Surrogate Of Insulin Resistance Research Articles

Triglyceride-Glucose Index, Modifiable Lifestyle, and Risk of Colorectal Cancer: A Prospective Analysis of the Korean Genome and Epidemiology Study.

Insulin-mediated pathways plausibly explain the pathogenesis of colorectal cancer (CRC). The triglyceride-glucose index (TyG) is a surrogate of insulin resistance (IR), but its association with CRC in the Korean population has not been evaluated. From the 2004-2013 Korean Genome and Epidemiology Study, 98,800 participants aged 40-69 years were followed through 2020. Data on CRC incidence were obtained from the Korean National Cancer Center registry. Cox regression models and restricted cubic splines were fitted to examine the association between the TyG; In [(triglycerides) × (fasting glucose)/2] and CRC incidence. Joint effects of modifiable lifestyle factors and TyG on CRC risk were also investigated. Median follow-up time was 10.6 years, and 699 CRC cases were observed. A unit-increment in TyG was associated with increased risk of CRC combined (hazard ratio, HR: 1.28, and 95% confidence interval, CI: 1.12-1.46), colon (1.29, 1.10-1.54), and rectal cancer (1.24, 1.01-1.52). Associations were dose-dependent, with linear associations observed for CRC and colon, but non-linear associations were observed for rectal cancer. A high TyG index (above 8.4) combined with overweight/obesity was linked to an increased risk of CRC (1.31, 1.07-1.61) and colon cancer (1.33, 1.03-1.72). When combined with low fruit and vegetable intake, the risks were higher for CRC (1.40, 1.12-1.74) and colon cancer (1.57, 1.18-2.09). Combined with high red meat consumption, the risks were elevated for CRC (1.32, 1.05-1.65) and colon cancer (1.52, 1.15-2.02). A high TyG index was associated with a higher risk of colorectal cancer, and the risk was highest among participants with a high BMI, low fruit and vegetable intake, and high intake of red meat, suggesting a role of both insulin resistance and modifiable lifestyle in colorectal cancer development.

Relationship between four insulin resistance surrogates and regression to normoglycemia from prediabetes among Chinese adults: A longitudinal Cohort Study.

We aimed to investigate the association of the triglyceride glucose-body mass index(TyG-BMI), metabolic score for insulin resistance (METS-IR) with regression to normoglycaemia, and further to compare the value of the four insulin resistance(IR) related indices(TyG-BMI, METS-IR, TyG and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio) in identifying regressions to normoglycaemia from prediabetes. A total of 15,025 patients with prediabetes from the DATA-DRYAD database were included. Cox proportional hazards regression models and restricted cubic spline functions were performed to explore the association and nonlinearity between the indices with the incidence rate of normoglycaemia. Sensitivity and subgroup analyses evaluated the robustness of our findings. Compared with the first quintile, TyG-BMI and METS-IR was negatively linked with the probability of regression to normoglycaemia from prediabetes, the adjusted effect size of the highest quintiles of METS-IR were the most obvious (HR:0.456,95% CI:0.4-0.519), followed by TG/HDL (HR:0.792, 95% CI:0.733-0.856), TyG-BMI (HR:0.816, 95% CI:0.73-0.911) and TyG (HR:0.841, 95% CI: 0.754-0.937) (all p for trend <0.001). A 1.0 SD increase in METS-IR induced a 43% decrease in the probability of regression to normoglycaemia, with 9.8% for TyG-BMI. There were nonlinear associations between TyG-BMI and METS-IR and outcomes, with the inflection point of the TyG-BMI being 218.2 and that of the METS-IR being 37. The METS-IR might be the most superior indicator among the four non-insulin indices in identifying regressions to normoglycaemia from prediabetes in clinical application. The inflection points of the METS-IR and TyG-BMI may be instructive therapeutic points for assessing the status of prediabetes in advance and making more appropriate management and health care decisions.

Comparison of Ten Surrogate Insulin Resistance and Obesity Markers to Identify Metabolic Syndrome in Mexican Adults.

Metabolic syndrome (MetS) is a group of clinical traits directly linked to type 2 diabetes mellitus and cardiovascular diseases, whose prevalence has been rising nationally and internationally. We aimed to evaluate ten known and novel surrogate markers of insulin resistance and obesity to identify MetS in Mexican adults. The present cross-sectional study analyzed 10575 participants from ENSANUT-2018. The diagnosis of MetS was based on the Adult Treatment Panel III (ATP III) criteria and International Diabetes Federation (IDF) criteria, stratified by sex and age group. According to ATP III, the best biomarker was the metabolic score for insulin resistance (METS-IR) in men aged 20-39 and 40-59 years and lipid accumulation product (LAP) in those aged ≥60 years. The best biomarker was LAP in women aged 20-39 and triglyceride-glucose index (TyG) in those aged 40-59 and ≥60 years. Using the IDF criteria, the best biomarker was LAP in men of all ages. TyG gave the best results in women of all ages. The best biomarker for diagnosis of MetS in Mexican adults depends on the criteria, including sex and age group. LAP and TyG are easy to obtain, inexpensive, and especially useful at the primary care level.

