The Triglyceride-Glucose Index Might Be a Better Indicator for Predicting Poor Cardiovascular Outcomes in Chronic Coronary Syndrome

Relationship and prognostic value of the triglyceride-glucose index and optical coherence tomography-derived physiological index in patients with acute coronary syndrome

The optical flow ratio (OFR), derived from optical coherence tomography (OCT) images, serves as a physiological index, while the Triglyceride-Glucose Index (TyG) is an alternative measure of insulin resistance. Both indices are positively correlated with poor prognosis in patients with acute coronary syndrome (ACS), but the relationship between the TyG index, OFR, and their prognostic value remains unclear. We included ACS patients who underwent OCT between January 1, 2021, and March 31, 2023. The TyG index was calculated as Ln[fasting triglycerides (mg/dL) × fasting blood glucose (mg/dL)/2]. Patients were grouped into three categories (T1, T2, and T3) based on TyG tertiles. The primary endpoint was major adverse cardiovascular events (MACE). In our analysis, the T3 group showed a significantly higher incidence of MACE (P < 0.05), with a progressive decrease in vessel-level OFR observed as the TyG index increased, demonstrating a linear correlation (r = - 0.0146, P < 0.001). The restricted cubic splines (RCS) model revealed a nonlinear relationship between the TyG index and the likelihood of MACE (P for nonlinear < 0.021). Additionally, the cumulative incidence of MACE was significantly higher in patients with a higher TyG index (all Log-rank P < 0.001).These findings suggest a nonlinear relationship between the TyG index and MACE, and a linear association between the TyG index and vessel-level OFR. The combination of the TyG index and OFR significantly improved discriminatory ability (c-index: 0.720 vs. 0.757; P < 0.001) and reclassification ability (net reclassification index [NRI]: 0.373; integrated discrimination improvement [IDI]: 0.031; P < 0.0001) for predicting MACE compared to vessel-level OFR alone. This combination effectively identifies high-risk ACS patients.

Association between triglyceride-glucose index and all-cause mortality in patients with congestive heart failure and atrial fibrillation

Background

The role of the triglyceride-glucose (TyG) index in critically ill patients with congestive heart failure (CHF) and atrial fibrillation (AF), requiring intensive care unit (ICU) admission, remains unclear. This study aimed to investigate the association between the TyG index and the clinical prognosis of critically ill patients with CHF and AF.

Methods

This retrospective observational cohort study utilized data from the Medical Information Mart for Intensive Care-IV (MIMIC IV2.2) database. Participants were categorized into four groups based on TyG index level. The primary outcome was hospital all-cause mortality. Multivariable logistic proportional regression analysis and restricted cubic spline regression were employed to assess the TyG index's association with hospital mortality in patients with CHF and AF. Sensitivity analysis included determining the TyG index's feature importance through subgroup analysis in different subgroups.

Results

A total of 787 patients were included in the study, with hospital and ICU mortalities of 14.2% and 8.3%, respectively. Multivariate logistic regression analysis demonstrated that the TyG index was independently associated with an increased risk of hospital mortality (odds ratio (OR), 1.59 [95% confidence interval (CI) 1.15-2.19], P = 0.005) and ICU mortality [OR 1.9; (95% CI 1.28-2.83), P = 0.001] after adjusting for confounders. The restricted cubic spline regression model indicated a linear increase in the risks of in-hospital and ICU mortality with a higher TyG index. Sensitivity analysis revealed consistent effect sizes and directions in different subgroups, ensuring result stability.

Conclusions

The results of our study suggest a significant association between the TyG index and hospital and ICU all-cause mortality in critically ill patients with CHF and AF. This finding implies that the TyG index could potentially serve as a valuable tool for identifying patients with CHF and AF at an elevated risk of all-cause mortality.

