Triglyceride-glucose index and triglyceride to high-density lipoprotein cholesterol ratio as potential cardiovascular disease risk factors: an analysis of UK biobank data

Triglyceride to high-density lipoprotein ratio as a predictor for 10-year cardiovascular disease in individuals with diabetes in Thailand

BACKGROUND

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide. The triglyceride to high-density lipoprotein cholesterol (TG/HDL) ratio has emerged as a potential marker for CVD risk. However, its predictive value for high 10-year predicted Cardiovascular (CV) risk remains unclear; This study evaluates the predictive value of the TG/HDL-C ratio for 10-year cardiovascular risk using the Framingham Heart Study (FHS) risk prediction model in individuals with Type 2 Diabetes Mellitus (T2DM).

METHODS

A cross-sectional study was conducted on 61,004 adults from 2014,2015, and 2018 aged 30-74 years with T2DM, without a history of CVD. The FHS model was used to estimate 10-year predicted CV risk, and high CVD risk was defined as ≥ 20%. ROC curve analysis was used to determine the optimal TG/HDL cutoff for high 10-year predicted CV risk in the overall population and age-specific subgroups. Logistic regression was performed to find the association between TG/HDL and high 10-year predicted CV risk, adjusting for potential confounders.

RESULTS

The optimal TG/HDL-C cutoff was 2.52 (AUC = 0.618, 95% CI: 0.612-0.624), with 67% sensitivity and 50% specificity. Higher TG/HDL were associated with increased odds of high predicted CVD risk in a dose-dependent manner, with an adjusted odds ratio (AOR) of 5.16 (95% CI: 4.86-5.49) in the highest TG/HDL quartile (> 4.91). Age-stratified analysis identified lower cutoffs for older adults (≥ 60 years: 2.42, AUC = 0.694) than younger individuals (< 60 years: 2.98, AUC = 0.636), indicating stronger predictive performance in older adults.

CONCLUSIONS

The TG/HDL ratio is significantly associated with 10-year predicted CVD risk in T2DM with age-specific differences in predictive value. The lower cutoff for older adults (2.42) suggests even modest elevations indicate increased risk. These findings support TG/HDL integration into routine CVD risk assessments and highlight the importance of age-specific cutoffs for improved risk stratification.

A non-fasting marker of metabolic syndrome in a high-risk population

OBJECTIVE

The rising prevalence of metabolic syndrome among young adults has prompted studies of fasting triglyceride-glucose (TyG) index as a marker of insulin resistance. We aimed to evaluate metabolic syndrome in young adults using non-fasting TyG index and a high-risk genetic model, 22q11.2 microdeletion.

METHODS

We assessed metabolic syndrome and its components in 350 adults (50.6% female) aged 18-59 (median 27.7, IQR 22.5-38.1) years with typical 22q11.2 microdeletions. We used multivariable logistic regression and receiver operating characteristic (ROC) curves to evaluate the association of non-fasting TyG index with metabolic syndrome.

RESULTS

Non-fasting TyG index was significantly associated with metabolic syndrome (OR 3.23, 95% CI 2.27-4.59, p < 0.0001), independent of age, sex, BMI, and hypothyroidism. Non-fasting TyG index was positively correlated with number of metabolic syndrome components per individual. In this high-risk population, prevalence of metabolic syndrome was 21.7% (60/277) among young adults (18-39 years), and 45.2% (33/73, p < 0.0001) among middle-aged adults (40-59 years). Non-fasting TyG index ≥4.81 was an effective indicator of prevalent metabolic syndrome, with an area under the ROC curve of 0.83 (95% CI 0.78-0.88).

CONCLUSIONS

The results support non-fasting TyG index as a practical marker of metabolic syndrome, and by extension insulin resistance, encouraging future studies evaluating non-fasting TyG index in young adults as a predictor of cardiovascular disease later in life. The high prevalence of metabolic syndrome at a young age in 22q11.2 microdeletion demonstrates the potential value of this genetic high-risk population for future prospective studies, with animal and cellular models available.

Relationship between insulin resistance surrogate markers with diabetes and dyslipidemia: A Bayesian network analysis of Korean adults

Insulin resistance (IR) can be optimally assessed using the euglycemic clamp, but practical clinical limitations necessitate surrogate markers. This study leveraged the Bayesian network analysis to evaluate three established IR markers: the Homeostatic Model Assessment of IR (HOMA-IR) using insulin level and fasting blood glucose (FBG), TG-Glucose (TyG) index using triglycerides (TG) and FBG, and TG-to-HDL ratio (TG/HDL ratio) using TG and high-density lipoprotein (HDL), based on the Korean National Health and Nutrition Examination Survey data (2019-2021). Our analysis revealed a sequential association pattern (TG/HDL ratio → TyG index → HOMA-IR), positioning the TyG index as a central connecting marker. The HOMA-IR exhibited strong predictive power for diabetes, while the TG/HDL ratio was most effective for assessing dyslipidemia. However, both had limited crossover utility. In contrast, the TyG index bridged this gap, demonstrating robust predictive capability for both conditions. The Markov blanket analysis illuminated the distinctive metabolic signatures of each marker: The TyG index displayed balanced glucose-lipid metabolic contributions, the HOMA-IR predominantly reflected glucose metabolism and obesity characteristics, and the TG/HDL ratio emphasized lipid metabolism. Notably, the TyG index's predictive performance showed significant enhancement when integrated with obesity information, contrasting with the HOMA-IR's minimal response owing to its inherent incorporation of obesity characteristics. These findings position the TyG index as a superior clinical marker, offering both comprehensive predictive capability and enhanced performance through synergistic integration with obesity measures. While each marker demonstrated reliability, the TyG index's unique combination of versatility and scalability establishes it as an effective tool for comprehensive metabolic risk assessment.

Clinical staging to guide management of metabolic disorders and their sequelae: a European Atherosclerosis Society consensus statement

Obesity rates have surged since 1990 worldwide. This rise is paralleled by increases in pathological processes affecting organs such as the heart, liver, and kidneys, here termed systemic metabolic disorders (SMDs). For clinical management of SMD, the European Atherosclerosis Society proposes a pathophysiology-based system comprising three stages: Stage 1, where metabolic abnormalities such as dysfunctional adiposity and dyslipidaemia occur without detectable organ damage; Stage 2, which involves early organ damage manifested as Type 2 diabetes, asymptomatic diastolic dysfunction, metabolic-associated steatohepatitis (MASH), and chronic kidney disease (CKD); and Stage 3, characterized by more advanced organ damage affecting multiple organs. Various forms of high-risk obesity, driven by maintained positive energy balance, are the most common cause of SMD, leading to ectopic lipid accumulation and insulin resistance. This progression affects various organs, promoting comorbidities such as hypertension and atherogenic dyslipidaemia. Genetic factors influence SMD susceptibility, and ethnic disparities in SMD are attributable to genetic and socioeconomic factors. Key SMD features include insulin resistance, inflammation, pre-diabetes, Type 2 diabetes, MASH, hypertension, CKD, atherogenic dyslipidaemia, and heart failure. Management strategies involve lifestyle changes, pharmacotherapy, and metabolic surgery in severe cases, with emerging treatments focusing on genetic approaches. The staging system provides a structured approach to understanding and addressing the multi-faceted nature of SMD, which is crucial for improving health outcomes. Categorization of SMD abnormalities by presence and progression is aimed to improve awareness of a multi-system trait and encourage a tailored and global approach to treatment, ultimately aiming to reduce the burden of obesity-related comorbidities.

Triglyceride-glucose index: a novel predictor of major adverse cardiovascular events and cerebrovascular events in patients with acute ST-segment elevation myocardial infarction

INTRODUCTION

Numerous studies have indicated the association of the triglyceride-glucose index (TyG) index with coronary artery disease, particularly myocardial infarction. However, limited mention exists regarding the predictive effects of major adverse cardiovascular events (MACE) and major adverse cardiac and cerebrovascular events (MACCE) in patients with ST-segment Elevation Myocardial Infarction (STEMI). This study aimed to investigate the predictive role of the TyG index on MACE and MACCE within 30 days in patients with STEMI.

METHODS

This study enrolled 586 patients with STEMI and conducted lipid, glucose, and myocardial biochemical testing. The TyG index was calculated; univariate analysis, multivariate analysis, and logistic regression analysis were employed to further investigate the correlation of the TyG index with MACE and MACCE. Subsequently, restricted cubic spline (RCS) analysis was conducted to determine whether they exhibit a linear correlation.

RESULTS

The study reported 105 MACCE patients. The results revealed a significant positive correlation between the TyG index and the occurrence of MACE and MACCE (odds ratio [OR] = 1.461, 95% confidence interval [CI] [1.091-1.956], p = 0.011 and OR = 1.427, 95%CI [1.064-1.914], p = 0.017, respectively). In univariate and multivariate analysis, the TyG index remains correlated with MACE and MACCE even after adjusting for related variables. Subsequent RCS analysis, accounting for different factors such as age, white blood cell count, and N-terminal pro-B-type natriuretic peptide (NT-proBNP), indicated that the correlation of TyG index with MACE and MACCE remains linear (p-non-linear = 0.662, p-non-linear = 0.781, respectively).

CONCLUSION

The TyG index effectively predicts MACE and MACCE in patients with STEMI within 30 days.

CLINICAL TRIAL NUMBER

Not applicable.

Associations of Socioeconomic Status and Phenotypic Frailty With Incident COPD: Findings From UK Biobank Participants

BACKGROUND

The independent, mediation, interaction, and joint effects of socioeconomic status (SES) and phenotypic frailty on the incidence of COPD are unclear.

RESEARCH QUESTION

Do SES and frailty increase the risk of COPD independently or jointly? Is there an interaction between the 2 factors in incident COPD? Does frailty play a mediating role between SES and COPD?

STUDY DESIGN AND METHODS

This study included 396,106 UK Biobank participants without COPD at baseline. Latent class analysis was used to define the SES of participants. Frailty was defined by the frailty phenotypes according to 5 factors. Cox regression models were used to examine the associations and calculate hazard ratios (HRs) and 95% CIs. Mediation and interaction analyses were used to explain the associations between SES and frailty on COPD risk.

RESULTS

During a median follow-up period of 13.5 years, 12,626 individuals were diagnosed with COPD. Compared with high SES or robust individuals, low SES (HR, 2.69; 95% CI, 2.48-2.92) or frailty (HR, 2.75; 95% CI, 2.58-2.93) increased the risk of COPD, respectively; 11.80% of the association between SES and COPD was mediated by frailty. In addition, there was a statistically significant additive interaction of low SES and frailty with COPD incidence (relative risk due to interaction, 3.591; 95% CI, 2.189-4.992; attributable proportion due to the interaction, 0.433; 95% CI, 0.276-0.589). Compared with robust individuals with high SES, frail individuals with low SES have the highest risk of COPD (HR, 7.85; 95% CI, 6.96-8.86).

INTERPRETATION

Our findings indicate that low SES and frailty are independent risk factors for COPD, and these 2 factors also have synergistic interaction in COPD. Frailty partially mediated the association between SES and COPD. Thus, the early identification and reversal of frailty may minimize the risk of COPD, especially in individuals with low SES.

Comparative Predictive Value of the TyG Index and UHR for Lower Extremity Artery Disease in Type 2 Diabetes: A Retrospective Analysis

Objective

To compare the predictive value of triglyceride glucose index (TyG) and the ratio of serum uric acid (SUA) to high-density lipoprotein cholesterol (HDL-C) (UHR) for lower extremity atherosclerotic disease (LEAD) in type 2 diabetes (T2DM) patients.

Methods

303 patients with T2DM were divided into LEAD group (n=192) and non-LEAD group (n=111) based on the results of lower extremity vascular color Doppler ultrasound. All patients were divided into a training set and a validation set at a 7:3 ratio. In the training set, Least absolute shrinkage and selection operator (LASSO) regression was applied to screen for predictive factors of LEAD, and a multivariate logistic regression model was constructed to analyze the predictive factors, with a nomogram being plotted. The discriminative ability and calibration of the model were evaluated using the receiver operating characteristic (ROC) curve area under the curve (AUC) and calibration curves in both the training and validation sets. Decision curve analysis (DCA) was used to evaluate the clinical net benefit.

