Predictive values of metabolic score for insulin resistance on risk of major adverse cardiovascular events and comparison with other insulin resistance indices among Chinese with and without diabetes mellitus: Results from the 4C cohort study

The association between the metabolic score for insulin resistance and mortality in patients with cardiovascular disease: a national cohort study

Background

The metabolic score for insulin resistance (METS-IR) is a novel index for evaluating insulin resistance and identifying high-risk cardiovascular disease (CVD) patients. This study aims to assess the prognostic value of METS-IR in predicting mortality risk in CVD patients.

Methods

We analyzed data from 2,515 CVD patients in the National Health and Nutrition Examination Survey (NHANES). Associations between METS-IR and all-cause mortality and cardiovascular mortality were evaluated using multivariable Cox proportional hazards models and restricted cubic splines (RCS). Threshold effects and sensitivity analyses were conducted to ensure robustness.

Results

Over a median follow-up of 91.4 months, 1,090 patients died, including 447 from cardiovascular causes. A U-shaped relationship was identified between lnMETS-IR and all-cause and cardiovascular mortality, with thresholds at 3.70 and 3.67. Below thresholds, an increase of lnMETS-IR was associated with a 75% reduction in the risk of all-cause mortality (HR: 0.25, 95% CI: 0.14-0.46) and a 79% reduction in the risk of cardiovascular mortality (HR: 0.21, 95% CI: 0.07-0.56). While above thresholds, an increase of lnMETS-IR was associated with a 180% increase in the risk of all-cause mortality (HR: 2.80, 95% CI: 1.61-4.88) and a 233% increase in the risk of cardiovascular mortality (HR: 3.33, 95% CI: 1.43-7.75).

Conclusions

This study identified a U-shaped association between lnMETS-IR and mortality among CVD patients, underscoring the potential of METS-IR as a valuable prognostic marker for mortality risk in patients with CVD.

Relationship between METS-IR and ABSI index and the prevalence of nocturia: a cross-sectional analysis from the 2005-2020 NHANES data

Nocturia, marked by frequent nighttime urination, significantly impacts quality of life. This study explores the association of METS-IR (Metabolic Score for Insulin Resistance) and ABSI (A Body Shape Index) with nocturia, using data from the National Health and Nutrition Examination Survey (NHANES). A cross-sectional analysis of NHANES data from 2005 to 2020 was performed. Multivariable logistic regression assessed the associations between METS-IR, ABSI, and nocturia, adjusting for demographic characteristics, chronic diseases, and lifestyle factors. Generalized additive models and smoothing splines were used to describe relationship dynamics. Among the 16,450 participants, both METS-IR (OR = 1.15, 95% CI: 1.11-1.20, p < 0.0001) and ABSI (OR = 1.14, 95% CI: 1.10-1.19, p < 0.0001) were significantly associated with nocturia based on z-scores. An incremental rise in the quartiles of METS-IR and ABSI was associated with a higher risk of nocturia. Specifically, compared to the lowest quartile (Q1), participants in the highest quartile (Q4) had an OR of 1.45 (95% CI: 1.30-1.61, p < 0.0001) for METS-IR and 1.38 (95% CI: 1.23-1.55, p < 0.0001) for ABSI. Subgroup analyses showed a stronger association between ABSI and nocturia among individuals living alone and those aged 20-38 years. Nonlinear modeling indicated a threshold effect for ABSI, with nocturia risk significantly increasing when ABSI exceeded 76.2. Higher METS-IR and ABSI indices are closely linked to a greater prevalence of nocturia, indicating that these indices can be valuable in clinical assessments for evaluating nocturia risk and supporting preventive strategies.