Which surrogate insulin resistance indices best predict coronary artery disease? A machine learning approach

BackgroundVarious surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as well as anthropometric features. However, there is still no agreement on the most suitable one for predicting CAD.MethodsWe followed a cohort of 2,000 individuals, ranging in age from 20 to 74, for a duration of 9.9 years. We utilized multivariate Cox proportional hazard models to investigate the association between TyG-index, TyG-BMI, TyG-WC, TG/HDL, plus METS-IR and the occurrence of CAD. The receiver operating curve (ROC) was employed to compare the predictive efficacy of these indices and their corresponding cutoff values for predicting CAD. We also used three distinct embedded feature selection methods: LASSO, Random Forest feature selection, and the Boruta algorithm, to evaluate and compare surrogate markers of insulin resistance in predicting CAD. In addition, we utilized the ceteris paribus profile on the Random Forest model to illustrate how the model’s predictive performance is affected by variations in individual surrogate markers, while keeping all other factors consistent in a diagram.ResultsThe TyG-index was the only surrogate marker of insulin resistance that demonstrated an association with CAD in fully adjusted model (HR: 2.54, CI: 1.34–4.81). The association was more prominent in females. Moreover, it demonstrated the highest area under the ROC curve (0.67 [0.63–0.7]) in comparison to other surrogate indices for insulin resistance. All feature selection approaches concur that the TyG-index is the most reliable surrogate insulin resistance marker for predicting CAD. Based on the Ceteris paribus profile of Random Forest the predictive ability of the TyG-index increased steadily after 9 with a positive slope, without any decline or leveling off.ConclusionDue to the simplicity of assessing the TyG-index with routine biochemical assays and given that the TyG-index was the most effective surrogate insulin resistance index for predicting CAD based on our results, it seems suitable for inclusion in future CAD prevention strategies.

Association between triglyceride glucose-body mass index and all-cause mortality in critically ill patients with acute myocardial infarction: retrospective analysis of the MIMIC-IV database.

Insulin resistance (IR) is closely related to the development of cardiovascular diseases. Triglyceride-glucose-body mass index (TyG-BMI) has been proven to be a reliable surrogate of IR, but the relationship between TyG-BMI and acute myocardial infarction (AMI) is unknown. The present study aims to determine the effects of TyG-BMI on the clinical prognosis of critically ill patients with AMI. The data of AMI patients were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. All patients were divided into four groups according to the TyG-BMI quartile. Outcomes were defined as 30-, 90-, 180-, and 365-day all-cause mortality. Kaplan-Meier (K-M) curve was used to compare survival rate between groups. Meanwhile, Cox regression analysis and restricted cubic splines (RCS) were used to explore the relationship between TyG-BMI index and outcome events. A total of 1,188 critically ill patients with AMI were included in this study. They were divided into four groups according to TyG-BMI quartiles, there were significant differences in 90-, 180-, and 365-day all-cause mortality while there was no difference in 30-day all-cause mortality. Interestingly, with the increase of TyG-BMI, the 90-, 180-, and 365-day survival rate increased first and then gradually decreased, but the survival rate after decreasing was still higher than that in the group with the lowest TyG-BMI. U-shaped relationships between TyG-BMI index and 90-, 180-, and 365-day all-cause mortality were identified using RCS curve and the inflection point was 311.1, 316.5, and 320.1, respectively, whereas the TyG-BMI index was not non-linearly associated with 30-day all-cause mortality. The results of Cox proportional hazard regression analysis are consistent with those of RCS analysis. U-shaped relationships are existed between the TyG-BMI index and 90-, 180-, and 365-day all-cause mortality in critically ill patients with AMI, but not 30-day all-cause mortality. The TyG-BMI index can be used as an effective index for early prevention of critically ill patients with AMI.

Associations of four surrogate insulin resistance indexes with non-alcoholic steatohepatitis in Chinese patients with obesity: a cross-sectional study.

