AUTHOR=Yu Lu , Liu Yutong , Guo Ruiying , Yang Tong , Pan Guangwei , He Yuanyuan , Gao Shan , Yang Rongrong , Li Zhu , Li Lin , Yu Chunquan 

TITLE=The metabolic syndrome-insulin resistance index: a tool for identifying dyslipidemia across varied glucose metabolic score in patients with cardiovascular disease

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2025.1473308

DOI=10.3389/fendo.2025.1473308

ISSN=1664-2392

ABSTRACT=PurposeThe METS-IR index, a non-insulin-based metabolic score, represents a new marker closely linked to insulin resistance. This study aimed to evaluate the relationship between the METS-IR index and dyslipidemia in individuals diagnosed with Cardiovascular disease (CVD), as well as to delve deeper into how varying glucose metabolic conditions influence this relationship.MethodsThis multicenter retrospective investigation encompassed 214,717 individuals diagnosed with CVD across China, spanning from September 1, 2014, to June 1, 2022, ultimately incorporating 17,632 cases in the conclusive analysis. All cases were grouped according to quartiles of METS-IR. The American College of Cardiology classifies dyslipidemia into four distinct categories: hyper-triglyceridemia (hyper-TG), hyper-cholesterolemia (hyper-TC), hypo-high-density lipoprotein cholesterolemia (hypo-HDL), and hyper-low-density lipoprotein cholesterolemia (hyper-LDL). Dyslipidemia is diagnosed when any one of these conditions is present. Logistic regression analysis was performed to estimate the odds ratio (OR) and 95% confidence interval (CI), assessing the relationship between the METS-IR index and dyslipidemia risk in patients with CVD. To evaluate the precision of the METS-IR index in identifying dyslipidemia, receiver operating characteristic (ROC) curve was produced.ResultsThe results of the baseline analysis showed that 11,934 cases had dyslipidemia, with notable variations observed in the clinical and biological attributes among CVD cases (P < 0.05 to < 0.001). Logistic regression analysis showed that the METS-IR index was significantly associated with the risk of dyslipidemia (odds ratio [OR]: 1.14; 95% confidence interval [CI] 1.13-1.15; P < 0.001). The OR for dyslipidemia in Q4 of the METS-IR index was 11.94 (95% CI 10.60-13.45; p < 0.001) compared to Q1. ROC analysis revealing an area under the curve (AUC) of 0.747 (95% CI 0.739-0.754; P < 0.001). The association between the METS-IR index and dyslipidemia proved significant across all glycemic status groups, with the highest OR observed in the Q4 subgroup of cases with NGR (OR: 15.43; 95% CI 12.21-19.49).ConclusionThe risk of developing dyslipidemia is positively associated with heightened METS-IR levels in individuals afflicted with CVD, and these relationships hold significance across all glycemic metabolic conditions. METS-IR could potentially aid in forecasting the risk of dyslipidemia development in individuals diagnosed with CVD.