Changes in the metabolic score for insulin resistance index for risk prediction of stroke in middle-aged and older Chinese population

Background

As a major noncommunicable disease, stroke poses a major threat to public health. In the context of predictive, preventative, and personalised medicine (PPPM/3PM), early identification of high-risk individuals is crucial for targeted prevention and personalised treatment for stroke. This study aimed to investigate the association between changes in the Metabolic Score for Insulin Resistance Index (METS-IR) and incident stroke. From the perspective of PPPM/3PM, we hypothesised that monitoring dynamic changes of the METs-IR levels and targeting cumulative METs-IR index contribute to risk prediction, targeted prevention, and personalised management of stroke.

Methods

All data were obtained from the China Health and Retirement Longitudinal Study (CHARLS), a nationwide prospective cohort study. The individuals were categorised into four subgroups based on the quartiles (Q) of the cumulative METS-IR index as a reflection of changes in the METS-IR values from 2012 to 2015. Logistic regression was employed to examine the association between cumulative METS-IR index and stroke incidence. Additionally, restricted cubic spline regression analysis was used to assess potential linearity.

Results

Among the 4288 participants, 275 (6.4%) experienced a stroke. The risk of stroke events increased with higher cumulative METS-IR index levels. Compared with the lowest quartile (Q1), the OR of having a stroke was 1.20 (0.81, 1.78) for Q2, 1.51 (1.04, 2.21) for Q3 and 2.17 (1.52, 3.10) for the highest quartile (Q4). After adjusting for multiple potential confounders, Q4 (OR: 1.57, 95% CI: 1.04, 2.35) remained significantly associated with stroke. The association between the cumulative METS-IR index and stroke incidence was linear in males, females, and the overall population (all P values for nonlinearity > 0.05).

Conclusions

A higher cumulative METS-IR index was associated with an increased risk of incident stroke among middle-aged and older Chinese individuals. In the context of PPPM/3PM, incorporating metabolic health into stroke risk assessment advances the prediction, prevention and personalised management of stroke.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00388-y.

Perioperative administration of sub-anesthetic ketamine/esketamine for preventing postpartum depression symptoms: A trial sequential meta-analysis

OBJECTIVE

Postpartum depression (PPD) is a major mental health issue affecting 10%-15% of women globally. This meta-analysis synthesized updated evidence on sub-anesthetic ketamine/esketamine's efficacy in preventing PPD.

METHODS

Randomized controlled trials (RCTs) comparing ketamine/esketamine to a placebo for PPD prevention were searched without language restriction. Primary outcomes were PPD risk at 1- and 4-6-week postpartum. Secondary outcomes included the difference in depression scores and risk of adverse events. Trial sequential analysis (TSA) was conducted to validate the reliability.

RESULTS

A meta-analysis of 22 RCTs (n = 3,463) showed that ketamine/esketamine significantly decreased PPD risk at 1- (risk ratio [RR], 0.41; 95% confidence interval [CI], 0.3-0.57) and 4-6-week (RR, 0.47; 95%CI, 0.35-0.63) follow-ups. Consistently, participants receiving ketamine/esketamine had lower depression-related scores at 1- (standardized mean difference [SMD], -0.94; 95%CI, -1.26 to -0.62) and 4-6-week (SMD, -0.89; 95%CI, -1.25 to -0.53) follow-ups. Despite potential publication bias, TSA confirmed the evidence's reliability. Subgroup analysis showed that ketamine/esketamine's preventive effect on 1-week PPD was consistent, regardless of administration timing, type of agents, or total dosage (<0.5 vs. ≥0.5 mg/kg). For the 4-6-week period, PPD risk was favorably reduced only with postoperative administration or the use of esketamine, with the total dosage having no observed influence. Participants on ketamine/esketamine experienced more frequency of hallucinations (RR, 4.77; 95%CI, 1.39-16.44) and dizziness (RR, 1.36; 95%CI, 1.02-1.81).

CONCLUSION

Our findings advocate for the postoperative administration of low-dose ketamine/esketamine to avert PPD, which needed additional research for confirmation.

