The triglyceride-glucose (TyG) index has emerged as a credible surrogate indicator of insulin resistance in recent years. This study aimed to investigate the relationship between the TyG index and the deterioration of kidney function in patients with cardiovascular-kidney-metabolic (CKM) syndrome.

In this retrospective cohort study from China, 27,407 hospitalized patients with stage 1-4 CKM syndrome were consecutively included. The participants were categorized into four groups according to TyG index quartiles. The study outcome was the deterioration of kidney function, defined as a decrease in estimated glomerular filtration rate (eGFR) ≥ 40% from baseline. Restricted cubic spline (RCS) curves and multivariate Cox analysis were used for analysis.

3,248 outcome events were recorded during a mean follow-up period of 34 months. The RCS plot displayed a U-shaped curve between the baseline TyG index and the deterioration of kidney function (P for non-linear < 0.001). The baseline TyG index with the lowest hazard ratio (HR) of eGFR decline ranges from 8.65 to 9.15, with an inflection point at 8.88. After fully adjusting for covariates, HRs and 95% confidence intervals (CIs) from the lowest to highest TyG index quartile were 1.00 (reference), 0.82 (0.74, 0.91), 0.78 (0.70, 0.86), and 0.93 (0.83, 1.03), respectively. According to the Kaplan-Meier survival curve, the risk of deterioration of kidney function was elevated in the lowest and highest TyG index quartiles (log-rank test, p < 0.0001).

In individuals with CKM syndrome, a non-linear U-shaped relationship existed between the baseline TyG index and the deterioration of kidney function.

The triglyceride-glucose (TyG) related indices, indicators for insulin resistance, and depression are both established predictors of cardiovascular diseases. However, the single and combined effect of TyG related indices and depression on cardio-renal-metabolic multimorbidity (CRMM) risk remain uncertain.

This study included 7848 respondents aged 45 years and older, derived from the China Health and Retirement Longitudinal Study (CHARLS) 2011, 2020. Cox regression was used to determine independent and joint effect of TyG indices and depression on CRMM incidence. Restricted cubic spline (RCS) was further performed to identify associations of TyG indices with CRMM.

Results demonstrated that both TyG indices (including TyG-WC, TyG-WHtR, and TyG-BMI) and depression were independently linked to increased risk of CRMM. The RCS model further confirmed the significant dose-response relationships. Participants experiencing both elevated TyG indices and depression exhibited the highest CRMM risk, in contrast to those with neither condition (HR = 1.630, 95%CI: 1.467-1.811; HR = 1.631, 95%CI: 1.465-1.817; HR = 1.582, 95%CI: 1.419-1.764; HR = 1.532, 95%CI: 1.372-1.711, respectively).

Firstly, disease diagnoses in the CHARLS were self-reported, which might cause recall bias. Then, data was specific to the population over 45 years old, so the results may not apply broadly to all populations.

This study revealed both the single and joint effect of TyG, TyG-WC, TyG-WHtR, as well as TyG-BMI and depression on CRMM risk. Combined evaluations of the TyG index with depression screening is crucial for identifying related risk factors and enhancing prevention strategies against CRMM.

Current literature lacks evidence to characterize the relationship between the triglyceride glucose - body mass index (TyG-BMI) and depression. Therefore, this study aimed to elucidate the potential association between TyG-BMI and depression risk in a Chinese middle-aged and elderly population.

The study utilized data from the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, which included 17,708 participants. We used multifactorial logistic regression modeling to investigate the relationship between TyG-BMI and depression in Chinese adults, using smoothed curve fitting to assess the nonlinear relationship between them. In addition, we performed sensitivity and subgroup analyses to verify the robustness of the results.

A total of 9328 participants were included in our study, After adjusting for all potential covariates, participants with higher levels of TyG-BMI had a lower risk of depression compared to Q1, the adjusted OR (95 % CI) values were Q2 (OR: 0.84, 95 % CI: 0.74-0.96, p = 0.009), Q3 (OR: 0.75, 95 % CI: 0.65-0.86, p < 0.001), and Q4 (OR: 0.67, 95 % CI: 0.57-0.79, p < 0.001). The association between TyG-BMI and depression exhibited an L-shaped curve (nonlinear, p = 0.004). When TyG-BMI <200, Increased TyG-BMI was associated with a significantly lower risk of depression (OR = 0.87 [95 %CI:0.82-0.93], p < 0.001). However, there was no association between TyG-BMI and depression when TyG-BMI ≥200 (OR = 0.96 [95 %CI:0.91-1.02], p = 0.22).

The connection between TyG-BMI and depression in Chinese adults is L-shaped, with an inflection point around 200.

Vascular insulin resistance has emerged as a pivotal factor in the genesis of cardiovascular disease (CVD) in people with diabetes. It forms a complex pathogenic partnership with metabolic insulin resistance to significantly amplify the CVD risk of diabetes and other affected populations. Metabolic insulin resistance (characterized by quantitatively diminished insulin action on glucose metabolism in skeletal muscle, liver, and adipose tissue) is a hallmark of diabetes, obesity, and related conditions. In contrast, vascular insulin resistance is a less appreciated and not well-quantified complication of these conditions. Importantly, an impaired vascular response to insulin contributes directly to vascular dysfunction and over 40 years of research has convincingly shown that vascular and metabolic insulin resistance synergize to create an environment that predisposes individuals to CVD. In this review, we examine the multifaceted vascular actions of insulin, including its roles in regulating blood pressure, blood flow, endothelial health, and arterial stiffness. We also examine how these processes become disrupted in the setting of vascular insulin resistance, which subsequently undermines endothelial function, compromises tissue microvascular perfusion, and promotes vascular rigidity and atherosclerosis. We then highlight potential therapeutic strategies with demonstrated efficacy to improve vascular insulin sensitivity in people with diabetes and suggest that targeting disordered vascular insulin signaling holds promise not only for refining the functional understanding of vascular insulin resistance but also for developing innovative treatments with potential to reduce CVD risk and improve cardiovascular outcomes in people with diabetes.

Triglyceride- glucose (TyG) index, a marker of insulin resistance, has been shown to be associated with the incidence of cardiometabolic diseases including hypertension. However, the prognostic role of TyG index is unknown. Hence, we aim to determine the association of TyG index with major adverse cardiovascular events (MACE) in hypertensive patients.

Systematic searching was conducted on 3 databases up till November 2024. We included studies with hypertensive patients despite their comorbidities. Outcome measured is MACE and its individual components. Random effect model meta-analysis is done to pool the results with similar reference point.

Twenty observational studies with a total of 451,455 patients of 40 - 70 years old are included. Meta-analysis result shows that higher TyG index is associated with a statistically significant increased risk of MACE (HR 1.90, CI: 1.41 - 2.57, I2 88 %), myocardial infarction (HR 1.55, CI: 1.27 - 1.88, I2 0 %), stroke (HR 1.84, CI: 1.41 - 2.39, I2 62 %), all- cause mortality (HR 1.86, CI: 1.70 - 2.03, I2 0 %) and cardiovascular mortality (HR 1.08, CI: 1.04 - 1.11, I2 0 %). Subgroups of older and younger population, male and female gender, diabetic and non- diabetic population, and higher BMI patients retains the statistically significant risk of MACE (p < 0.05). U- shaped phenomena of TyG index is also demonstrated with the risk of all- cause mortality.

