

Inclusion and exclusion criteria

Rayyan software was used to organize the identified studies according to the inclusion and exclusion criteria. After employing automation tools for duplicate removal, we primarily screened titles/abstracts to find potentially relevant literature. Subsequently, full texts of these studies were reviewed to apply the inclusion/exclusion criteria and determine the final set of papers. The entire process of literature searching, applying inclusion/exclusion criteria, data extraction, and analyses was performed blindly by two authors (S.S. and A.M.). Any disagreements were resolved through consultation with a senior author.

The inclusion criteria were established using the PICOS framework: (1) Participants: adults aged 18 years or older with known diabetes mellitus status (populations entirely with a history of diabetes mellitus, populations entirely having nondiabetic status, and populations categorized into subgroups based on having diabetes mellitus or not); (2) Exposure: TyG index; (3) Comparator: a group exhibiting the highest TyG index compared with a group exhibiting the lowest TyG index; (4) Outcome: Correlation between TyG index and MACE outcomes; (5) Study types: Cohort studies. Studies were excluded if they did not meet any of the following criteria: (1) Included more than two subgroups based on TyG index (quartile/tertile/specific cut-offs); (2) reported MACE outcomes; (3) included a population divided into diabetes and/or non-diabetes groups; (4) had full-text availability; (5) original researches; or (6) were not abstracts, letters, or conference abstracts.

Data extraction

Two authors (S.S. and A.M.) conducted independent data extraction from the chosen studies and sought guidance from the senior author (H.R.) to resolve any discrepancies that arose. The following data were extracted based on these parameters: (1) First author; (2) year of publication; (3) study design; (4) country; (5) population; (6) baseline characteristics such as gender (%), mean age, mean body mass index (BMI), and population diabetes status; (7) mean TyG index; (8) left ventricular ejection fraction (LVEF); (9) duration of the follow-up; and (10) hazard ratios (HRs) with confidence intervals (CIs), demonstrating association between various outcomes incidence and TyG index amount across different subgroups categorized by TyG index. Our outcomes included MACE events that included (1) cardiovascular death, (2) stroke, (3) MI, (4) all-cause mortality, and (5) need for revascularization.

Quality assessment

Two authors (A.M. and I.A.) evaluated the bias risk assessment of the included cohort studies by utilizing the Newcastle–Ottawa scale (NOS) tool, which considers exposure, comparability, selection, and outcome as domains for potential risk of bias.²² Any disagreements were addressed through discussions with the senior author (H.R.).

Statistical analysis

To assess the connection between the TyG index and cardiovascular outcomes, a meta-analysis was performed utilizing HRs along with 95% CIs. The analysis focused on determining the risk of cardiovascular outcomes correlated with a 1-unit increase in the TyG index. HRs were pooled across studies, and the impact of TyG index increase on all-cause mortality and stroke was evaluated for diabetic and nondiabetic populations, separately. The heterogeneity across studies was assessed using the I² statistic, with values above 50% considered indicative of substantial heterogeneity. Fixed-effects models were used when heterogeneity was low, while random-effects models were employed in the presence of high heterogeneity. Subgroup analyses were performed based on diabetic status (diabetic vs. nondiabetic populations) to explore potential differences in risk estimates. Additionally, sensitivity analyses were performed to examine the reliability of the results. Meta-regression was employed to investigate how different study characteristics, such as the average age and gender distribution of participants, on the effect estimates. Publication bias was examined using funnel plots and Egger’s test, with a P value <0.05 considered significant for asymmetry, suggesting potential bias. All statistical analyses were performed using the meta and metafor packages in R.

Results

Baseline characteristics

The comprehensive search yielded 2295 studies. After removing duplicates and title/abstract screening, 180 studies remained. By evaluating exclusion criteria through full-texts, finally, 25 studies were included to the meta-analysis. The PRISMA figure depicts the summary of the study selection (Fig. 1).

FIG. 1.