Results

The variables selected by the LASSO regression included age, pulse pressure difference (PP), TyG, and UHR. The multivariate logistic regression model indicated that age, PP, TyG, and UHR were predictive factors for LEAD in T2DM patients (P<0.05). ROC curve analysis suggested that the discriminatory ability was in the following order: the nomogram model (AUC=0.872), TyG (AUC=0.751), and UHR (AUC=0.709), which were greater than that of age and PP. TyG and UHR cut-off values were 9.836 and 216.248, respectively. The specificities of TyG and UHR were 0.760 and 0.547, and the sensitivities were 0.629 and 0.807, respectively. The calibration curve showed the model's predictions matched actual conditions. DCA verified the model's clinical benefit.

Conclusion

Both TyG and UHR have good predictive value and are suitable for screening LEAD in T2DM patients.

Remnant cholesterol inflammatory index and its association with all-cause and cause-specific mortality in middle-aged and elderly populations: evidence from US and Chinese national population surveys

BACKGROUND

The remnant cholesterol inflammatory index (RCII) is a novel metric that combines remnant cholesterol and high-sensitivity C-reactive protein, reflecting the metabolic and inflammatory risk. This study investigates the association between RCII and long-term risks of all-cause and cause-specific mortality in middle-aged and elderly populations in the US and China.

METHOD

We analyzed data from the National Health and Nutrition Examination Survey (NHANES) and the China Health and Retirement Longitudinal Study (CHARLS), including 7,565 and 12,932 participants aged 45 years and older, respectively. The participants were categorized into quartiles based on natural log-transformed RCII (lnRCII) values. Kaplan-Meier survival analysis, Cox proportional hazards models, restricted cubic splines (RCS) and mediation analysis were used to examine the relationship between lnRCII and mortality outcomes, adjusting for potential covariates.

RESULT

The mean age of the participants was 59.90 ± 10.44 years (NHANES) and 58.64 ± 9.78 years (CHARLS), with 53.28% and 52.50% female, respectively. Kaplan-Meier survival analysis showed that higher lnRCII quartiles (≥ 0.79 in NHANES, ≥ -0.13 in CHARLS) were significantly associated with increased all-cause mortality risk (p < 0.001). Each standard deviation (SD) increase in lnRCII corresponded to a higher risk of all-cause mortality, and the hazard ratios (HRs) and 95% confidence interval (CI) were 1.29 (95% CI: 1.21-1.36) in NHANES and 1.26 (95% CI: 1.15-1.38) in CHARLS. In NHANES, lnRCII was also associated with elevated risks of cardiovascular mortality (HR = 1.21, 95% CI: 1.08-1.35) and cancer mortality (HR = 1.30, 95% CI: 1.09-1.55). RCS analysis indicated a J-shaped relationship between lnRCII and both all-cause and cardiovascular mortality, and a linear association with cancer mortality. Mediation analysis showed that systolic blood pressure and fasting plasma glucose partially mediated these associations. Subgroup analyses suggested a stronger association between lnRCII and all-cause mortality in middle-aged US participants (p for interaction = 0.010).

CONCLUSIONS

Elevated RCII levels are significantly associated with increased all-cause mortality risk middle-aged and elderly populations in both the US and China. In the US population, RCII is also associated with increased risks of cardiovascular and cancer mortality. By integrating metabolic and inflammatory risk factors, RCII may serve as a valuable tool for mortality risk stratification and clinical decision-making.

The relationship between the ratio of triglyceride to high-density lipoprotein cholesterol and left ventricular hypertrophy in Chinese hypertension adults

Left ventricular hypertrophy (LVH) is a major cardiac complication of hypertension. The ratio of triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C) (TG/HDL-C) has been identified as a biomarker of insulin resistance and a predictor of atherosclerosis. We aimed to investigate the relationship between TG/HDL-C and LVH in hypertensive patients among the Han Chinese. Our community-based cross-sectional study recruited 4552 patients with hypertension. LVH was diagnosed by transthoracic echocardiography in these patients based on a criterion of left ventricular mass index (LVMI) over 49.2 g/m2.7 in men and 46.7 g/m2.7 in women. The independent association between the TG/HDL-C ratio quartiles and LVH prevalence was analyzed by logistic regression models. The ratio of TG/HDL-C was higher (1.27 ± 1.26, 1.15 ± 1.07, P = 0.001) in LVH patients. The prevalence of LVH with the first quartile of TG/HDL-C (Q1: < 0.61), second (Q2: 0.61 ~ 0.91), the third (Q3: 0.92 ~ 1.41), and the highest quartile (Q4: >1.41) was 36.1%, 42%, 42.6%, 44.9%, respectively. Logistic regression analysis suggested that the ratio of TG/HDL-C was independently correlated with the risk of LVH with adjustment of confounding factors. The correlation was more significant in female patients rather than males. Compared to the first quartile of TG/HDL-C (Q1), the odds ratios (ORs) and their 95% confidence intervals (CIs) for LVH in the increasing quartiles (Q2-Q4) were 1.21(1.01-1.45), 1.28(1.07-1.54), and 1.48(1.23-1.78), respectively. Similar results were also observed in the subjects younger than 60 years with coronary heart disease (CAD). The ratio of TG/HDL-C may be an independent risk factor of LVH in Han Chinese with hypertension.

Associations of the triglyceride-glucose index and triglyceride-glucose/body mass index with all-cause mortality in Chinese centenarians

BACKGROUND

The triglyceride-glucose (TyG) index and triglyceride-glucose/body mass index (TyG-BMI) have been shown to be associated with cardiovascular and cerebrovascular disorders and the risk of death. The aim of this study was to explore the relationships of the TyG index and TyG-BMI with all-cause mortality among Chinese centenarians.

METHODS

Data from the China Hainan Centenarian Cohort Study (CHCCS) were analyzed. Eligible centenarians were divided into quartiles on the basis of their TyG and TyG-BMI indices. Kaplan‒Meier analysis was used to compare survival times across groups. The associations of the TyG index and TyG-BMI with all-cause mortality were investigated using restricted cubic splines (RCSs) and Cox proportional hazards regression models. Moreover, the concordance of the associations of the TyG index and TyG-BMI with all-cause mortality in different subgroups was further explored by subgroup analysis.

RESULTS

A total of 921 centenarian participants were included in this study. During a median follow-up of 29.70 months, 852 (92.5%) centenarians died. The results of the RCS analysis demonstrated that the TyG index and TyG-BMI were both linearly and negatively associated with all-cause mortality. Compared with that for the highest the TyG index and TyG-BMI quartile groups, higher risks of death were found for the lowest quartile groups (TyG Q1 vs. Q4, HR 1.27, 95% CI 1.03-1.56, P = 0.024; TyG-BMI Q1 vs. Q4, HR 1.60, 95% CI 1.30-1.96, P < 0.001). Centenarians with lower TyG index and TyG-BMI values had significantly greater mortality risks according to the Kaplan‒Meier analysis (log-rank P = 0.020, log-rank P < 0.001, respectively). Subgroup analysis demonstrated that blood pressure could influence the linear negative correlation between the TyG-BMI and all-cause mortality.

CONCLUSION

Both lower TyG and TyG-BMI indices were significantly associated with higher all-cause mortality in Chinese centenarians, whereas the TyG-BMI was superior to the TyG index in predicting the mortality risk of centenarians.

Association of insulin resistance-related indicators with cardiovascular disease in Chinese people with different glycemic states

Background

This study compares the association of eight insulin resistance (IR)-related markers (triglyceride-glucose index (TyG), TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), triglycerides-to-high-density lipoprotein cholesterol ratio (TG/HDL), lipid accumulation product (LAP), visceral adiposity index (VAI), and estimated glucose disposal rate (eGDR)) with cardiovascular disease (CVD).

Methods

Spearman's coefficients were used for correlations between IR-related markers. Predictive capacities were evaluated using receiver operating characteristic (ROC) curve analysis, Akaike Information Criterion, and Bayesian Information Criterion were calculated. Multivariable-adjusted Cox regression models and restricted cubic spline (RCS) analysis were performed to explore associations between IR-related markers and CVD.

Results

In Pearson correlation analysis, TyG-WC and TyG-WHtR had a correlation coefficient of 0.95, while TG/HDL ratio and VAI had a correlation coefficient of 0.97. Regarding predictive capacity across different glycemic states, eGDR showed the best performance among the 8 IR-related markers, particularly in predicting stroke. According to Cox regression analysis, with each unit increase in TyG, TyG-BMI, TyG-WC, and TyG-WHtR, the risk of heart disease increased by 24.1%, 0.4%, 0.1%, and 17.56%, respectively; and the risk of stroke increased by 69.3%, 0.6%, 0.2%, and 36.5%, respectively. Additionally, TG/HDL ratio, VAI, and LAP exhibited nonlinear associations with heart disease and stroke risk. For each unit increase in eGDR, the risks of heart disease and stroke decreased by 21% and 14.2%, respectively.

Conclusion

eGDR is the most effective marker for predicting CVD, especially stroke, across all glycemic states. Modified TyG indices provide better predictive value than TyG alone.

The non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio as a predictor of NAFLD prevalence and steatosis severity

Altered lipid metabolism is a crucial jeopardy cause for developing non-alcoholic fatty liver disease (NAFLD). Among various lipid metrics, the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) has recently emerged as a promising indicator showing significant potential in predicting the prevalence of NAFLD. This study aimed to provide novel insights for the prevention of NAFLD by examining the relationship between NHHR and the prevalence of NAFLD. To identify the connection between NHHR and NAFLD, this study utilized descriptive analysis, multivariate logistic regression, and restricted cubic spline regression to investigate data collected by the National Health and Nutrition Examination Survey performed from 2017 to 2020. Furthermore, the connection between NHHR and the controlled attenuation parameter (CAP) was assessed using multiple linear regression, smoothed curve fitting, and threshold effect analysis. The NAFLD group showed higher NHHR levels than the non-NAFLD group (2.990 vs 2.240, P < 0.001). Multiple logistic and linear regression analyses indicated significant positive associations between NHHR and its quartiles with both the prevalence of NAFLD and CAP levels. Additionally, NHHR was positively associated with the prevalence of NAFLD in a linear dose-response relationship. Furthermore, smoothed curve fitting demonstrated a positive relationship between NHHR and CAP, with a threshold effect at an inflection point of 3.398. Higher NHHR levels were significantly associated with the prevalence of NAFLD and steatosis, and maintaining NHHR in the appropriate range may reduce these conditions.

Triglycerides/high-density lipoprotein-cholesterol ratio outperforms traditional lipid indicators in predicting metabolic dysfunction-associated steatotic liver disease among U.S. adults

Objective

Triglycerides (TG), high-density lipoprotein cholesterol (HDL-c), and their ratio (TG/HDL-c) are key lipid markers associated with metabolic dysfunction. This study aims to investigate the association of TG, HDL-c, and TG/HDL-c ratio with metabolic dysfunction-associated steatotic liver disease (MASLD) and to assess whether TG/HDL-c ratio provides superior predictive ability for MASLD compared to TG or HDL-c alone.

Importance

Although previous research has explored the relationship between TG/HDL-c and MASLD, the applicability of these findings across different ethnicities and populations remains uncertain. Additionally, this study is based on NHANES data, which relies on self-reported measures and lacks longitudinal follow-up, limiting the ability to establish causal relationships. While we adjusted for multiple covariates, residual confounding cannot be ruled out. Therefore, further large-scale, prospective studies are needed to validate these associations and assess the long-term predictive value of TG/HDL-c ratio for MASLD.