This study was designed to evaluate the association of four surrogate indexes of IR with NASH in patients with obesity. A total of 270 patients who underwent bariatric surgery, were included in this cross-sectional study. NASH was diagnosed based on liver biopsies. Binary logistics regression analyses were performed to assess the associations of four surrogate indexes of IR (HOMA-IR, Matsuda index, TyG, and TG/HDL-C) with NASH in patients with obesity. The restricted cubic spline was used to assess the dose-response associations of surrogate indexes of IR with NASH after adjusting for confounding factors. NASH was diagnosed in 136 patients, with a prevalence of 50.37%. Compared with tertile 1, the fully adjusted ORs (95% CIs) of NASH for tertile 3 were 2.711(1.113-6.608) and 0.297 (0.152-0.579) for TyG and Matsuda index. Consistently, per SD increment of TyG were still significantly associated with 64% increased risks of NASH, and per SD increment of Matsuda index were still significantly associated with 38% decreased risks of NASH. In contrast, no significant associations were found between HOMA-IR and TG/HDL-C and the risk of NASH in patients with obesity (all P > 0.05). After adjusting covariates in restricted cubic splines, the risk of NASH decreased with the increment of Matsuda Index levels (P-nonlinear = 0.442, P-overall = 0.007) and with the decrement of TyG levels (P-nonlinear = 0.004, P-overall = 0.001). In patients with obesity, TyG and Matsuda index were independently related to the risk of NASH after adjustment for traditional risk factors. In addition, compared with HOMA-IR and TG/HDL-C, the Matsuda index and TyG may be more suitable for NASH prediction in patients with obesity.

A national study exploring the association between triglyceride-glucose index and risk of hyperuricemia events in adults with hypertension

BackgroundThe triglyceride-glucose (TyG) index has been recommended as a practical surrogate of insulin resistance (IR). However, the association between the TyG index and hyperuricemia among adults with hypertension remains to be elucidated. MethodsWe included and analyzed 3134 HTN patients and 4233 non-HTN participants from the cross-sectional 2013–2018 U.S. National Health and Nutrition Examination Surveys (NHANES). Multivariable logistic regression and restricted cubic splines (RCS) were used to explore the association between the TyG index and hyperuricemia. Stratifed analyses were performed to assess the association in populations with different subgroups of hypertension. ResultsThe prevalence of hyperuricemia was higher in HTN patients (28.00 %) than in non-HTN participants (12.47 %). The multivariable logistic regression showed that the TyG index was significantly associated with hyperuricemia. After multivariable adjustment, higher TyG index levels were found to be associated with a higher prevalence of hyperuricemia in HTN patients (OR: 2.39, 95 % CI: 1.37–4.17, Ptrend < 0.001) and non-HTN participants (OR: 2.61, 95 % CI: 1.45–4.69, Ptrend < 0.001). Restricted cubic spline regression showed linearity of the associations between the TyG index and hyperuricemia (p-nonlinear > 0.05). In the subgroup analysis suggested that the positive association seemed to be strong among male, alcohol use, and diabetes group (P for interaction < 0.05). ConclusionsTyG index, a practical surrogate of IR, was linearly and positively associated with hyperuricemia in HTN and non-HTN participants. Proactive measures are needed to prevent the comorbidity of IR-driven hyperuricemia in the future.

Accessing the relationship between six surrogate insulin resistance indexes and the incidence of rapid kidney function decline and the progression to chronic kidney disease among middle-aged and older adults in China: Results from the China health and retirement longitudinal study

AimsInsulin resistance is closely related to kidney function decline, but which insulin resistance index could better predict rapid kidney function decline (RKFD) remains unclear. We aimed to evaluate the prospective association between six insulin resistance indexes: Chinese Visceral Adiposity Index (CVAI), Lipid Accumulation Product (LAP), Atherogenic Index of Plasma (AIP), triglyceride-glucose (TyG) index, triglyceride-glucose × Body Mass Index (TyGBMI) and triglyceride-glucose × waist circumference (TyGWC) with RKFD and further the progression to chronic kidney disease (CKD). Methods and measurementsData were obtained from the China Health and Retirement Longitudinal Study. Participants with normal kidney function (eGFRcr-cys ≥60 ml/min per 1.73 m2) and ≥45 years old were included at the baseline (year 2011). The eGFR was estimated by a combination of serum creatinine and cystatin C. The primary outcome was RKFD, defined as an annualized decline in eGFRcr-cys of 5 ml/min per 1.73 m2 or more. Secondary outcome was progression to CKD under the condition of RKFD, defined as an annualized decline in eGFRcr-cys of 5 ml/min per 1.73 m2 or more combined with eGFRcr-cys <60 ml/min per 1.73 m2 at the exit visit. Logistic analysis was applied for analysis of the association between six insulin resistance indexes and RKFD or progression to CKD. We use receiver operating characteristic curves to study the predictive performance of six insulin resistance indexes. Subgroup analysis were conducted by diabetes or hypertension status of the participants. ResultsA total of 3899 participants with normal kidney function were included in this study. After a 3.99 years follow-up, 191 of them ended up with RKFD. Among them, 66 participants progressed to CKD. Logistic analysis showed that per SD increase of all the six insulin resistance indexes were significantly associated with the incidence of RKFD (all P < 0.01), among which, TyGWC had the best predictive value for RKFD. There were significant association between per SD increase of CVAI, LAP, TyGBMI and TyGWC with progression to CKD (all P < 0.01), and CVAI had better predictive role than other indexes. In subgroup analysis, we found that the association between insulin resistance indexes and progression to CKD was more significant in subjects with hypertension or without diabetes. However, no significant differences were observed in the RKFD group. ConclusionsIn this study we proved six insulin resistance indexes were predictively associated with RKFD in Chinese with normal renal function over age 45. TyGWC is the best insulin resistance index for predicting RKFD. CVAI is the best index for predicting further progression to CKD.