TyG index is a reliable prognostic marker of MACE in hypertensive patients and can be utilized in population despite their age, diabetic status, and gender.

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

Data for the study cohort were sourced from the National Health and Nutrition Examination Survey (1999-2018). Study participants were classified as obese (BMI ≥ 30 kg/m²) or nonobese (BMI < 30 kg/m²) then further categorized as metabolically healthy or unhealthy on the basis of metabolic syndrome criteria, resulting in four groups: metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), metabolically healthy nonobese (MHNO), and metabolically unhealthy nonobese (MUNO). Complex sampling statistical methods were employed for descriptive analysis. The associations between the TyG index and mortality, including all-cause and cardiovascular mortalities, were examined by using multivariable Cox regression and restricted cubic splines (RCS). The reliability of the results was confirmed through multiple sensitivity analyses.

Data for the study cohort were sourced from the National Health and Nutrition Examination Survey (1999-2018). Study participants were classified as obese (BMI ≥ 30 kg/m²) or nonobese (BMI < 30 kg/m²) then further categorized as metabolically healthy or unhealthy on the basis of metabolic syndrome criteria, resulting in four groups: metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), metabolically healthy nonobese (MHNO), and metabolically unhealthy nonobese (MUNO). Complex sampling statistical methods were employed for descriptive analysis. The associations between the TyG index and mortality, including all-cause and cardiovascular mortalities, were examined by using multivariable Cox regression and restricted cubic splines (RCS). The reliability of the results was confirmed through multiple sensitivity analyses.

A total of 16 179 participants were included, with a median follow-up of 129 months. Over this follow-up period, 1875 participants (11.59%) died from all causes, including 568 (3.51%) who died due to cardiovascular diseases. After adjustment for confounding variables, the TyG index significantly predicted mortality in the overall and metabolically unhealthy populations: for each one standard deviation increase in the TyG index, all-cause mortality increased by 1.42 times (95% confidence interval [CI]: 1.27, 1.58) in the overall population, by 1.62 times (95% CI: 1.36, 1.93) in the MUNO group, and by 1.47 times (95% CI: 1.26, 1.71) in the MUO group. Cardiovascular mortality in the overall population increased by 1.52 times (95% CI: 1.27, 1.82), that in the MUNO group increased by 2.01 times (95% CI: 1.49, 2.72), and that in the MUO group increased by 1.47 times (95% CI: 1.14, 1.88). No significant association was found in the metabolically healthy populations regardless of obesity status. RCS and sensitivity analyses further confirmed and visualized these conclusions.

The TyG index is positively correlated with mortality risk in the overall and metabolically unhealthy populations but not in the metabolically healthy populations. This finding indicates that the predictive value of the TyG index for mortality differs across populations, highlighting the necessity of accounting for metabolic status when the TyG index is used for prognostic evaluation.

The triglyceride-glucose (TyG) index was associated with higher risk of mortality in individuals with Cardiovascular-Kidney-Metabolic (CKM) syndrome stages 0-3. However, the relationship between cumulative of TyG (cumTyG) and incidence of stroke remains unclear in individuals with CKM syndrome stages 0-3.

Participants with CKM syndrome stage 0-3 were enrolled from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2015. TyG was calculated as ln [fasting triglyceride (mg/dL)×fasting glucose (mg/dL)/2], and the cumTyG, as an area-under-the-curve estimate (mean TyG × time span), was calculated as (TyG2012 + TyG 2015)/2 * time (2015-2012). TyG control levels were classified using k-mean clustering analysis. Logistic regression was used to analyze the effect of cumTyG and TyG control levels on the incidence of stroke. Restricted cubic spline models (RCS) were performed to explore the potential non-linear relationship between cumTyG and stroke risk at different CKM syndrome stages 0-3.

A total of 4,700 CKM syndrome stages 0-3 participants were enrolled, among 280 patients had developed stroke during the 3-year follow-up period. After adjusting for confounders, compared to class 1 group, the odds ratio (OR) of incidents of stroke for class 2 was 1.39 [95% confidence interval (CI) 1.003, 1.92], P = 0.046; the OR of incidents of stroke for class 3 was 1.28 (95% CI 0.92-1.77), P = 0.147, the OR of incidents of stroke for class 4 was 1.28 (95% CI 0.84-1.94), P = 0.238. Elevated cumTyG was associated with an increase in incidence of stroke (OR 1.13, 95% CI 1.05, 1.22, P = 0.002). The relationship between the cumTyG index and stroke was linear in restricted cubic spline regression.

Elevated cumTyG was associated with an increased risk of stroke events in the population of CKM syndrome stages 0-3. Long-term dynamic monitoring of changes of TyG may help in the early identification of patients at high risk of developing stroke in the individuals with CKM syndrome stages 0-3.

The triglyceride-glucose (TyG) index is regarded as a surrogate marker of systemic insulin resistance (IR). Studies have substantiated the impact of IR on cardiovascular diseases. Nonetheless, the prognostic value of the TyG index in critical patients with heart failure (HF) with intensive care unit (ICU) admission remains unclear. This study aims to assess the association between the TyG index and all-cause mortality in critically ill patients with HF. Patients with HF requiring ICU admission were identified from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and subsequently stratified into quartiles based on their TyG index. The primary outcome was 30-day all-cause mortality, and the secondary outcome was 1-year all-cause mortality. The relationship between the TyG index and all-cause mortality in HF patients was analyzed using multivariable Cox proportional hazards models and restricted cubic splines. A total of 1220 patients (62.4% men) were enrolled, with a mean age of 70.6 years. The 30-day and one-year all-cause mortality rate were 15.7% and 34.6%, respectively. Multivariable Cox regression revealed that TyG index was significantly associated with an elevated risk of 30-day all-cause mortality (adjusted HR, 1.360; 95% CI, 1.093-1.694; P = 0.006), but not with one-year mortality (adjusted HR 1.046; 95% CI 0.895-1.222, P = 0.574). Restricted cubic splines showed a progressively increasing risk of 30-day mortality was linearly related to an elevated TyG index. Subgroup analyses indicated a more prominent association between TyG index and 30-day mortality in patients with age ≤ 65, female or BMI > 30 kg/m2. In critically ill patients with HF, the TyG index is significantly associated with short-term all-cause mortality. Our results highlight that the TyG index can be useful in identifying HF patients at high risk of all-cause mortality and require close follow-up after discharge.

Insulin resistance and central obesity are major risk factors for cardiometabolic diseases. The triglyceride-glucose index (TyG) and lipid accumulation product (LAP) are markers that independently predict cardiometabolic risk. However, their combined long-term trajectories and impact on cardiometabolic multimorbidity (CMM) development remain unclear.

