Evidence mapPaperPMID 42010586Full record

SynthesisBMC endocrine disorders2026

The association between the triglyceride-glucose index and serum uric acid: a systematic review and meta-analysis.

Lanlan Feng, Hua Fan, Xiyun Rao, Ting Tang, Yongmin Shi, Qingwen Yu, Xuhan Tong, Xinyan Fu, Zhao Xu, Juan Chen and 4 more

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in BMC endocrine disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Lanlan Feng *Zhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China.
Hua Fan *School of Clinical Medicine, The First Affiliated Hospital of Henan University of Science and Technology, Henan University of Science and Technology, Luoyang, Henan, 471003, China.
Xiyun RaoZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China.
Ting TangZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China.
Yongmin ShiZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China.
Qingwen YuZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China.
Xuhan TongZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China.
Xinyan FuZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China.
Zhao XuZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China.
Juan ChenZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China.
Xingwei ZhangZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China.
Hu WangZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China. wanghu19860315@163.com.
Jiake TangZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China. 20241230@hznu.edu.cn.
Mingwei WangZhejiang Key Laboratory of Medical Epigenetics, Department of Cardiology, School of Basic Medical Sciences, Engineering Research Center of Mobile Health Management System & Ministry of Education, The Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Hangzhou Normal University, Hangzhou, 310015, China. wmw990556@hznu.edu.cn.

Funding

Hangzhou bio-medicine and health industry development support science and technology project No.2022WJC024;No.2021WJCY001;No.2021WJCY238;No.2021WJCY047;No.2021WJCY115
6 · The paper itself

Abstract

backgroundThe triglyceride-glucose (TyG) index has emerged as a surrogate marker for insulin resistance. This systematic review and meta-analysis of observational studies aimed to investigate the association between the TyG index and hyperuricaemia and gout, which represent two consecutive disease stages.

methodsSeven electronic databases, including PubMed, Embase, Web of Science, China BioMedical Literature Database (CBM), Chinese National Knowledge Infrastructure (CNKI), VIP, and Wanfang, were searched from inception to 15 April 2025. A random-effects model was applied to account for inherent clinical heterogeneity among studies, with statistical heterogeneity evaluated using Cochrane’s Q-test and the I² statistic. Meta-regression, subgroup analyses, and sensitivity analyses were conducted to explore the potential sources of heterogeneity. A Bonferroni correction was applied for multiple comparisons. Publication bias was assessed using funnel plots, as well as Egger’s and Begg’s tests.

resultsA total of 2,865 records were obtained, and 34 studies were included in this systematic review and meta-analysis. 32 studies examined the association between TyG index and hyperuricaemia and were included in the meta-analysis. The results showed that the TyG index was significantly higher in patients with hyperuricaemia (HUA group) compared to those without hyperuricaemia (NUA group), with a mean difference (MD = 0.31, 95% CI: 0.25 to 0.37, P < 0.00001, I2 = 99%). Additionally, the TyG index was associated with an increased risk of hyperuricaemia (OR = 2.28, 95% CI: 1.85 to 2.81, P < 0.00001, I2 = 92%). Two studies focused on the relationship between TyG index and gout. The narrative synthesis of the evidence suggested that TyG index tended to be higher in gout patients than in non-gout patients.

conclusionThe TyG index is a simple and valuable marker of insulin resistance. This study provides evidence of an association between TyG index and hyperuricaemia, and highlights a possible link with gout, although further studies are needed to confirm this finding.

Indexed as

Blood GlucoseGoutHyperuricemiaTriglyceridesUric AcidBiomarkersHumansInsulin ResistanceBiomarkersBlood GlucoseTriglyceridesUric AcidGoutHyperuricaemiaInsulin resistanceMeta-analysisMetabolic healthSerum uric acidSystematic reviewTriglyceride-glucose index

Identifiers

PMID42010586
PMCPMC13112796

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.