The role of TyG index in predicting low left ventricular ejection fraction after acute coronary syndrome

AIMS

This study aimed to investigate whether triglyceride-glucose (TyG) index and other clinical and demographic parameters are associated with left ventricular ejection fraction (LVEF) following an acute coronary syndrome (ACS) event.

METHODS & RESULTS

This retrospective cohort study included patients hospitalized with a diagnosis of ACS. The TyG index was calculated using the formula: TyG = ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. A total of 2,135 patients were included in the study (mean age: 57.49 ± 11.45 years, 78.64% male). Multivariable logistic regression revealed that mildly reduced or reduced LVEF was associated with immigrant population (p = 0.004), diabetes mellitus (p = 0.017), previous coronary artery disease (CAD) (p < 0.001), ST-elevation myocardial infarction (STEMI) (p < 0.001) and high (≥4.95) TyG index (p < 0.001). Reduced LVEF (≤40%) was independently associated with an immigrant status (p = 0.031), previous CAD (p = 0.001), peripheral artery disease (p = 0.038), renal diseases (p = 0.011), STEMI (p < 0.001) and high (≥5.10) TyG index (p < 0.001).

CONCLUSIONS

The TyG index shows potential as an independent risk factor for low LVEF after ACS.However, its relatively low sensitivity and specificity suggest that it may have a supportive role in risk stratification. Further research is needed to confirm its utility as a reliable prognostic marker for heart failure in ACS patients.

Establishing and internally validating a predictive model for coronary heart disease incorporating triglyceride-glucose index, monocyte-to-high-density lipoprotein cholesterol ratio and conventional risk factors in patients experiencing chest pain and referred for invasive coronary angiography

BACKGROUND

Coronary heart disease (CHD) represents a severe form of ischemic cardiac condition that necessitates timely and accurate diagnosis. Although coronary angiography (CAG) remains widely used to detect CHD, healthcare facilities, medical expenses, and equipment technology often limit its availability. Therefore, it is imperative to identify a non-invasive diagnostic approach with high accuracy for CHD.

METHODS

This cross-sectional research included patients with chest pain (≥ 18 years) hospitalized at Chengde Central Hospital between September 2020 and March 2024. Among the participants, 70% were split into the training, and 30% were randomly entered into the validation sets. In the training dataset, univariate and multivariate logistic regression analyses were rigorously employed to ascertain predictors of CHD. A model was formulated by incorporating these predictors in a nomogram, which was evaluated for accuracy using calibration curves. The model's discrimination was quantified by calculating the area under the receiver operating characteristic (ROC) curve, denoted as the area under the curve (AUC), and its clinical application value was determined through decision curve analysis (DCA). Finally, we compare our model against the pretest probability (PTP) calculated by the Update Diamond-Forrester Model (UDFM) as recommended by the ECS guidelines to comprehensively assess its performance.

RESULTS

This study included 1501 patients who presented with chest pain, with a mean age of 60.45 years, 865 males (57.60%). Multivariate logistic regression analysis revealed TyG index, MHR, male, age, diabetes, systolic blood pressure (SBP), regional wall motion abnormality (RWMA), ST-T changes, and low-density lipoprotein cholesterol (LDL-C) as independent predictors of CHD. A novel nomogram incorporating these independent risk factors exhibited high accuracy and perfect consistency, with a training set AUC calculated to be 0.733 (95% CI: 0.698-0.768), and the validation set maintained a strong performance at 0.721 (95% CI: 0.663-0.779). The calibration curves and the Hosmer-Lemeshow test confirmed the well-fitting model (P = 0.576 and P = 0.694). ROC curve analysis and DCA demonstrated that the model has robust forecasting capability.

CONCLUSION

The nomogram model in this study exhibited good discriminative ability, calibration, and a favorable net benefit. Its predictive performance exceeds that of the traditional PTP tool and may serve as a non-invasive and promising approach to aid clinicians in the early identification of CHD risk in patients presenting with chest pain.

