BACKGROUND: The triglyceride-glucose (TyG) index is associated with the development and prognosis of coronary artery disease (CAD). However, the impact of the TyG index on CAD severity across different glucose metabolism states exhibits significant disparities in previous research.
METHODS: This cross-sectional study comprised 10,433 participants from a prospective cohort. Participants were categorized into four groups based on glucose metabolism state: normal glucose regulation (NGR), prediabetes (pre-DM), diabetes mellitus (DM) without insulin prescribed (Rx), and DM with insulin Rx. The TyG index was determined by the following formula: Ln [TG (mg/dL) × FPG (mg/dL) / 2], where TG is triglycerides and FPG is fasting plasm glucose. Statistical methods such as binary logistic regression, interaction analysis, restricted cubic spline (RCS), and receiver operating characteristic (ROC) were employed to analyze the relationship between the TyG index and CAD severity across the entire population and glucose metabolism subgroups. Mediation analysis was conducted to examine the mediating effects of glycated hemoglobin (HbA1c) on these relationships. Sensitivity analysis was performed to ensure the robustness of the findings.
RESULTS: Multivariable logistic regression analysis revealed a significant positive association between the TyG index and multi-vessel CAD in the entire population (OR: 1.34; 95% CI: 1.22-1.47 per 1-unit increment). Subgroup analysis demonstrated consistent positive associations in the NGR, pre-DM, and DM non-insulin Rx groups, with the highest OR observed in the NGR group (OR: 1.67; 95% CI: 1.3-2.14 per 1-unit increment). No correlation was found in the DM with insulin Rx subgroup. RCS analyses indicated the distinct dose-response relationships across different glucose metabolism subgroups. Including the TyG index in the established model slightly improved the predictive accuracy, particularly in the NGR group. Mediation analyses showed varying mediating effects of HbA1c among different glucose metabolism subgroups. Sensitivity analysis confirmed the robustness of the aforementioned relationships in the new-onset CAD population and in individuals not using antilipidemic medications.
CONCLUSIONS: The TyG index positively associated with CAD severity across all glucose metabolism states, except for individuals receiving insulin treatment. Moreover, it might serve as a supplementary noninvasive predictor of CAD severity in addition to established factors, especially in NGR patients.

OBJECTIVE: Insulin resistance (IR) has previously been associated with hypertension, and obesity is a risk factor for IR and hypertension. There is likely an association between body mass index (BMI) and risk for hypertension through the triglyceride-glucose (TyG) index but this relationship remains uncharacterized.
RESULTS: This study is based on the Hanzhong Adolescent Hypertension Cohort, which is an ongoing prospective study established in 1987. The TyG index was calculated as ln [fasting triglyceride (mg/dl) × fasting plasma glucose (mg/dl)/2]. The total area under the curve (AUCt) and incremental AUC (AUCi) were calculated as the long-term burden and trend of BMI, respectively. We found that BMI AUCt and BMI AUCi were significantly associated with the risk of adult hypertension, both without (RR = 1.30/1.31 for BMI AUCt/AUCi) and with (RR = 1.25/1.26 for BMI AUCt/AUCi) the inclusion of the TyG index as a covariate. Importantly, mediation analysis revealed that the TyG index mediated the BMI AUCt-SBP association (19.3%), the BMI AUCt-DBP association (22.7%), the BMI AUCi-SBP association (18.5%) and the BMI AUCi-DBP association (21.3%). Furthermore, the TyG index had a significant mediating effect of 15.9% on the BMI AUCt-hypertension association and 14.9% on the BMI AUCi-hypertension association.
CONCLUSIONS: These findings suggest that the TyG index plays an important mediating role in the association between the cumulative burden and increasing trends of BMI originating in childhood and the risk of hypertension in midlife. We emphasize that early weight management has the potential to reduce the burden of hypertension caused by IR.
BACKGROUND: The study was clinically registered at the ClinicalTrials.gov (NCT02734472) and approved by the Academic Committee of the First Affiliated Hospital of Xi\'an Jiaotong University (XJTU1AF2015LSL-047).

