Non-insulin-based insulin resistance indexes in predicting severity for coronary artery disease

Triglyceride-glucose index and health outcomes: an umbrella review of systematic reviews with meta-analyses of observational studies

BACKGROUND

Numerous meta-analyses have explored the association between the triglyceride-glucose (TyG) index and diverse health outcomes, yet the comprehensive assessment of the scope, validity, and quality of this evidence remains incomplete. Our aim was to systematically review and synthesise existing meta-analyses of TyG index and health outcomes and to assess the quality of the evidence.

METHODS

A thorough search of PubMed, EMBASE, and Web of Science databases was conducted from their inception through to 8 April 2024. We assessed the quality of reviews using A Measurement Tool to Assess Systematic Reviews (AMSTAR) and the certainty of the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system. This study was registered with PROSPERO (CRD: 42024518587).

RESULTS

Overall, a total of 95 associations from 29 meta-analyses were included, investigating associations between TyG index and 30 health outcomes. Of these, 83 (87.4%) associations were statistically significant (P < 0.05) according to the random effects model. Based on the AMSTAR tool, 16 (55.2%) meta-analyses were high quality and none was low quality. The certainty of the evidence, assessed by the GRADE framework, showed that 6 (6.3%) associations were supported by moderate-quality evidence. When compared with the lowest category of the TyG index, the risk of contrast-induced nephropathy (CIN) [relative risk (RR) = 2.25, 95%CI 1.82, 2.77], the risk of stroke in patients with diabetes mellitus (RR = 1.26, 95%CI 1.18, 1.33) or with acute coronary syndrome disease (RR = 1.56, 95%CI 1.06, 2.28), the prognosis of coronary artery disease (CAD)-non-fatal MI (RR = 2.02, 95%CI 1.32, 3.10), and the severity of CAD including coronary artery stenosis (RR = 3.49, 95%CI 1.71, 7.12) and multi-vessel CAD (RR = 2.33, 95%CI 1.59, 3.42) increased with high TyG index.

CONCLUSION

We found that the TyG index was positively associated with many diseases including the risk of CIN and stroke, the prognosis of CAD, and the severity of CAD which were supported by moderate-quality evidence. TyG index might be useful to identify people at high-risk for developing these diseases.

Potential molecular mechanism of exercise reversing insulin resistance and improving neurodegenerative diseases

Neurodegenerative diseases are debilitating nervous system disorders attributed to various conditions such as body aging, gene mutations, genetic factors, and immune system disorders. Prominent neurodegenerative diseases include Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and multiple sclerosis. Insulin resistance refers to the inability of the peripheral and central tissues of the body to respond to insulin and effectively regulate blood sugar levels. Insulin resistance has been observed in various neurodegenerative diseases and has been suggested to induce the occurrence, development, and exacerbation of neurodegenerative diseases. Furthermore, an increasing number of studies have suggested that reversing insulin resistance may be a critical intervention for the treatment of neurodegenerative diseases. Among the numerous measures available to improve insulin sensitivity, exercise is a widely accepted strategy due to its convenience, affordability, and significant impact on increasing insulin sensitivity. This review examines the association between neurodegenerative diseases and insulin resistance and highlights the molecular mechanisms by which exercise can reverse insulin resistance under these conditions. The focus was on regulating insulin resistance through exercise and providing practical ideas and suggestions for future research focused on exercise-induced insulin sensitivity in the context of neurodegenerative diseases.

The prognostic impact of insulin resistance surrogates in patients with acute myocardial infarction with and without type 2 diabetes

BACKGROUND

Cardiovascular disease is the major cause of morbidity and mortality, particularly in type 2 diabetes mellitus (T2DM). Novel markers of insulin resistance and progression of atherosclerosis include the triglycerides and glucose index (TyG index), the triglycerides and body mass index (Tyg-BMI) and the metabolic score for insulin resistance (METS-IR). Establishing independent risk factors for in-hospital death and major adverse cardiac and cerebrovascular events (MACCE) in patients with myocardial infarction (MI) remains critical. The aim of the study was to assess the risk of in-hospital death and MACCE within 12 months after ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) in patients with and without T2DM based on TyG index, Tyg-BMI and METS-IR.

METHODS

Retrospective analysis included 1706 patients with STEMI and NSTEMI hospitalized between 2013 and 2021. We analyzed prognostic value of TyG index, Tyg-BMI and METS-IR for in-hospital death and MACCE as its components (death from any cause, MI, stroke, revascularization) within 12 months after STEMI or NSTEMI in patients with and without T2DM.

RESULTS

Of 1706 patients, 58 in-hospital deaths were reported (29 patients [4.3%] in the group with T2DM and 29 patients [2.8%] in the group without T2DM; p = 0.1). MACCE occurred in 18.9% of the total study population (25.8% in the group with T2DM and 14.4% in the group without T2DM; p < 0.001). TyG index, Tyg-BMI and METS-IR were significantly higher in the group of patients with T2DM compared to those without T2DM (p < 0.001). Long-term MACCE were more prevalent in patients with T2DM (p < 0.001). The area under the ROC curve (AUC-ROC) for the prediction of in-hospital death and the TyG index was 0.69 (p < 0.001). The ROC curve for predicting in-hospital death based on METS-IR was 0.682 (p < 0.001). The AUC-ROC values for MACCE prediction based on the TyG index and METS-IR were 0.582 (p < 0.001) and 0.57 (p < 0.001), respectively.