This cohort study utilized data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, which tracked 3467 participants at baseline. Dual-trajectory of TyG and LAP were identified using a group-based dual-trajectory model. Cox proportional hazards models were employed to assess the relationships between dual-trajectory groups and primary cardiometabolic outcomes, including first cardiometabolic disease (FCMD), CMM (two or more conditions such as type 2 diabetes, coronary heart disease, or stroke), and all-cause mortality. Multi-state models were performed to assess the associations of dual-trajectory with CMM development.

The study included 3467 participants with a mean age of 25.08 years (SD = 3.59). Of these, 43.4% (n = 1505) were male, and 53.2% (n = 1561) were White. Three distinct dual-trajectory groups were identified: low-increasing (61.5%), high-amplitude fluctuation (7.6%), and high-increasing (30.9%). After multivariate adjustment, compared with the low-increasing group, the high-amplitude fluctuation group exhibited significantly higher risks for FCMD (hazard ratio [HR] 1.38, 95% confidence interval [CI]: 1.08-1.77), CMM (HR 2.63, 95% CI 1.21-5.71), and all-cause mortality (HR 2.16, 95% CI 1.30-3.56), as well as elevated risks for transitions from baseline to FCMD (HR 1.41, 95% CI 1.17-1.63), FCMD to CMM (HR 2.07, 95% CI 1.53-3.96), CMM to death (HR 2.87, 95% CI 1.19-7.62). The high-increasing group showed similar results.

Elevated and fluctuating trajectories of TyG and LAP from early adulthood are associated with increased risks of CMM development in midlife.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is closely associated with insulin resistance (IR). However, the prognostic value of different alternative IR surrogates in patients with MASLD remains unclear. This study aimed to evaluate the association between various IR indices and all-cause mortality and cardiovascular mortality in MASLD patients.

A total of 8,753 adults aged ≥ 20 years with MASLD from the National Health and Nutrition Examination Survey (NHANES, 2003-2018) were included, and their mortality data were obtained from the National Death Index (NDI). Insulin resistance surrogates [including the triglyceride-glucose (TyG) index, TyG-body mass index (TyG-BMI), TyG-waist circumference index, TyG-waist-to-height ratio index, and Homeostatic Model Assessment for IR] were stratified into quartiles. Cox proportional hazards models, receiver operating characteristic (ROC) curve analysis, restricted cubic spline (RCS), mediation analyses, and subgroup analyses were used to explore the associations between these indices and all-cause mortality as well as cardiovascular mortality in MASLD patients.

During a median follow-up of 98 months, 1,234 deaths were observed, including 409 cardiovascular disease (CVD)-related deaths. In the fully adjusted model, higher quartiles of TyG-related indices were significantly associated with an increased risk of all-cause mortality in MASLD patients. Furthermore, the TyG-BMI index was associated with both all-cause mortality and CVD mortality [all-cause mortality: HR (95% CI) 2.84 (1.73-4.67), P < 0.001; CVD mortality: HR (95% CI) 5.32 (2.26-12.49), P < 0.001]. The RCS analyses indicated a U-shaped relationship between TyG-BMI and mortality, with a threshold value of 270.49. Subgroup analyses demonstrated that TyG-related indices had stronger associations with mortality in elderly MASLD patients.

Our findings highlight the prognostic value of IR indices, particularly TyG-BMI index, in predicting all-cause mortality and CVD mortality in MASLD patients.

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.

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.

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).

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.

Many studies have demonstrated that multiple metabolic risk factors (MRFs) predict cardiovascular disease (CVD) in patients with diabetes, but changes in these markers before CVD onset are not well characterized. We aimed to explore the trajectories of various MRFs before the occurrence of CVD in patients with newly diagnosed diabetes.

Prospective cohort study.

We selected 21,798 patients with newly diagnosed diabetes from seven cycles in the Kailuan cohort. MRFs were measured at two-year intervals prior to CVD diagnosis. We used the mixed effects models to construct trajectories for 16 MRFs respectively.

During up to 15 years of follow-up, a total of 2,105 CVD events occurred. Participants who developed CVD had more adverse levels of most MRFs at baseline and during follow-up than those who did not develop CVD. Before CVD diagnosis, fasting plasma glucose, insulin resistance, pulse pressure, heart rate, liver function, and inflammatory biomarkers showed linear increases, while insulin sensitivity, lipids profiles, obesity indices, and diastolic blood pressure showed linear decreases. Systolic blood pressure, as one of the most important components in predicting CVD, showed a quadratic increase.

In patients with newly diagnosed diabetes, unfavorable levels of MRFs were present before CVD developed. Key MRFs, including the TyG index, VAI, SBP, and pulse pressure, progressively increased over time and remained higher compared to non-CVD populations. This highlights the need for early prevention to reduce the burden of cardiovascular complications in diabetes.

The relationship between triglyceride-glucose (TyG) index and all-cause or cardiovascular mortality among infertile women remains unclear. In this study, we intended to utilize a national cohort from National Health and Nutrition Examination Survey (NHANES) to check the association between them.

Ten datasets from the NHANES database spanning almost 20 years were used as the data source and were combined within National Death Index for mortality follow-up. Multiple-variable Cox proportionate hazards regression models and three others were employed in this study to for assessing relationships among TyG index levels with all-cause and cardiovascular mortality. SPSS (version 29.0) and online websites were utilized for conducting the primary statistical analyses.

1,450 female participants were identified in this study. The samples were classified based on TyG index quartiles (7.05-11.95). The TyG index had a mean of 8.58±0.66. Participants with higher TyG indices were older-aged, had greater body mass index (BMI), and a stronger likelihood of having hypertension and diabetes (P < 0.05). Participants whose TyG indices were higher were older in age, along with increased BMI, and blood pressure along with diabetes (P < 0.05). Significant positive associations were observed among the TyG index and total mortality in the crude model (HR: 1.81, 95% CI: 1.27-2.58). Correlation persisted in Model 2 (following the adjustment of age and race) and Model 3 (following the adjustment of age, race, BMI, education, family poverty income ratio, smoking and drinking habits, menstrual regularity, hypertension, and diabetes). The TyG index did not affect the cardiovascular mortality in infertile women.

TyG index levels were in positive association with all-cause mortality within the female infertile population.