Role of Triglyceride-Glucose Index in Type 2 Diabetes Mellitus and Its Complications

Insulin resistance (IR) is the major mechanism in the pathogenesis of type 2 diabetes mellitus (T2DM). Early identification of IR is of great significance for preventing the onset of T2DM and delaying the progression of the disease. Previous studies have shown that triglyceride-glucose (TyG) index can be used as an effective surrogate marker for IR. There is a significant correlation between TyG index and T2DM and its common complications. In addition, the predictive efficacy of TyG index is better than that of other IR surrogate indicators. TyG index may not only become an important marker to identify people at high risk of T2DM and its complications, but is also expected to become a strong predictor of the prognosis of these diseases. However, there are still some challenges in the widespread application of TyG index in clinical practice. In the future, more high-quality studies are needed to clarify the assessment methods of TyG index for the prognosis of T2DM and its complications. Further investigations of the relationship between TyG index and T2DM and its complications will be expected to provide new ideas and methods for the prevention and treatment of T2DM and its complications.

Association between metabolic score for insulin resistance and regression to normoglycemia from prediabetes in Chinese adults: A retrospective cohort study

BACKGROUND

Metabolic score for insulin resistance (METS-IR) is a surrogate index to estimate insulin sensitivity. The aim of this study was to examine the association between METS-IR and regression to normoglycemia in Chinese adults with prediabetes.

METHODS

A total of 15,415 Chinese adults with prediabetes defined by their fasting blood glucose were included in this retrospective study. The association between METS-IR and regression to normoglycemia from prediabetes was evaluated using the Cox proportional hazards regression model. A Cox proportional hazards regression with cubic spline function was performed to explore the nonlinear association between METS-IR and regression to normoglycemia. Kaplan-Meier curves was used to describe the probability of regression to normoglycemia from prediabetes.

RESULTS

In multivariate Cox proportional hazards regression analyses, the increase in METS-IR was independently associated with a reduced probability of regression to normoglycemia from prediabetes (all p < 0.01 in models 1-3). A nonlinear association between METS-IR and the probability of regression to normoglycemia was observed, with an inflection point of 49.3. The hazard ratio on the left side of the inflection point was 0.965 (95% CI 0.953-0.976). Subgroup analyses demonstrated the robustness of our findings.

CONCLUSION

This study demonstrated a negative and nonlinear association between METS-IR and regression to normoglycemia in Chinese adults with prediabetes. When METS-IR is below 49.3, reducing METS-IR could significantly increase the probability of regression to normoglycemia from prediabetes.

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

BACKGROUND

Various 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.

METHODS

We 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.

RESULTS

The 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.

CONCLUSION

Due 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 metabolic score for insulin resistance and clinical outcomes: insights from the Tehran lipid and glucose study

BACKGROUND

We aimed to assess the relationship between Metabolic Score for Insulin Resistance (METS-IR) and the incidence of coronary heart disease (CHD), stroke, mortality, diabetes, hypertension, and chronic kidney disease (CKD) in a population from the Middle East and North Africa (MENA) region.

METHOD

Individuals aged ≥ 20 years were enrolled. Cox proportional hazards regression models were applied to assess the association between METS-IR and incident CHD, stroke, all-cause mortality, diabetes, hypertension, and CKD.

RESULTS

Over a median follow-up period of 9-18 years, 1080 (10.6%), 267 (2.6%), 1022 (9.6%), 1382 (16.4%), 2994 (58.5%), and 2002 (23.0%) CHD, stroke, all-cause mortality, diabetes, hypertension, and CKD events occurred, respectively. Compared to the lowest quartile (reference), the hazard ratios (HR) associated with the highest quartile of METS-IR were 1.527 (95% confidence interval [CI]: 1.208-1.930, P for trend 0.001), 1.393 (0.865-2.243, > 0.05), 0.841 (0.682-1.038, > 0.05), 3.277 (2.645-4.060, < 0.001), 1.969 (1.752-2.214, < 0.001), and 1.020 (0.874-1.191, > 0.05) for CHD, stroke, all-cause mortality, diabetes, hypertension, and CKD, respectively. METS-IR, as a continuous variable, was significantly associated with the risk of incident CHD [HR, 95% CI: 1.106, 1.034-1.184], diabetes [1.524, 1.438-1.616], and hypertension [1.321, 1.265-1.380]. These associations were also independent of metabolic syndrome (METS) and remained unchanged in a subgroup of individuals without METS and/or diabetes.

