Evidence mapPaperPMID 41497886Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2025

Association Between GGT/HDL-C Ratio and Diabetic Kidney Disease in Patients with Type-2 Diabetes Mellitus.

Chenhuai Teng, Hao Lin, Jing Xu, Xiaoying Wu

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Comment on the Association Between the GGT/HDL-C Ratio and Diabetic Kidney Disease Risk [Letter].Diabetes, metabolic syndrome and obesity : targets and therapy · 2026
    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.

Chenhuai Teng *Department of Emergency Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China.
Hao Lin *Department of Gastroenterology, Pingyang Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China.
Jing XuDepartment of Endocrinology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China.ORCID 0000-0001-6785-9846
Xiaoying WuDepartment of Endocrinology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The ratio of gamma-glutamyl transferase (GGT) to high-density lipoprotein cholesterol (HDL-C) (GHR) represents a novel non-insulin-based biomarker for evaluating the risk of NAFLD and T2DM. However, its correlation with diabetic kidney disease (DKD) remains unexplored. This study aims to explore the association between GHR and DKD in patients with T2DM. Patients and Methods: In this cross-sectional study, 2798 patients diagnosed as T2DM admitted to the hospital from 2018 to 2023 were assessed. The analysis was conducted through restricted cubic spline (RCS) and logistic regression methodologies, complemented by additional stratified and interaction analyses. Results: As the quartiles of GHR increase, there is a notable increase in the prevalence of DKD, with the rates of 43.2%, 47.2%, 52.1%, and 57.4%, respectively. Logistic regression analysis showed a positive association between GHR and DKD (OR=1.17, 95% CI: 1.05-1.30), which was consistently observed across all subgroups through stratified analysis. RCS analysis identified an inverted L-shaped association, with an inflection point at 84.5. Additionally, AUC for GHR (AUC = 0.637, 95% CI: 0.616-0.657) was significantly higher compared to those of GGT and HDL alone. Conclusion: GHR exhibits a positive association with the risk of DKD, underscoring its potential utility as a cost-effective biomarker for stratifying the risk of DKD.

Indexed as

diabetic kidney diseaseGHRinsulin resistanceTyGtype 2 diabetes mellitus

Identifiers

PMID41497886
PMCPMC12766118

What Socratic holds

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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.