The triglyceride glucose-weight adjusted waist index (TyG-WWI) has emerged as a straightforward and reliable alternative for assessing insulin resistance (IR). However, the relationship between the TyG-WWI index and the incidence of stroke, especially in individuals with different glucose metabolism status, is still unclear. The data for this study was obtained from the China Health and Retirement Longitudinal Study (CHARLS). The primary endpoint was the occurrence of stroke events. We utilized multivariate Cox proportional hazard models and restricted cubic spline (RCS) analysis to examine the relationship between the TyG-WWI index and the risk of stroke in individuals with different glycemic metabolic states. A total of 8895 participants were included in this study, 831 (9.3%) stroke events were recorded during the follow-up period. After fully adjusting for covariates, per SD increase in the TyG-WWI index was associated with a 11% increase in stroke risk (HR: 1.11, 95% CI 1.02, 1.20) in all participants. The TyG-WWI index was further categorized into quartiles, the adjusted HRs (95% CIs) for Q2, Q3, and Q4 compared to Q1 being 1.37 (95% CI 1.09, 1.72), 1.42 (95% CI 1.13, 1.78), and 1.50 (95% CI 1.17, 1.93), respectively. Furthermore, high levels of the TyG-WWI index were found to be linked to an increased risk of stroke in prediabetes mellitus (Pre-DM) participants across Cox models. However, this association was not observed in participants with normal glucose regulation (NGR) and diabetes mellitus (DM) (all P > 0.05). RCS analysis also demonstrated that higher baseline TyG-WWI index levels were associated with higher HRs for stroke in all participants and those with Pre-DM. The TyG-WWI index significantly associates with stroke risk in middle-aged and elderly Chinese populations. Moreover, this relationship exhibits distinct characteristics influenced by the individual's glucose metabolism status.

Obesity and insulin resistance are well-established risk factors for atherosclerosis and cardiovascular disease (CVD). Although some obesity- and insulin resistance-related indices (OIRIs) have been linked to CVD, their associations with subclinical carotid atherosclerosis (SCA) in individuals with type 1 diabetes (T1D) remain unclear. This study aims to systematically explore and compare the associations of various common OIRIs with SCA in T1D population.

A total of 418 adult inpatients with classic T1D admitted from October 2008 to June 2021 to the First Affiliated Hospital of Air Force Medical University in Xi'an, China were included in this study. Demographic, anthropometric, and laboratory data were collected. Studied OIRIs comprised body mass index, waist-to-height ratio, waist-to-hip ratio (WHR), a body shape index, abdominal volume index, body adiposity index, body roundness index, conicity index, triglyceride-glucose index, visceral adiposity index, Chinese visceral adiposity index (CVAI), lipid accumulation product, estimated glucose disposal rate (eGDR), triglyceride-to-HDL ratio, and cardiometabolic index. Binary logistic regression, restricted cubic spline (RCS), and receiver operating characteristic curves were used to examine the associations of these indices with SCA.

In multivariable logistic regression analyses, after adjusting for potential confounders, per 1.0-standard deviation (SD) increase in CVAI (OR, 95% CI: 1.68, 1.16-2.47), eGDRWHR (eGDR calculated with WHR; OR, 95% CI: 0.44, 0.22-0.82), and eGDRWC (eGDR calculated with waist circumference; OR, 95% CI: 0.49, 0.24-0.93) were significantly associated with SCA. CVAI exhibited the highest area under the curve (AUC) in diagnosing SCA, with a value of 0.73 (95% CI: 0.69-0.77). RCS analyses indicated a linear and positive association between CVAI and SCA in the overall population and the females. Subgroup analyses and sensitivity analyses further supported the association between CVAI and SCA. Additionally, adding CVAI to the Steno Type 1 Risk Engine (ST1RE) improved the reclassification, but did not enhance the overall discriminative ability of ST1RE to identify SCA.

Among various OIRIs, CVAI shows the strongest association with SCA in adults with T1D. These findings suggest that CVAI may merit further longitudinal investigation as a potential marker for SCA assessment in this population.

Currently, there is a paucity of literature addressing personalized risk stratification using multimodal data in patients with symptomatic aortic stenosis and heart failure with preserved ejection fraction (HFpEF) following transcatheter aortic valve replacement (TAVR).

This study aimed to enhance the performance of risk assessment models in this patient population by developing a predictive model for adverse outcomes using various machine learning (ML) techniques.

This multicenter cohort study included 326 patients diagnosed with severe AS and HFpEF who underwent TAVR between January 2017 and December 2023. Patients were allocated to training (n=195) and independent validation (n=131) sets based on hospital affiliation. A dual-phase feature selection process, combining least absolute shrinkage and selection operator logistic regression and the Boruta algorithm, was used to identify relevant variables from the multimodal dataset. A total of 5 ML model-decision trees, K-nearest neighbors, random forest, support vector machine, and extreme gradient boosting were used to construct a visualization and explainable predictive framework to elucidate model decision-making processes.

The primary features identified included age, N-terminal pro-brain natriuretic peptide, fasting blood glucose, triglyceride/high-density lipoprotein cholesterol ratio, triglyceride glucose index, triglyceride glucose-BMI index, atherogenic index of plasma index, and Apolipoprotein B. Among the 5 models, the support vector machine demonstrated the best predictive performance for major adverse cardiovascular and cerebrovascular events in patients with severe AS and HFpEF following TAVR, achieving an area under the curve of 0.756 (95% CI 0.631-0.881) in the independent validation set. The model exhibited good calibration and robust predictive power in both training and validation sets and demonstrated the highest net benefit in decision curve analysis compared to other models. To extract significant variables influencing the algorithm and ensure model appropriateness, we interpreted cohort and personalized model predictions using Shapley Additive Explanations values.

Our ML-based multimodal model, incorporating 8 readily accessible predictors, demonstrated robust predictive capability for 12 months of major adverse cardiovascular and cerebrovascular events risk. This model can be used to identify high-risk individuals with AS and HFpEF following TAVR, potentially aiding in risk stratification and personalized treatment strategies.

The triglyceride-glucose index (TyG) and the triglyceride to high-density lipoprotein ratio (TG/HDL-c) are novel indicators for assessing insulin resistance (IR) in epidemiological studies. This study aimed to evaluate the association between 25-hydroxy-vitamin D [25(OH)D] levels and these two indicators in the adult population of the United States. 14,380 participants aged 20 years and older were included from the National Health and Nutrition Examination Survey (NHANES). Multivariable linear regression models were used to analyze the association between 25(OH)D and TyG, as well as TG/HDL-c. Smooth fitting curves were employed to identify potential non-linear relationships between 25(OH)D, TyG, and TG/HDL-c. The findings revealed a negative association between 25(OH)D and TyG, with the effect being more pronounced in males and individuals with diabetes (p < 0.01). Similarly, 25(OH)D was negatively associated with TG/HDL-c, with a stronger impact observed in males compared to females. The study population was divided into four quartiles based on 25(OH)D concentration, and TyG and TG/HDL-c levels in Q3 and Q4 were lower than those in Q1. Furthermore, a non-linear relationship was observed between 25(OH)D and TyG, with an inflection point at 19.352 ng/mL. A non-linear relationship was also found between TG/HDL-c and 25(OH)D, with an inflection point at 37.211 ng/mL. 25(OH)D is an independent factor significantly associated with TyG and TG/HDL-c indexes. This negative association may be related to the role of 25(OH)D in insulin resistance.

Delirium is a complex medical condition marked by acute episodes of cognitive dysfunction and behavioral disturbances, with a multifaceted etiology and challenging management across various clinical settings. Older adults, particularly in postoperative contexts, are at increased risk of developing delirium. Despite extensive research, a single underlying pathophysiological mechanism for delirium remains elusive. However, emerging evidence suggests a correlation between lipid dysregulation and delirium development in elderly patients, especially in postoperative settings. This connection has led to proposed treatments targeting dyslipidemia and associated neuroinflammatory effects in acute-phase delirium. This review aims to synthesize current literature on the relationship between lipid dysregulation and delirium in older adults, highlighting the need for further research into specific neurolipidome constituents and age-related lipid profile changes, potentially uncovering novel therapeutic strategies for delirium.

