Evidence mapPaperPMID 40421238Full record

ArticleFrontiers in endocrinology2025

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

Lu Yu, Yutong Liu, Ruiying Guo, Tong Yang, Guangwei Pan, Yuanyuan He, Shan Gao, Rongrong Yang, Zhu Li, Lin Li and 1 more

Abstract readMulticenter Study
In one paragraph

Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Lu YuInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Yutong LiuInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Ruiying GuoInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Tong YangInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Guangwei PanInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Yuanyuan HeInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Shan GaoInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Rongrong YangInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Zhu LiSchool of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, China.
Lin LiInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Chunquan YuInstitute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The 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. Methods: This 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. Results: The 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 ( Conclusion: The 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.

Indexed as

Blood GlucoseCardiovascular DiseasesDyslipidemiasInsulin ResistanceMetabolic SyndromeAdultAgedBiomarkersChinaFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsROC CurveBiomarkersBlood Glucosecardiovascular diseasedyslipidemiaglucose metabolic statesinsulin resistanceMETS-IR

Identifiers

PMID40421238
PMCPMC12104048

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.