CONCLUSIONS

TyG index was an independent risk factor for in-hospital death in patients with STEMI or NSTEMI. TyG index, TyG-BMI and METS-IR were not independent risk factors for MACCE at 12 month follow-up. TyG index and METS-IR have low predictive value in predicting MACCE within 12 months after STEMI and NSTEMI.

The impact of triglyceride glucose-body mass index on all-cause and cardiovascular mortality in elderly patients with diabetes mellitus: evidence from NHANES 2007-2016

BACKGROUND

The relationship between triglyceride glucose-body mass index (TyG-BMI) index and mortality in elderly patients with diabetes mellitus (DM) are still unclear. This study aimed to investigate the association between TyG-BMI with all-cause and cardiovascular mortality among elderly DM patients in the United States (US).

METHODS

Patients aged over 60 years with DM from the National Health and Nutrition Examination Survey (2007-2016) were included in this study. The study endpoints were all-cause and cardiovascular mortality and the morality data were extracted from the National Death Index (NDI) which records up to December 31, 2019. Multivariate Cox proportional hazards regression model was used to explore the association between TyG-BMI index with mortality. Restricted cubic spline was used to model nonlinear relationships.

RESULTS

A total of 1363 elderly diabetic patients were included, and were categorized into four quartiles. The mean age was 70.0 ± 6.8 years, and 48.6% of them were female. Overall, there were 429 all-cause deaths and 123 cardiovascular deaths were recorded during a median follow-up of 77.3 months. Multivariate Cox regression analyses indicated that compared to the 1st quartile (used as the reference), the 3rd quartile demonstrated a significant association with all-cause mortality (model 2: HR = 0.64, 95% CI 0.46-0.89, P = 0.009; model 3: HR = 0.65, 95% CI 0.43-0.96, P = 0.030). Additionally, the 4th quartile was significantly associated with cardiovascular mortality (model 2: HR = 1.83, 95% CI 1.01-3.30, P = 0.047; model 3: HR = 2.45, 95% CI 1.07-5.57, P = 0.033). The restricted cubic spline revealed a U-shaped association between TyG-BMI index with all-cause mortality and a linear association with cardiovascular mortality, after adjustment for possible confounding factors.

CONCLUSIONS

A U-shaped association was observed between the TyG-BMI index with all-cause mortality and a linear association was observed between the TyG-BMI index with cardiovascular mortality in elderly patients with DM in the US population.

Correlation between alternative insulin resistance indexes and diabetic kidney disease: a retrospective study

PURPOSE

This retrospective study aimed to investigate the relationship between alternative insulin resistance (IR) indexes not reliant on insulin and diabetic kidney disease (DKD) incidence in a newly diagnosed cohort of individuals with type 2 diabetes mellitus (T2DM).

METHODS

We conducted a retrospective analysis of baseline characteristics in a cohort of 521 individuals with T2DM, then followed up on the outcome of DKD. To assess the predictive ability of IR indexes, we compared the performance of four non-insulin-based IR indexes and the homeostasis model for insulin resistance (HOMA-IR) using logistic regression and consistency-statistics (C-statistics). Furthermore, we computed the net reclassification index (NRI) and integrated discrimination improvement (IDI) to evaluate the additional effects of the indexes.

RESULTS

The four alternative IR indexes of DKD patients were significantly higher than those of non-DKD. After adjustment for other variables, the highest tertile of all indexes was significantly related to DKD incidence, compared with the lowest tertile. Furthermore, the C-statistics for the triglyceride-glucose index (TyG index) and triglyceride to high-density lipoprotein ratio (TG/HDL) were all 0.652, while triglyceride glucose-body mass index (TyG-BMI) and metabolic score for insulin resistance (METS-IR) were 0.639 and 0.651, respectively. The incorporation of the alternative IR indexes into the baseline model revealed positive additional effects, leading to an improved prediction of the risk for DKD.

CONCLUSIONS

It was discovered that the alternative IR indexes served as independent risk factors of DKD. Among the four alternative indexes, TyG index and TG/HDL had the best prediction performance for DKD, followed by METS-IR.

METS-IR and all-cause mortality in Korean over 60 years old: Korean genome and epidemiology study-health examinees (KoGES-HEXA) cohorts

Background

The metabolic score for insulin resistance index (METS-IR) is a novel non insulin-based marker that indicates the risk for metabolic syndrome and type 2 diabetes mellitus (T2DM). However, METS-IR has not been investigated in relation to all-cause mortality. We investigated the longitudinal effect of METS-IR on all-cause mortality in a significantly large cohort of Korean adults over 60 years old.

Methods

Data were assessed from 30,164 Korean participants over 60 years of age from the Korean Genome and Epidemiology Study-Health Examinees (KoGES-HEXA) cohort data, linked with the death certificate database of the National Statistical Office. The participants were grouped into three according to METS-IR tertiles. We used multivariate Cox proportional-hazard regression models to prospectively assess hazard ratios (HRs) for all-cause mortality with 95% confidence intervals (CIs) over an 11-year postbaseline period.