PRISMA chart. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

All studies were cohort studies from five different countries, with the majority conducted in China,^{17–19,23–38} two each in the United States^39,40 and North America,^41,42 and one each in Japan²⁰ and Spain.⁴³ The total population included in the study was 105,755, with a mean age of 62.31 years and a mean BMI of 27.78 kg/m². Males comprised 52.6% of the population. The mean TyG index, LVEF, and detailed characteristics of the included studies are summarized in Table 1.

Table 1.

Baseline Characteristics of Included Studies

First author/year	Study design	Country	Total population	Mean age	Gender male (%)	Mean BMI	Diabetic status	TyG index mean	LVEF (%)	Follow-up duration (month)
Lin/2024¹⁸	Cohort	China	9996	60.3 ± 9.3	75.1	26.3 ± 3.2	Yes	9.2 ± 0.6	61.6 ± 6.8	36
Otsuka/2024²⁰	Cohort	Japan	684	65 ± 11	65.7	24 ± 4	Both	8.8 ± 0.1	NA	36
Wei/2024¹⁹	Cohort	China	960	63 ± 2.8	67.5	NA	Yes	9.1 ± 0.1	NA	83
Abuduaini/2023²³	Cohort	China	1514	65.7 ± 2.2	73.9	25.8 ± 0.7	Yes	7.6 ± 0.1	41.9 ± 1.5	55.4
Chen/2023²⁵	Cohort	China	633	68 ± 10.6	67.2	24.9 ± 3.1	Yes	9.1 ± 0.3	54.6 ± 9.7	18.8
Huang/2023²⁸	Cohort	China	555	64.5 ± 11.3	68.3	NA	Yes	9 ± 0.1	NA	63
Shen/2023³²	Cohort	China	231	81.6 ± 1.9	67.5	24.8 ± 3.4	Both	9 ± 0.7	56.3 ± 9.2	120
Wu/2023³⁴	Cohort	China	830	62.8 ± 8.1	74.3	25.6 ± 3.6	No	8.6 ± 0.2	58.8 ± 10.2	68
Zhao/2023⁴¹	Cohort	United States	2998	64.5 ± 5.7	53.16	NA	Yes	NA	NA	82
Chen/2022²⁴	Cohort	China	1578	62.9	70.7	26 ± 3.1	Yes	9.1 ± 0.3	59.5 ± 7.7	24
Liu/2022 (1)²⁹	Cohort	China	3359	65 ± 2.2	59.2	24.3 ± 0.5	Yes	1.9 ± 0.8	NA	12
Liu/2022 (2)³⁰	Cohort	China	6095	48.7 ± 9.9	49.1	24.5 ± 3.5	No	NA	NA	120
Quiroga/2022⁴⁴	Cohort	Spain	1142	59 ± 12	60	28 ± 5	No	8.6 ± 0.1	NA	46
Tai/2022 (1)⁴²	Cohort	North America	10,196	62.8 ± 6.6	61.5	32.2 ± 5.4	Yes	9.5 ± 0.7	NA	60
Tai/2022 (2)⁴³	Cohort	North America	5695	62.6 ± 6.5	61.9	32.2 ± 5.3	Yes	36.5 ± 2.4^a	NA	61
Yao/2022³⁶	Cohort	China	858	68.1 ± 2.3	55.7	24 ± 0.5	Yes	NA	NA	41
Zhang/2022³⁷	Cohort	China	1655	65.6 ± 10.2	73.9	25.4 ± 3.4	No	8.4 ± 0.4	63.3 ± 9	34
Guo/2021²⁶	Cohort	China	546	65.2 ± 12	66.3	21.1 ± 1.8	Yes	NA	40.2 ± 14.9	12
Hou/2021²⁷	Cohort	China	12,964	64.9 ± 12	57.4	NA	No	NA	NA	12
Yang/2021 (1)³⁵	Cohort	China	5489	57.1 ± 10.1	79.4	25.6 ± 3.1	No	8.7 ± 0.2	63.4 ± 7	24
Yang/2021 (2)⁴⁰	Cohort	United States	9323	67.9 ± 9.3	NA	29.8 ± 5.7	No	8.6 ± 0.2	NA	39.1
Zhou/2021³⁹	Cohort	China	24,349	61.9 ± 2.5	40.2	NA	No	7.3 ± 0.1	NA	215
Ma/2020³¹	Cohort	China	776	61 ± 10	72.1	26.1 ± 3.3	Yes	9.1 ± 0.1	63.8 ± 1.1	30
Wang/2020³³	Cohort	China	2531	66 ± 6.8	55.9	25.9 ± 2.9	Yes	9.1 ± 0.3	57.6 ± 8.6	36
Zhao/2020³⁸	Cohort	China	798	60.9 ± 8.3	68.3	26.7 ± 3.2	Yes	9.1 ± 0.6	64 ± 6.6	36