Triglyceride-glucose index (TyG) as a novel biomarker in the era of cardiometabolic medicine

In the period of increasing prevalence of metabolic disorders such as obesity and diabetes, healthcare professionals are facing significant challenges. Therefore, an accurate global assessment of insulin resistance is of utmost importance. Current medical research is focused on identifying an easily accessible and reproducible gold-standard surrogate marker for insulin resistance. Ideally, such a marker would enable healthcare providers to predict the risk of type 2 diabetes and cardiovascular diseases. The triglyceride-glucose index (TyG) is a promising marker for preventive cardiology and cardiometabolic medicine. This narrative review article aims to provide a comprehensive evaluation of the credibility of TyG as a surrogate marker of insulin resistance among patients at different stages across the cardiometabolic continuum. This assessment fully complies with evidence-based medicine and offers valuable insight into the clinical utility of TyG.

Association between triglyceride-glucose index and in-hospital all-cause mortality under different glucose metabolism status among patients with coronary artery disease

BACKGROUND

This current study aimed to investigate the relationship between the triglyceride-glucose (TyG) index and in-hospital all-cause mortality of coronary artery disease (CAD) in patients with different glucose metabolic statuses.

METHODS

Participants were divided into three groups according to tertiles of the TyG index. Glucose metabolic status was classified as normal glucose regulation, pre-diabetes mellitus, and diabetes mellitus (DM). The primary outcome was in hospital all-cause mortality.

RESULTS

We observed a significant relationship between the TyG index and in-hospital deaths of patients with CAD in this study. After adjusting for multiple factors in the logistic regression model, the TyG index was still an independent risk factor, and the T3 group (OR, 2.311; 95% CI = 1.237-4.317; P = 0.009) was correlated with a 2.311-fold risk compared with the T1 group. In the subgroup analysis of different glucose metabolic status, the T3 group (OR, 1.541; 95% CI: 1.013-2.344; P = 0.043) were associated with a significantly higher risk of in-hospital deaths in CAD patients with DM.

CONCLUSIONS

An increased TyG index was correlated with a higher risk of in-hospital all-cause mortality. Our study indicated that TyG index could be a valuable predictor of in-hospital death of CAD patients, especially for individuals with DM.

Lack of incremental prognostic value of triglyceride glucose index beyond coronary computed tomography angiography features for major events

This study was aim to determine the prognostic value of triglyceride-glucose (TyG) index and coronary computed tomography angiography (CTA) features for major adverse cardiovascular events (MACE). In addition, we investigate the incremental prognostic value of TyG index beyond coronary CTA features in patients with suspected or known coronary artery disease (CAD). The present study ultimately includes 3528 patients who met the enrollment criteria. The TyG index was calculated based on measured levels of triglycerides and fasting blood glucose. Primary combined endpoint consisted of MACE, which defined as myocardial infraction (MI), all-cause mortality and stroke. Three multivariate Cox proportional hazard regression models were performed to assess the association between TyG index and MACE. C-statistic was performed to assess the discriminatory value of models. 212 (6.0%) patients developed MACE during a median follow-up of 50.4 months (IQR, 39.4-55.1). TyG index remained to be a significantly and independent risk factors for predicting MACE after adjusting by different models (clinical variables alone or plus coronary CTA features) in multivariable analysis. Both the addition of TyG index to clinical model plus Coronary Artery Disease Reporting and Data System (CAD-RADS) and to clinical model plus CAD-RADS 2.0 slightly but not significantly increased the C-statistic index (0.725 vs. 0.721, p = 0.223; 0.733 vs. 0.731, p = 0.505). TyG index was associated with an increased risk of MACE. However, no incremental prognostic benefit of TyG index over CAD-RADS or CAD-RADS 2.0 was detected for MACE in patients with suspected or known CAD.