CONCLUSIONS

Increasing levels of METS-IR were significantly associated with a greater risk of incident CHD, diabetes, and hypertension; therefore, this index can be a useful tool for capturing the risk of these clinical outcomes.

Negative correlation between metabolic score for insulin resistance index and testosterone in male adults

BACKGROUND

Insulin resistance (IR) is strongly correlated with the decreased deficiency of testosterone levels in males. The metabolic score for insulin resistance (METS-IR) index is regarded as an innovative measure for the assessment on IR. The research aims to explore the correlation between the METS-IR index and the testosterone levels in males.

METHODS

In this study, a cross-sectional design was made through the data obtained from the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2020. Besides, the METS-IR index was derived from serum triglyceride levels, fasting plasma glucose, HDL-C and BMI.

RESULTS

A total of 2082 participants were included in the final analysis. After controlling for confounding variables, it was found that METS-IR was independently and negatively correlated with testosterone levels (β = -3.88, 95% CI = -4.49, -3.27, P < 0.001). As shown by the generalized smooth curve fitting, METS-IR had a linear correlation with testosterone levels without threshold or saturation effects, which was consistently observed across all subgroups through stratified analysis (all P > 0.05). As revealed by the analysis on the ROC curve, the area under the curve (AUC) for the METS-IR index (0.732, 95% CI = 0.705, 0.760) was significantly larger than that of homeostatic model assessment of insulin resistance (HOMA-IR), TG/HDL ratio, triglyceride-glucose index (TyG) and body mass index (BMI).

CONCLUSION

The findings suggest a negative relationship between the METS-IR index and the testosterone levels in male adults. Furthermore, the METS-IR index demonstrates superior predictive ability for testosterone deficiency in comparison to HOMA-IR, TG/HDL ratio, TyG and BMI.

Association of non-insulin-based insulin resistance indices with disease severity and adverse outcome in idiopathic pulmonary arterial hypertension: a multi-center cohort study

BACKGROUND

Insulin resistance (IR) plays an important role in the pathophysiology of cardiovascular disease. Recent studies have shown that diabetes mellitus and impaired lipid metabolism are associated with the severity and prognosis of idiopathic pulmonary arterial hypertension (IPAH). However, the relationship between IR and pulmonary hypertension is poorly understood. This study explored the association between four IR indices and IPAH using data from a multicenter cohort.

METHODS

A total of 602 consecutive participants with IPAH were included in this study between January 2015 and December 2022. The metabolic score for IR (METS-IR), triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, triglyceride and glucose (TyG) index, and triglyceride-glucose-body mass index (TyG-BMI) were used to quantify IR levels in patients with IPAH. The correlation between non-insulin-based IR indices and long-term adverse outcomes was determined using multivariate Cox regression models and restricted cubic splines.

RESULTS

During a mean of 3.6 years' follow-up, 214 participants experienced all-cause death or worsening condition. Compared with in low to intermediate-low risk patients, the TG/HDL-C ratio (2.9 ± 1.7 vs. 3.3 ± 2.1, P = 0.003) and METS-IR (34.5 ± 6.7 vs. 36.4 ± 7.5, P < 0.001) were significantly increased in high to intermediate-high risk patients. IR indices correlated with well-validated variables that reflected the severity of IPAH, such as the cardiac index and stroke volume index. Multivariate Cox regression analyses indicated that the TyG-BMI index (hazard ratio [HR] 1.179, 95% confidence interval [CI] 1.020, 1.363 per 1.0-standard deviation [SD] increment, P = 0.026) and METS-IR (HR 1.169, 95% CI 1.016, 1.345 per 1.0-SD increment, P = 0.030) independently predicted adverse outcomes. Addition of the TG/HDL-C ratio and METS-IR significantly improved the reclassification and discrimination ability beyond the European Society of Cardiology (ESC) risk score.