Cumulative TyG.

BMI, body mass index; LVEF, left ventricular ejection fraction; TyG, triglyceride-glucose index.

Quality assessment

Among the 25 studies included in our meta-analysis, 23 were assessed as having good quality according to the NOS quality assessment tool. Of the remaining two studies, one was classified as poor quality, while the other received a fair quality rating based on their respective scores. Supplementary Table S3 presents the detailed results.

Analysis of outcomes on the comparison of groups with the highest and lowest TyG index

Analysis of outcomes based on the comparison of groups with the highest and lowest mean TyG index revealed significant differences. MACE outcomes, based on 14 studies, demonstrated significantly higher risk in group with the highest versus lowest TyG index (HR = 1.87, 95% CI 1.49; 2.33) (Fig. 2). Additionally, all-cause mortality, MI, stroke, and the need for revascularization outcomes showed significantly higher risks in the highest TyG group compared with the lowest TyG group (HR = 1.70, 95% CI 1.22; 2.38), (HR = 1.75, 95% CI 1.37; 2.24), (HR = 1.27, 95% CI 1.11; 1.46), and (HR = 1.81, 95% CI 1.31; 2.49), respectively (Figs. 3A–3E). Subgroup analysis based on glycemic status (diabetes mellitus and nondiabetic) revealed a significant MACE risk for the group with highest versus lowest TyG index (Fig. 4). The notable differences and higher risks were observed for all-cause mortality within both diabetic and nondiabetic groups (Supplementary Fig. S1A). However, cardiovascular mortality, MI, and stroke were only significant in the diabetic patient group (Supplementary Figs. S1B–1D). In contrast, the need for revascularization risk was significant when comparing the highest and lowest TyG groups in the nondiabetic group (Supplementary Fig. S1E). Table 2 summarizes the outcomes in detail.

FIG. 2.

Forest plot for comparison of MACE outcome between the group with the highest TyG and the group with the lowest TyG. MACE, major adverse cardiovascular events; TyG, triglyceride-glucose.

FIG. 3.

Forest plot for comparison of outcomes incidence between the group with the highest TyG and the group with the lowest TyG. (A) All-cause mortality. (B) Cardiovascular mortality. (C) Myocardial infarction. (D) Stroke. (E) Need for revascularization.

FIG. 4.

Forest plot for comparison of MACE outcome between the group with the highest TyG and the group with the lowest TyG among diabetic and non-diabetic subgroups.

Table 2.

Outcomes by Comparing the Group with the Highest TyG Index Versus the Group with the Lowest TyG Index

Outcome	Study numbers	HR (95% CI)	I ²	P-value total	P-value heterogeneity
MACE
Total	14	1.87 (1.49; 2.33)	93%	<0.01	<0.01
Diabetic	9	1.89 (1.42; 2.53)	95%	<0.01	<0.01
Nondiabetic	5	1.78 (1.24; 2.56)	75%	<0.01	<0.01
All-cause mortality
Total	12	1.70 (1.22; 2.38)	91%	<0.01	<0.01
Diabetic	8	2.02 (1.35; 3.03)	89%	<0.01	<0.01
Nondiabetic	4	1.17 (1.12; 1.22)	68%	<0.01	0.03
Cardiovascular mortality
Total	5	1.45 (0.95; 2.23)	72%	0.09	<0.01
Diabetic	4	1.64 (1.11; 2.41)	65%	0.01	0.04
Nondiabetic	1	0.77 (0.44; 1.35)	—	—	—
MI
Total	7	1.75 (1.37; 2.24)	27%	<0.01	0.22
Diabetic	5	2.02 (1.51; 2.70)	16%	<0.01	0.32
Nondiabetic	2	1.20 (0.75; 1.92)	0%	0.44	0.80
Stroke
Total	9	1.27 (1.11; 1.46)	29%	<0.01	0.18
Diabetic	5	1.55 (1.21; 1.97)	0%	<0.01	0.46
Nondiabetic	4	1.15 (0.97; 1.37)	26%	0.10	0.25
Need for revascularization
Total	3	1.81 (1.31; 2.49)	0%	<0.01	0.93
Diabetic	1	1.96 (0.91; 4.22)	—	—	—
Nondiabetic	2	1.77 (1.25; 2.53)	0%	<0.01	0.76

