Evidence map›Paper›PMID 40837609›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2025

Assessment of the Association Between Cardiac Metabolic Markers and Carotid Atherosclerosis, and the Role of Insulin Resistance.

Yazhao Sun, Chunlan Bai, Shitong Yin, Jianfeng Liu

Abstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 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

4 authors.

Yazhao SunDepartment of Cardiology, Cangzhou People's Hospital, Cangzhou, Hebei, 06100, People's Republic of China.
Chunlan BaiDepartment of Cardiology, Cangzhou People's Hospital, Cangzhou, Hebei, 06100, People's Republic of China.
Shitong YinDepartment of Cardiology, Cangzhou People's Hospital, Cangzhou, Hebei, 06100, People's Republic of China.
Jianfeng LiuDepartment of Endocrinology and Metabolism, Cangzhou People's Hospital, Cangzhou, Hebei, 06100, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Obesity is a growing global health concern. The cardiometabolic index (CMI), a novel marker of fat distribution, has been proposed as a potential risk indicator. This study investigates the association between CMI and carotid atherosclerosis (CAS), as assessed by carotid intima-media thickness (cIMT), and explores whether insulin resistance (IR) mediates this relationship. Methods: This cross-sectional study enrolled type 2 diabetes mellitus (T2DM) patients hospitalized at Cangzhou People's Hospital between September 2024 and March 2025. Logistic regression models, restricted cubic spline (RCS) analysis, and subgroup analysis were used to examine the CMI-CAS relationship. The predictive ability of CMI was assessed using receiver operating characteristic (ROC) curves, and its incremental value beyond traditional risk factors was evaluated by integrated discrimination improvement (IDI) and net reclassification improvement (NRI). Mediation analysis assessed the role of IR. Results: After adjustment, higher CMI was significantly associated with increased odds of CAS (OR = 1.48, 95% CI: 1.21-1.81, Conclusion: Elevated CMI is independently associated with higher risk of CAS in T2DM patients, and insulin resistance partially mediates this relationship. CMI may be a valuable marker for early vascular risk stratification in diabetic populations.

Indexed as

atherosclerosiscardiometabolic indexcarotid intima-media thicknessinsulin resistanceobesity

Identifiers

PMID40837609
PMCPMC12363553

What Socratic holds

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LicenceCC BY-NC
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Registered trials

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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.