The triglyceride-glucose (TyG) index, recognized as a surrogate marker for insulin resistance, is an established cardiovascular risk factor. We aimed to prospectively investigate the association between the TyG index and aortic valve calcific (AVC) progression, as well as its relationship with incident calcific aortic valve stenosis (CAVS).

A post hoc analysis was conducted on 5589 participants from the Multi-Ethnic Study of Atherosclerosis (MESA) database. The TyG index was calculated using ln (fasting triglycerides [mg/dL] × fasting glucose [mg/dL]/2). Multivariate Cox regression assessed the association between baseline TyG index and AVC progression. Two-sample Mendelian randomization (MR) analysis was employed to evaluate the potential causality between the TyG index and CAVS.

Over a median 2.4 years follow up, 567 cases of AVC progression were idenrified. After adjusting for traditional cardiovascular risk factors, each 1-SD increase in the TyG index was associated with a 20.8% increased risk of AVC progression. Robustness was confirmed in sensitivity analyses and nearly all subgroups. Two sample MR analysis supported a causal relationship between a higher TyG index and increased risk of CAVS.

A higher TyG index independently predicts AVC progression and causally influences CAVS incidence in the general population.

This study examines the relationship between the TyG index and the risk of sudden cardiac death (SCD) in the patients with diabetic foot ulcer (DFU).

688 type 2 diabetes mellitus (T2DM) inpatients with DFU between January 2010 and December 2023 was included in this retrospective study. The 1:1 propensity score matching (PSM) method was applied. The relationship between TyG index and SCD risk was analyzed using the Kaplan-Meier (K-M) survival curve analysis, multivariate Cox proportional hazard regression model, Restricted cubic spline (RCS) model analysis and subgroup analyses.

Over a median follow-up period of 61 months, 38 cases of SCD were recorded. After PSM, 71 pairs of score-matched patients according to TyG index were generated. K-M survival curves revealed higher SCD rates in patients with TyG index ≥9.65. The Cox proportional hazard model, independently associated with the risk of SCD (HR: 75.98; 95 % CI: 9.16 ∼ 630.40; P < 0.001). RCS model showed that SCD risk was non-linearly correlated with gradual increases in TyG index levels. Stratified analyses indicated a consistent relationship between increasing TyG index and SCD risk across all subgroups.

Elevated TyG index independently confers an increased risk for SCD in individuals with DFU.

Limited researches have investigated the association between the Triglyceride-glucose index (TyG) and frailty vulnerability in middle-aged and older Chinese populations. This study aims to strengthen the scientific foundation for frailty prevention and management by analyzing the correlation between TyG and frailty, ultimately providing more targeted intervention strategies.

This study included middle-aged and older individuals who participated in the China Health and Retirement Longitudinal Study (CHARLS) from 2015. A multiple logistic regression model was constructed to assess the correlation between the TyG index and frailty. Additionally, restricted cubic spline (RCS) analysis was employed to evaluate the dose-response correlation between the two variables.

Among the 3,978 participants included in the study, 667 individuals (16.8%) were identified with frailty. After adjusting for multiple factors in a logistic regression model, it was determined that individuals in the highest quartile group of the TyG index had a 1.43 times higher risk of frailty compared to those in the lowest quartile group (OR = 1.43, 95% CI: 1.10 ~ 1.85, p = 0.007). The RCS analysis further revealed a positive dose-response relationship, indicating that a higher TyG index was associated with an increased risk of frailty in middle-aged and older adults.

Research has shown a significant positive linear relationship between an increased TyG index and a higher prevalence of frailty in middle-aged and older individuals. Elevated TyG index levels could signal an increased vulnerability to frailty among individuals.

To investigate the potential correlation between the triglyceride-glucose (TyG) index and overactive bladder (OAB) symptoms within the female population.

This study used data from 7941 individuals obtained from the National Health and Nutrition Examination Survey (NHANES) 2005-2018 dataset. The following equation is used to calculate the TyG index: TyG = Ln [fasting triglycerides (mg/dL) * fasting glucose (mg/dL)/2]. The symptoms of OAB were based on individuals' self-reported comprehensive score. Weighted logistic regression models, encompassing both univariable and multivariable analyses, were employed to evaluate the relationship between the TyG index and OAB in women.

After conducting extensive modifications, the multivariable logistic regression model revealed a significant correlation between the TyG index and mild OAB among American female adults (OR 1.36, 95% CI 1.09-1.70, P = 0.006). Upon categorizing the TyG index into 4 grades (Q1-Q4), a positive increase in OR values corresponding to higher TyG index grades can be observed.

In this study, our findings reveal a significantly positive relationship between elevated TyG index values and an increased prevalence of mild OAB among female adults. These findings suggest that metabolic dysregulation may drive early-stage OAB, while severe OAB symptoms may be more dependent on non-metabolic pathological changes. Further investigation is warranted to elucidate the underlying mechanisms in female adults.

Atrial fibrillation (AF) is the most common persistent arrhythmia and demonstrates a notable recurrence rate after ablation. Previous studies suggested that surrogate markers of insulin resistance could predict post-ablation AF recurrence.

This systematic review and meta-analysis aims to assess studies examining the relationship between surrogate insulin resistance markers and the recurrence of AF following ablation.

We searched PubMed, Web of Science, Embase, and Scopus for observational studies published from inception to August 2024. We incorporated studies that assessed the relationship between surrogate insulin resistance markers and the occurrence of post-ablation AF in patients with either paroxysmal or persistent AF. The random effects model was employed for meta-analysis. The Newcastle-Ottawa Scale was used to evaluate risk of bias and the leave-one-out method was applied for sensitivity analysis (PROSPERO: CRD42024584526).

Nine studies involving 7,729 participants met the inclusion criteria. Significant associations with AF recurrence were observed for the TyG index (HR = 1.29, 95% CI [1.15, 1.44], I2 = 44%), HOMA-IR (HR = 1.27, 95% CI [1.14, 1.42], I2 = 0%), and METS-IR (HR = 1.04, 95% CI [1.03, 1.05], I2 = 0%). However, the Triglyceride/HDL ratio did not demonstrate a statistically significant association with AF recurrence (HR = 1.09, 95% CI [0.96, 1.24], I2 = 86%).

Surrogate markers of insulin resistance can be valuable predictors for assessing the risk of AF recurrence in patients who have undergone catheter ablation, potentially aiding in preventive strategies. Nevertheless, further prospective studies are required to validate our findings.