CI, confidence interval; HR, hazard ratio; MACE, major adverse cardiovascular events; MI, myocardial infarction.

Analysis of outcome risk per 1-unit increase in TyG index

A 1-unit higher TyG index was associated with a 76% higher risk of MACE in comparison to a 1-unit lower TyG index (HR = 1.76, 95% CI 1.37; 2.26) (Fig. 5). Similar significant results for MACE were demonstrated in both diabetic and nondiabetic populations (Supplementary Fig. S2). All-cause mortality showed a notably significant difference among diabetic patients when increasing the TyG index by 1 unit. However, the results were not significant in the total population and non-diabetic populations. All studies evaluating the 1-unit TyG increase risk for stroke were conducted on the non-diabetic population and showed no significant difference (Supplementary Fig. S3A–3B) (Table 3).

FIG. 5.

Forest plot for MACE outcome incidence with a 1-unit increase in TyG index.

Table 3.

Outcomes Risk of Occurrence by 1-Unit Increase in TyG Index

Outcome	Study numbers	HR (95% CI)	I ²	P-value total	P-value heterogeneity
MACE
Total	7	1.76 (1.37; 2.26)	88%	<0.01	<0.01
Diabetic	4	1.93 (1.36; 2.73)	84%	<0.01	<0.01
Nondiabetic	3	1.52 (1.08; 2.15)	77%	0.02	0.01
All-cause mortality
Total	4	1.41 (0.93; 2.12)	89%	0.10	<0.01
Diabetic	2	1.79 (1.38; 2.33)	0%	<0.01	0.72
Nondiabetic	2	1.11 (0.58; 2.11)	82%	0.75	0.02
Stroke
Total	3	1.26 (0.92; 1.73)	64%	0.15	0.06
Diabetic	—	—	—	—	—
Nondiabetic	3	1.26 (0.92; 1.73)	64%	0.15	0.06

Publication bias

To evaluate sensitivity, we performed a leave-one-out meta-analysis for each outcome (Supplementary Figs. S4, S5, S6, S7, S8, S9, S10, S11 and S12). Omitting individual studies from the cardiovascular mortality analysis showed a significantly elevated risk of cardiovascular mortality in the group with the highest TyG compared to the lowest TyG group. However, the overall analysis showed no meaningful difference between these two groups.³⁶ Additionally, when omitting the study by Hou et al from the all-cause mortality outcome, the results demonstrated a significantly increased risk for all-cause mortality with one unit elevation in TyG index.²⁷ Overall, low risk of publication bias was considered.

Discussion

Our results showed that patients with an elevated TyG index faced a significantly increased risk of MACE, MI, stroke, all-cause mortality, and the need for revascularization. Our subgroup analysis of diabetic and nondiabetic populations indicated similar outcomes, with a significantly greater MACE risk and all-cause mortality observed in the group with higher TyG index. However, only the diabetic group showed significantly higher results in terms of stroke, MI, and cardiovascular mortality. Conversely, the risk of the need for revascularization was only meaningfully elevated in the nondiabetic group. We also found that a 1-unit rise in the TyG index is correlated with a 76% increase in the risk of MACE. Furthermore, the risk of MACE was similarly notably elevated in both subgroups with diabetic and nondiabetic populations with 1-unit increase in the TyG index.