Predictive value of the triglyceride-glucose index for short- and long-term all-cause mortality in patients with critical coronary artery disease: a cohort study from the MIMIC-IV database

BACKGROUND

Triglyceride-glucose (TyG) index is linked to a poor prognosis for cardiovascular condition and is a valid indicator of insulin resistance. This study evaluated the potential predicting usefulness of the TyG index for all-cause mortality, both short- and long-term, for those concerning critical coronary artery disease (CAD).

METHODS

In this study, information from 5452 critically-ill individuals with CAD in intensive care units were gathered from the Medical Information Marketplace in Intensive Care (MIMIC-IV) database. Depending on the TyG index degree, the patients were categorized into three categories. Clinical outcomes included short-term (30-day) and long-term (365-day) all-cause mortality. The corresponding relationships involving the TyG index and clinical outcomes were examined by deploying restricted cubic spline (RCS) regression analysis and Cox proportional risk regression.

RESULTS

An increased TyG index was associated with increased 30-day (Tertile 1: 6.1%, Tertile 2: 7.3%, Tertile 3: 9.2%, P = 0.001) and 365-day (Tertile 1: 15.2%, Tertile 2: 17.0%, Tertile 3: 19.6%, P = 0.002) death rates across all causes. Cox regression with multiple variables indicates that higher TyG indices were linked to higher all-caused mortality hazard ratios throughout the short and long terms, with a larger predictive value for the former. RCS regression analyses suggested that the risk of death was notably and linearly that is associated with TyG index.

CONCLUSIONS

The TyG index is a reliable predictor of all-cause mortality at different stages in critically ill CAD patients, with a higher predictive ability for short-term mortality. Early intervention in patients with elevated TyG index may improve their survival outcomes. Future research should delve into understanding its pathophysiological mechanisms and develop intervention strategies based on the TyG index, providing new insights and strategies to enhance the outlook for critically ill CAD patients.

Lipid-based insulin-resistance markers predict cardiovascular events in metabolic dysfunction associated steatotic liver disease

BACKGROUND

Insulin resistance (IR) is the cornerstone of Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD), pathophysiologically being the key link between MASLD, metabolic disorders, and cardiovascular (CV) diseases. There are no prospective studies comparing the predictive values of different markers of insulin resistance (IR) in identifying the presence of MASLD and the associated risk of cardiovascular events (CVEs).

METHODS

Post hoc analysis of the prospective Plinio Study, involving dysmetabolic patients evaluated for the presence of MASLD. The IR markers considered were Homeostatic Model Assessment for IR (HOMA-IR), Triglycerides-Glycemia (TyG) index, Triglycerides to High-Density Lipoprotein Cholesterol ratio (TG/HDL-C), Lipid Accumulation Product (LAP) and Visceral Adiposity Index (VAI). Receiver operative characteristic (ROC) analyses were performed to find the optimal cut-offs of each IR marker for detecting MASLD and predicting CVEs in MASLD patients. Logistic and Cox multivariable regression analyses were performed, after dichotomizing the IR markers based on the optimal cut-offs, to assess the factors independently associated with MASLD and the risk of CVEs.

RESULTS

The study included 772 patients (age 55.6 ± 12.1 years, 39.4% women), of whom 82.8% had MASLD. VAI (Area Under the Curve [AUC] 0.731), TyG Index (AUC 0.723), and TG/HDL-C ratio (AUC: 0.721) predicted MASLD but was greater with HOMA-IR (AUC: 0.792) and LAP (AUC: 0.787). After a median follow-up of 48.7 (25.4-75.8) months, 53 MASLD patients experienced CVEs (1.8%/year). TyG index (AUC: 0.630), LAP (AUC: 0.626), TG/HDL-C (AUC: 0.614), and VAI (AUC: 0.590) demonstrated comparable, modest predictive values in assessing the CVEs risk in MASLD patients.

CONCLUSION

In dysmetabolic patients HOMA-IR and LAP showed the best accuracy in detecting MASLD. The possible use of lipid-based IR markers in stratifying the CV risk in patients with MASLD needs further validation in larger cohorts.