Neglected cardiometabolic risk factors and subclinical target organ damage in post-menopausal women with normal glucose tolerance.

Menopausal transition is a crucial step in the women's cardiovascular health, and the risk stratification in apparently health post-menopausal females has been rarely assessed. Heart ultrasonography, unusually performed in such subjects, would be able to detect initial signs of organ damage. We described the cardiovascular risk profile of non-diabetic post-menopausal women, evaluating how easily computed, biochemistry-derived scores were related to ultrasonographic measures of target organ damage. We analyzed the characteristics of a cohort of two-hundred and seventy-three women consecutively referring to a prevention program of Azienda Ospedaliero-Universitaria Pisana (years 2017-2022) who underwent clinical evaluation, complete routine biochemical analyses with proxies of insulin resistance, heart and carotid ultrasonography. The cohort was further divided into four groups according to presence of isolated hypercholesterolemia (HC, 37%), isolated hypertension (HT, 5%), both HC/HT (38%), or none of them. In HC and HC/HT, LDL cholesterol was sharply above the recommended values (149 [134-171] mg/dL and 141 [123-159] mg/dL, respectively). E/e' ratio and left atrium size were augmented in HT women and further worsened in HT/HC, with an independent effect of hypertension (E/e' ß=0.055, P=0.013, left atrium volume ß=0.059, P=0.003). Presence of carotid plaques was independently linked to hypertension (ß=0.474, P=0.003). In HC and HC/HT, the Triglycerides-Glucose Index, a surrogate of insulin resistance, was higher than in the other classes (P=0.0013), and it was associated with E/A in HC and HT/HC, with a significative interaction (P=0.0004) with hypertension. Past hormone replacement therapy did not influence clinical, biochemical or echocardiographic parameters. Postmenopausal women display a high cardiovascular risk burden; a simple clinical and biochemistry screening would be advisable to identify and treat those more at risk. Cardiac ultrasonographic parameters were worse in hypertensive, hypercholesterolemic and insulin-resistant subjects, who may also deserve a deep and early instrumental characterization, especially when these conditions are associated.

Association Between Insulin Resistance Indices and Liver Function Parameters Among Women With Polycystic Ovary Syndrome.

This study aimed to investigate whether polycystic ovary syndrome (PCOS) status changes the association between insulin resistance (IR) indices and liver function parameters among women. This is a cross-sectional, population-based study. We selected 1101 subjects aged ≥20 years from participants of Tehran Lipid and Glucose Study (TLGS). All of them had known the status of PCOS, and all variables were related to the IR indices and liver function parameters. The main outcome measures were TG/HDL-C and triglyceride-glucose (TyG) and liver function parameters (hepatic steatosis index [HSI], alanine transaminase [ALT] and aspartate transaminase [AST]). In the present study, there was no significant difference between the PCOS and the non-PCOS regarding the presence of liver function abnormalities. A model adjusted by age and BMI showed that the upper tertile of TyG index was positively associated with high AST (OR = 3.04 [95% CI: 1.20-7.68], p < 0.05), high ALT (4.76 [3.07-7.36], p < 0.05) and high HSI (8.44 [1.82-39.17], p < 0.05). Although the history of diabetes had a positive impact on elevated AST (1.66 [1.15, 2.40], p < 0.05), the third tertile of TG/HDL-C was associated with increased odds of elevated ALT (3.35 [2.21-5.06]) and HSI (6.55 [1.17-36.46]), whereas the second tertile of TG/HDL-C (OR = 2.65, CI 95%: 1.74-4.03) was also positively associated with elevated ALT. PCOS had no significant association with elevated liver function tests. The highest tertile of TyG index and the TG/HDL-C ratio as a surrogate of IR might play a role in detecting abnormalities of liver function parameters among women. However, PCOS status cannot change the association between IR and liver dysfunction.

First-Trimester Triglyceride-Glucose Index and Triglyceride/High-Density Lipoprotein Cholesterol are Predictors of Gestational Diabetes Mellitus Among the Four Surrogate Biomarkers of Insulin Resistance.