Background: The triglyceride glucose (TyG) index has been correlated with all kinds of diseases. However, its association with hyperuricemia is still a subject of controversy. Methods: This meta-analysis encompassed relevant studies on the TyG index and hyperuricemia obtained from electronic databases, from the launch date until March 2025. The effect sizes and corresponding 95% confidence intervals (CIs) were obtained using a random effects model. Results: Twenty-six trials with 637,954 subjects were incorporated in this study. It was revealed that the TyG index was linked to hyperuricemia (OR = 2.67; 95% CI: 2.34, 3.04; p < 0.001). A dose-response analysis demonstrated that with each 1 mg/dL rise in the TyG index, the risk of being diagnosed with hyperuricemia increased by 2.07 times (OR = 2.07; 95% CI: 1.89, 2.25; p < 0.001). Conclusions: The TyG index has an association with hyperuricemia. Given the constraints identified in our meta-analysis, further cohort studies will be essential to confirm this correlation.

Ultra-process foods (UPF) were suspected to induce many diseases and threaten consumers' health. The aim of this study was to examine the association between the consumption of highly processed foods and adiposity indexes in Tehranian adults.

In a cross-sectional design, 850 Tehranian adults were included. NOVA classification was used to assess the intake of UPF in participants. The amount of calorie intake through processed foods was assessed. Adiposity indexes outcomes include body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), visceral adiposity index (VAI), body roundness index (BRI), and body adiposity index (BAI). Lipid accumulation product (LAP) and triglyceride-glucose index (TyG) were also assessed. Binary logistic regression was used to evaluate the association between the intake of UPF and adiposity indexes measurements.

there was a higher intake of UPF in men than women (p < 0.001). The results of logistic regression revealed that there is a significant association between intake of UPF with WHR (odds ratio (OR): 1.09, 95% confidence interval (CI): 0.73-1.61) and BRI (OR: 2.10, 95% CI: 1.38-3.19) in the crude model. Nevertheless, after adjusting for confounders, the results were insignificant (WHR: OR, 0.77, 95% CI, 0.46-1.27, and BRI: OR, 1.70, 95% CI, 1.05-2.73). No significant association was seen for other outcomes (p > 0.001 for all). The results of dose-response analyses revealed a substantial association between UPF intake and BMI, WHrT, WC, VAI, BRI, BAI, LAP, and TyG.

UPF consumption was significantly related to increased risk of high-risk adiposity indexes in the dose-response analysis. More studies are needed to strengthen the results of this study.

The triglyceride-glucose (TyG) index is associated with the severity of metabolic-associated fatty liver disease (MASLD), but its link to liver fat content is not fully understood. This study investigates the relationship between the TyG index and liver fat content and explores the role of body mass index (BMI) as a mediator.

This cross-sectional study analyzed data from 12,750 participants who underwent health screenings at the first affiliated hospital of Xinxiang Medical University between January 2018 and December 2023. The TyG index, derived as Ln [triglycerides (mg/dl) * fasting plasma glucose (mg/dl)/2], was the independent variable, while liver fat content, measured by quantitative computed tomography (QCT), was the dependent variable. Participants were grouped into tertiles based on their TyG index. Univariate and multivariate analyses, smooth curve fitting (generalized additive models), threshold effect analysis, and subgroup analyses were used to assess the TyG-liver fat content relationship. BMI's mediating effect was also examined.

Liver fat content increased steadily across TyG index tertiles. After adjusting for confounders, the TyG index remained independently associated with liver fat content [β = 1.42, 95% CI: 1.26-1.57]. Participants in the highest TyG tertile (T3) had a 1.58-fold higher liver fat content compared to those in the lowest tertile (T1) (95% CI: 1.37-1.80, P<0.001). A generalized additive model showed a nonlinear relationship between TyG index and liver fat content. When the TyG index ≤ 7.39, liver fat content increased gradually (β = 0.74, 95% CI: 0.50-0.99, P<0.001). Beyond this threshold, liver fat content rose sharply (β = 2.19, 95% CI: 1.92-2.46, P<0.001). Subgroup analysis indicated that the association between TyG index and liver fat content was stronger at higher BMI levels (P for interaction < 0.001). Mediation analysis revealed that BMI accounted for 26.68% of the observed effect.

The TyG index is positively associated with liver fat content in a nonlinear manner, with BMI amplifying this effect. These results suggest that the TyG index may be a useful marker for predicting liver fat content, and managing weight could help slow the progression of MASLD.

The triglyceride-glucose (TyG) index serves as a reliable indicator of insulin resistance and metabolic risk factors. Most research has focused on obese individuals, with limited exploration in those with a normal body mass index (BMI).

This study analyzed 4,440 adults with normal BMI from NHANES 2003-2018. Logistic regression, linear regression, subgroup analysis, and survival analysis examined the relationship between TyG-related indices (TyG, TyG-BMI, TyG-WC, TyG-WHtR) and outcomes like liver fibrosis, stroke, cardiovascular disease (CVD), and mortality.

In 4,440 individuals, 279 developed CVD, 134 had stroke, 1,382 developed liver fibrosis, and 548 died, with a median observation period of 100 months (IQR, 59-145 months). The TyG index was divided into four quartiles (Q1, Q2, Q3, Q4) and significant trends in various clinical indicators across the quartiles were observed (demographic characteristics, metabolic and biochemical indicators). Further analysis revealed linear correlations between TyG, TyG-WC, TyG-BMI, TyG-WHtR and liver function metrics (ALT, AST, GGT, FIB-4, APRI), kidney function metrics (creatinine, eGFR, uric acid), and blood lipids (triglycerides, cholesterol) (P < 0.01). Univariate logistic regression showed that compared to Q1, Q4 showed a significantly higher risk of liver fibrosis, CVD, stroke, and death for all TyG-related parameters (P < 0.001). After adjusting for cofounders, TyG Q4 still had a significantly higher risk of liver fibrosis (P < 0.05) and mortality (P < 0.001); TyG-BMI Q4 showed a higher risk of mortality (P < 0.001); TyG-WC Q4 showed a significantly higher risk of liver fibrosis (P < 0.001), stroke (P < 0.01), CVD (P < 0.001), and mortality (P < 0.001); TyG-WHtR Q4 showed a significantly higher risk of liver fibrosis (P < 0.001), stroke (P < 0.01), CVD (P < 0.001), and mortality (P < 0.001). Subgroup analysis yielded similar conclusions. Additionally. Survival analysis revealed significant differences in survival across the different quartiles of TyG, TyG-WC, TyG-BMI, and TyG-WHtR (P < 0.001).

The study identified a link between TyG-related markers and negative outcomes in individuals with a normal BMI, indicating that insulin resistance exists even in non-obese populations.

