Evidence map›Paper›PMID 42286669›Full record

SynthesisLipids in health and disease2026

Association between the triglyceride-glucose index and kidney stone disease: a systematic review and dose-response meta-analysis.

Shiva Maleki, Bahar Darouei, Alireza Amin, Ali Amani-Beni, Arsham Seifnezhad, David J Tunnicliffe, Javier A Neyra, Reza Amani-Beni

Abstract readSystematic ReviewMeta-AnalysisReview
In one paragraph

Synthesis in Lipids in health and disease, 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

8 authors.

Shiva Maleki *Isfahan Kidney Diseases Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.ORCID http://orcid.org/0009-0002-5725-1698
Bahar Darouei *Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Hezar Jerib Avenue, Isfahan, Isfahan Province, Iran.ORCID http://orcid.org/0000-0002-5269-0061
Alireza AminWater and Electrolytes Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.ORCID http://orcid.org/0009-0008-2523-0060
Ali Amani-BeniUrology and Nephrology Research Center, Research Institute for Urology and Nephrology, Center of Excellence in Urology, Shahid Labbafinejad Medical Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID http://orcid.org/0000-0003-4833-730X
Arsham SeifnezhadIsfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Hezar Jerib Avenue, Isfahan, Isfahan Province, Iran.ORCID http://orcid.org/0000-0001-7209-522X
David J TunnicliffeSydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.ORCID http://orcid.org/0000-0003-3270-3475
Javier A NeyraDepartment of Medicine, Division of Nephrology, University of Alabama at Birmingham, Birmingham, AL, USA.ORCID http://orcid.org/0000-0002-2817-2459
Reza Amani-BeniIsfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Hezar Jerib Avenue, Isfahan, Isfahan Province, Iran. reza.amani.b13@gmail.com.ORCID http://orcid.org/0000-0002-8383-6676

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe triglyceride-glucose (TyG) index is an accessible marker of insulin resistance and may reflect metabolic susceptibility to kidney stone disease (KSD). This review synthesizes observational evidence on TyG and KSD and examines whether the association varies with increasing TyG.

methodsPubMed, Embase, Web of Science, Scopus, the Cochrane Library, and ProQuest were searched up to May 22, 2026 according to PRISMA 2020 and a PROSPERO-registered protocol. Eligible studies enrolled adults, assessed TyG as either a continuous or categorical exposure, reported KSD as the outcome, and provided extractable effect estimates. Study quality was evaluated using the Joanna Briggs Institute (JBI) tools. Maximally adjusted odds ratios (ORs) were synthesized using the restricted maximum likelihood (REML) random-effects model. One-stage dose-response meta-analyses using linear and restricted cubic spline models were also conducted, and the certainty of evidence was judged using GRADE.

resultsFourteen studies (total n = 1,066,215; KSD cases = 50,286) met the inclusion criteria. In the continuous analysis, each 1-unit increment in TyG corresponded to higher KSD odds (pooled adjusted OR: 1.33; 95% confidence interval [CI]: 1.15-1.54). Compared with the lowest TyG category, the highest had 52% higher odds of KSD (OR: 1.52; 95% CI: 1.26-1.84). In a one-stage random-effects dose-response meta-analysis, restricted cubic spline models provided the best fit but showed no statistical evidence of non-linearity, supporting a linear association with a 26% increase in odds per 1-unit increase in TyG (OR: 1.26; 95% CI: 1.12-1.42; 95% PI: 0.91-1.75).

conclusionA higher TyG index was associated with greater odds of KSD in a broadly linear manner; however, the marked heterogeneity across studies suggests that TyG should be viewed as a potential metabolic risk marker rather than a routine screening tool. These findings may support broader cardiometabolic risk assessment and standard preventive counseling in patients at risk of KSD.

Indexed as

Blood GlucoseKidney CalculiTriglyceridesHumansInsulin ResistanceOdds RatioBlood GlucoseTriglyceridesBlood GlucoseInsulin resistanceMeta-Analysis as TopicNephrolithiasisTriglyceride-glucose indexTriglycerides

Identifiers

PMID42286669
PMCPMC13495508

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.