This study seeks to assess the potential of early pregnancy Triglyceride Glucose Index (TyG), triglyceride to High-Density Lipoprotein Cholesterol ratio (TG/HDL-c), Low-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol ratio (LDL-C/HDL-C), and Total Cholesterol to High-Density Lipoprotein Cholesterol ratio (TC/HDL-C) in predicting Gestational Diabetes Mellitus (GDM). A total of 1073 adults singleton pregnant women were enrolled from June 2017 to September 2019. Complete anthropometric data and lipid profiles were measured in the first trimester (before 12 weeks gestation) and a 75g oral glucose tolerance test (OGTT) at 24-28 weeks was performed. Based on OGTT results, participants were categorised into Normal Glucose Tolerance (NGT) group (n=872) and GDM group (n=201). General data, laboratory test results, and surrogate insulin resistance indicators such as TyG index, TG/HDL-C, LDL-C/HDL-C, and TC/HDL-C were documented and compared. To compare differences between the two groups, t-test was used, Spearman correlation analysis and linear regression analysis were performed to establish associations between these indicators and insulin resistance in GDM. Receiver Operating Characteristic (ROC) curves were generated to compare the thresholds of these indicators for predicting GDM during pregnancy and to quantify overall diagnostic accuracy. Individuals with GDM had higher TyG, TG/HDL-C, and LDL-C/HDL-C levels (P < 0.001), but with no significant difference observed in TC/HDL-C. All four ratios were positively correlated with Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), yet only TyG emerged as an independent risk factor for HOMA-IR. The Area under the Curve (AUC) of TyG index (0.692) was comparable to that of HOMA-IR (0.703). The cut-off points for TyG index, TG/HDL-C, and HOMA-IR in predicting GDM were 7.088, 0.831, and 1.8, respectively. HOMA-IR exhibited the highest sensitivity (79.1%), while TyG index (64.3%) and TG/HDL-C ratio (64.3%) demonstrated better specificity compared to HOMA-IR (56.3%). LDL-C/HDL-C and TC/HDL-C offered no discernible predictive advantage. Early pregnancy TyG index and TG/HDL-C can aid in identifying pregnant women at risk for GDM, potentially facilitating early and effective intervention to improve prognosis. TyG index exhibited superior predictive capability compared to TG/HDL-C.

Clinical features of early-onset type 2 diabetes and its association with triglyceride glucose-body mass index: a cross-sectional study.

The incidence of early-onset type 2 diabetes (T2D) has increased significantly, with insulin resistance (IR) and obesity being the main drivers of its onset. This study aims to investigate the clinical characteristics of early-onset T2D and its association with triglyceride glucose body mass index (TyG-BMI), an emerging surrogate of IR. A total of 1000 adults newly diagnosed with T2D were enrolled and divided into early-onset T2D (18~40 years, N=500) and late-onset T2D groups (≥40 years, N=500). Independent t and chi-squared tests were used to compare the characteristics of the two groups, and logistic regression analysis, trend tests, restricted cubic spline curves (RCSs), and receiver operating characteristic (ROC) curves were used to identify the relationship between TyG-BMI and early-onset T2D. Patients with early-onset T2D were more likely to have a higher body mass index (BMI), hemoglobin A1C (HbA1c), fasting plasma glucose (FPG), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), serum uric acid (SUA), triglyceride glucose index (TyG), and TyG-BMI (P < 0.05). A higher TyG-BMI was associated with an increased risk of early-onset T2D (P < 0.001). The RCSs showed a nonlinear relationship between TyG-BMI and early-onset T2D, and the slope of the curve increased with an increase in TyG-BMI (P for nonlinearity < 0.001). In the subgroup analysis, additive interactions between TyG-BMI and the risk of early-onset T2D were observed for sex, family history of diabetes, BMI, fatty liver, and hypertension (P < 0.001). ROC curve showed that the area under the curve of TyG-BMI was 0.6781, which was larger than its main components (TyG, BMI, FPG, TG). The best cutoff value was 254.865, the sensitivity was 74.6%, and the specificity was 53.6%. Patients with early-onset T2D are characterized by severe IR, metabolic disorders, and being overweight/obese and an increase in TyG-BMI is independently associated with an increased risk of early-onset T2D.

Association between different insulin resistance surrogates and all-cause mortality in patients with coronary heart disease and hypertension: NHANES longitudinal cohort study