Methods

A cross-sectional study utilizing the NHANES 2017-2020 database was conducted. We performed univariate and multivariate logistic regression analyses to examine the associations between TG, HDL-c, and the TG/HDL-c ratio with MASLD. Receiver Operating Characteristic (ROC) curve analysis was used to evaluate the predictive effectiveness. Sensitivity analysis was carried out using multiple imputation for missing data and subgroup stratification to validate the findings.

Results

TG, HDL-c, and TG/HDL-c ratio were significantly associated with MASLD (p < 0.05 for all). The TG/HDL-c ratio demonstrated the highest predictive value (AUC = 0.732, 95% CI: 0.683-0.781), compared to TG (AUC = 0.713, 95% CI: 0.664-0.762) and HDL-c (AUC = 0.313, 95% CI: 0.264-0.362). The weak predictive power of HDL-c alone may be attributed to its complex role in lipid metabolism and potential confounding by other metabolic factors.

Conclusion

Maintaining favorable levels of TG, HDL-c and TG/HDL-c ratio may lower MASLD risk. Using TG/HDL-c ratio could improve prediction models compared to individual TG or HDL-c markers.

Triglyceride/high-density lipoprotein cholesterol ratio associates major adverse cardiac and cerebrovascular events: a 13-year prospective cohort study

BACKGROUND

Few studies have been conducted to investigate the association between the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio and major adverse cardiac and cerebrovascular events (MACCEs) in a predominantly male cohort from China.

METHODS

A prospective cohort study was conducted on a total 95,837 individuals (males account for 79.67) extracted from the Kailuan study. All individuals were grouped according to the TG/HDL-C ratio quartile. The endpoints of this study were composite MACCEs and its subtypes [non-fatal myocardial (MI), non-fatal stroke and all-cause mortality]. The Kaplan-Meier method was employed to illustrate the cumulative incidence curve. The incidence rate was reported as per 1000 person-years. To explore the impact of varying quartiles of the TG/HDL-C ratio on the risk of MACCEs, Cox proportional hazard regression analysis was conducted. Furthermore, multivariate adjusted spline regression models were applied to examine the relationship between the TG/HDL-C ratio and the risk of MACCEs.

RESULTS

A total of 18,430 cases of composite MACCEs occurred during a 13.97-year follow-up. In brief, 1762 cases of MI, 6653 cases of stroke, and 12,524 cases of all-cause mortality were reported, respectively. The cumulative incidence and incidence rate of composite MACCEs, MI, and stroke increased with increment in the TG/HDL-C ratio (p < 0.001). In comparison to quartile 1, the hazard ratios of quartile 4 for composite MACCEs, MI, stroke, and all-cause mortality were 1.13 (95% CI 1.07-1.19), 1.55 (95% CI 1.30-1.84), 1.21 (95% CI 1.12-1.31), and 1.12 (95% CI 1.05-1.20), respectively. Multivariate adjusted spline regression models showed a nonlinear relationship between baseline TG/HDL-C ratio and risk of composite MACCEs (p for non-linearity < 0.01), MI (p for non-linearity < 0.01), stroke (p for non-linearity < 0.01), and all-cause mortality (p for non-linearity = 0.029).

CONCLUSIONS

The TG/HDL-C ratio is significantly associated with an increased risk of MACCEs in a predominantly male cohort from northern China.

The clinical value of triglyceride to high-density lipoprotein cholesterol ratio for predicting stroke-associated pneumonia after spontaneous intracerebral hemorrhage

OBJECTIVE

Stroke-associated pneumonia (SAP) is relevant to the poor functional outcomes of patients with spontaneous intracerebral hemorrhage (SICH). It is unclear if the triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio (TG/HDL-C) is related to the risk of SAP in SICH patients. This study aimed to investigate the association between TG/HDL-C and SAP in SICH patients.

METHODS

Consecutive patients with SICH were enrolled in this retrospective study. Relevant clinical variables were extracted from electronic medical records. All enrolled participants were divided into SAP (n = 71) and non-SAP (n = 187) groups. Multivariate binary logistic regression analysis was used to explore the association between TG/HDL-C and SAP. The optimal cutoff value of TG/HDL-C was defined by the receiver operating characteristic (ROC).

RESULTS

Among 258 patients, 71 (27.5%) had SAP. Patients with SAP were older (72.75 ± 11.10 vs. 64.81 ± 12.70 years), with a lower TG, higher HDL-C, and lower TG/HDL-C than participants in the non-SAP group. TG/HDL-C was an independent protective factor for SAP (adjusted OR 0.516, 95% CI 0.339-0.784) after adjusting for relevant risk factors. According to ROC analysis, the optimal cutoff value was a TG/HDL-C > 1.09 for decreased SAP [area under the ROC curve (AUC) 0.705; sensitivity 76.1% and specificity 59.4%]. Patients with a TG/HDL-C of > 1.09 were independently associated with decreased SAP (adjusted OR 0.285, 95% CI 0.138-0.591 ) after adjustment.

CONCLUSION

This study suggests that a lower TG/HDL-C is independently associated with increased SAP after SICH.

Triglyceride-glucose index and triglyceride-to-high-density lipoprotein cholesterol ratio in predicting severity of acute pancreatitis: a cross-sectional clinical study

BACKGROUND

The aim of this study is to investigate the correlation of triglyceride-glucose (TyG) index and triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio with acute pancreatitis (AP), and to compare the predictive value of the two indexes for severe AP (SAP).

METHODS

This study was a clinical cross-sectional study. Spearman's correlation, logistic regression analysis and receiver operating characteristic (ROC) curves were used to investigate the relationship between the TyG index and TG/HDL-C ratio with SAP.

RESULTS

Of the 311 enrolled AP patients, the mean age was 62.59 ± 9.03 years, and 131 (42.12%) were male. A total of 34 (10.93%) patients met the diagnostic criteria for SAP. The results of Spearman's correlation showed that TyG index (Spearman rho = 0.262; p < 0.001), TG/HDL-C ratio (Spearman rho = 0.206; p < 0.001) were associated with SAP. Logistic regression analysis showed that TyG index was independently and positively correlated with SAP [odds ratio (OR), 4.311; 95% confidence interval (CI), 1.222-15.208; p = 0.023]. However, this association was not further confirmed on TG/HDL-C ratio (OR, 2.530; 95% CI, 0.883-7.251; p = 0.084). According to the ROC curve analysis, the area under the curve (AUC) for TyG index was 0.712 (p < 0.001), and the AUC for TG/HDL-C ratio was 0.691 (p < 0.001).

CONCLUSIONS

TyG index and TG/HDL-C ratio have different diagnostic values in AP patients. And the TyG index may be a more useful auxiliary tool for predicting SAP.

Association between TG/HDL-C and hypertension in Chinese middle-aged and older adults: findings from CHARLS

BACKGROUND

The triacylglycerol to high-density lipoprotein cholesterol ratio (TG/HDL-C) has been recognized as one of the risk factors for cardiovascular diseases, insulin resistance and metabolic syndrome. We aimed to investigate the relationship between TG/HDL-C and hypertension in a Chinese middle-aged and elderly population.

METHODS

We used data from the CHARLS database 2011-2018 to explore the relationship between TG/HDL-C and hypertension through cross-sectional and longitudinal studies. Hypertension was identified by self-report or taking anti-hypertensive medications. Participants aged below 45, or with missing data on TG/HDL-C or hypertension record, or taking lipid-lowering medication were excluded. Participants were divided into three or two groups based on triplets TG/HDL-C and median TG/HDL-C in cross-sectional and longitudinal analysis. Multivariate logistic regression analysis, subgroup analysis, and restricted cubic splines were used in statistics.

RESULTS

In the cross-sectional analysis, a total of 12,824 participants were included, after adjusting for potential confounders, there was a significant association between higher TG/HDL-C and increased prevalence of hypertension (OR = 1.86, 95% CI: 1.65-2.09, p < 0.001), systolic blood pressure (SBP) above 140 mmHg (OR = 1.37, 95% CI: 1.25-1.50, p < 0.0001), diastolic blood pressure (DBP) above 90 mmHg (OR = 1.47, 95% CI: 1.29-1.67, p < 0.0001), and pulse pressure (PP) above 60 mmHg (OR = 1.17, 95% CI: 1.07-1.29, p < 0.0011). The longitudinal analysis included 7909 participants, there was a significant association between higher TG/HDL-C and increased incidence of hypertension (OR = 1.51, 95% CI: 1.32-1.73,p < 0.001). Restricted cubic splines show nonlinear relationship between TG/HDL-C and hypertension.

CONCLUSION

These results demonstrated significant positive association between TG/HDL-C and the prevalence & incidence of hypertension, in a nationwide representative middle-aged and elderly population in China.

Associations of modified triglyceride-glucose indices and the triglyceride/high-density lipoprotein ratio with all-cause and cause-specific mortality in the general population: an analysis of the UK biobank database

BACKGROUND

This study investigates the associations between modified triglyceride-glucose (TyG) indices and the triglyceride-to-high-density lipoprotein (TG/HDL) ratio, which are recognized as simple surrogate indicators of insulin resistance, with all-cause and cause-specific mortality.

METHODS

A cohort of 410,515 participants from the UK Biobank was analyzed. Cox proportional hazard models and restricted cubic spline regression analyses were employed to examine the relationships between the TyG index, TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), TG/HDL ratio, and all-cause and cause-specific mortality. Structural equation modeling was employed to elucidate the associations between the TyG index, TG/HDL ratio, inflammation, metabolism, and mortality.

RESULTS

The TyG index, TyG-WC, and TG/HDL ratio were associated with an increased risk of all-cause mortality by 3.7% (HR 1.037 [1.016, 1.059]), 0.1% (HR 1.001 [1.024, 1.031]), and 1.5% (HR 1.015 [1.006, 1.025]), respectively. Restricted cubic spline regression models revealed nonlinear trends in the TyG index, TyG-BMI, TyG-WC, and TG/HDL ratio in relation to both all-cause and cause-specific mortality (P for nonlinearity < 0.05). TyG index and TG/HDL ratio exhibited a J-shaped relationship with all-cause mortality as well as mortality from cancer, cardiovascular diseases, and respiratory diseases. Similarly, TyG-BMI demonstrated an L-shaped association with all-cause mortality and mortality due to cancer, cardiovascular diseases, and respiratory diseases. Additionally, TyG-WC was associated with a progressively increasing mortality risk once it exceeded a certain threshold. Structural equation modeling demonstrated that the TyG index and TG/HDL ratio influenced mortality through inflammation and lifestyle factors.

CONCLUSIONS

In conclusion, TyG, TyG-BMI, TyG-WC, and TG/HDL ratio are significantly associated with all-cause and cause-specific mortality in the general population.These associations appear to be linked to inflammation and lifestyle.

Data-driven cluster analysis of lipids, inflammation, and aging in relation to new-onset type 2 diabetes mellitus

PURPOSE

Early detection and intervention are vital for managing type 2 diabetes mellitus (T2DM) effectively. However, it's still unclear which risk factors for T2DM onset are most significant. This study aimed to use cluster analysis to categorize individuals based on six known risk factors, helping to identify high-risk groups requiring early intervention to prevent T2DM onset.

METHODS

This study comprised 7402 Korean Genome and Epidemiology Study individuals aged 40 to 69 years. The hybrid hierarchical k-means clustering algorithm was employed on six variables normalized by Z-score-age, triglycerides, total cholesterol, non-high-density lipoprotein cholesterol, high-density lipoprotein cholesterol and C-reactive protein. Multivariable Cox proportional hazard regression analyses were conducted to assess T2DM incidence.

RESULTS

Four distinct clusters with significantly different characteristics and varying risks of new-onset T2DM were identified. Cluster 4 (insulin resistance) had the highest T2DM incidence, followed by Cluster 3 (inflammation and aging). Clusters 3 and 4 exhibited significantly higher T2DM incidence rates compared to Clusters 1 (healthy metabolism) and 2 (young age), even after adjusting for covariates. However, no significant difference was found between Clusters 3 and 4 after covariate adjustment.