Results

During the mean 11.7 years of follow-up, 2,821 individuals expired. The HRs of mortality for METS-IR tertiles were 1.16 (95% CI, 1.01-1.34) in T3 after adjustment for metabolic parameters, but the T2 did not show statistical significance towards increases for incident mortality respectively. In subgroup analysis depending on the cause of mortality, higher METS-IR was associated with cancer mortality (HR, 1.23, 95% CI, 1.01-1.51) but not with cardiovascular mortality (HR, 1.14, 95% CI, 0.83-1.57) after adjustment for the same confounding variables.

Conclusion

The METS-IR may be a useful predictive marker for all-cause mortality and cancer mortality, but not for cardiovascular mortality in subjects over 60 years of age. This implies that early detection and intervention strategies for metabolic syndrome could potentially benefit this identified group.

Predictive value of insulin resistance surrogates for the development of diabetes in individuals with baseline normoglycemia: findings from two independent cohort studies in China and Japan

BACKGROUND

Insulin resistance (IR) plays a crucial role in the occurrence and progression of diabetes. This study aimed to evaluate and compare the predictive value of four IR surrogates, including the triglycerides glucose (TyG) index, TyG and body mass index (TyG-BMI), triglycerides/high-density lipoprotein cholesterol (TG/HDL-C) ratio, and the metabolic score for IR (MetS-IR) for diabetes in two large cohorts.

METHODS

A total of 116,661 adult participants from the China Rich Healthcare Group and 15,464 adult participants from the Japanese NAGALA cohort were included in the study. Multivariable Cox proportional hazards models were used to assess the standardized hazard ratio (HR) of the TyG index, TyG-BMI, TG/HDL-C ratio, and MetS-IR directly associated with diabetes. Receiver operating characteristic (ROC) curve and time-dependent ROC curve analysis were performed to evaluate and compare the predictive value of the four IR surrogates for diabetes.

RESULTS

In the two independent cohorts, the average follow-up time was 3.1 years in the China cohort, with 2681(2.30%) incident cases of diabetes recorded, and 6.13 years in the Japan cohort, with 373 incident cases (2.41%) of diabetes recorded. After adjusting for potential confounding factors, we found that among the four IR surrogates, TyG-BMI and MetS-IR showed stronger associations with diabetes. The stronger associations persisted even after further stratification by age, sex, hypertension, and obese subgroups. In terms of diabetes prediction, based on ROC analysis, TyG-BMI demonstrated the highest predictive accuracy for diabetes in the Chinese population, while both TyG-BMI and MetS-IR showed the highest predictive accuracy in the Japanese population. The results of further subgroup ROC analysis confirmed the robustness of these findings. Furthermore, the time-dependent ROC results indicated that among the four IR surrogates, MetS-IR exhibited the highest accuracy in predicting future diabetes at various time intervals in the Japanese population.

CONCLUSION

Our findings suggest that evaluating TyG-BMI and MetS-IR as IR surrogates may be the most useful for predicting diabetes events and assessing the risk of developing diabetes in East Asian populations.

Non-insulin-based insulin resistance indexes in predicting atrial fibrillation recurrence following ablation: a retrospective study

BACKGROUND

Insulin resistance (IR) is involved in the pathophysiological processes of arrhythmias. Increasing evidence suggests triglyceride and glucose (TyG) index, metabolic score for insulin resistance (METS-IR), triglyceride glucose-body mass index (TyG-BMI), and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio are simple and reliable surrogates for IR. Although they have been associated with atrial fibrillation (AF), evidence supporting this is limited. Here, this is the first study to investigate the association between TyG-BMI index and AF recurrence following radiofrequency catheter ablation (RFCA). The performance of the four non-insulin-based IR indexes in predicting AF recurrence after ablation was explored.

METHODS

A total of 2242 AF patients who underwent a de novo RFCA between June 2018 to January 2022 at two hospitals in China were included in this retrospective study. The predictive values of IR indexes for AF recurrence after ablation were assessed.

RESULTS

During 1-year follow-up, 31.7% of patients experienced AF recurrence. The multivariable analysis revealed that TyG index, METS-IR, and TyG-BMI index were independent risk factors for AF recurrence. Restricted cubic spline analysis revealed a connection between METS-IR, TyG-BMI index, and AF recurrence (P < 0.001). Furthermore, incorporating the METS-IR or TyG-BMI index to the basic risk model with fully adjusted factors considerably enhanced the forecast of AF recurrence, as demonstrated by the C-statistic, continuous net reclassification improvement, and integrated discrimination improvement.

CONCLUSIONS

TyG index, METS-IR, and TyG-BMI index were independently associated with AF recurrence following ablation. Among the four non-insulin-based IR indexes, TyG-BMI had the highest predictive value, followed by METS-IR.

Insulin resistance and coronary inflammation in patients with coronary artery disease: a cross-sectional study

BACKGROUND

Insulin resistance (IR) is associated with coronary artery disease (CAD) severity. However, its underlying mechanisms are not fully understood. Therefore, our study aimed to explore the relationship between IR and coronary inflammation and investigate the synergistic and mediating effects of coronary inflammation on the association between IR and CAD severity.

METHODS

Consecutive patients with CAD who underwent coronary angiography and coronary computed tomography angiography between April 2018 and March 2023 were enrolled. The triglyceride-glucose index (TyG index) and peri-coronary adipose tissue (PCAT) attenuation around the proximal right coronary artery (RCA) were used to evaluate IR and coronary inflammation, respectively. The correlation between the TyG index and PCAT attenuation was analyzed using linear regression models. Logistic regression models were further used for investigating the correlation of the TyG index and PCAT attenuation with CAD severity. A mediation analysis assessed the correlation between IR and CAD severity mediated by coronary inflammation.