BackgroundStudies on the relationship between insulin resistance (IR) surrogates and long-term all-cause mortality in patients with coronary heart disease (CHD) and hypertension are lacking. This study aimed to explore the relationship between different IR surrogates and all-cause mortality and identify valuable predictors of survival status in this population.MethodsThe data came from the National Health and Nutrition Examination Survey (NHANES 2001–2018) and National Death Index (NDI). Multivariate Cox regression and restricted cubic splines (RCS) were performed to evaluate the relationship between homeostatic model assessment of IR (HOMA-IR), triglyceride glucose index (TyG index), triglyceride glucose-body mass index (TyG-BMI index) and all-cause mortality. The recursive algorithm was conducted to calculate inflection points when segmenting effects were found. Then, segmented Kaplan–Meier analysis, LogRank tests, and multivariable Cox regression were carried out. Receiver operating characteristic (ROC) and calibration curves were drawn to evaluate the differentiation and accuracy of IR surrogates in predicting the all-cause mortality. Stratified analysis and interaction tests were conducted according to age, gender, diabetes, cancer, hypoglycemic and lipid-lowering drug use.Results1126 participants were included in the study. During the median follow-up of 76 months, 455 participants died. RCS showed that HOMA-IR had a segmented effect on all-cause mortality. 3.59 was a statistically significant inflection point. When the HOMA-IR was less than 3.59, it was negatively associated with all-cause mortality [HR = 0.87,95%CI (0.78, 0.97)]. Conversely, when the HOMA-IR was greater than 3.59, it was positively associated with all-cause mortality [HR = 1.03,95%CI (1.00, 1.05)]. ROC and calibration curves indicated that HOMA-IR was a reliable predictor of survival status (area under curve = 0,812). No interactions between HOMA-IR and stratified variables were found.ConclusionThe relationship between HOMA-IR and all-cause mortality was U-shaped in patients with CHD and hypertension. HOMA-IR was a reliable predictor of all-cause mortality in this population.

Relationship between four insulin resistance surrogates and left ventricular hypertrophy among hypertensive adults: a case-control study.

Hypertension-induced left ventricular hypertrophy (LVH) is intricately linked to insulin resistance (IR). This research aimed to elucidate the relationship of advanced indices, namely the triglyceride-glucose (TyG) index, the TyG adjusted for body mass index (TyG-BMI), the triglycerides-to-high-density lipoprotein cholesterol ratio (TG/HDL-c), and the metabolic score for IR (METS-IR), with LVH in hypertensive cohorts. This analytical case-control investigation encompassed 800 individuals aged 18 or above from the Cardiology Department of the Second Affiliated Hospital of Baotou Medical College over a span from January 2021 to April 2022. Data extraction was conducted from inpatient records. The nexus between the four metrics and LVH susceptibility was ascertained via logistic regression models. Furthermore, the receiver operating characteristic (ROC) curve's area (AUC) shed light on the discriminative capacities of the distinct IR indicators for LVH, considering other concomitant risk variables. Post multifaceted covariate adjustments, the fourth quartile figures for TyG-BMI emerged as the most starkly significant (OR: 5.211, 95% CI: 2.861-9.492), succeeded by METS-IR (OR: 4.877, 95% CI: 2.693-8.835). In juxtaposition with other IR-derived indices (TyG and TG/HDL-c), TyG-BMI manifested the paramount AUC (AUC: 0.657; 95% CI: 0.606-0.708). Concurrently, METS-IR exhibited commendable predictive efficacy for LVH (AUC: 0.646; 95% CI: 0.595-0.697). TyG-BMI and METS-IR displayed superior discriminative capabilities for LVH, underscoring their potential as supplementary indicators in gauging LVH peril in clinical settings and prospective epidemiological research.

Comparison of seven surrogate insulin resistance indexes for prediction of incident coronary heart disease risk: a 10-year prospective cohort study.

There were seven novel and easily accessed insulin resistance (IR) surrogates established, including the Chinese visceral adiposity index (CVAI), the visceral adiposity index (VAI), lipid accumulation product (LAP), triglyceride glucose (TyG) index, TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC) and TyG-waist to height ratio (TyG-WHtR). We aimed to explore the association between the seven IR surrogates and incident coronary heart disease (CHD), and to compare their predictive powers among Chinese population. This is a 10-year prospective cohort study conducted in China including 6393 participants without cardiovascular disease (CVD) at baseline. We developed Cox regression analyses to examine the association of IR surrogates with CHD (hazard ratio [HR], 95% confidence intervals [CI]). Moreover, the receiver operating characteristic (ROC) curve was performed to compare the predictive values of these indexes for incident CHD by the areas under the ROC curve (AUC). During a median follow-up period of 10.25 years, 246 individuals newly developed CHD. Significant associations of the IR surrogates (excepted for VAI) with incident CHD were found in our study after fully adjustment, and the fifth quintile HRs (95% CIs) for incident CHD were respectively 2.055(1.216-3.473), 1.446(0.948-2.205), 1.753(1.099-2.795), 2.013(1.214-3.339), 3.169(1.926-5.214), 2.275(1.391-3.719) and 2.309(1.419-3.759) for CVAI, VAI, LAP, TyG, TyG-BMI, TyG-WC and TyG-WHtR, compared with quintile 1. Furthermore, CVAI showed maximum predictive capacity for CHD among these seven IR surrogates with the largest AUC: 0.632(0.597,0.667). The seven IR surrogates (excepted for VAI) were independently associated with higher prevalence of CHD, among which CVAI is the most powerful predictor for CHD incidence in Chinese populations.