CONCLUSION

Clusters 3 and 4 showed notably higher T2DM incidence rates, emphasizing the distinct risks associated with insulin resistance and inflammation-aging clusters.

The association of the triglyceride-glucose index with the risk of atrial fibrillation: Analysis of the UK Biobank

BACKGROUND AND AIMS

The relationship between the triglyceride-glucose (TyG) index and the incidence of atrial fibrillation (AF) remains insufficiently explored. This investigation aims to elucidate the association between the TyG index and the long-term risk of developing AF.

METHODS AND RESULTS

This cohort study analyzed data from 409,705 participants sourced from the UK Biobank database. Participants were stratified into three groups based on TyG index tertiles. The association between the TyG index and AF was evaluated using Cox proportional hazards models. Restricted cubic spline (RCS) analysis was employed to investigate potential linear or nonlinear relationships. During a mean follow-up period of 13.9 years, 26,092 AF cases were recorded. Compared with the T2 group, participants in the T1 group and T3 group presented a significantly higher risk of AF (T1: HR: 1.22, 95%CI: 1.17-1.27; T3: HR: 1.09, 95%CI: 1.05-1.14). RCS analysis documented a U-shaped relationship between the TyG index and the risk of AF (P for non-linearity <0.001). In non-type 2 diabetes (T2D) participants, TyG levels were associated with AF risk in a U-shaped relationship. Among T2D participants, only the T3 group had an increased risk of AF (reverse "L" pattern). The U-shaped relationship between TyG levels and AF risk remained consistent across heart valve disease (HVD) and non-HVD patients, as well as different strata of genetic susceptibility to AF.

CONCLUSIONS

This study demonstrates a U-shaped association between the TyG index and the risks of AF, underscoring the index's potential utility in identifying individuals at elevated risk for these conditions.

Cardiometabolic index predicts cardiovascular events in aging population: a machine learning-based risk prediction framework from a large-scale longitudinal study

Background

While the Cardiometabolic Index (CMI) serves as a novel marker for assessing adipose tissue distribution and metabolic function, its prognostic utility for cardiovascular disease (CVD) events remains incompletely understood. This investigation sought to elucidate the predictive capabilities of CMI for cardiovascular outcomes and explore underlying mechanistic pathways to establish a comprehensive risk prediction framework.

Methods

The study encompassed 7,822 individuals from a national health and retirement longitudinal cohort, with participants stratified by CMI quartiles. Following baseline characteristic comparisons and CVD incidence rate calculations, we implemented multiple Cox regression models to assess CMI's cardiovascular risk prediction capabilities. For nomogram construction, we utilized an ensemble machine learning framework, combining Boruta algorithm-based feature selection with Random Forest (RF) and XGBoost analyses to determine key predictive parameters.

Results

Throughout the median follow-up duration of 84 months, we documented 1,500 incident CVD cases, comprising 1,148 cardiac events and 488 cerebrovascular events. CVD incidence demonstrated a positive gradient across ascending CMI quartiles. Multivariate Cox regression analysis, adjusting for potential confounders, confirmed a significant association between CMI and CVD risk. Notably, mediation analyses revealed that hypertension and glycated hemoglobin (HbA1c) potentially serve as mechanistic intermediaries in the CMI-CVD relationship. Sex-stratified analyses suggested differential predictive patterns between gender subgroups. Given CMI's robust and consistent predictive capability for stroke outcomes, we developed a machine learning-derived nomogram incorporating five key predictors: age, CMI, hypertension status, high-sensitivity C-reactive protein (hsCRP) and renal function (measured as serum creatinine). The nomogram demonstrated strong discriminative ability, achieving areas under the receiver operating characteristic curve (AUC) of 0.76 (95% CI: 0.56-0.97) and 0.74 (95% CI: 0.66-0.81) for 2-year and 6-year stroke prediction, respectively.

Conclusions

Our findings establish CMI as a significant predictor of cardiovascular events in the aging population, with the relationship partially mediated through hypertension and insulin resistance pathways. The validated nomogram, developed using longitudinal data from a substantial elderly cohort, incorporates CMI to enable preclinical risk stratification, supporting timely preventive strategies.

Associations of the hs-CRP/HDL-C ratio with cardiovascular disease among US adults: Evidence from NHANES 2015-2018

BACKGROUND AND AIMS

Inflammation, lipid signaling, and their interplay are involved in the pathogenesis and development of cardiovascular diseases (CVDs), while the relationships of composite indices combining inflammation and lipids with CVD remained inexplicit.

METHODS AND RESULTS

Our study enrolled 8581 adults from the National Health and Nutrition Examination Survey 2015-2018. Logistic regression model was applied to assess the associations of high-sensitivity C-reactive protein (hs-CRP)-to-high-density lipoprotein cholesterol (HDL-C) ratio with CVD prevalence. Potential mediating effects of hypertension, diabetes, hypercholesterolemia, and obesity on significant associations were explored. Receiver operating characteristic (ROC) curves were generated to compare diagnostic values of the hs-CRP/HDL-C ratio, HDL-C, and hs-CRP. Compared with those in the first quartile of the hs-CRP/HDL-C ratio, participants in the fourth quartile presented higher risks of CVD subtypes and total CVD. Each one-unit increment of the log-transformed hs-CRP/HDL-C ratio was associated with a 25 % increase in CVD risk (95 % confidence interval: 1.11, 1.41) with significant uptrends across the hs-CRP/HDL-C ratio quartiles. Four metabolic disorders significantly mediated associations of the hs-CRP/HDL-C ratio with CVDs. Younger participants were more sensitive to higher hs-CRP/HDL-C ratio with significant interactions in CVD. ROC curves further illustrated the relatively good diagnostic efficacy of the hs-CRP/HDL-C ratio for CVD.

CONCLUSION

The hs-CRP/HDL-C ratio was a significant risk factor for CVD among US adults, in which hypertension, diabetes, hypercholesterolemia, and obesity played important mediating roles. Early attention to people with elevated hs-CRP/HDL-C ratio would be helpful for CVD risk reduction.

Exploring the nonlinear association between cardiometabolic index and hypertension in U.S. Adults: an NHANES-based study

BACKGROUND

Hypertension is a prevalent chronic disease affecting over 1.2 billion people worldwide, representing a major modifiable risk factor for cardiovascular diseases. The Waist-to-Height Ratio (WHtR) and Triglyceride to High-Density Lipoprotein Cholesterol (TG/HDL-C) ratio are established metabolic indicators linked to the risk of cardiovascular and metabolic diseases. Recently, a Cardiometabolic Index (CMI), combining WHtR and TG/HDL-C ratios, has been proposed to provide a comprehensive assessment of metabolic health. This study investigates the association between CMI and hypertension using data from the National Health and Nutrition Examination Survey (NHANES).

METHODS

The study utilized NHANES data from nine cycles spanning 2001 to 2018, encompassing 20,049 participants aged over 20. Exclusions were made for individuals with incomplete CMI or hypertension data, and pregnant women. CMI was calculated by multiplying the WHtR by the TG/HDL-C ratio. Hypertension was defined according to American Heart Association guidelines. The relationship between CMI and hypertension was evaluated using multivariate logistic regression analyses, with additional subgroup analyses conducted based on demographic factors. Nonlinear relationships were analyzed using smoothing curve fitting techniques.

RESULTS

The study identified a significant positive correlation between CMI and hypertension risk, with an increase of one unit in CMI associated with a 9% heightened risk of hypertension (OR: 1.09, 95% CI: 1.05, 1.13). The association remained significant across various demographic subgroups. A nonlinear relationship was observed, with a critical CMI threshold of 2.64. Below this threshold, higher CMI values were associated with a progressively higher prevalence of hypertension, whereas beyond this threshold, further increases in CMI did not significantly correlate with an elevated risk of hypertension.

CONCLUSION

The study demonstrates that CMI is significantly associated with hypertension risk and may serve as a valuable tool for early screening and risk assessment, particularly in identifying individuals at higher risk before reaching the critical CMI threshold. These results underscore the importance of addressing metabolic health in the prevention and management of hypertension. Future research should focus on longitudinal studies to establish causality, explore the clinical utility of CMI in hypertension screening, and examine its applicability in diverse populations.

Association between TyG index with obesity indicators and coronary heart disease: a cohort study

The potential of utilizing the Triglyceride Glucose Index (TyG), along with its combination with obesity indicators, for predicting the risk of coronary heart disease (CHD) in the middle-aged and elderly population remains uncertain. This research aims to conduct a cohort study to assess the predictive capacity of the TyG and its combination with obesity indicators in forecasting the 10-year incidence of new-onset CHD among the middle-aged and elderly population in the Luzhou region. The study population was derived from the The China Cardiometabolic Disease and Cancer Cohort (4C) Study, comprising 8647 ordinary residents meeting specific criteria. The subjects were grouped based on quartiles of TyG, TyG-WC, TyG-WtHR, TyG-BMI, and TyG-WHR, and the occurrence of new-onset coronary heart disease was observed over a 10-year period. The study comprised 8647 participants, with 484 developing new-onset CHD, resulting in an incidence rate of 5.5% of the overall follow-up population. The comparison of new-onset CHD across quartiles of different indicators revealed a statistically significant difference (P < 0.001), with the order being the 4th quartile > 3rd quartile > 2nd quartile > 1st quartile. Cox proportional hazards regression analysis results indicated that, after adjusting for multiple influencing factors, the risk of new-onset CHD gradually increased with the quartiles of the 5 indicators. Specifically, when grouped according to TyG and TyG-WC quartiles, a statistically significant difference (P < 0.05) was observed between the 3rd and 4th quartiles compared to the 1st quartile. The ROC curve analysis results demonstrate that TyG-WC (area under the curve 0.608, P < 0.001) and TyG-WtHR (area under the curve 0.608, P < 0.001) exhibit superior predictive value for new-onset coronary heart disease compared to TyG (area under the curve 0.568, P < 0.001), TyG-BMI (area under the curve 0.576, P < 0.001), and TyG-WHR (area under the curve 0.595, P < 0.001). 1. TyG, TyG-WC, TyG-WtHR, TyG-BMI, and TyG-WHR demonstrate varying degrees of correlation with the incidence of new-onset coronary heart disease in the middle-aged and elderly population. 2. Specifically, TyG-WC may serve as a significant predictive factor for the occurrence of coronary heart disease in the elderly population.

Remnant cholesterol, lipid ratios, and the severity of coronary artery lesions: a retrospective cohort study in patients with coronary heart disease

Background

Emerging genetic and observational evidence indicates that remnant cholesterol (RC) is a significant residual risk factor for cardiovascular diseases. However, there is a relative paucity of evidence exploring the correlation among RC, lipid ratios, and atherosclerotic lesion severity. This study aimed to investigate the predictive value of RC and lipid ratios alone or in combination for the severity of coronary artery stenosis in patients with coronary heart disease (CHD).

Methods

The Gensini score was used to assess the severity of coronary atherosclerotic lesions. CHD patients were categorized into mild stenosis and moderate-to-severe stenosis groups. Logistic regression was used to evaluate the risk of a high Gensini score associated with RC and lipid ratios. Our study also examined the relationship between inconsistencies in RC and non-high-density lipoprotein cholesterol (non-HDL-C) levels and the severity of coronary artery stenosis. Receiver operating characteristic (ROC) curves were used to assess the predictive power of RC and lipid ratios alone or in combination for moderate to severe coronary artery lesions.

Results

Multivariate regression models suggested that RC was a strong predictor of moderate to severe coronary artery stenosis [odds ratio (OR): 5.44, P < 0.001]. When grouped by curve-fitting inflection points, the group with inconsistent high RC/low non-HDL-C, rather than the low RC/high non-HDL-C group, was associated with an increased risk of moderate to severe coronary stenosis compared with the consistent low RC group (OR: 2.72, P < 0.001). ROC curves showed that RC predicted an area under the curve (AUC) of 0.715 for coronary stenosis severity, improving the predictive efficacy of the combined predictors comprising lipid ratios (AUC: 0.723 vs. 0.703, P < 0.05).