RESULTS

A total of 569 participants (mean age, 62 ± 11 years; 67.8% men) were included in the study. PCAT attenuation was positively associated with the TyG index (r = 0.166; P < 0.001). After adjusting for potential confounders, the per standard deviation increment in the TyG index was associated with a 1.791 Hounsfield unit (HU) increase (95% confidence interval [CI], 0.920-2.662 HU; P < 0.001) in the PCAT attenuation. In total, 382 (67.1%) patients had multivessel CAD. The patients in the high-TyG index/high PCAT attenuation group had approximately 3.2 times the odds of multivessel CAD compared with those in the low-TyG index/low PCAT attenuation group (odds ratio, 3.199; 95%CI, 1.826-5.607; P < 0.001). Mediation analysis indicated that PCAT attenuation mediated 31.66% of the correlation between the TyG index and multivessel CAD.

CONCLUSIONS

The TyG index positively correlated with PCAT attenuation in patients with CAD. The TyG index and PCAT attenuation showed a synergistic correlation with multivessel CAD. Furthermore, PCAT attenuation partially mediated the relationship between the TyG index and CAD severity. Controlling inflammation in patients with high IR and coronary inflammation may provide additional benefits.

Association of the triglyceride glucose-body mass index with the extent of coronary artery disease in patients with acute coronary syndromes

BACKGROUND

Studies have shown that insulin resistance is strongly associated with the development of cardiovascular disease, and the triglyceride glucose-body mass index (TyG-BMI index) is considered to be a reliable surrogate marker of insulin resistance. There are limited studies on the relationship between TyG-BMI index and the extent of coronary artery disease in patients with acute coronary syndrome (ACS). This study aimed to investigate the relationship between TyG-BMI index and the extent of coronary artery disease in patients with ACS.

METHODS

Overall, 2,317 patients with ACS who underwent percutaneous coronary intervention at the Affiliated Hospital of Zunyi Medical University were included in this study. The TyG-BMI index was grouped according to the tertile method. The extent of coronary artery disease in patients with ACS was quantitatively assessed using the SYNTAX score, which was categorised as low (≤ 22), intermediate (23-32), and high risk (≥ 33).

RESULTS

In the overall population, multivariate logistic regression analyses showed that TyG-BMI index was associated with mid/high SYNTAX score in patients with ACS (odds ratio [OR] = 1.0041; 95% confidence interval [CI] = 1.0000-1.0079; p = 0.0310). Subgroup analyses showed that TyG-BMI index was an independent risk factor for mid/high SYNTAX score in female ACS patients after adjusting for multiple confounders (OR = 1.0100; 95% CI = 1.0000-1.0200; p = 0.0050), and that the risk of mid/high SYNTAX score was 2.49 times higher in the T3 group (OR = 2.4900; 95% CI = 1.2200-5.0600; p = 0.0120). Restricted cubic spline analysis showed a linear correlation between TyG-BMI index and complex coronary artery disease (SYNTAX score > 22) in women with ACS. In female ACS patients, inclusion of the TyG-BMI index did not improve the predictive power of the underlying risk model (net reclassification improvement: 0.0867 [-0.0256-0.1989], p = 0.1301; integrated discrimination improvement: 0.0183 [0.0038-0.0329], p = 0.0135).

CONCLUSIONS

TyG-BMI index is linearly associated with the degree of complex coronary artery disease in female ACS patients. However, the inclusion of the TyG-BMI index did not improve the predictive power of the underlying risk model for female ACS patients.

Triglyceride-glucose body mass index predicts prognosis in patients with ST-elevation myocardial infarction

Triglyceride glycemic-body mass index (TyG-BMI) is a simple and reliable surrogate for insulin resistance (IR). However, it is still unclear if TyG-BMI has any predictive value in patients having percutaneous coronary intervention (PCI) for ST-segment elevation myocardial infarction (STEMI). The purpose of this study was to examine the TyG-BMI index's prognostic significance and predictive power in patients with STEMI. The study comprised a total of 2648 consecutive STEMI patients who underwent PCI. The primary endpoint was the occurrence of major adverse cardiovascular events (MACE), defined as the combination of all-cause death, nonfatal myocardial infarction, nonfatal stroke, and coronary revascularization. The TyG-BMI index was formulated as ln [fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2] × BMI. 193 patients in all experienced MACE over a median follow-up of 14.7 months. There was a statistically significant difference between the Kaplan-Meier survival curves for the TyG-BMI index tertiles (log-rank test, p = 0.019) for the cumulative incidence of MACE. The adjusted HRs for the incidence of MACE in the middle and highest quartiles of the TyG-BMI index compared with the lowest quartile were 1.37 (95% CI 0.92, 2.03) and 1.53 (95% CI 1.02, 2.29), respectively, in the fully adjusted Cox regression model. At six months, one year, and three years, the TyG-BMI area under the curve (AUC) for predicting MACE was 0.691, 0.666, and 0.637, respectively. Additionally, adding the TyG-BMI index to the risk prediction model enhanced outcome prediction. In STEMI patients undergoing PCI, TyG-BMI was independently linked to MACE. TyG-BMI could be a simple and solid way to assess MACE risk and prognosis.