The prognostic significance of insulin resistance in COVID-19: a review.

Emerging publications indicate that diabetes predisposes patients with COVID-19 to more severe complications, which is partly attributed to inflammatory condition. In the current review, we reviewed recent published literature to provide evidence on the role of insulin resistance (IR) in diabetes, the association between diabetes and COVID-19 severity and mortality, the impact of COVID-19 infection on incident new-onset diabetes, mechanisms responsible for IR in COVID-19 patients, and the predictive value of different surrogates of IR in COVID-19. The literature search performs to find out studies that have assessed the association between IR surrogates and morbidity and mortality in patients with COVID-19. We showed that there is a bulk of evidence in support of the fact that diabetes is a potent risk factor for enhanced morbidity and mortality in COVID-19 patients. COVID-19 patients with diabetes are more prone to remarkable dysglycemia compared to those without diabetes, which is associated with an unfavourable prognosis. Furthermore, SARS-COV2 can make patients predispose to IR and diabetes via activating ISR, affecting RAAS signaling pathway, provoking inflammation, and changing the expression of PPARɣ and SREBP-1. Additionally, higher IR is associated with increased morbidity and mortality in COVID-19 patients and different surrogates of IR can be utilized as a prognostic biomarker for COVID-19 patients. Different surrogates of IR can be utilized as predictors of COVID-19 complications and death.

The association between hyperuricemia and insulin resistance surrogates, dietary- and lifestyle insulin resistance indices in an Iranian population: MASHAD cohort study

BackgroundPrevious studies have reported insulin resistance (IR) to be associated with hyperuricemia. In this study, we aimed to assess the possible associations between the empirical dietary index for IR (EDIR), the empirical lifestyle index for IR (ELIR), and non-insulin-based surrogates (triglyceride–glucose (TyG) index, triglyceride-to-high-density-lipoprotein-cholesterol (TG/HDL-C) ratio, metabolic score for insulin resistance (METS-IR) and TyG with body mass index (TyG-BMI)) and hyperuricemia in an Iranian population.MethodsIn this cross-sectional study, 6457 participants aged 35–65 years were recruited as part of the MASHAD cohort study. EDIR and ELIR were calculated using dietary intakes, body mass index, and physical activity information. Insulin resistance surrogates including TyG, TyG-BMI, TG/HDL-C, and METS-IR were calculated for all participants. Hyperuricemia was defined as serum uric acid ≥ 7 mg/dl in men or ≥ 6 mg/dl in women. Multivariable logistic regression models were applied to determine the association between indexes of IR and hyperuricemia.ResultsThe mean ELIR and IR surrogates (TyG, TyG-BMI, TG/ HDL, and METS-IR) were significantly higher in subjects with hyperuricemia compared to non-hyperuricemic subjects (p < 0.001). After adjusting for confounding variables, the association between hyperuricemia and EDIR was not significant, but ELIR had a significant association in all models (p < 0.001). All four IR surrogates (TyG, TyG-BMI, TG/ HDL, and METS-IR) showed a significant association with hyperuricemia (p < 0.001).ConclusionThere was a significant association between indexes of insulin resistance: TyG, TyG-BMI, TG/HDL-c, METS-IR, and ELIR with hyperuricemia, in a population sample from northeastern Iran.

Assessment of six surrogate insulin resistance indexes for predicting cardiometabolic multimorbidity incidence in Chinese middle-aged and older populations: Insights from the China health and retirement longitudinal study.

Insulin resistance (IR) is associated with cardiometabolic multimorbidity (CMM). We aimed to explore the predictive value of six surrogate IR indexes-Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), triglyceride-glucose (TyG), atherogenic index of plasma (AIP), TyG-body mass index (TyGBMI), and TyG-waist circumference (TyGwaist)-to establish the CMM incidence in Chinese middle-aged and older populations. To estimate the odds ratio (OR) with a 95% confidence interval (95% CI) for incident CMM using six surrogates, we analysed data from the China Health and Retirement Longitudinal Study using multivariate logistic regression models. The nonlinear dose-response correlation was evaluated using restricted cubic spline analysis; predictive performance was assessed using receiver operator characteristic curves. Among 6451 eligible participants, 268 (4.2%) developed CMM during the 4-year follow-up period. The ORs (95% CI) for incident CMM increased with increasing CVAI quartiles (Q) [Q2: 1.71, 1.03-2.90; Q3: 2.72, 1.70-4.52; Q4: 5.16, 3.29-8.45; all p<0.05] after full adjustment, with Q1 as the reference. Other indexes yielded similar results. These associations remained significant in individuals with a normal body mass index. Notably, CVAI, AIP, and TyG exhibited a linear dose-response relationship with CMM (Pnonlinear ≥0.05), whereas LAP, TyGBMI, and TyGwaist displayed significant nonlinear correlations (Pnonlinear <0.05). The area under the curve for the CVAI (0.691) was significantly superior to that of other indexes (all p<0.05). The six IR surrogates were independently associated with CMM incidence. CVAI may be the most appropriate indicator for predicting CMM in middle-aged and older Chinese populations.