These results align with a similar study by Liu et al.,¹² which showed that a higher TyG index significantly correlated with elevated incidence of MI, CVD, and CAD. Similarly, they found a dose–response correlation in which every unit increase in the TyG index was correlated to a 35% elevated CAD risk and a 23% increased risk of CVD. Contrary to our results, they found no statistically meaningful relationship between higher TyG index and CV mortality or all-cause mortality. Another meta-analysis² evaluated the impact of the TyG index on MACE and ACS, revealing a nonlinear dose–response relationship between an increased TyG index and the risk of MACE. However, none of these two studies^2,12 have subgroups based on diabetes status. Similar to our study, a 2021 meta-analysis by Luo et al.⁸ including 12 studies and 28,795 patients with CAD demonstrated that subjects with higher TyG index were at 2.14-fold elevated risk of MACEs compared with participants in the low TyG index group. Moreover, their results exhibited no meaningful difference between diabetic and non-diabetic populations which is in line with the present study. However, the present study’s rationale lies in the fact that we included 25 studies with 105,755 patients. Moreover, our primary focus in the subgroup analysis was to differentiate the relationship between the TyG index and MACE outcomes in subgroups based on diabetes status.

IR is a known risk factor for cardiovascular events.¹⁵ The HIEG clamp test was formerly known as the gold standard for IR measurement.⁴⁴ However, the high cost and extended time requirements have restricted its widespread use.⁴⁵ Subsequently, several other measurements were introduced, such as quantitative insulin sensitivity check index, HOMA-IR, TG/HDL-c, and TyG index.^46–48 Among these, the TyG index is an effective yet inexpensive and easy-to-use standard with high sensitivity and specificity for measuring IR.⁴⁸ Research shows that the TyG index is a better IR indicator in comparison to HOMA-IR.⁴⁹ The TyG index, calculated by fasting blood glucose and triglyceride, acts as a specific and sensitive index for IR.¹⁵ Fasting triglycerides and glucose measurements are simple and inexpensive tests in both hospital and outpatient settings, and it’s unlikely that the TyG index assessment leads to a significantly higher burden for the health care system or patients. The TyG index was also shown to be more related to the calcified coronary artery plaques in healthy adults in comparison with HOMA-IR.⁵⁰ In a cohort study with 5014 participants, the TyG index has shown to be a better predictor for MACE comparing with other common indices such as TG, TG/HDL-c ratio, and plasma atherogenic index.¹⁵ The TyG index is also associated with cardiovascular events such as hypertension,⁵¹ HF,⁵² CAD,⁵³ stroke,⁵⁴ and a worse prognosis.⁵⁵ Additionally, a dose–effect correlation was reported to be present across multi-vessel CAD and the TyG index, most significantly in elderly and male subjects.⁵⁶ A recent meta-analysis showed that higher TyG index is correlated with a worse outcome in individuals with non-obstructive coronary arteries, ACS, and CCS.⁵⁵

A TyG index above 10 has been previously reported to be correlated with an above 70% stenosis in coronary arteries.⁵⁷ Additionally, it is reported that higher TyG index in patients undergoing CABG is correlated with a higher graft failure rate due to IR-induced endothelial dysfunction.²⁴ In a meta-analysis by Liu et al., both continuous and categorical analysis of the TyG index showed significant association with an elevated risk of coronary artery calcification and stiffness.⁵⁸

The relationship between the TyG index and poor prognosis in patients with CAD could be explained through the relationship between IR and CAD. Consistently, various mechanisms have been identified through which IR can deteriorate cardiovascular function and lead to CADs. IR elevates blood pressure and cardiac burden through increasing sympathetic activity, hyperinsulinemia, and renal retention of sodium.^55,59 It also causes vascular and kidney damage through its metabolic effects, such as dyslipidemia and hyperglycemia.⁵⁹ In addition, insulin dysregulations and IR may cause oxidative stress, immune system dysregulation, inflammation, and improper renin–angiotensin–aldosterone system activation, leading to cardiac dysfunction.^60,61 IR may occur before the development of diabetes and CVDs, which contributes to atherosclerosis formation in even seemingly healthy individuals.⁶² Moreover, insulin induces vasodilation through promoting the production of nitric oxide (NO); thus, malfunctions in insulin regulation reduce NO activity and induce vascular stiffness.⁶³