Association between the cumulative average triglyceride glucose-body mass index and cardiovascular disease incidence among the middle-aged and older population: a prospective nationwide cohort study in China

BACKGROUND

Findings from earlier research have established that insulin resistance (IR) is implicated in atherosclerosis progression, representing a noteworthy risk factor for cardiovascular disease (CVD). Recently, the triglyceride glucose-body mass index (TyG-BMI) has been introduced as a straightforward and robust alternative indicator for early detection of IR. Nevertheless, there is a scarcity of studies that have examined the capability of TyG-BMI for predicting incident CVD. Consequently, the core objective of this study was to determine whether the cumulative average TyG-BMI correlated with CVD incidence.

METHODS

All data was sourced from the China Health and Retirement Longitudinal Study (CHARLS). The exposure was the cumulative average TyG-BMI, determined by the average of TyG-BMI values for the baseline and follow-up investigations (Wave 1 in 2011, Wave 3 in 2015, respectively). The calculation of TyG-BMI involved a combination of triglyceride, fasting blood glucose, and body mass index. The primary outcome was incident CVD. Logistic regression analyses as well as restricted cubic spline (RCS) regression analyses were performed for examining the association between the cumulative average TyG-BMI and CVD incidence.

RESULTS

In all, 5,418 participants were enrolled in our analysis, with 2,904 (53.6%) being female, and a mean (standard deviation, SD) age of 59.6 (8.8) years. The mean (SD) cumulative average TyG-BMI among all participants was 204.9 (35.7). Totally, during a 4-year follow-up, 543 (10.0%) participants developed CVD. The fully adjusted logistic regression analysis revealed a significant association between the cumulative average TyG-BMI and incident CVD [odds ratio (OR), 95% confidence interval (CI): 1.168, 1.040-1.310, per 1 SD increase]. The RCS regression analysis displayed a positive, linear association of the cumulative average TyG-BMI with CVD incidence (P for overall = 0.038, P for nonlinear = 0.436).

CONCLUSIONS

Our study revealed a noteworthy correlation between the cumulative average TyG-BMI and incident CVD among the middle-aged and older population. The cumulative average TyG-BMI emerges as a valuable tool that may enhance the primary prevention and treatment of CVD.

Triglyceride-glucose index as a suitable non-insulin-based insulin resistance marker to predict cardiovascular events in patients undergoing complex coronary artery intervention: a large-scale cohort study

BACKGROUND

Insulin resistance (IR), a hallmark of proceeding diabetes and cardiovascular (CV) disease, has been shown to predict prognosis in patients undergoing percutaneous coronary intervention (PCI). The triglyceride-glucose (TyG) index, triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio and metabolic score for insulin resistance (METS-IR) have been shown to be simple and reliable non-insulin-based surrogates for IR. However, limited studies have determined the associations between distinct non-insulin-based IR markers and CV outcomes in patients undergoing complex PCI who are at higher risk of CV events after PCI. Therefore, this study aimed to investigate and compare the prognostic value of these markers in patients undergoing complex PCI.

METHODS

This was a descriptive cohort study. From January 2017 to December 2018, a total of 9514 patients undergoing complex PCI at Fuwai Hospital were consecutively enrolled in this study. The 3 IR indices were estimated from the included patients. The primary study endpoint was CV events, defined as a composite of CV death, nonfatal myocardial infarction and nonfatal stroke.

RESULTS

During a median follow-up of 3.1 years, 324 (3.5%) CV events occurred. Multivariable Cox regression models showed per-unit increase in the TyG index (hazard ratio [HR], 1.42; 95% confidence interval [CI] 1.13-1.77), rather than per-unit elevation in either Ln(TG/HDL-C ratio) (HR, 1.18; 95%CI 0.96-1.45) or METS-IR (HR, 1.00; 95%CI 0.98-1.02), was associated with increased risk of CV events. Meanwhile, adding the TyG index to the original model led to a significant improvement in C-statistics (0.618 vs. 0.627, P < 0.001), NRI (0.12, P = 0.031) and IDI (0.14%, P = 0.003), whereas no significant improvements were observed when adding Ln (TG/HDL-C ratio) or METS-IR (both P > 0.05) to the original model.

CONCLUSIONS

The TyG index, not TG/HDL-C ratio and METS-IR, was positively associated with worse CV outcomes in patients undergoing complex PCI. Our study, for the first time, demonstrated that the TyG index can serve as the suitable non-insulin-based IR marker to help in risk stratification and prognosis in this population.

Insulin resistance is associated with the presence and severity of retinopathy in patients with type 2 diabetes

BACKGROUND

To assess the relationship between novel insulin resistance (IR) indices and the presence and severity of diabetic retinopathy (DR) in patients with type 2 diabetes.

METHODS

This is a cross-sectional study involving 2211 patients. The study outcomes were DR events. The study exposures were IR indices including estimated glucose disposal rate (eGDR), natural logarithm of glucose disposal rate (lnGDR), metabolic insulin resistance score (METS-IR), triglyceride glucose index-body mass index (TyG-BMI), triglyceride glucose index-waist-to-hip ratio (TyG-WHR), and triglyceride/high-density lipoprotein cholesterol(TG/HDL-c ratio). We used binary and multivariate ordered logistic regression models to estimate the association between different IR indices and the presence and severity of DR. Subject work characteristic curves were used to assess the predictive power of different IR indices for DR.