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

This study aimed to assess the association of baseline insulin resistance (IR) surrogates and their longitudinal trajectories with cardiovascular diseases (CVD) to provide a useful reference for preventing CVD. This study was a prospective cohort study conducted in the 51st Regiment of the Third Division of Xinjiang Corps. A total of 6362 participants were recruited in 2016 to conduct the baseline survey, and the follow-up surveys in 2019, 2020, 2021, and 2022. The Kaplan-Meier method was used to estimate the cumulative incidence of CVD according to the baseline IR surrogates of metabolic insulin resistance score (METS-IR) and triglyceride-glucose (TyG) index. Cox regression models were used to assess the association between the baseline IR surrogates and CVD. The impact of the longitudinal trajectories of the IR surrogates on CVD was analyzed after excluding those with IR surrogate data measured ≤2 times. Based on the group-based trajectory model (GBTM), the trajectory patterns of IR surrogates were determined. The Kaplan-Meier method was used to estimate the cumulative incidence of CVD in each trajectory group of METS-IR and TyG index. Cox regression models were used to analyze the association between different trajectory groups of each index and CVD. In addition, the Framingham model was utilized to evaluate whether the addition of the baseline IR surrogates increased the predictive potential of the model. Baseline data analysis included 4712 participants. During a median follow-up of 5.66 years, 572 CVD events were recorded (mean age, 39.42 ± 13.67 years; males, 42.9%). The cumulative CVD incidence increased with the ascending baseline METS-IR and TyG index quartiles (Q1-Q4). The hazard ratio and 95% confidence interval for CVD risk in Q4 of the METS-IR and TyG index were 1.79 (1.25, 2.58) and 1.66 (1.28, 2.17), respectively, when compared with Q1. 4343 participants were included in the trajectory analysis, based on the longitudinal change patterns of the METS-IR and TyG index, the following three trajectory groups were identified: low-increasing, moderate-stable, and elevated-increasing groups. Multivariate Cox regression revealed that the hazard ratio (95% confidence interval) for CVD risk in the elevated-increasing trajectory group of the METS-IR and TyG index was 2.13 (1.48, 3.06) and 2.63 (1.68, 4.13), respectively, when compared with the low-rising group. The C-index, integrated discrimination improvement value, and net reclassification improvement value were enhanced after adding the baseline METS-IR and TyG index values to the Framingham model (P<0.05). Elevated baseline IR surrogates and their higher long-term trajectories were strongly associated with a high risk of CVD incidence in Xinjiang's rural areas. Regular METS-IR and TyG index monitoring can aid in the early detection of CVD-risk groups.

Association of cardiometabolic factors and insulin resistance surrogates with mortality in participants from the Korean Genome and Epidemiology Study

BackgroundSimple biochemical and anthropometric measurements such as fasting blood glucose (FBG), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), waist circumference (WC), and body mass index (BMI) are used to formulate insulin resistance (IR) indices. Whether these indices provide new predictive information for mortality remains unknown. This study examined the relationships of biochemical, anthropometric, and IR indices with mortality risk, as well as their predictive performance.MethodsThe data source was the Korean Genome and Epidemiology Study (2004–2020) involving 114,957 participants whose data were linked to death records. The IR indices- triglyceride-glucose index (TyG), TyG-BMI, TyG-WC, visceral adiposity index (VAI), lipid accumulation product (LAP), and metabolic score for insulin resistance (METS-IR) were computed using standard formulae. The associations were examined using restricted cubic splines. The predictive performance was compared using the log-likelihood ratio chi-square test.ResultsBody mass index was U-shaped, HDL-C was reverse J-shaped, and FBG and TG levels were J-shaped associated with all-cause mortality. Results showed U-shaped (TyG), J-shaped (TyG-BMI, VAI, LAP, and METS-IR), and reverse J-shaped (TyG-WC) associations with all-cause mortality. The percentages of new predictive information for all-cause mortality explained by the FBG level, BMI, TyG-BMI, and METIR were 3.34%, 2.33%, 1.47%, and 1.37%, respectively. Other IR indices and biochemical and anthropometric measurements provided < 1.0% of new predictive information. For cardiovascular disease mortality, the FBG, BMI, METIR, TyG-BMI, and HDL-C levels explained 2.57%, 2.12%, 1.59%, 1.30%, and 1.27% of new predictive information respectively. Moreover, the risks of cancer mortality explained by FBG level, VAI, and HDL-C level were 2.05%, 1.49%, and 1.28%, respectively.ConclusionsFasting blood glucose level is a superior predictor of mortality risk and may be used as a simple predictive and preventative factor.