Background: Alcohol consumption is a major public health concern, influencing metabolic health and insulin resistance (IR). While moderate alcohol intake has been associated with potential metabolic benefits, excessive consumption is linked to IR and related disorders. This study examines the association between sociodemographic variables, health habits, and IR risk using validated metabolic indices. Methods: A dual-phase study was conducted, including a cross-sectional analysis of 139,634 Spanish workers and a retrospective longitudinal follow-up of 40,431 participants (2009-2019). Data on sociodemographic factors (age, sex and socioeconomic status) and health habits (smoking, alcohol consumption, diet and physical activity) were collected through standardized occupational health assessments. IR risk was assessed using the Triglyceride-Glucose Index (TyG), Metabolic Score for Insulin Resistance (METS-IR), and Single-Point Insulin Sensitivity Estimator (SPISE-IR). Binary logistic regression was used for statistical analysis. Results: Age, male sex, lower socioeconomic status, smoking, alcohol consumption, physical inactivity and low adherence to the Mediterranean diet were significantly associated with higher IR risk across all indices (p < 0.001). Alcohol consumption exhibited a dose-dependent relationship with IR, with excessive intake significantly increasing the risk of IR. Longitudinal data revealed a worsening IR profile over time, particularly among older, low-income and physically inactive individuals. Conclusions: Sociodemographic factors and lifestyle habits strongly influence IR. Preventive strategies focused on reducing alcohol consumption, smoking cessation and promoting physical activity and dietary improvements are essential to mitigate the risk of IR, especially in vulnerable populations. Further longitudinal studies are needed to establish causal relationships and refine intervention strategies.

The triglyceride‒glucose index (TyG index) has been verified to be a useful predictor of insulin resistance (IR), and is associated with the occurrence of acute coronary syndrome (ACS). However, the effect of the TyG index on vulnerable plaques (VP), which were identified when at least two high-risk features are present within the same lesion, in type 2 diabetes mellitus (T2DM) patients is not fully understood. This study aimed to explore the association between the TyG index and the presence of VP.

We retrospectively enrolled 2056 T2DM patients who underwent coronary computed tomography angiography (CCTA) examinations at West China Hospital from February 2017 to February 2022. These patients were divided into four groups on the basis of the quartiles of the TyG index. The high-risk coronary plaque features, vulnerable plaques, plaque type, coronary artery stenosis, segment involvement score (SIS), segment stenosis score (SSS) and multivessel disease (MVD) based on CCTA data were evaluated and compared among the four groups.

Patients with a higher TyG index had more noncalcified and mixed plaques, high-risk plaque features, vulnerable plaques and fewer calcified plaques (P < 0.05 for all). The proportion of patients with high-risk plaque features, including low-attenuation noncalcified plaques, positive remodeling and "napkin ring" sign was associated with the TyG index (P for trend < 0.05 for all). Multivariate analysis revealed that the TyG index was significantly associated with vulnerable plaques in T2DM patients [OR = 1.23 (95% CI 1.00-1.51), P = 0.046]. Subgroup analysis revealed that the association between the TyG index and vulnerable plaques varied with age and the prevalence of cardiovascular (CVD) symptoms, even after controlling for confounding factors (P for interaction < 0.05 for both).

The TyG index was independently associated with vulnerable plaques of the coronary artery among patients with T2DM. The TyG index could be regarded as a marker to reduce the incidence of cardiovascular events in the targeted population of T2DM patients.

Upper gastrointestinal bleeding (UGIB) is a common complication in patients with non-ST-segment elevation myocardial infarction (NSTEMI) after percutaneous coronary intervention (PCI), and the aim of our study is to construct a nomogram for predicting the occurrence of UGIB within 1 year after PCI in NSTEMI patients.

In this study, 784 patients with NSTEMI after PCI in the Affiliated Hospital of Xuzhou Medical University between September 1, 2017 and August 31, 2019 were included as the training group, and 336 patients from the East Affiliated Hospital of Xuzhou Medical University were included as the external validation group. Classical regression methods were combined with a machine learning model to identify the independent risk factors. These factors based on multivariate logistic regression analysis were then utilized to develop a nomogram. The performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA).

The nomogram consisted of six independent predictors, including HASBLED, triglyceride glucose index, alcohol drinking, red blood cell count, use of proton pump inhibitor, and angiographic microvascular resistance of culprit vessel. Training and validation groups accurately predicted the occurrence of UGIB (AUC, 0.936 and 0.910). The calibration curves showed that the nomogram agreed with the actual observations and the DCA also demonstrated that the nomogram was applicable in the clinic.

We developed a simple and effective nomogram for predicting the occurrence of UGIB within 1 year in NSTEMI patients after PCI based on angiographic microvascular resistance.

The triglyceride-glucose (TyG) index has emerged as a surrogate marker for insulin resistance and is associated with the incidence and progression of chronic kidney disease (CKD) in patients with type 2 diabetes.

Data from the ACCORD trial were used. The Cox proportional hazards model was employed to calculate hazard ratios (HRs), while generalized additive mixed models were used to capture the non-linear eGFR slope in each group. The primary outcome was CKD.

9360 participants were included in this study, divided into tertiles based on their TyG index, with 3 119, 3 121, and 3 120 individuals in T1 (low), T2 (medium), and T3 (high), respectively. After a median follow-up of 4 years, 1 229 cases of CKD (13.30 %) occurred. Among women rather than men, CKD risk increased across ascending TyG index groups (adjusted HR for T3, Model 3, 1.46 [95 % CI, 1.13-1.88]) (p for interaction = 0.03). Additionally, longitudinal analysis revealed a rapid eGFR decline in women in the T3 group (-4.79 mL/min/1.73 m2) than the T1 group (-3.07 mL/min/1.73 m2, p < 0.05), but not in men.

A higher TyG index was associated with elevated CKD risk and accelerated eGFR decline, particularly in women.

Hyperinsulinemia (HI) is a common endocrine metabolic disorder in obesity and is closely associated with cardiovascular disease.

This study aims to investigate the effects of progressive weight reduction on HI and cardiovascular risk factors.

We enrolled 68 patients with overweight or obesity. Body composition assessments, clinical indicator sampling and a 75g-oral glucose tolerance test were conducted at baseline and after 12-month weight loss to assess HI and insulin sensitivity. And the people were divided into four groups based on the percent of weight loss (<10%, ~20%, ~30%, >30%) to study the remission of HI and changes in body composition and cardiovascular risk factors.

A total of 66 participants were studied at the end. Progressive weight loss significantly reduced plasma glucose and insulin (P<0.001, P for trend <0.001) and did not progressively reduce cardiovascular risk factors (P for trend <0.001). The greater the percentage of weight loss, the greater the remission rate of insulin resistance and hyperinsulinemia (P for trend <0.001), which reaches 100% when weight loss exceeds 30%. After adjusting for factors such as age, gender, and medication usage, remission of HI was still associated with progressive weight loss.

With progressive weight loss, people with overweight or obesity experienced further improvements in glycemic outcomes, body compositions, HI and insulin resistance.

The triglyceride-glucose (TyG) index serves as a surrogate marker for insulin resistance. Multiple studies have demonstrated a positive correlation between the TyG index and blood pressure, indicating that a high TyG index is related to a greater risk of developing pre-hypertension (pre-HTN) and hypertension (HTN). However, the relationship between changes in the TyG index during childhood and pre-HTN in adulthood requires further clarification.