RESULTS

DR was present in 25.4% of participants. After adjusting for all covariates, per standard deviation (SD) increases in eGDR (ratio [OR] 0.38 [95% CI 0.32-0.44]), lnGDR (0.34 [0.27-0.42]) were negatively associated with the presence of DR. In contrast, per SD increases in METS-IR (1.97 [1.70-2.28]), TyG-BMI (1.94 [1.68-2.25]), TyG-WHR (2.34 [2.01-2.72]) and TG/HDL-c ratio (1.21 [1.08-1.36]) were positively associated with the presence of DR. eGDR was strongly associated with severity of DR. Of all variables, eGDR had the strongest diagnostic value for DR (AUC = 0.757).

CONCLUSIONS

Of the six IR indices, eGDR was significantly associated with the presence and severity of DR in patients with type 2 diabetes. eGDR has a good predictive value for DR. Thus, eGDR maybe a stronger marker of DR.

Impact of the baseline insulin resistance surrogates and their longitudinal trajectories on cardiovascular disease (coronary heart disease and stroke): a prospective cohort study in rural China

Background

This study aimed to assess the association of baseline insulin resistance (IR) surrogates and their longitudinal trajectories with cardiovascular diseases (CVD) to provide a useful reference for preventing CVD.

Methods

This study was a prospective cohort study conducted in the 51st Regiment of the Third Division of Xinjiang Corps. A total of 6362 participants were recruited in 2016 to conduct the baseline survey, and the follow-up surveys in 2019, 2020, 2021, and 2022. The Kaplan-Meier method was used to estimate the cumulative incidence of CVD according to the baseline IR surrogates of metabolic insulin resistance score (METS-IR) and triglyceride-glucose (TyG) index. Cox regression models were used to assess the association between the baseline IR surrogates and CVD. The impact of the longitudinal trajectories of the IR surrogates on CVD was analyzed after excluding those with IR surrogate data measured ≤2 times. Based on the group-based trajectory model (GBTM), the trajectory patterns of IR surrogates were determined. The Kaplan-Meier method was used to estimate the cumulative incidence of CVD in each trajectory group of METS-IR and TyG index. Cox regression models were used to analyze the association between different trajectory groups of each index and CVD. In addition, the Framingham model was utilized to evaluate whether the addition of the baseline IR surrogates increased the predictive potential of the model.

Results

Baseline data analysis included 4712 participants. During a median follow-up of 5.66 years, 572 CVD events were recorded (mean age, 39.42 ± 13.67 years; males, 42.9%). The cumulative CVD incidence increased with the ascending baseline METS-IR and TyG index quartiles (Q1-Q4). The hazard ratio and 95% confidence interval for CVD risk in Q4 of the METS-IR and TyG index were 1.79 (1.25, 2.58) and 1.66 (1.28, 2.17), respectively, when compared with Q1. 4343 participants were included in the trajectory analysis, based on the longitudinal change patterns of the METS-IR and TyG index, the following three trajectory groups were identified: low-increasing, moderate-stable, and elevated-increasing groups. Multivariate Cox regression revealed that the hazard ratio (95% confidence interval) for CVD risk in the elevated-increasing trajectory group of the METS-IR and TyG index was 2.13 (1.48, 3.06) and 2.63 (1.68, 4.13), respectively, when compared with the low-rising group. The C-index, integrated discrimination improvement value, and net reclassification improvement value were enhanced after adding the baseline METS-IR and TyG index values to the Framingham model (P<0.05).

Conclusions

Elevated baseline IR surrogates and their higher long-term trajectories were strongly associated with a high risk of CVD incidence in Xinjiang's rural areas. Regular METS-IR and TyG index monitoring can aid in the early detection of CVD-risk groups.

Association between triglyceride glucose-body mass and one-year all-cause mortality of patients with heart failure: a retrospective study utilizing the MIMIC-IV database

BACKGROUND

The triglyceride glucose-body mass (TyG-BMI) index is acknowledged as both a reliable indicator of the risk of cardiovascular disease and an accurate surrogate biomarker for evaluating insulin resistance (IR). The importance of the TyG-BMI index among people with heart failure (HF), however, requires more investigation. The objective of this study was to inquire about the relationship between HF patients' TyG-BMI index and their risk of 360-day mortality.

METHODS

The Medical Information Mart for Intensive Care (MIMIC-IV) database provided the study's patient data, which were divided into quartiles according to their TyG-BMI index. The endpoint was mortality from all causes within 360 days. Kaplan-Meier analysis was used to compare this primary endpoint amongst the four groups indicated above. The association between the TyG-BMI index and the endpoint was investigated using restricted cubic splines and Cox proportional hazards analysis.

RESULTS

The study enrolled a total of 423 patients with HF (59.2% male), of whom 70 patients (16.9%) died within 360 days. Patients with higher TyG-BMI indexes had significantly lower mortality risks, according to the Kaplan-Meier analysis (log-rank P = 0.003). Furthermore, the restricted cubic spline analysis illustrated a decrease in the risk of all-cause mortality with an increasing TyG-BMI index. Additionally, multivariable Cox proportional hazards analyses showed that the risk of 360-day death from all causes was considerably higher in the lowest quartile of TyG-BMI. In comparison to the lowest TyG-BMI group, the fully adjusted Cox model yielded a hazard ratio (HR) of 0.24 (95% CI: 0.10, 0.59; p = 0.002) for 360-day mortality.