Conclusions

RC and various lipid ratios [triglyceride/HDL-C, total cholesterol/HDL-C, low-density lipoprotein cholesterol/HDL-C, and apoloprotein (apo)B/apoA] correlated with the degree of coronary artery stenosis in patients with CHD, suggesting that RC has potential value as a biomarker reflecting the degree of coronary artery stenosis independent of the traditional risk factors and the levels of non-HDL-C. This could enhance the predictive efficacy based on the lipid ratio model and had better predictive value for moderate to severe coronary artery lesions.

Assessing the impact of insulin resistance trajectories on cardiovascular disease risk using longitudinal targeted maximum likelihood estimation

BACKGROUND

Cardiovascular disease (CVD) is closely associated with Insulin Resistance (IR). However, there is limited research on the relationship between trajectories of IR and CVD incidence, considering both time-invariant and time-varying confounders. We employed advanced causal inference methods to evaluate the longitudinal impact of IR trajectories on CVD risk.

METHODS

The data for this study were extracted from a Chinese nationwide cohort, named China Health and Retirement Longitudinal Study (CHARLS). Triglyceride-glucose (TyG) index and TyG body mass index (BMI) were used as surrogate markers for IR, and their changes were recorded as exposures. Longitudinal targeted maximum likelihood estimation (LTMLE) was used to study how dynamic shifts in IR trajectories (i.e., increase, decrease, etc.) influence long-term CVD risk, adjusting for both time-invariant and time-varying confounders.

RESULTS

A total of 3,966 participants were included in the analysis, with 2,152 (54.3%) being female. The average age at baseline was 58.28 years. Over the course of a 7-year follow-up period, 499 (12.6%) participants developed CVD. Four distinct trajectories of TyG index and TyG-BMI were identified: low stable, increasing, decreasing, and high stable. LTMLE analyses revealed individuals in the 'high stable' and 'increasing' groups had a significantly higher risk of developing CVD compared to those in the 'low stable' group, while the 'decreasing' group showed no significant differences. Specifically, when the exposure was set as TyG-BMI, the odds of CVD in the 'high stable' group were 1.694 (95% CI: 1.361-2.108) times higher than in the 'low stable' group. Similar trends were observed across other models, with ORs of 1.708 (95% CI: 1.367-2.134) in Model 2, 1.389 (1.083-1.782) in Model 3, 1.675 (1.185-2.366) in Model 4, and 1.375 (95% CI:1.07 - 1.768) in Model 5. When the exposure was changed to the TyG index, the results remained consistent, with a slightly lower magnitude of the odds ratios.

CONCLUSIONS

High stable and increasing TyG-BMI and TyG index trajectories were associated with the risk of CVD. TyG-BMI consistently exhibited higher odds ratios (ORs) of CVD risk when comparing with TyG index. Early identification of IR trajectories could provide insights for preventing CVD later in life.

Cholesterol, high-density lipoprotein, and glucose index versus triglyceride-glucose index in predicting cardiovascular disease risk: a cohort study

BACKGROUND

Cardiovascular disease (CVD) represents a significant global health challenge, characterized by high incidence rates and substantial morbidity and mortality. A newer index, the Cholesterol, High-Density Lipoprotein, and Glucose (CHG) index, has been proposed as a potential diagnostic tool for metabolic disorders but has not been investigated for its ability to predict CVD risk. This study aims to evaluate the predictive efficacy of the CHG index in comparison to the well-established Triglyceride-Glucose (TyG) index.

METHODS

In this cohort study, 6249 adults aged 45 and older were recruited from the CHARLS database, with data collected from 2011 to 2020. CVD events were tracked over a nine-year follow-up. The TyG and CHG indices were calculated, and their relationships with CVD risk were assessed using univariate and multivariate Cox regression models. Additionally, restricted cubic spline (RCS) analysis was performed to further explore these associations. Receiver operating characteristic (ROC) analysis was conducted to compare the predictive performance of both indices, and subgroup analysis evaluated their applicability in different populations.

RESULTS

Among the 6249 participants, 1667 (26.68%) developed CVD during the nine-year follow-up. In unadjusted Cox regression models, the TyG index had a hazard ratio (HR) of 1.18 (95% confidence interval CI 1.10-1.27, p < 0.001), while the CHG index showed a higher HR of 1.35 (95% CI 1.21-1.51, p < 0.001). In the adjusted models, the relationship still persisted. The RCS models showed that the TyG index exhibited a non-linear relationship with the risk of CVD, while the CHG index demonstrated a positive linear correlation. ROC curve analysis revealed comparable predictive performance for both indices. The subgroup analysis indicated that there was no interaction between the subgroups and the both indices (p for interaction > 0.05).

CONCLUSIONS

An elevated CHG index is significantly correlated with an increased risk of CVD, demonstrating a linear relationship. Furthermore, it exhibits predictive capabilities comparable to those of the TyG index in assessing CVD risk.

TRIAL REGISTRATION

Not applicable.

A 6-Month mHealth Low-Carbohydrate Dietary Intervention Ameliorates Glycaemic and Cardiometabolic Risk Profile in People with Type 2 Diabetes

Aim: Mobile health (mHealth) applications have been reported to be effective in improving glycaemic control and cardiometabolic health, but mainly as part of shorter-term intervention studies. The aim of this study is to examine the effect of the ongoing Defeat Diabetes mHealth low-carbohydrate diet (LCD) intervention on clinical markers and cardiometabolic risk after 6 months of intervention. Methods: Data were collected via primary care physicians as part of routine T2D monitoring. These included HbA1c (primary outcome), blood pressure, blood lipids, and markers of kidney and liver function. Anthropometrics, as well as changes in the prescription of diabetes, hypertension, and dyslipidaemia medication, were also recorded. Calculated variables, total cholesterol to HDL-c, triglyceride to HDL-c, and waist to height ratios, were analysed to examine changes in cardiometabolic risk profile. Three-day food records were used to assess dietary intake and intervention adherence. Univariate regression models examined changes from baseline to 6 months. Results: Ninety-four participants remained in the study out of the ninety-nine at baseline (mean age 59 ± 11 years, 55 females). After 6 months of intervention, there were significant reductions in HbA1c by -1.0% (95% CI: -1.3 to -0.6), as well as in the liver enzymes ALT (-9.3 U/L 95% CI -16.3 to -2.4) and GGT (-18.8 U/L 95% CI: -31.4 to -6.3) across the cohort. In addition, there was a significant reduction in cardiometabolic risk, as measured by the calculated variables and a decrease in waist circumference (-4.6 cm 95% CI: -8.9 to -0.2). Conclusions: People with T2D receiving LCD education and resources through the Defeat Diabetes mHealth app (version 3.3.8) improved their glycaemic control after 6 months of intervention. Cardiometabolic risk profile and liver function also showed significant improvement. These findings indicate that the use of an LCD digital app is a valuable adjunct in the management of T2D.

Glucose Disorders in Patients With Pheochromocytoma/Paraganglioma: Profile and Influence Effects in a Large Cohort With 705 Patients

OBJECTIVE

Some patients with pheochromocytoma and paraganglioma (PPGL) suffer from glucose metabolic disorders. The aim was to investigate the relationship between glucose metabolic disorders and catecholamine levels in 705 patients with PPGL.

METHODS

A retrospective analysis was conducted on the clinical data of 705 patients diagnosed with PPGL at Peking Union Medical College Hospital from 2018 to 2023. Bar chart was utilized to depict the manifestations of glycemic disorder across different genders, age groups, body mass index, and catecholamine secretion types. Comparison of characteristics between patients with PPGL who had glycemic disorders and those who did not was conducted. Binary logistic regression analysis coupled with receiver operating characteristic curves was utilized to predict the occurrence of glycemic disorders.

RESULTS

Of 705 patients, 492 patients were diagnosed with glucose abnormalities, while the remaining 213 had normal glucose metabolism. Compared to the normal glycemic group, the glycemic disorder group had significantly higher levels of HOMA-IR and TyG index, as well as higher high density lipoprotein, low-density lipoprotein, and total cholestrol. Univariate logistic regression identified age, norepinephrine, and epinephrine as independent risk factors for the occurrence of glucose metabolism disorders. After adjusting for confounding variables, age at diagnosis and norepinephrine levels both remained significant, confirming their roles as key risk factors.

CONCLUSIONS

Almost 70% of the patients manifested disturbances in glucose metabolism, with over one-third diagnosed with diabetes. These findings underscore the pivotal role catecholamines play in metabolic processes and emphasize the imperative need for close monitoring of blood glucose levels in patients with PPGL.

The association between the triglyceride‒glucose index and short-term mortality in ICU patients with sepsis-associated acute kidney injury

BACKGROUND

The triglyceride-glucose (TyG) index has emerged as a novel marker for insulin resistance and is commonly observed in patients suffering from sepsis-associated acute kidney injury (SA-AKI). This study explored the correlation between the TyG index and short-term all-cause mortality among SA-AKI patients.

METHODS

We performed a retrospective analysis of ICU patients with SA-AKI using data from the MIMIC-IV database. The primary outcomes were 28-day and 90-day all-cause mortality. Multivariate Cox proportional hazards regression, restricted cubic spline (RCS) models, and Kaplan‒Meier (K‒M) survival analyses were used to examine the associations between the TyG index and mortality. Subgroup and sensitivity analyses were conducted to ensure the robustness of the findings.

RESULTS

The study included 4971 SA-AKI patients, with 2873 males (57.8%), an average age of 65.4 years (± 15.8), and an average TyG index of 9.10 (± 0.70). RCS analysis revealed a U-shaped relationship between the TyG index and mortality. When the TyG index was below 9.04, the risk of mortality at both 28 days and 90 days was reduced (adjusted HRs of 0.695, 95% CI: 0.542-0.890 and 0.691, 95% CI: 0.557-0.858, respectively). In contrast, values above 9.04 were associated with increased mortality, though the relationship was not statistically significant (adjusted HRs of 1.026, 95% CI: 0.855-1.231 and 1.012, 95% CI: 0.863-1.188, respectively). K‒M analysis revealed higher mortality rates for patients with either high (T3) or low (T1) TyG indices than for those with moderate (T2) TyG indices. Sensitivity analyses confirmed these associations even after excluding patients with diabetes, cerebrovascular diseases, or ICU stays of less than 2 days.

CONCLUSION

The TyG index is significantly and nonlinearly associated with short-term all-cause mortality in SA-AKI patients; however, establishing a causal relationship between the two requires validation through larger prospective studies.

Association between air pollution and cardiovascular disease risk in middle-aged and elderly individuals with diabetes: inflammatory lipid ratio accelerate this progression

BACKGROUND

Long-term exposure to air pollution significantly increases the risk of cardiovascular disease (CVD); however, the association and underlying mechanisms in individuals with diabetes remain unconfirmed.

METHODS

We used data from the China Health and Retirement Longitudinal Study (CHARLS) to follow 5,430 adults over a four-year period. Baseline CVD and diabetes status were determined, and high-resolution data were used to assess air pollution exposure to PM1, PM2.5, PM10, and O3. The inflammatory lipid ratio (ILR) was calculated to reflect inflammatory and lipid metabolic states. A generalized linear model (GLM) was employed to analyze the effects of air pollution and ILR on diabetes-related CVD risk.

RESULTS

The prevalence of CVD was 8.5% in the healthy population and 13.8% in the diabetic population. Air pollution exposure was significantly associated with an increased risk of CVD among diabetic individuals. For each interquartile range (IQR) increase in concentrations of pollutants O3, PM1, PM10, and PM2.5, CVD risk in the diabetic group rose by 21%, 19%, 28%, and 19%, respectively. Higher ILR values were positively associated with CVD incidence (OR = 1.019, 95% CI: 1.001-1.037, P < 0.05), with a nonlinear relationship observed between ILR levels and CVD risk (PNonlinear = 0.0381), indicating that higher ILR values exacerbate the impact of air pollution on diabetic individuals.