CONCLUSIONS

IR is associated with the severity and long-term prognosis of IPAH. TyG-BMI and METS-IR can independently predict clinical worsening events, while METS-IR also provide incremental predictive performance beyond the ESC risk stratification.

Effects of triglyceride glucose (TyG) and TyG-body mass index on sex-based differences in the early-onset heart failure of ST-elevation myocardial infarction

BACKGROUND AND AIM

Heart failure (HF) is an important complication of ST-elevation myocardial infarction (STEMI), including early- and late-onset HF. This study aimed to investigate the association between insulin resistance (IR)-related parameters triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) index and early-onset HF in STEMI between sexes.

METHODS AND RESULTS

This cross-sectional study included patients with STEMI who underwent primary percutaneous coronary intervention (PCI) between January 2016 and September 2022. Patients were divided into tertiles according to TyG/TyG-BMI index levels in males and females. The presence of early-onset HF was compared between tertiles in both sexes. Moreover, patients were stratified according to the tertiles of TyG/Tyg-BMI index. Differences in early-onset HF of STEMI were compared between males and females in each tertile group. 1118 patients were included in this study, 20.3% of whom were females. The incidence rate of early-onset HF was significantly higher in females than in males (29% vs. 14.8%). TyG-BMI index was negatively correlated with early-onset HF. In both females and males, there was no difference in the occurrence of early-onset HF between the highest and lowest TyG/TyG-BMI index groups. Sex disparity was observed in females who had a significantly higher prevalence of early-onset HF than males in each TyG/TyG-BMI index tertile group; however, after adjustment, the differences disappeared.

CONCLUSIONS

For patients with STEMI who undergo primary PCI, the incidence of early-onset HF is higher in females than in males. The TyG/TyG-BMI index do not contribute to the difference in early-onset HF between sexes.

The association between metabolic syndrome and insulin resistance with risk of cardiovascular events in different states of cardiovascular health status

AIMS/INTRODUCTION

The aim was to examine the joint effect of metabolic syndrome (MetS) and insulin resistance (IR) with ideal cardiovascular health (iCVH) status on incident cardiovascular diseases (CVDs).

MATERIALS AND METHODS

The study included 6,240 Iranian adults ≥30 years, free of prior cardiovascular disease. Ideal cardiovascular health was determined based on American Heart Association's Life Simple 7. Metabolic syndrome was defined according to the Joint Interim Statement Criteria, and insulin resistance was defined as HOMA-IR ≥1.85 in women and ≥2.17 in men. Multivariable Cox proportional hazard ratios (HRs) were applied to examine the impact of metabolic syndrome, and insulin resistance at various levels of iCVH status.

RESULTS

During the median follow-up of 14.0 years, 909 cases of cardiovascular disease occurred. Metabolic syndrome and insulin resistance were significantly associated with incident cardiovascular disease events. In the poor and intermediate status, metabolic syndrome increased cardiovascular disease events with HRs of 1.83 and 1.57, respectively; the corresponding values for insulin resistance in the mentioned categories were 1.91 and 1.25, respectively (P values < 0.05). In the intermediate and poor iCVH status, hypertriglyceridemia was linked to a 40% and 35% higher risk of cardiovascular disease, the corresponding values for low HDL-C was 20% and 60%, respectively (P values < 0.05). Although adding metabolic syndrome, its dyslipidemia and insulin resistance to iCVH status in both poor and intermediate status significantly improve the prediction of cardiovascular disease using net reclassification improvement (P values < 0.05), the value of C-index did not change.

CONCLUSIONS

Metabolic syndrome and the dyslipidemia component had a negligible but significant improvement in the prediction of cardiovascular disease among individuals with non-optimal iCVH status.