Vitamin D deficiency (VDD) is associated with increased risk of type 2 diabetes mellitus (T2DM) and insulin resistance (IR). We aimed to investigate the association between the triglyceride-glucose (TyG) index that represents IR and VDD in elderly patients with T2DM. We enrolled 572 elderly participants with T2DM in this study. TyG index was calculated as ln [fasting triglyceride (TG, mg/dL) × fasting blood glucose (mg/dL)/2]. Serum 25-hydroxyvitamin D [25(OH)D] level below 50 nmol/L was defined as VDD. The association between the TyG index and the VDD risk was evaluated by multivariate logistic regression analysis. We observed a significant decreased 25(OH)D level with the increase of the TyG index in elderly diabetic patients, and a negative correlation between the TyG index and 25(OH)D level. The participants in the highest TyG quartile had a 2.40-fold higher risk of VDD than those in the lowest TyG index quartile [OR 2.40; 95% CI 1.47-3.92; P < 0.001]. The association persisted after adjustments for age, sex, smoking, obesity, insulin therapy, hypoglycemic agents\' medication, and some biochemical parameters. TyG index may be involved in the pathophysiology of VDD, which could be a predictor for VDD in elderly diabetic patients.

OBJECTIVE: Insulin resistance (IR) is a risk factor for several cardiometabolic disorders; however, there is conflicting evidence about the reliability of certain IR markers. In this context, the triglyceride-glucose index (TyG) has been proposed as a surrogate marker for IR. This study aimed to compare the TyG index and homeostasis model assessment of insulin resistance (HOMA-IR).
RESULTS: A cross-sectional analysis was conducted using baseline data from 11,314 adults (aged 35-74 years) from the ELSA-Brasil study. The correlation between TyG and HOMA-IR, their interrater reliability, and their predictive value in identifying metabolic syndrome (MetS) were assessed. The mean TyG and HOMA-IR in our sample were 8.81 ± 0.52 and 2.78 ± 1.58 for men, and 8.53 ± 0.48 and 2.49 ± 1.38 for women, respectively. TyG and HOMA-IR showed a weak to moderate correlation with each other (Pearson\'s r for men: 0.395 and 0.409 for women, p-value <0.05) and other markers of glycemic metabolism. Additionally, the area under the curve for the prediction of MetS was greater for TyG than HOMA-IR, regardless of sex (TyG: 0.836 for men and 0.826 for women; HOMA-IR: 0.775 for men and 0.787 for women). The concordance between these markers was low (Coheńs kappa coefficient: 0.307 for men and 0.306 for women). Individuals with increased TyG exhibited mainly anthropometrical and glycemic metabolic alterations, whereas those with elevated HOMA-IR displayed mostly lipid-associated metabolic alterations.
CONCLUSIONS: TyG and HOMA-IR might indicate different profiles of cardiometabolic disorders, showing poor agreement in classifying individuals (normal vs. altered) and a weak correlation. Therefore, further studies are needed to investigate the role of TyG as a surrogate marker of IR.

BACKGROUND: The prevalence of obesity-associated insulin resistance (IR) is increasing along with the increase in obesity rates. In this study, we compared the predictive utility of four alternative indexes of IR [triglyceride glucose index (TyG index), metabolic score for insulin resistance (METS-IR), the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio and homeostatic model assessment of insulin resistance (HOMA-IR)] for all-cause mortality and cardiovascular mortality in the general population based on key variables screened by the Boruta algorithm. The aim was to find the best replacement index of IR.
METHODS: In this study, 14,653 participants were screened from the National Health and Nutrition Examination Survey (2001-2018). And TyG index, METS-IR, TG/HDL-C and HOMA-IR were calculated separately for each participant according to the given formula. The predictive values of IR replacement indexes for all-cause mortality and cardiovascular mortality in the general population were assessed.
RESULTS: Over a median follow-up period of 116 months, a total of 2085 (10.23%) all-cause deaths and 549 (2.61%) cardiovascular disease (CVD) related deaths were recorded. Multivariate Cox regression and restricted cubic splines analysis showed that among the four indexes, only METS-IR was significantly associated with both all-cause and CVD mortality, and both showed non-linear associations with an approximate \"U-shape\". Specifically, baseline METS-IR lower than the inflection point (41.33) was negatively associated with mortality [hazard ratio (HR) 0.972, 95% CI 0.950-0.997 for all-cause mortality]. In contrast, baseline METS-IR higher than the inflection point (41.33) was positively associated with mortality (HR 1.019, 95% CI 1.011-1.026 for all-cause mortality and HR 1.028, 95% CI 1.014-1.043 for CVD mortality). We further stratified the METS-IR and showed that significant associations between METS-IR levels and all-cause and cardiovascular mortality were predominantly present in the nonelderly population aged < 65 years.
CONCLUSIONS: In conjunction with the results of the Boruta algorithm, METS-IR demonstrated a more significant association with all-cause and cardiovascular mortality in the U.S. population compared to the other three alternative IR indexes (TyG index, TG/HDL-C and HOMA-IR), particularly evident in individuals under 65 years old.

