Assessment of six insulin resistance surrogate indexes for predicting stroke incidence in Chinese middle-aged and elderly populations with abnormal glucose metabolism: a nationwide prospective cohort study

Cardiovascular Diabetology, Journal Year: 2025, Volume and Issue: 24(1)

Published: Feb. 6, 2025

Estimate glucose disposal rate (eGDR), Chinese visceral adiposity index (CVAI), triglyceride-glucose (TyG), TyG-body mass (TyG-BMI), metabolic score for insulin resistance (METS-IR), and atherogenic of plasma (AIP) are considered surrogate indexes (IR). There is a lack studies comparing the predictive values different IR stroke risk among individuals with abnormal metabolism. This study aimed to investigate relationships between six in metabolism, evaluate their abilities risk. Data from China Health Retirement Longitudinal Study (CHARLS) were analysed this study. Multivariate logistic regression models applied analyse The dose-response explored using restricted cubic splines. areas under curve (AUCs) calculated by receiver operating characteristic (ROC) analysis. After adjusting potential confounders, we observed that each standard deviation (SD) increase eGDR was associated reduced stroke, an adjusted odds ratio (OR) 0.746 [95% confidence interval (CI): 0.661-0.842]. In contrast, SD CVAI, TyG, TyG-BMI, METS-IR, AIP increased ORs (95% CIs) 1.232 (1.106-1.373), 1.246 (1.050-1.479), 1.186 (1.022-1.376), 1.222 (1.069-1.396), 1.193 (1.050-1.355), respectively. Dose-response analyses showed eGDR, TyG-BMI METS-IR linearly (Pnonlinear ≥ 0.05), whereas TyG nonlinearly < 0.05). According ROC analysis, AUC predicting overall population metabolism (AUC: 0.612, 95% CI: 0.584-0.640) significantly higher than other indexes. closely high promising middle-aged elderly populations

Language: Английский

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The role of glucose disposal efficiency in predicting stroke among older adults: a cohort study

Frontiers in Neurology, Journal Year: 2025, Volume and Issue: 16

Published: March 11, 2025

Background Glucose disposal rate (eGDR) has recently been validated as a surrogate marker of insulin resistance, providing novel approach to assess metabolic health. However, the relationship between changes in eGDR levels and stroke incidence remains underexplored. The current study aims investigate impact control on related events. Methods Data were obtained from China Longitudinal Study Health Retirement (CHARLS). analysis included 6,375 participants aged 45 above with complete data CHARLS for 2011, 2013, 2015. Logistic multivariable regression examined stroke, using threshold identify inflection points. we categorized into distinct subgroups based sociodemographic variables see other variables. Results Out 8,060 individuals analyzed cohort, 821 diagnosed new-onset stroke. There was notable negative correlation found risk eGDR, each Interquartile Range (IQR) increment leading 38% reduction [OR: 0.62; 95% CI: (0.45,0.84)]. Stratified analyses revealed age potential modifier age-stroke ( P interaction = 0.01). Conclusion Poorly controlled level is associated an increased middle-aged elderly people. Monitoring may help at high early.

Language: Английский

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The prognostic significance of stress hyperglycemia ratio in evaluating all-cause and cardiovascular mortality risk among individuals across stages 0–3 of cardiovascular–kidney–metabolic syndrome: evidence from two cohort studies

Cardiovascular Diabetology, Journal Year: 2025, Volume and Issue: 24(1)

Published: March 24, 2025

The American Heart Association (AHA) proposed the concept of cardiovascular–kidney–metabolic (CKM) syndrome, underscoring interconnectedness cardiovascular, renal, and metabolic diseases. stress hyperglycemia ratio (SHR) represents an innovative indicator that quantifies blood glucose fluctuations in patients experiencing acute or subacute stress, correlating with detrimental clinical effects. Nevertheless, prognostic significance SHR within individuals diagnosed CKM syndrome stages 0 to 3, particularly respect all-cause cardiovascular disease (CVD) mortality risks, has not been fully understood yet. current study analyzed data from 9647 participants covering based on NHANES (National Health Nutrition Examination Survey) collected 2007 2018. In this study, primary exposure variable was SHR, computed as fasting plasma divided by (1.59 * HbA1c − 2.59). main endpoints were well CVD mortality, death registration sourced through December 31, 2019. CHARLS database (China Retirement Longitudinal Study) utilized validation enhance reliability findings. This included participants, who followed for a median duration 6.80 years. During period, 630 cases 135 CVD-related deaths total recorded. After full adjustment covariates, our results displayed robust positive association (Hazard [HR] = 1.09, 95% Confidence interval [CI] 1.04–1.13). However, exhibited no significant relationship (HR 1.00, CI 0.91–1.11). mediation analysis suggested between risk is partially mediated RDW, albumin, RAR. Specifically, mediating effects 17.0% (95% 46.7%, 8.7%), 10.1% 23.9%, 4.7%), 23.3% 49.0%, 13.0%), respectively. Additionally, analyses indicated correlation among across 0–3 during follow-up period 2011 2020. An increased value positively associated elevated likelihood 0–3, yet it shows mortality. important tool predicting long-term adverse outcomes population. Cardiovascular–kidney–metabolic emphasizes kidney, novel marker reflecting stress-induced fluctuations, but its (stages 0–3) remains uncertain. explores Our findings indicate significantly 1.04–1.13), CI: Mediation Validation using supports these These suggest could serve biomarker patients, offering potential utility stratification management.

Language: Английский

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Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0–3 and the development of a machine learning prediction model: a nationwide prospective cohort study

Cardiovascular Diabetology, Journal Year: 2025, Volume and Issue: 24(1)

Published: April 16, 2025

Background The American Heart Association recently introduced the concept of cardiovascular-kidney-metabolic (CKM) syndrome, highlighting increasing importance complex interplay between metabolic, renal, and cardiovascular diseases (CVD). While substantial evidence supports a correlation estimated glucose disposal rate (eGDR) CVD events, its predictive value compared with other insulin resistance (IR) indices, such as triglyceride–glucose (TyG) index, TyG-waist circumference, TyG-body mass TyG-waist-to-height ratio, triglyceride-to-high density lipoprotein cholesterol metabolic score for resistance, remains unclear. Methods This prospective cohort study utilized data from China Health Retirement Longitudinal Study (CHARLS). individuals were categorized into four subgroups based on quartiles eGDR. associations eGDR incident evaluated using multivariate logistic regression analyses restricted cubic spline. Seven machine learning models to assess index events. To model’s performance, we applied receiver operating characteristic (ROC) precision-recall (PR) curves, calibration decision curve analysis. Results A total 4,950 participants (mean age: 73.46 ± 9.93 years), including 50.4% females, enrolled in study. During follow-up 2011 2018, 697 (14.1%) developed CVD, 486 (9.8%) heart disease 263 (5.3%) stroke. outperformed six IR indices predicting demonstrating significant linear relationship all outcomes. Each 1-unit increase was associated 14%, 19% lower risk disease, stroke, respectively, fully adjusted model. incorporation significantly improved prediction performance area under ROC PR curves equal or exceeding 0.90 both training testing sets. Conclusions outperforms stroke CKM syndrome stages 0–3. Its enhances stratification may aid early identification high-risk this population. Further studies are needed validate these findings external cohorts. Graphical abstract

Language: Английский

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