The triglyceride-glucose index as a biomarker of diabetic retinopathy: A systematic review and meta-analysis.

This project presents a systematic review and meta-analysis investigating the association between the triglyceride-glucose (TyG) index—a surrogate marker of insulin resistance—and the presence and severity of diabetic retinopathy (DR). The study aims to synthesize existing evidence from observational studies, including cross-sectional, cohort, and case–control designs, to clarify whether elevated TyG levels are associated with an increased risk of DR in individuals with diabetes mellitus. The protocol was preregistered on PROSPERO (CRD420251110467) and follows PRISMA 2020 guidelines. Comprehensive database searches were performed in PubMed, Scopus, and Web of Science, and risk of bias was assessed using validated tools (AHRQ checklist for cross-sectional studies and Newcastle-Ottawa Scale). Meta-analytic techniques were used to pool effect sizes, evaluate heterogeneity, and assess publication bias. Subgroup analyses explored the influence of study design, diabetes type, and geographic region.The expected outcomes include pooled odds ratios or risk estimates for DR based on TyG index categories or continuous levels, identification of sources of heterogeneity, and evaluation of the predictive potential of the TyG index. This project aims to provide clinicians and researchers with a clearer understanding of the TyG index as a potential biomarker for microvascular complications, specifically diabetic retinopathy.\n\nAll data extraction forms, statistical code, risk of bias assessments, and figures are made available here to enhance reproducibility and transparency.

Publication Details

Journal
Open Science Framework
Published
2025-01-01
DOI
https://doi.org/10.17605/osf.io/vdr7z
Primary Topic
Retinal Diseases and Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The triglyceride-glucose index as a biomarker of diabetic retinopathy: A systematic review and meta-analysis.

Open Science Framework
Retinal Diseases and Treatments
article

The triglyceride-glucose index as a biomarker of diabetic retinopathy: A systematic review and meta-analysis.

article en

Abstract

This project presents a systematic review and meta-analysis investigating the association between the triglyceride-glucose (TyG) index—a surrogate marker of insulin resistance—and the presence and severity of diabetic retinopathy (DR). The study aims to synthesize existing evidence from observational studies, including cross-sectional, cohort, and case–control designs, to clarify whether elevated TyG levels are associated with an increased risk of DR in individuals with diabetes mellitus. The protocol was preregistered on PROSPERO (CRD420251110467) and follows PRISMA 2020 guidelines. Comprehensive database searches were performed in PubMed, Scopus, and Web of Science, and risk of bias was assessed using validated tools (AHRQ checklist for cross-sectional studies and Newcastle-Ottawa Scale). Meta-analytic techniques were used to pool effect sizes, evaluate heterogeneity, and assess publication bias. Subgroup analyses explored the influence of study design, diabetes type, and geographic region.The expected outcomes include pooled odds ratios or risk estimates for DR based on TyG index categories or continuous levels, identification of sources of heterogeneity, and evaluation of the predictive potential of the TyG index. This project aims to provide clinicians and researchers with a clearer understanding of the TyG index as a potential biomarker for microvascular complications, specifically diabetic retinopathy.\n\nAll data extraction forms, statistical code, risk of bias assessments, and figures are made available here to enhance reproducibility and transparency.

Open Science Framework
Openalex Percentile: Top 39%
Retinal Diseases and Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.