The present prospective study utilized data from the Bogalusa Heart Study, a long-term follow-up study. Data on triglycerides (TG), fasting glucose (Fg), and low-density lipoprotein cholesterol (LDL-C) were collected from cross-sectional examinations of participants during childhood. Blood pressure (BP) in early adulthood was categorized into normotensive and pre-HTN groups. Logistic regression was employed to evaluate the relationship between the TyG index in childhood and pre-HTN in adulthood.

A total of 1,222 participants were included in the study, of whom 258 presented with pre-HTN in adulthood. Significant differences were observed in baseline TyG index, body mass index (BMI), and high-density lipoprotein cholesterol (HDL-C) between the two groups. In both unadjusted logistic regression (Odds Ratio (OR):1.8, 95% CI: 1.4, 2.5, P < 0.001) and simple adjustment (OR: 1.7, 95% CI: 1.2, 2.3, P = 0.003), childhood TyG index were significantly associated with pre-HTN in adulthood. However, this significant relationship disappeared after full adjustment (OR: 1.2, 95% CI: 0.8, 1.9, P = 0.373) which extended Model 1 by including adjustments for baseline BMI, baseline HDL-C, baseline LDL-C, smoking status, drinking status, use of antihypertensive medication and family history of HTN.Stratified analysis in Model 2 showed that gender and race significantly affected the relationship between TyG index and BP. In the male population, elevated TyG index levels increased the probability of pre-HTN, whereas no such relationship was found in female (Male: OR: 1.9, 95% CI: 1.1, 3.5, P = 0.029; Female: OR: 0.8, 95% CI: 0.4, 1.4, P = 0.447; P for interaction = 0.037). Similarly, in American Caucasians, TyG was positively associated with the risk of pre-HTN, but this relationship was not observed in African American (American Caucasian: OR: 1.7, 95% CI: 1.0, 2.9, P = 0.035; African American: OR: 0.5, 95% CI: 0.2, 1.1, P = 0.087; P for interaction = 0.007).

In males and Caucasians, elevated TyG index during childhood can increase the risk of pre-HTN in adulthood. Monitoring the TyG index may help in screening individuals at higher risk of pre-HTN.

The incidence of postoperative adverse cardiovascular events (PACE) in non-cardiac surgery has significantly increased, severely affecting surgical outcomes and patient prognosis. This study investigates the relationship between preoperative triglyceride-glucose (TyG) index and PACE in patients who underwent non-cardiac surgery.

We conducted a single-center retrospective study, including adult patients (age ≥18 years) who underwent non-cardiac surgery. Univariate and multivariate logistic regression analyses assessed the relationship between the TyG index and PACE. Nonlinear correlations were investigated using restricted cubic splines (RCS). Additionally, subgroup analysis was performed to evaluate the relationship between the TyG index and PACE in different subsamples.

16,066 patients were studied, among which 1505 cases (9.37%) developed PACE, with a median TyG index of 8.61 (8.22, 9.07). Using the lowest quartile of the TyG index as a reference, the fully adjusted (ORs) (95% CIs) for PACE in the second, third, and fourth quartiles of the TyG index were 1.78 (1.49~2.11), 2.16 (1.81~2.59), and 2.30 (1.88~2.83), respectively. After adjusting for all confounding factors, we found that patients with the highest TyG index had a 68% increased risk of PACE (OR 1.68, 95% CI 1.50~1.90). The results of the subgroup analysis were similar to those of the primary analysis. The RCS model suggests a linear positive correlation between the TyG index and the risk of PACE occurrence. (P for overall < 0.001, P for nonlinear = 0.547).

This cohort study indicates that preoperative TyG index is linearly and positively correlated with an increased incidence of PACE in the non-cardiac surgery population. This finding suggests that intensifying the evaluation of the TyG index may provide a more convenient and effective tool for identifying individuals at risk of PACE during non-cardiac surgeries.

Osteoporosis is a systemic metabolic bone disorder characterized by a decrease in bone mass and the degradation of bone microarchitecture. Nevertheless, the precise influence of the core marker of metabolic syndrome-insulin resistance-on the prognosis of patients with osteoporosis and osteopenia remains insufficiently understood. This study seeks to clarify the association between a novel insulin resistance metric, METS-IR, and the risks of all-cause and cardiovascular mortality among individuals diagnosed with OP. This study utilizes data from the National Health and Nutrition Examination Survey (NHANES) collected between 2007 and 2023, employing multivariable Cox proportional hazards regression models and restricted cubic splines to investigate the association between the METS-IR index and the risk of all-cause and cardiovascular mortality in patients diagnosed with osteoporosis and osteopenia. Furthermore, subgroup analyses were performed to identify potential effect modifications and high-risk subpopulations. The study cohort included 2175 individuals with osteoporosis and osteopenia, followed for 16 years, during which 468 all-cause deaths and 102 cardiovascular-related deaths were documented. The study identified a nonlinear positive association between the METS-IR index and the risks of all-cause mortality among patients with osteoporosis and osteopenia. However, no significant association was observed between METS-IR and cardiovascular mortality. At a METS-IR threshold of 2.3, the hazard ratio reached 1, indicating a shift in the risk of all-cause mortality from low to high. Furthermore, subgroup analyses demonstrated a stronger association between METS-IR and all-cause mortality risks in individuals with elevated METS-IR levels or comorbid diabetes, while no such significant relationship was found for cardiovascular mortality. This study highlights a nonlinear positive association between the insulin resistance marker METS-IR and all-cause mortality among patients with osteoporosis and osteopenia, whereas no significant association was observed with cardiovascular mortality. These findings enhance the understanding of insulin resistance's role in osteoporosis and its comorbidities, particularly in relation to all-cause mortality. This underscores the importance of managing insulin resistance to improve overall survival outcomes, while further studies are needed to explore its specific impacts on cardiovascular outcomes.

Delirium frequently occurs in individuals with acute kidney injury (AKI), leading to serious adverse outcomes. However, there are currently no predictors of early intervention for delirium in clinical practice. This study aims to investigate whether a correlation exists between TyG indices and the clinical symptoms of delirium in patients with AKI.

Eligible participants diagnosed with AKI from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database were categorised based on their TyG index. The primary outcome of this study was the incidence of delirium. The TyG indices were quartile and Kaplan-Meier (K-M) cumulative curve was conducted to compare the consequence of each group. Cox proportional hazards and restricted cubic spline (RCS) analyses were employed to explore the associations between TyG indices and outcomes. To mitigate potential biases, a no-replacement propensity score matching (PSM) approach was employed. Subgroup analyses were conducted to explore differences across various demographic and clinical categories.

A positive correlation between the quartile groupings of TyG-AVG and an increased cumulative incidence of delirium in individuals with severe AKI, as demonstrated through K-M cumulative curves and Cox regression analysis. Regarding the TyG index, patients in the 4th group displayed the highest hazard of delirium in both of the methods mentioned above. Furthermore, RCS analysis indicated that the interaction between the two variables is approximately linear. Subgroup analyses revealed that the effects of both metrics remained consistent across most examined subgroups.

Higher TyG indices were clearly associated with the incidence of delirium in patients with severe AKI. These indices could serve as valuable tools for identifying delirium-prone individuals with AKI.