BACKGROUND: The birth of large-for-gestational-age (LGA) infants is associated with many short-term adverse pregnancy outcomes. It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus (GDM) is significantly higher than that born to healthy pregnant women. However, traditional methods for the diagnosis of LGA have limitations. Therefore, this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants.
OBJECTIVE: To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM, and provide strategies for the effective prevention and timely intervention of LGA.
METHODS: The multivariable prediction model was developed by carrying out the following steps. First, the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses, for which the P value was < 0.10. Subsequently, Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations, and the optimal combination factors were selected by choosing lambda 1se as the criterion. The final predictors were determined by multiple backward stepwise logistic regression analysis, in which only the independent variables were associated with LGA risk, with a P value < 0.05. Finally, a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve, calibration curve and decision curve analyses.
RESULTS: After using a multistep screening method, we establish a predictive model. Several risk factors for delivering an LGA infant were identified (P < 0.01), including weight gain during pregnancy, parity, triglyceride-glucose index, free tetraiodothyronine level, abdominal circumference, alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks. The nomogram\'s prediction ability was supported by the area under the curve (0.703, 0.709, and 0.699 for the training cohort, validation cohort, and test cohort, respectively). The calibration curves of the three cohorts displayed good agreement. The decision curve showed that the use of the 10%-60% threshold for identifying pregnant women with GDM who are at risk of delivering an LGA infant would result in a positive net benefit.
CONCLUSIONS: Our nomogram incorporated easily accessible risk factors, facilitating individualized prediction of pregnant women with GDM who are likely to deliver an LGA infant.

The triglyceride-glucose (TyG) index is a simple and inexpensive new marker of insulin resistance that is being increasingly used for the clinical prediction of metabolic syndrome (MetS). Nevertheless, there are only a few comparative studies on its predictive capacity for MetS versus those using the traditional homeostasis model assessment (HOMA). We conducted a cross-sectional study using a database from the National Health and Nutrition Examination Survey (1999 March to 2020 pre-pandemic period). Using statistical methods, we compared the predictive abilities of the TyG index and HOMA (including HOMA of insulin resistance [HOMA-IR] and HOMA of beta-cell function [HOMA-β]) for MetS. A total of 34,195 participants were enrolled and divided into the MetS group (23.1%) or no MetS group (76.9%) according to the International Diabetes Federation (IDF) diagnostic criteria. After applying weighted data, the baseline characteristics of the population were described. Following the exclusion of medication influences, the final count was 31,304 participants. Receiver operating characteristic curve analysis revealed that while distinguishing between MetS and no MetS, the TyG index had an area under the curve (AUC) of 0.827 (sensitivity = 71.9%, specificity = 80.5%), and the cutoff was 8.75, slightly outperforming HOMA-IR (AUC = 0.784) and HOMA-β (AUC = 0.614) with a significance of P < 0.01. The prevalence of MetS in the total population calculated using the TyG index cutoff value was 30.9%, which was higher than that reported in the IDF diagnostic criteria. Weighted data analysis using univariate and multivariate logistic regression displayed an independent association between elevated TyG and HOMA-IR with the risk of MetS. Subgroup analysis further revealed differences in the predictive ability of the TyG index among adult populations across various genders and ethnicities, whereas such differences were not observed for children and adolescents. The TyG index is slightly better than HOMA in predicting MetS and may identify more patients with MetS; thus, its applications in a clinical setting can be appropriately increased.