CONCLUSION

Among middle-aged and older adults with diabetes, exposure to air pollution is associated with an increased risk of CVD, and ILR intensifies this process. Therefore, implementing effective public health interventions to reduce air pollution exposure in diabetic populations is essential.

Association Between Triglyceride-Glucose Related Index and Endometriosis Varies According to Educational Level

BACKGROUND

The association between the triglyceride-glucose (TyG) level, its obesity-related derivatives, and the occurrence of endometriosis (EMS) remains ambiguous, particularly in individuals with higher levels of education. This study sought to explore the relationship between TyG, its obesity-related derivatives, and EMS across various educational backgrounds.

METHODS

This study utilized a substantial dataset obtained from four cycles of the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2006. To explore the relationship between TyG, its obesity-related derivatives, and EMS, we employed a variety of analytical methods, including multivariable logistic regression models, smooth curve fitting, threshold effect analysis, and subgroup analysis, which were applied to participants with varying educational levels.

RESULTS

Among the 2347 participants, 203 (8.65%) were diagnosed with EMS. In the overall population, only the TyG, TyG-waist-to-height ratio (TyG-WHtR), and TyG-waist circumference (TyG-WC) variables demonstrated a positive association with EMS. However, within the group with high educational attainment, TyG, TyG-WHtR, TyG-WC, and TyG-body mass index (TyG-BMI) all exhibited positive correlations with EMS. These associations remained robust after adjustment for multiple potential confounding variables. The subgroup analysis demonstrated that these associations were consistent across different subgroups (p > 0.05). Furthermore, both linear and nonlinear relationships were observed between TyG and its obesity-related derivatives and EMS, as evidenced by the smooth curve fittings and threshold effect analyses. In contrast, no significant associations were identified in the group with lower levels of education.

CONCLUSIONS

Our study suggests that there is variation in the association between TyG and its obesity-related derivatives and EMS across different educational levels, warranting further investigation. In individuals with higher education, elevated levels of TyG and its obesity-related derivatives were associated with a higher prevalence of EMS. Conversely, this correlation was not observed among those with lower educational levels.

Vitisin A Outperforms Cyanidin-3-O-Glucoside in Triglyceride Reduction by Modulating Hepatic Lipogenesis and Fatty Acid β-Oxidation

Pyranoanthocyanins exhibit greater bioactivity compared to monomeric anthocyanins, yet the lipid-lowering effects of pyranoanthocyanin Vitisin A, a primary derivative found in aged red wines, have not been extensively studied in vivo. This study evaluated the triglyceride-lowering effects of Vitisin A and its anthocyanin counterpart Cyanidin-3-O-glucoside (C3G) in both free fatty acid -induced HepG2 cells and high-fat diet-fed ApoE-/- mice, with a focus on their roles in lipid metabolism. In vitro, Vitisin A significantly reduced triglyceride levels and lipid accumulation in HepG2 cells compared to C3G at equivalent concentrate. In vivo, dietary supplementation with 100 mg/kg of Vitisin A reduced body weight gain and plasma triglyceride levels by 19.6% and 29.5%, respectively, whereas no significant effects were observed with C3G. Mechanistically, Vitisin A markedly inhibited hepatic de novo lipogenesis (DNL) by activating the AMPK/ACC signaling pathway and downregulating FASN expression. Concurrently, Vitisin A enhanced fatty acid β-oxidation more robustly than C3G by upregulating CPT-1A via AMPK/SIRT1/PGC-1α and PPAR-α/PGC-1α pathways. Both Vitisin A and C3G driving peroxisomal β-oxidation of very-long-chain fatty acids. In summary, Vitisin A demonstrated superior triglyceride-lowering effects compared to C3G, primarily through dual mechanisms of inhibiting hepatic DNL and enhancing fatty acid β-oxidation.

Development and validation of a novel metabolic health-related nomogram to improve predictive performance of cardiovascular disease risk in patients with prediabetes

OBJECTIVE

The prevalence of prediabetes among adults in the U.S. is three times higher than that of diabetes, highlighting a greater disease burden. Both diabetes and prediabetes have been demonstrated to be associated with an increased risk of cardiovascular disease (CVD). However, research has primarily focused on diabetes, with limited attention to CVD risk prediction in prediabetes. Emerging 13 metabolic health-related indicators have been proposed to optimize the predictive effect on CVD risk in patients with prediabetes. This study aimed to compare the predictive efficacy of these biomarkers and further develop a nomogram to improve predictive performance of the CVD risk in patients with prediabetes.

METHODS

All eligible participants in the National Health and Nutrition Examination Survey (NHANES) 1999-2020 were enrolled in this study and randomly assigned to the development and validation cohorts in a ratio of 7:3. In the development cohort, the efficacy of 13 indicators used to predict the CVD risk was assessed by receiver operative characteristic (ROC) curves. Independent risk predictors identified by multivariate logistic regression were used to construct a nomogram, and internal and external validation were further implemented.

RESULTS

The ROC curve demonstrated that the triglyceride-glucose (TyG) index was an effective predictor of CVD risk [area under the curve (AUC) = 0.694] and exhibited the best predictive performance among the 13 metabolic health-related indices. Based on independent risk factors identified by multivariate logistic regression, the CVD risk nomogram [including age, gender, hypertension, TyG, stress hyperglycemia ratio (SHR), and neutrophil-to-lymphocyte ratio (NLR)] was successfully constructed and validated with good performance (AUCs/C-indexes > 0.70 for all).

CONCLUSION

This study developed a reliable nomogram for predicting CVD risk in patients with prediabetes. The model demonstrated robust performance and offered a simple yet individualized approach for predicting the CVD risk in patients with prediabetes.

Insulin resistance surrogates are associated with all-cause mortality and cardiovascular mortality in population with metabolic syndrome: a retrospective cohort study of NHANES

The study aimed to assess the association of five insulin resistance surrogates, namely HOMA-β (Homeostasis Model Assessment of Beta-cell Function), QUICKI (Quantitative Insulin Sensitivity Check Index), IGR (Insulin Glucose Ratio), e-IS (Estimated Insulin Sensitivity), and Bennett ISI(Bennett's insulin sensitivity index) with all-cause and cardiovascular mortality in respondents with metabolic syndrome(MetS). The prospective cohort of 6662 participants aged 18 years and older with metabolic syndrome was extracted from the National Health and Nutrition Examination Survey(NHANES 1999-2016). The multivariate Cox proportional hazards regression model, Kaplan-Meier survival curve, and log-rank tests were applied to determine the association between the five indices and all-cause mortality and cardiovascular mortality in the MetS population. Restricted cubic splines, a two-piece segmented Cox proportional hazards model, and threshold effect analyses were performed to evaluate the nonlinear relationship. Sensitivity analyses were then conducted by removing individuals with CKD, CHF, CAD, stroke, or cancer, respectively. All five insulin resistance (IR) surrogates displayed a negative association with all-cause and cardiovascular mortality in participants with metabolic syndrome. Restricted cubic spline curves showed QUICKI, IGR, and e-IS had a nonlinear relationship with statistical significance. MetS population at the highest quartile of HOMA-β or IGR exhibited lower all-cause and cardiovascular event probabilities compared with those at the lowest quartile, and e-IS had a similar correlation with cardiovascular events. Threshold effect analyses showed that there were inflection points of IGR for all-cause and cardiovascular mortality. As IGR gradually approached inflection points, the two types of mortality risks descended by 15%[HR 0.85(0.80,0.91)] and 19%[HR 0.81(0.71,0.92)], respectively. Sensitivity analysis indicated most results were robust, but Bennett ISI did not exhibit significant outcomes in participants without CKD. Our study provides evidence that HOMA-β, QUICKI, IGR, e-IS, and Bennett ISI displayed a reverse correlation with all-cause mortality and cardiovascular mortality in participants with metabolic syndrome. The five IR surrogates should be given more attention during the follow-up of MetS population.

Analyzing the correlation between acute ischemic stroke and triglyceride-glucose index based on ordered logistic regression

Objective

To investigate the association between insulin resistance, measured by the triglyceride-glucose (TyG) index, and clinical outcomes in patients with acute ischemic stroke who underwent intravenous thrombolysis with alteplase.

Methods

This retrospective study included 165 patients with acute ischemic stroke treated with intravenous alteplase. Insulin resistance was evaluated using the TyG index, and its relationship with the modified Rankin Scale (mRS) scores was analyzed. The analysis was conducted using R software (version R 4.1.3) to evaluate the correlation between the TyG index and functional outcomes at 14, 30, and 90 days post-stroke.

Results

The study found that each unit increase in the TyG index significantly raised the risk of poor functional outcomes at 14 days (OR 9.86; 95% CI: 3.32-32.21; P < 0.001), 30 days (OR 5.82; 95% CI: 2.08-17.45; P = 0.001), and 90 days (OR 9.79; 95% CI: 3.33-31.66; P < 0.001) following a stroke. Higher TyG index values were associated with worse neurological outcomes. Although male gender, older age, and smoking were also linked to poorer outcomes, these associations did not reach statistical significance.

Conclusion

The findings suggest that a higher TyG index, indicating greater insulin resistance, is associated with worse neurological outcomes in stroke patients. Early intervention targeting insulin resistance may improve clinical outcomes in ischemic stroke patients, and further research is needed to explore additional factors affecting neurological recovery.

The triglyceride-glucose index trajectories are associated with cardiovascular diseases in people living with HIV: evidence from a prospective cohort study in China, 2005-2022

BACKGROUND

The triglyceride-glucose (TyG) index has been validated as a novel biomarker for cardiovascular disease (CVD) risk. However, the prospective relationship between baseline and long-term trajectories of the TyG index and CVD risk in people living with HIV (PLWH) remains unexplored.

METHODS

This cohort study included 16,122 treatment-naive PLWH who initiated antiretroviral therapy (ART) at the Third People's Hospital of Shenzhen from 2005 to 2022. The TyG index was calculated as Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. Group-based trajectory modeling was used to identify distinct TyG index trajectories over the follow-up period. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using multivariate Cox proportional hazards models to assess the association between TyG index trajectories and CVD risk. Nonlinear relationships were investigated using a restricted cubic spline plot.

RESULTS

During a median follow-up of 70 months, 214 PLWH developed CVD. Each 1-standard deviation (SD) increase in the baseline TyG index was associated with a 39% higher risk of CVD (HR 1.39, 95% CI 1.22, 1.59) after adjusting for covariates. Participants were categorized into four distinct TyG trajectory groups: low-stable, low-moderate-stable, high-moderate-stable, and high-increasing. After multivariate adjustment, the high-increasing trajectory group had a 2.92-fold (95% CI 1.68, 5.05) increased risk of CVD compared to the low-stable group. The restricted cubic spline plot showed an upward trend between the baseline TyG index and the CVD occurrence (P < 0.001), with the threshold at 8.479 for all HIV patients. Significantly positive correlations between the TyG index and CVD were observed both below the TyG threshold with HR 3.38 (95% CI 1.07, 10.68) and above the threshold with HR 1.43 (95% CI 1.07, 1.92) (both P < 0.05). After stratifying by sex, the spline curves in men were nearly identical to those observed in the overall HIV-infected population. While women also demonstrated a nonlinear association with a similar threshold (8.484), the relationship above the threshold was not statistically significant.

CONCLUSIONS

Higher baseline TyG index levels and the high-increasing trajectory were significantly associated with increased CVD risk in PLWH. These findings underscore the TyG index as a valuable marker for CVD risk assessment in PLWH, particularly in male populations. Incorporating TyG index monitoring into routine clinical assessments could enhance risk stratification and inform tailored prevention strategies. Further studies are needed to validate these findings in other cohorts and to explore their applicability in women.