CONCLUSIONS

In patients diagnosed with HF, a lower TyG-BMI index is strongly related to a higher risk of 360-day mortality. This index can be employed to categorize the risk levels of patients with HF and predict their one-year all-cause mortality .

Triglyceride glucose-body mass index and cardiovascular mortality in patients undergoing peritoneal dialysis: a retrospective cohort study

BACKGROUND

Recent studies have shown that triglyceride glucose-body mass index (TyG-BMI) is associated with the risk of ischemic stroke and coronary artery disease. However, little attention has been given to the association between TyG-BMI and cardiovascular disease (CVD) mortality in patients undergoing peritoneal dialysis (PD). Therefore, this study aimed to explore the relationship between TyG-BMI and CVD mortality in southern Chinese patients undergoing PD.

METHODS

Incident patients receiving PD from January 1, 2006, to December 31, 2018, with baseline serum triglyceride, glucose, and body mass index (BMI) information, were recruited for this single-center retrospective cohort study. TyG-BMI was calculated based on fasting plasma glucose, triglyceride, and BMI values. The association between TyG-BMI, CVD and all-cause mortality was evaluated using a multivariate-adjusted Cox proportional hazard regression model.

RESULTS

Of 2,335 patients, the mean age was 46.1 ± 14.8 years; 1,382 (59.2%) were male, and 564 (24.2%) had diabetes. The median TyG-BMI was 183.7 (165.5-209.2). Multivariate linear regression showed that advanced age, male sex, history of CVD, higher levels of albumin and low-density lipoprotein cholesterol, and higher urine output were correlated with a higher TyG-BMI (P < 0.05). During a median follow-up period of 46.6 (22.4-78.0) months, 615 patients died, of whom 297 (48.2%) died as a result of CVD. After adjusting for demographics and comorbidities, TyG-BMI was significantly associated with an increased risk of CVD mortality (hazard ratio [HR] 1.51, 95% confidence interval [CI] 1.05-2.17) and all-cause mortality (HR 1.36, 95% CI 1.05-1.75). After full adjustment, the 28% risk of CVD mortality (HR 1.28, 95% CI 1.13-1.45) and 19% risk of all-cause mortality were elevated (HR 1.19, 95% CI 1.09-1.31) when TyG-BMI increased by 1 stand deviation (SD) (34.2).

CONCLUSIONS

A higher baseline TyG-BMI was independently associated with an increased risk of CVD and all-cause mortality in patients receiving PD.

Mets-IR as a predictor of cardiovascular events in the middle-aged and elderly population and mediator role of blood lipids

Background

Cardiovascular disease (CVD) is a global health concern, with a significant impact on morbidity and mortality rates. Using fasting glucose, fasting triglycerides, body mass index (BMI), and high-density lipoprotein cholesterol (HDL-C), the metabolic score of insulin resistance (Mets-IR), a novel index created by Mexican researchers to assess insulin sensitivity, is a more precise way to measure insulin sensitivity. This study aimes to explore the association between Mets-IR and CVD, as well as investigate the potential mediating role of of low-density lipoprotein cholesterol (LDL-C).

Methods

The study's data came from the 2011 and 2018 China Health and Retirement Longitudinal Studies (CHARLS). We used three logistic regression models to account for the potential effects of ten factors on cardiovascular disease/stroke/heart disease. Moreover, We performed mediation analyses to evaluate the role of LDL-C in the association between Mets-IR and incident CVD.

Results

This study comprised 4,540 participants, of whom 494 (10.88%) were found to develop disease (CVD). Each interquartile range (IQR) increased in Mets-IR raised the risk of developing CVD by 38% (OR=1.38; 95% CI, 1.21-1.56) and there was a linear dose-response relationship between Mets-IR and the risk of new-onset cardiovascular disease, stroke, and heart disease (P overall<0.05, P non-linear>0.05). Approximately 5% (indirect effect/total effect) of the significant association of Mets-IR with stroke was mediated by LDL-C, respectively. With the addition of Mets-IR to the base model, the continuous net reclassification improvement and integrated discrimination improvement for predicting cardiovascular disease increased by 0.175 (P <0.001) and 0.006 (P <0.001), respectively.

Conclusion

ets-IR is associated with an increased risk of cardiovascular disease/stroke/cardiac issues, with LDL-C mediating these relationships. Improving insulin sensitivity and lipid regulation may be essential and effective preventive measures for cardiovascular events.

The metabolic score for insulin resistance in the prediction of major adverse cardiovascular events in patients after coronary artery bypass surgery: a multicenter retrospective cohort study

BACKGROUND

The metabolic score for insulin resistance (METS-IR) is a simple, convenient, and reliable marker for resistance insulin (IR), which has been regarded as a predictor of cardiovascular disease (CVD) and cardiovascular events. However, few studies examined the relationship between METS-IR and prognosis after coronary artery bypass graft (CABG). This study aimed to investigate the potential value of METS-IR as a prognostic indicator for the major adverse cardiovascular events (MACE) in patients after CABG.

METHOD

1100 CABG patients were enrolled in the study, including 760 men (69.1%) and 340 women (30.9%). The METS-IR was calculated as Ln [(2 × FPG (mg/dL) + fasting TG (mg/dL)] × BMI (kg/m²)/Ln [HDL-C (mg/dL)]. The primary endpoint of this study was the occurrence of major adverse cardiovascular events (MACE), including a composite of all-cause death, non-fatal myocardial infarction (MI), coronary artery revascularization, and stroke.