BACKGROUND: The Triglyceride-glucose (TyG) index, a surrogate marker of insulin resistance, has been implicated in the risk of ischemic stroke. However, the interplay between TyG levels, lifestyle factors, and their collective impact on stroke risk in non-diabetic populations remains inadequately explored. This study aims to evaluate the association of ischemic stroke with the joint development of the TyG index and lifestyle in the non-diabetic population.
METHODS: In this prospective cohort study, data was collected across three consecutive biennial surveys of the Kailuan Study from 2006 to 2011. The dual-trajectory model was used to determine the temporal development of TyG levels and lifestyle scores. Statistical analysis involved Cox regression models to evaluate the association between TyG-lifestyle trajectories and ischemic stroke risk, adjusting for potential confounders.
RESULTS: A total of 44,403 participants were included, with five distinct TyG levels and lifestyle scores trajectory subtypes identified. In the multivariable-adjusted analyses, significant differences in ischemic stroke risk among the trajectory subtypes. Group 5, characterized by the highest TyG levels and moderate lifestyle scores, exhibited the greatest ischemic stroke risk (HR = 1.81, 95% CI: 1.51-2.18), while group 4, with moderate TyG levels and higher lifestyle scores, demonstrated the lowest risk (HR = 1.19, 95% CI: 1.04-1.37), compared with group 3. Participants with elevated TyG levels were at an increased risk of ischemic stroke in cases of pronounced insulin resistance, even with a healthy lifestyle.
CONCLUSIONS: This study reveals the significant associations between the identified TyG and lifestyle trajectories and the stratification of ischemic stroke risk among non-diabetics. The TyG index is a valuable indicator for assessing insulin resistance. However, the potential benefits of lifestyle changes for those with significantly high TyG levels need to be clarified by more research to develop more effective stroke prevention strategies.

UNASSIGNED: The triglyceride-glucose (TyG) index is a sign of atherosclerosis in cardiovascular diseases. The TyG index is thought to have clinical significance for the assessment of vascular damage. In this study we aimed to demonstrate the connection between the TyG index and retinal vein occlusion (RVO).
UNASSIGNED: This case-control observational study involved 492 participants aged 40-90, admitted to the ophthalmology outpatient clinic of our hospital. TyG index was calculated using the formula: ln(fasting TG [mg/dL] × fasting plasma glucose [mg/dL]/2).
UNASSIGNED: The RVO group included 387 patients (181 women and 206 men) and the control group included 115 patients (61 women and 54 men). The average patient age was 62.9±11.1 years in the RVO group and 56.7±8.7 years in the control group. The TyG index was higher in the RVO group (8.9±0.7) than in the control group (8.8±0.6). This difference was statistically significant (p=0.04). The correlation was statistically significant when evaluated according to age and sex by multivariate logistic regression analysis (odds ratio: 1.45, confidence interval: 1.03- 2.02, p=0.03).
UNASSIGNED: The TyG index is a novel atherogenicity index that is derived from routine blood tests and can be used to determine the risk of RVO in at-risk individuals with a simple calculation. Therefore, the TyG index could help as a reliable guide to identify individuals at RVO with high risk and initiate early intervention.

Background: A correlation between plasma lipids and timing of pubertal development has been hypothesized, though lipid influence remains unclear in central precocious puberty (CPP). Aim: To assess any possible alterations in the lipid profile and triglyceride glucose index (TyG) in children diagnosed with CPP. Patients and Methods: Retrospective single-center study conducted on children (aged 6.3 ± 2.1 years) evaluated for the suspicion of CPP. Results: Based on the results of the gonadotropin releasing hormone (GnRH) test, considering 5 IU/L as cut-off of the luteinizing hormone peak, CPP was confirmed in 43 patients (57.3%). Sixteen (37.2%) had a pathologic body mass index (BMI), with 9 (20.9%) being overweight and 7 (16.27%) obese. High total cholesterol was found in 3 patients with CPP (6.97%), high triglycerides were found in 11 patients with CPP (25.58%), high LDL cholesterol was found in 5 patients with CPP (11.62%), low HDL cholesterol was found in 12/43 patients with CPP (27.9%), a pathologic TyG was found in 13/43 patients with CPP (30.23%). No significant association was observed in the lipid profile for patients with or without CPP, except for HDL cholesterol, which was lower in the CPP group (47.1 ± 10.9; p = 0.033). However, the association between serum HDL cholesterol and CPP was not confirmed at the multivariate logistic regression analysis adjusted for patients\' sex and age (p = 0.1; OR: 1.035; 95% CI: 0.993-1.078). Conclusion: The overall lipid profile of our pediatric patients diagnosed with CPP did not differ from patients having idiopathic precocious thelarche or normal variants of puberty development.