TYG Index as a Novel Predictor of Clinical Outcomes in Advanced Chronic Heart Failure with Renal Dysfunction Patients

Background

The triglyceride-glucose (TYG) index is a novel and reliable marker reflecting insulin resistance. Its predictive ability for cardiovascular disease onset and prognosis has been confirmed. However, for advanced chronic heart failure (acHF) patients, the prognostic value of TYG is challenged due to the often accompanying renal dysfunction (RD). Therefore, this study focuses on patients with aHF accompanied by RD to investigate the predictive value of the TYG index for their prognosis.

Methods and Results

717 acHF with RD patients were included. The acHF diagnosis was based on the 2021 ESC criteria for acHF. RD was defined as the eGFR < 90 mL/(min/1.73 m2). Patients were divided into two groups based on their TYG index values. The primary endpoint was major adverse cardiovascular events (MACEs), and the secondary endpoints is all-cause mortality (ACM). The follow-up duration was 21.58 (17.98-25.39) months. The optimal cutoff values for predicting MACEs and ACM were determined using ROC curves. Hazard factors for MACEs and ACM were revealed through univariate and multivariate COX regression analyses. According to the univariate COX regression analysis, high TyG index was identified as a risk factor for MACEs (hazard ratio = 5.198; 95% confidence interval [CI], 3.702-7.298; P < 0.001) and ACM (hazard ratio = 4.461; 95% CI, 2.962-6.718; P < 0.001). The multivariate COX regression analysis showed that patients in the high TyG group experienced 440.2% MACEs risk increase (95% CI, 3.771-7.739; P < 0.001) and 406.2% ACM risk increase (95% CI, 3.268-7.839; P < 0.001). Kaplan-Meier survival analysis revealed that patients with high TyG index levels had an elevated risk of experiencing MACEs and ACM within 30 months.

Conclusion

This study found that patients with high TYG index had an increased risk of MACEs and ACM, and the TYG index can serve as an independent predictor for prognosis.

The association of atherogenic index of plasma with cardiovascular outcomes in patients with coronary artery disease: A systematic review and meta-analysis

BACKGROUND

Atherogenic index of plasma (AIP) represents a novel marker in the current era of cardiovascular diseases. In this meta-analysis, we aimed to evaluate the association of AIP with cardiovascular prognosis in patients with coronary artery disease (CAD).

METHODS

PubMed, Scopus, and Web of Science databases were searched from inception through 2024. The primary outcome was major cardiovascular events (MACE). The secondary outcomes included all-causes death, cardiovascular death, myocardial infarction (MI), stroke, revascularization, and no-reflow phenomenon. AIP was determined by taking the logarithm of the ratio of triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C). The data analysis was represented using the risk ratio (RR) along with a 95% confidence interval (CI).

RESULTS

Sixteen studies with a total number of 20,833 patients met the eligible criteria. The pooled-analysis showed a significant increased risk of MACE in the highest AIP group compared with the lowest AIP group (RR = 1.63; 95% CI, 1.44-1.85; P < 0.001). A similar result was observed when AIP was regarded as a continuous variable (RR = 1.54; 95% CI, 1.30-1.83; P < 0.001). Besides, elevated AIP was associated with increased risk of cardiovascular death (RR = 1.79; 95% CI, 1.09-2.78; P = 0.02), MI (RR = 2.21; 95% CI, 1.55-3.13; P < 0.001), revascularization (RR = 1.62; 95% CI, 1.34-1.97; P < 0.001), no-reflow phenomenon (RR = 3.12 95% CI, 1.09-8.96; P = 0.034), and stent thrombosis (RR = 13.46; 95%CI, 1.39-129.02; P = 0.025). However, AIP was not significantly associated with the risk of all-causes death and stroke among patients with CAD.

CONCLUSIONS

The results of this study demonstrated that increased AIP is an independent prognostic factors in patients with CAD. Further research is warranted to elucidate the potential development of targeted interventions to modify AIP levels and improve patient outcomes.