RESULT

The following-up time of this study was 49-101 months (median, 70 months; interquartile range, 62-78 months). During the follow-up period, there were 243 MACEs (22.1%). The probability of cumulative incidence of MACE increased incrementally across the quartiles of METS-IR (log-rank test, p < 0.001). Multivariate Cox regression analysis demonstrated a hazard ratio (95% CI) of 1.97 (1.36-2.86) for MACE in quartile 4 compared with participants in quartile 1. The addition of the METS-IR to the model with fully adjusting variables significantly improved its predictive value [C-statistic increased from 0.702 to 0.720, p < 0.001, continuous net reclassification improvement (NRI) = 0.305, < 0.001, integrated discrimination improvement (IDI) = 0.021, p < 0.001].

CONCLUSION

METS-IR is an independent and favorable risk factor for predicting the occurrence of MACE and can be used as a simple and reliable indicator that can be used for risk stratification and early intervention in patients after CABG.

Association between non-insulin-based insulin resistance indices and cardiovascular events in patients undergoing percutaneous coronary intervention: a retrospective study

BACKGROUND

Insulin resistance (IR) has been confirmed that getting involved in the pathophysiological process of cardiovascular diseases (CVD). Recently, increasing evidence suggests metabolic score for insulin resistance (METS-IR), triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, triglyceride and glucose (TyG) index, triglyceride glucose-body mass (TyG-BMI) index are simple and reliable surrogates for IR. However, their abilities in predicting cardiovascular outcomes in patients undergoing percutaneous coronary intervention (PCI) are not well explored. Therefore, this study aimed to investigate the association and evaluate the predictive performance of each index.

METHODS

A total of 2533 consecutive participants undergoing PCI were included in this study, and the data from 1461 patients were used to determine the correlation of these non-insulin-based IR indices with major adverse cardiac and cerebrovascular events (MACCEs) via performing the multivariate logistic models and restricted cubic splines (RCS).

RESULTS

During a median of 29.8 months follow-up, 195 cases of 1461 patients experienced incident MACCEs. In the overall population, both univariate and multivariate logistic regression analyses indicated no statistically significant connection between these IR indices and MACCEs. Subgroup analyses revealed significant interactions between age subgroups and TyG-BMI index, as well as METS-IR, and between sex subgroups and TyG index. In elderly patients, per 1.0-SD increment in TyG-BMI index and METS-IR had a significant association with MACCEs, with odds ratios (ORs) [95% confidence interval (CI)] of 1.24 (1.02-1.50) and 1.27 (1.04-1.56), respectively (both P < 0.05). Moreover, in female patients, all the IR indices showed significant associations with MACCEs. Multivariable-adjusted RCS curves demonstrated a linear relationship between METS-IR and MACCEs in elderly and female patients, respectively. However, all the IR indices failed to enhance the predictive performance of the basic risk model for MACCEs.

CONCLUSION

All the four IR indices showed a significant association with MACCEs in female individuals, whereas only TyG-BMI index and METS-IR showed associations in elderly patients. Although the inclusion of these IR indices did not improve the predictive power of basic risk model in either female or elderly patients, METS-IR appears to be the most promising index for secondary prevention of MACCEs and risk stratification in patients undergoing PCI.

Relationship between Atherogenic Dyslipidaemia and Lipid Triad and Scales That Assess Insulin Resistance

BACKGROUND

Atherogenic dyslipidaemia (AD) and lipid triad (LT) are characterised by high triglyceride levels together with low HDL and normal or high LDL cholesterol and are favoured by a persistent state of insulin resistance (IR), which increases the release of free fatty acids from abdominal adipose tissue. This alteration in the lipid profile favours the accelerated development of atherosclerosis, which is the most important cause of morbidity and mortality in all countries in the developed and developing world. One of the elements that plays a major role in the genesis of AD is IR. The aim of this study was to determine the relationship between variables that assess atherogenic risk (AD and LT) and scales that assess the risk of presenting insulin resistance.

METHODS

A descriptive cross-sectional study of 418,343 workers was conducted to evaluate atherogenic dyslipidaemia and lipid triad; a relationship with three insulin resistance risk scales (Triglycerides/HDL, TyG index, METS-IR) was established. The usefulness of IR risk scales for predicting AD and LT was calculated by applying ROC curves, obtaining the area under the curve (AUC) and cut-off points with their sensitivity, specificity, and Youden index. Multivariate analysis was performed by binary logistic regression.

RESULTS

The prevalence of high-risk values for insulin resistance with all of the scales is much higher in people with AD and LT compared to those without. The ROC curves present us with an AUC with the three insulin resistance risk scales for the two dyslipidaemias studied with figures ranging between 0.856 and 0.991, which implies that the results are good/very good.

CONCLUSIONS

A relationship between atherogenic dyslipidaemia and the three insulin resistance risk scales assessed is revealed, with higher IR mean values and prevalence in people with atherogenic dyslipidaemia and lipid triad. The three scales make it possible to adequately classify the presence of AD and LT. The highest AUC is presented by the triglycerides/HDL scale, with a result close to 1. METS-IR is the most recommended formula to estimate insulin resistance.