Evidence map›Paper›PMID 41798832›Full record

ArticleFrontiers in nutrition2026

Evaluation of the CHG index for identifying metabolic dysfunction associated steatotic liver disease: evidence from two independent Asian non-obese populations.

Jun Chen, Qiuyi Liang, Zeru Chen, Wang Liu, Xiaomi Chen, Huan Li, Dongjie Huang, Shuyue Zhou, Riken Chen, Junqi Ren and 2 more

Abstract read
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Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Jun Chen *The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Qiuyi Liang *The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Zeru Chen *The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Wang Liu *The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Xiaomi ChenThe Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Huan LiThe Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Dongjie HuangThe Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Shuyue ZhouThe Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Riken ChenThe Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Junqi RenThe Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Xiaoling WuThe Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.
Jinhua LiangThe Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is highly prevalent and is driven by coupled abnormalities in glucose and lipid metabolism. Single metabolic markers such as total cholesterol (TC), fasting blood glucose (FBG), or high-density lipoprotein cholesterol (HDL-C) reflect isolated pathways and often show limited predictive value. The cholesterol, high-density lipoprotein, and glucose (CHG) index integrates lipid and glycaemic information and may better capture MASLD-related metabolic risk. Methods: Two de-identified health-check cohorts from the Dryad repository were analyzed: a Chinese derivation cohort from Wenzhou Medical Center (2010-2014; Results: Higher CHG was consistently associated with MASLD in both populations, showing clear dose-response gradients. Participants in the highest CHG quartile had approximately fourfold higher adjusted odds of MASLD than those in the lowest quartile. CHG yielded the highest AUC among all markers in both cohorts and improved baseline model discrimination and reclassification, with positive NRI and IDI. Conclusion: The CHG is robustly and dose-dependently associated with MASLD and demonstrates superior, reproducible discriminative performance compared with traditional single markers across two independent Asian cohorts. CHG may serve as a practical, low-cost tool for MASLD screening and risk stratification at baseline health check-ups.

Indexed as

CHG indexglucose-lipidmetabolismidentificationinsulin resistancemetabolic dysfunction-associated steatotic liver diseaseultrasonography

Identifiers

PMID41798832
PMCPMC12963058

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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 OpenQuestion graph.