Impact of diabetes mellitus and triglyceride glucose index on mortality and cardiovascular outcomes in patients with chronic coronary syndrome undergoing coronary computed tomography angiography

Background

There is limited knowledge regarding whether an elevated triglyceride glucose (TyG) index can serve as a prognostic marker for mortality and cardiovascular outcomes, independent of diabetes mellitus (DM) and plaque burden, in patients with chronic coronary syndrome (CCS).

Methods

Patients with CCS (n = 684) were categorized into subgroups based on the presence of DM, and patients without DM were further divided into two groups based on presence or absence of an elevation of TyG index >8.8. Coronary plaque burden was evaluated using coronary computed tomography angiography. Major cardiovascular adverse event (MACE) was defined as a composite event of nonfatal myocardial infarction, unstable angina or unplanned coronary revascularization, stroke, non-cardiovascular mortality and cardiovascular mortality.

Results

Patients without DM exhibited significantly greater plaque and epicardial adipose tissue volumes than those with DM. Multivariable Cox proportional hazards models demonstrated that DM and an elevated TyG index >8.8 were independently associated with the risk of MACE after adjusting for age, sex, and plaque volume. Patients with DM (hazard ratio, 3.74; 95% confidence interval, 1.97-7.08; p < 0.001) and patients without DM with an elevated TyG index (hazard ratio, 1.99; 95% confidence interval, 1.01-3.91; p = 0.045) had an increased risk of MACE.

Conclusion

This study indicates that DM and an elevated TyG index are predictors of MACE, independent of plaque volume, in patients with CCS.

Multi-trajectories of triglyceride-glucose index and lifestyle with Cardiovascular Disease: a cohort study

BACKGROUND

Previous studies using trajectory models focused on examining the longitudinal changes in triglyceride-glucose (TyG) levels and lifestyle scores separately, without exploring the joint evolution of these two factors. This study aimed to identify the multi-trajectories of TyG levels and lifestyle scores and assess their association with the risk of cardiovascular disease (CVD).

METHODS

The study enrolled 47,384 participants from three health surveys of the Kailuan Study. The TyG index was computed as Ln [fasting triglycerides (mg/dL) × fasting blood glucose (mg/dL)/2], and the lifestyle scores were derived from five factors, including smoking, alcohol consumption, physical activity, sedentary behaviors, and salt intake. A group-based multi-trajectory model was adopted to identify multi-trajectories of TyG levels and lifestyle scores. The association of identified multi-trajectories with incident CVD was examined using Cox proportional hazard model.

RESULTS

Five distinct multi-trajectories of TyG levels and lifestyle scores were identified. During a median follow-up period of 10.98 years, 3042 participants developed CVD events (2481 strokes, 616 myocardial infarctions, and 55 co-current stroke and myocardial infarctions). In comparison to group 3 with the lowest TyG levels and the best lifestyle scores, the highest CVD risk was observed in group 5 characterized by the highest TyG levels and moderate lifestyle scores (HR = 1.76, 95% CI: 1.50-2.05). Group 2 with higher TyG levels and the poorest lifestyle scores had a 1.45-fold (95% CI 1.26-1.66) risk of CVD, and group 1 with lower TyG levels and poorer lifestyle scores had a 1.33-fold (95% CI 1.17-1.50) risk of CVD. Group 4, with moderate TyG levels and better lifestyle scores, exhibited the lowest CVD risk (HR = 1.32, 95% CI: 1.18-1.47).

CONCLUSIONS

Distinct multi-trajectories of TyG levels and lifestyle scores corresponded to differing CVD risks. The CVD risk caused by a high level TyG trajectory remained increased despite adopting healthier lifestyles. These findings underscored the significance of evaluating the combined TyG and lifestyle patterns longitudinally, and implementing early interventions to reduce CVD risk by lowering TyG levels.