Delving into biomarkers and predictive modeling for CVD mortality: a 20-year cohort study

Accurate prediction of cardiovascular disease (CVD) mortality is essential for effective treatment decisions and risk management. Current models often lack comprehensive integration of key biomarkers, limiting their predictive power. This study aims to develop a predictive model for CVD-related mortality using a machine learning-based feature selection algorithm and assess its performance compared to existing models. We analyzed data from a cohort of 4,882 adults recruited between 1999 and 2004, followed for up to 20 years. After applying the Boruta algorithm for feature selection, key biomarkers including NT-proBNP, cardiac troponins, and homocysteine were identified as significant predictors of CVD mortality. Predictive models were built using these biomarkers alongside demographic and clinical variables. Model performance was evaluated using the concordance index (C-index), sensitivity, specificity, and accuracy, with internal validation conducted through bootstrap sampling. Additionally, decision curve analysis (DCA) was performed to assess clinical benefit. The combined model, incorporating both biomarkers and demographic variables, demonstrated superior predictive performance with a C-index of 0.9205 (95% CI: 0.9129-0.9319), outperforming models with demographic variables alone (C-index: 0.9030 (95% CI: 0.8938-0.9147)) or biomarkers alone (C-index: 0.8659 (95% CI: 0.8519-0.8826)). Cox regression analysis further identified key predictors of CVD mortality, including elevated AST/ALT, TyG, BUN, and systolic blood pressure, with protective factors such as higher chloride and iron levels. Nomogram construction and DCA confirmed that the combined model provided substantial net benefit across various time points. The integration of cardiac biomarkers, lipid profiles, and inflammatory markers significantly improves the accuracy of predictive models for CVD-related mortality. This novel approach offers enhanced prognostication, with potential for further optimization through the inclusion of additional clinical and lifestyle data.

Exposure to perchlorate and cardiovascular disease in China: A community-based cross-sectional study and benchmark dose estimation

The association between exposure to perchlorate, which inhibits thyroidal iodine uptake, and cardiovascular disease (CVD) is unclear in China. Moreover, the point of departure (POD) for perchlorate based on observed adverse health effect in Chinese populations remains absent. A total of 2355 adults (mean age 50.4 years and 39.2% male) from four communities in Shenzhen were included in analyses. Spot urine specimens were collected to measure urinary perchlorate concentrations, which were applied to estimate daily intakes of perchlorate. Multivariable logistic regression model was applied to examine the association between perchlorate and CVD. The roles of cardiometabolic risk factors, including obesity, abdominal obesity, hypertension, diabetes, and hyperlipidemia, were evaluated with mediation analyses. We further employed Bayesian benchmark dose (BMD) modeling to derive the POD for risk assessment. Comparing extreme tertiles, subjects in the highest perchlorate tertile had a significantly elevated risk of prevalent CVD (OR: 2.16; 95% CI: 1.28, 3.65). Multivariable-adjusted ORs for hypertension, diabetes, and hyperlipidemia associated with per doubling in urinary perchlorate concentration were 1.11 (95% CI: 1.01, 1.21), 1.15 (95% CI: 1.02, 1.28), and 1.11 (95% CI: 1.01, 1.20), respectively. Hypertension, diabetes, and hyperlipidemia partially mediated the perchlorate-CVD association (mediated proportion ranged from 7.75% to 11.30%). Given a benchmark response of 5% and 10%, the model-averaged BMD lower bounds (BMDLs) of perchlorate exposure on CVD were 0.15 and 0.40 μg/kg-bw day, respectively. Our estimated POD for perchlorate was lower than those recommended by other groups. These findings call for stricter regulations on perchlorate contamination to promote cardiovascular health in China.

Thymidine phosphorylase participates in platelet activation and promotes inflammation in rheumatoid arthritis

The elevated risk of cardiovascular disease (CVD) associated with inflammatory rheumatic diseases has long been recognized. Patients with established rheumatoid arthritis (RA) have a higher mortality rate compared to the general population due to abnormal platelet activation. Thymidine phosphorylase (TYMP) plays a crucial role in platelet activation and thrombosis, following bridging the link between RA and CVD. Data from Gene Expression Omnibus (GEO) database exhibited that TYMP levels were highly expressed in synovial tissues, immune cells, and whole blood of RA patients especially those with high levels of inflammation. Platelet count (PLT) and plateletcrit (PCT) were positively correlated with the severity of inflammation in rheumatoid arthritis while platelet distribution width (PDW) and mean platelet volume (MPV) were adverse. Levels of CD62P and TYMP in platelets of patients with active RA were significantly elevated compared to patients in the inactive phase. In vivo experiments showed that reducing TYMP expression levels of platelets could relieve inflammation in Adjuvant-Induced Arthritis (AIA) mice. Platelet activation was significantly elevated in AIA model mice, along with increased levels of intracellular calcium (Ca2+), reactive oxygen species (ROS), and decreased Mitochondrial Membrane Potential (ΔΨm). However, treatment with Tipiracil hydrochloride (TPI) or the utilization of Tymp-/- mice reversed these effects. In vitro stimulation of wild type (WT) mouse platelets with tumor necrosis factor-alpha (TNF-α) promoted platelet activation, elevated levels of intracellular Ca2+as well as ROS while decreased ΔΨm. Platelets of WT mice treated with TPI or platelets of Tymp-/- mice exhibited the adverse results. Our study illustrates the vital role of TYMP in promoting RA inflammation and platelet activation, suggesting that TYMP may be a potential therapeutic target for RA.

Association between triglyceride-glucose index and its composite obesity indexes and cardio-renal disease: analysis of the NHANES 2013-2018 cycle

Background

The association between triglyceride-glucose (TYG) and its composite obesity indexes and cardio-renal disease in the American population remains insufficiently researched.

Methods

This study examined a cohort of 11,491 American adults aged 20 years and older from the 2003-2018 National Health and Nutrition Examination Survey (NHANES). To explore the associations between TYG, TyG-Waist-to-Height Ratio (TyG-WHtR), TyG-Body Mass Index (TyG-BMI), TyG-Waist Circumference (TyG-WC), and chronic kidney disease (CKD), cardiovascular disease (CVD), and cardiorenal syndrome (CRS), we utilized weighted multivariate logistic regression, restricted cubic spline (RCS), Receiver operating characteristic (ROC), and subgroup analyses.

Results

Adjusted for confounding factors, there are positive associations between the likelihood of CKD, CVD, and CRS, as well as TYG and its composite obesity indexes. The TYG index was correlated most strongly with CKD (OR 1.42, 95% CI 1.11, 1.82; P = 0.007), while TyG-WHtR had the strongest correlations with CVD (OR 1.63, 95% CI 1.19, 2.22; P = 0.003) and CRS (OR 1.44, 95% CI 1.00, 2.08; P = 0.055). A nonlinear connection was found by RCS analysis between TYG and its composite obesity indexes with CKD (P for overall < 0.001, P for nonlinear < 0.05), while the association with CVD and CRS was predominantly linear (P for overall < 0.001, P for nonlinear > 0.05). Based on ROC curves, TyG-WHtR and TyG-WC emerged as more reliable diagnostic tools than TYG for cardiac and renal diseases. According to subgroup analyses, TyG and its composite obesity measurements were more strongly associated with CKD in younger individuals (≤ 50), males, and those with diabetes mellitus (P for interaction 0.05).

Conclusions

The TyG-WHtR and TyG-WC are associated with an increased risk of cardiac and renal disease, indicating enhanced diagnostic accuracy. These metrics provide an effective tool for identifying early cardiorenal disease and improving risk stratification.

Association between triglyceride glucose index and adverse cardiovascular prognosis in patients with atrial fibrillation without diabetes: a retrospective cohort study

BACKGROUND

Atrial fibrillation (AF) is the most prevalent arrhythmia encountered in clinical practice. Triglyceride glucose index (Tyg), a convenient evaluation variable for insulin resistance, has shown associations with adverse cardiovascular outcomes. However, studies on the Tyg index's predictive value for adverse prognosis in patients with AF without diabetes are lacking.

METHODS

This retrospective study utilized electronic medical records to collect data on patients with AF hospitalized at West China Hospital from January to June 2020. Participants were categorized into three groups based on their Tyg index levels. The primary outcome, major adverse cardiovascular events, included cardiac death, stroke, and myocardial infarction. Kaplan-Meier curve, Cox proportional hazards regression model, and restricted cubic spline were employed to explore the relationship between the Tyg index and outcomes. The predictive performance of the CHA2DS2-VASc model was evaluated after incorporating the Tyg index.

RESULTS

The study comprised 864 participants (mean age 67.69 years, 55.32% male, 57.52% paroxysmal AF). Patients with high Tyg index had a significantly higher risk of developing major adverse cardiovascular events (MACE) (P < 0.001, hazard ratio: 2.05, 95% confidence interval:1.65-2.56). The MACE risk in the middle Tyg group was similar to that in the low Tyg group (P = 0.1) during the 48-month follow-up period. However, focusing on the last 24 months revealed a higher MACE risk (P = 0.015) in the middle Tyg group. The restricted cubic spline analysis revealed an S-shaped correlation between Tyg and MACE. The CHA2DS2-VASc model combined with the Tyg index showed improved predictive performance and net benefit.

CONCLUSIONS

A high Tyg index is associated with poorer prognosis in patients with AF without diabetes. Integrating the Tyg index into the CHA2DS2-VASc model may enhance its predictive performance, offering clinical utility.

A comprehensive analysis of stroke risk factors and development of a predictive model using machine learning approaches

Stroke is a leading cause of death and disability globally, particularly in China. Identifying risk factors for stroke at an early stage is critical to improving patient outcomes and reducing the overall disease burden. However, the complexity of stroke risk factors requires advanced approaches for accurate prediction. The objective of this study is to identify key risk factors for stroke and develop a predictive model using machine learning techniques to enhance early detection and improve clinical decision-making. Data from the China Health and Retirement Longitudinal Study (2011-2020) were analyzed, classifying participants based on baseline characteristics. We evaluated correlations among 12 chronic diseases and applied machine learning algorithms to identify stroke-associated parameters. A dose-response relationship between these parameters and stroke was assessed using restricted cubic splines with Cox proportional hazards models. A refined predictive model, incorporating age, sex, and key risk factors, was developed. Stroke patients were significantly older (average age 69.03 years) and had a higher proportion of women (53%) compared to non-stroke individuals. Additionally, stroke patients were more likely to reside in rural areas, be unmarried, smoke, and suffer from various diseases. While the 12 chronic diseases were correlated (p < 0.05), the correlation coefficients were generally weak (r < 0.5). Machine learning identified nine parameters significantly associated with stroke risk: TyG-WC, WHtR, TyG-BMI, TyG, TMO, CysC, CREA, SBP, and HDL-C. Of these, TyG-WC, WHtR, TyG-BMI, TyG, CysC, CREA, and SBP exhibited a positive dose-response relationship with stroke risk. In contrast, TMO and HDL-C were associated with reduced stroke risk. In the fully adjusted model, elevated CysC (HR = 2.606, 95% CI 1.869-3.635), CREA (HR = 1.819, 95% CI 1.240-2.668), and SBP (HR = 1.008, 95% CI 1.003-1.012) were significantly associated with increased stroke risk, while higher HDL-C (HR = 0.989, 95% CI 0.984-0.995) and TMO (HR = 0.99995, 95% CI 0.99994-0.99997) were protective. A nomogram model incorporating age, sex, and the identified parameters demonstrated superior predictive accuracy, with a significantly higher Harrell's C-index compared to individual predictors. This study identifies several significant stroke risk factors and presents a predictive model that can enhance early detection of high-risk individuals. Among them, CREA, CysC, SBP, TyG-BMI, TyG, TyG-WC, and WHtR were positively associated with stroke risk, whereas TMO and HDL-C were opposite. This serves as a valuable decision-support resource for clinicians, facilitating more effective prevention and treatment strategies, ultimately improving patient outcomes.