Clinical implications and future prospects

Fasting blood glucose and TG are almost always among the routine lab tests for patients admitted to the hospital for ACS and other MACEs. Current evidence shows that the TyG index can be considered a cheap and accessible prognostic tool during the evaluations of patients with MACEs. However, there is still no universal consensus on the appropriate TyG index cut-off point for risk stratification. Several studies incorporated the TyG index in the common scoring systems for CADs and found promising results.^15,32,64,65 Framingham risk score showed an enhanced predictive accuracy in intermediate-risk patients after adding the TyG index to the scoring system.¹⁵ Xiong et al. incorporated the TyG index into the residual SYNTAX scoring system, which exhibited a synergistically better prediction of the MACEs in type 2 diabetic patients.⁶⁴ Additionally, supplementation of the GRACE score with the TyG index resulted in an enhanced prognostic ability in ACS patients.⁶⁵ Furthermore, including the TyG index in the Gensini score led to a meaningfully improved predictive ability in terms of the all-cause mortality risk.³² Therefore, we encourage future research to concentrate on establishing an accurate cutoff point for risk stratification and exploring the possibility of adding the TyG index to existing cardiovascular scoring tools. Particularly, it would be beneficial to conduct studies involving populations with prediabetic status, as understanding the impact of prediabetes management could provide valuable insights into cardiovascular outcomes. By examining this relationship more closely, further guidelines may better recommend risk stratification methods and effective patterns to control prediabetes status which could influence the cardiovascular outcomes.

Limitations

To the best of our knowledge, this study represents the first systematic review and meta-analysis examining the association between the TyG index and risk of MACE outcomes in diabetic and non-diabetic subgroups separately. Our meta-analysis was conducted on cohort studies; therefore, we could not establish a cause-and-effect correlation between the TyG index and MACE outcomes. Additionally, although most studies have adjusted confounders such as diabetes mellitus, hypertension, and BMI, there might be some unadjusted confounding factors such as secondhand smoking and dietary and lifestyle habits. Moreover, the definition of MACE has changed over time and has evolved from a three-point to a five-point variable, which complicates the interpretation of results across studies. For instance, a lower number of studies included hospitalization or revascularization as part of MACE compared with those that included cardiovascular death, stroke, and acute MI. Thus, the strength of evidence may vary among different MACE outcomes. Furthermore, most of the studies were done on the Asian population groups, which highlight the need for further research in other populations.

Conclusions

This systematic review and meta-analysis demonstrate that the TyG index is a crucial predictor of MACE in both diabetic and nondiabetic populations. Our results show that higher TyG levels are correlated with increased risks of MI, cardiovascular mortality, all-cause mortality, stroke, and the need for revascularization. Specifically, the highest TyG group had HRs of 1.89 for diabetics and 1.78 for nondiabetics, underscoring the index’s predictive value. Given that insulin resistance is considered a major risk factor for cardiovascular complications, the total role of TyG index in assessing this risk is vital for clinical practice. While our findings highlight the association between TyG and MACE, future study is needed to confirm these results and clarify the clinical implications of using the TyG index in routine assessments. This includes investigating its potential to guide treatment decisions and improve patient outcomes.

Footnotes

Authors’ Contributions

Conceptualization: A.M. and S.S. Methodology: A.M., H.R., I.A., A.N.S., H.F., A.A., and S.S. Investigation: A.M. Validation: H.R. Formal analysis: A.A. Supervision: H.R. and S.S. Visualization: A.N.S. Project administration: A.M., H.R., and S.S. Writing—original draft: A.M., I.A., A.N.S., H.F., A.A., and S.S.; Writing—review and editing: H.R.

Confirmation Statement

All authors confirm that this research is supported by institutions that are primarily involved in education or research.

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Author Disclosure Statement

The authors declare no competing interests.

Funding Information

No funding was received for this article.

Supplementary Material

Abbreviations Used

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