Predictive value of TG/HDL-C and GFR-adjusted uric acid levels on cardiovascular mortality: the URRAH study

BACKGROUND

Insulin resistance (IR) and serum uric acid (SUA) are closely interconnected: SUA contributes to adversely affects the insulin signaling pathway and contributes to IR, while IR is a known predictor for the development of hyperuricemia. The triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio has been proposed as an easily obtainable marker for IR. This research aimed to investigate the interaction between IR and glomerular filtration rate (GFR)-adjusted uricemia (SUA/GFR ratio) in determining CV risk in a large population cohort study.

METHODS

Data from 18,694 subjects were analyzed from Uric acid Right foR heArt Healt (URRAH) database. The study evaluated the association between TG/HDL-C ratio and SUA/GFR ratio, as well as their impact on the development of outcomes during the follow-up study period. The primary endpoint was CV mortality.

RESULTS

After a mean follow-up of 124 ± 64 months, 2,665 (14.2%) CV deaths occurred. The incidence of fatal and non-fatal CV events increased in parallel with the increase of TG/HDL-C quintiles. TG/HDL-C ratio showed a positive association with increasing of SUA/GFR ratio, even in non-diabetic patients. Multivariate analysis showed that the TG/HDL-C ratio increases the mortality risk even after adjustment for potential confounding factors. Finally, IR and GFR-adjusted hyperuricemia showed an additive effect on CV mortality.

CONCLUSIONS

Both IR and SUA/GFR ratio independently predict CV mortality, regardless of age, gender, BMI, diabetes, hypertension and statin use. The joint effect of the TG/HDL-C ratio and the elevated SUA/GFR ratio was greater than the presence of each single risk factor on CV mortality. This highlights the importance of monitoring these markers to better assess cardiovascular risk.

Association between non-insulin-based insulin resistance surrogate makers and Helicobacter pylori infection: a population-based study

BACKGROUND

Current evidence on the associations between insulin resistance (IR) and Helicobacter pylori (H. pylori) infection remains limited. This study aimed to investigate the association between non-insulin-based surrogate markers of IR, including the triglyceride glucose (TyG) index, triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, and the metabolic score for IR (METS-IR), and H. pylori infection in U.S.

POPULATIONS

METHODS

This cross-sectional study involving 939 U.S. participants from the National Health and Nutrition Examination Survey (NHANES) 1999-2000. The associations between three IR surrogate markers and H. pylori infection were respectively investigated using logistic regression model, restricted cubic spline (RCS) curve and subgroup analysis.

RESULTS

Three IR surrogate markers levels were significantly elevated in H. pylori infection participants. There was a positive association between three IR surrogate markers and H. pylori infection, even after adjusting for potential confounding variables by three different models. In subgroup analysis, the adjusted association between three IR surrogate markers and H. pylori infection were more likely to be observed in female and Non-Hispanic White. Additionally, the RCS curve revealed a positive linear correlation between TyG index and H. pylori infection across all three models, and between METS-IR and H. pylori infection in Model 3. However, a positive nonlinear correlation was observed between TG/HDL-C ratio and H. pylori infection in all three models.

CONCLUSIONS

These findings suggest that non-insulin-based IR surrogate markers including TyG index, TG/HDL-C ratio, and METS-IR were all positively associated with H. pylori infection. These markers may serve as the potential indicators for identifying the risk of H. pylori infection in U.S.

POPULATIONS

CLINICAL TRIAL NUMBER

Not applicable.

Association of TyG index with mortality at 28 days in sepsis patients in intensive care from MIMIC IV database

The relationship between the triglyceride‒glucose (TyG) index and the clinical prognosis of septic patients in intensive care units (ICUs) remains unclear. This study aimed to explore the correlation between the TyG index and 28-day all-cause mortality in septic patients. A retrospective observational cohort study was conducted, including 8955 septic patients from the MIMIC IV 2.2 database. The primary outcome was 28-day all-cause mortality. Multivariate logistic regression analysis and restricted cubic spline regression analysis were used to assess the relationship between the TyG index and 28-day all-cause mortality in septic patients. Subgroup analyses and sensitivity analyses were performed to further validate the robustness of the results. A total of 8955 septic patients were included, 5219 (58.3%) of whom were male, with a mean age of 66.3 (15.8) years and an average TyG index of 9.08 (0.70) and the number of deaths within 28 days was 1639 (18.3%). The RCS curve demonstrated a U-shaped relationship between the TyG index and 28-day all-cause mortality (nonlinear P value = 0.0003). The risk of 28-day all-cause mortality was negatively associated with the TyG index until it decreased to 9.03 (adjusted odds ratio [OR] 0.727, 95% confidence interval [CI] 0.577-0.915). However, when the TyG index exceeded 9.03, the odds ratio for 28-day all-cause mortality significantly increased (adjusted OR 1.185, 95% CI 1.001-1.404). These findings were consistent across subgroups and various sensitivity analyses. Our study revealed a nonlinear U-shaped relationship between the TyG index and 28-day all-cause mortality, with a critical point at a TyG index of 9.03. Our results suggest that the TyG index may be a novel and important factor for the short-term clinical prognosis of critically ill septic patients.

Association between triglyceride-glucose (TyG) related indices and cardiovascular diseases and mortality among individuals with metabolic dysfunction-associated steatotic liver disease: a cohort study of UK Biobank

BACKGROUND

Triglyceride-glucose (TyG) related indices, which serve as simple markers for insulin resistance, have been closely linked to metabolic dysfunction-associated steatotic liver disease (MASLD), cardiovascular disease (CVD), and mortality. However, the prognostic utility of TyG-related indices in predicting the risk of CVD and mortality among patients with MASLD remains unclear.

METHODS

Data of 97,331 MASLD patients, with a median age of 58.0 years and free of CVD at baseline, were obtained from the UK Biobank. The TyG index, along with its combination with adiposity parameters (i.e. body mass index [BMI], waist circumference [WC], and waist-to-height ratio [WHtR]), were calculated. Cox proportional hazards models and restricted cubic spline (RCS) were performed to evaluate the associations between TyG-related indices and the risk of overall CVD, coronary heart disease (CHD), stroke, all-cause mortality, and cardiovascular mortality. Additionally, Harrell's C-index, net reclassification index (NRI), and integrated discrimination improvement index (IDI) were used to assess the predictive performance of these indices.

RESULTS

Over a median follow-up of 13.56 years, we identified 13,256 cases of overall CVD, 10,980 CHD, 2,926 stroke, 8,809 all-cause mortality, and 1,796 cardiovascular mortality. Compared with the lowest quartile of TyG-related indices, participants with MASLD in the high quartile of TyG-related indices had a significantly increased risk of incident overall CVD, CHD, stroke, and mortality. Specifically, the hazard ratios of occurring overall CVD in the fourth versus the first quartiles were 1.19 (95% confidence interval: 1.13-1.25) for TyG, 1.35 (1.28-1.42) for TyG-BMI, 1.33 (1.26-1.40) for TyG-WC, and 1.39 (1.32-1.46) for TyG-WHtR. RCS analyses indicated a nonlinear association of TyG with CVD outcomes (all P values for nonlinearity < 0.05), whereas there exhibited linear trends in TyG-BMI, TyG-WC, and TyG-WHtR with CVD outcomes (all P values for nonlinearity > 0.05, except for TyG-WC with stroke). Furthermore, TyG-WC and TyG-WHtR demonstrated the significantly higher C-index, NRI, and IDI in predicting risk of CVD and mortality in MASLD patients.

CONCLUSION

TyG-related indices, especially TyG-WC and TyG-WHtR, had significant predictive values for the risk of incident CVD and mortality in individuals with MASLD. TyG-related indices may serve as effective surrogate predictors of CVD and mortality in MASLD patients.

Inflammatory markers link triglyceride-glucose index and obesity indicators with adverse cardiovascular events in patients with hypertension: insights from three cohorts

BACKGROUND

Among hypertensive cohorts across different nations, the relationship between the triglyceride-glucose index (TyG) and its conjunction with obesity metrics in relation to cardiovascular disease (CVD) incidence and mortality remains to be elucidated.

METHODS

This study enrolled 9,283, 164,357, and 5,334 hypertensives from the National Health and Nutrition Examination Survey (NHANES), UK Biobank (UKBB), and Shanghai Pudong cohort. The related outcomes for CVD were defined by multivariate Cox proportional hazards models, Generalized Additive Models and Mendelian randomization analysis. Mediation analysis explored the mediating role of inflammatory markers in the above relationships.

RESULTS

Five measures of insulin resistance were linked to CVD and related death in a U-shaped pattern, with the highest group having different risk increases. Higher glucose triglyceride-waist height ratio (TyG-WHTR) was linked to higher all-cause mortality (UKBB: HR 1.21, 95%CI 1.16-1.26, NHANES: HR 1.17, 95%CI 1.00-1.36), CVD mortality (UKBB: HR 1.36, 95%CI 1.23-1.49, NHANES: HR 1.32, 95%CI 1.00-1.72) risks. In the China Pudong cohort, higher triglyceride/high-density lipoprotein-cholesterol (TG/HDL_C) ratio was associated with higher risks of CVD and stroke (HR 1.31, 95%CI 1.00-1.73 and 1.67, 1.06-2.63). Inflammation markers like systemic inflammatory response index (SIRI) and C-reactive protein (CRP) partially explained these links, with CRP having a stronger effect. Genetically predicted TyG was also linked to stroke (OR 1.26, 95%CI 1.10-1.45) risk.

CONCLUSIONS

An elevated TyG index and its related indices are significantly correlated with an increased risk of CVD and related mortality across three national cohorts. These indices are anticipated to serve as valid predictors of incident CVD and mortality in individuals with hypertension.

Atherosclerosis and the Bidirectional Relationship Between Cancer and Cardiovascular Disease: From Bench to Bedside, Part 2 Management

The first part of this review highlighted the evolving landscape of atherosclerosis, noting emerging cardiometabolic risk factors, the growing impact of exposomes, and social determinants of health. The prominent role of atherosclerosis in the bidirectional relationship between cardiovascular disease and cancer was also discussed. In this second part, we examine the complex interplay between multimorbid cardio-oncologic patients, cardiometabolic risk factors, and the harmful environments that lend a "syndemic" nature to these chronic diseases. We summarize management strategies targeting disordered cardiometabolic factors to mitigate cardiovascular disease and explore molecular mechanisms enabling more tailored therapies. Importantly, we emphasize the early interception of atherosclerosis through multifactorial interventions that detect subclinical signs (via biomarkers and imaging) to treat modifiable risk factors and prevent clinical events. A concerted preventive effort-referred to by some as a "preventome"-is essential to reduce the burden of atherosclerosis-driven chronic diseases, shifting from mere chronic disease management to the proactive promotion of "chronic health".

Exploring the mediating role of depression in the relationship between sarcopenia and cardiovascular health in the middle-aged and elderly: A cross-sectional study

BACKGROUND

Cardiovascular health is influenced by various factors, including sarcopenia and depression. It has been demonstrated that sarcopenia has a negative impact on cardiovascular disease, with depression also being a contributing factor. However, the complex interplay between sarcopenia, depressive symptoms, and cardiovascular health in middle-aged and elderly populations is not fully explored.

METHODS

A total of 23,445 participants participated in China Health and Retirement Longitudinal Study and completed relevant measurements, including the Centre for Epidemiological Studies Depression Scale. The study also assessed sarcopenia and cardiovascular health score. The focus of the study was to test whether the association between sarcopenia and cardiovascular health scores was mediated by depression using PROCESS macros in R 4.3.2. Sensitivity analyses were conducted to affirm the robustness of our findings.

RESULT

The study revealed a partial mediation between sarcopenia and cardiovascular health score among the middle and elder adults, mediated by depression. Sarcopenia had a significant negative correlation with cardiovascular health score (B = -12.404, P < 0.05), and depression also showed a significant negative correlation (B = -1.515, P < 0.001).

CONCLUSION

The results support the notion that depression partially mediated the association between sarcopenia and cardiovascular health score. Therefore, interventions aimed at improving mood and addressing other cardiovascular risk factors may help alleviate the adverse effects of sarcopenia and potentially reduce the progression to cardiovascular disease.