MétaCan
Menu
Back to cohort
Record W4417449811 · doi:10.3389/fmed.2025.1639704

Association of glucagon-like peptide-1 (GLP-1) receptor agonists and diabetic retinopathy (DR) – a systematic review and meta-analysis

2025· article· en· W4417449811 on OpenAlexaboutno aff
Hassan Alwafi, Sami Sunaid Alharbi, Ghada Ahmad Al-adwani, Safaa Alsanosi, Tope Oyelade, Fahd Almalki, Husna Irfan Thalib, Abdallah Y. Naser, Manal Z. Alfahmi, Basil Alotaibi, M. Mujeeb Zubair, Abdulelah M. Aldhahir, Widya N. Insani, Abdullah A. Alqarni, Jaber S. Alqahtani, Deema Sami Ashoor, Mohammad S. Dairi

Bibliographic record

VenueFrontiers in Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsDiabetic retinopathyDiabetes mellitusReceptorAgonistAssociation (psychology)

Abstract

fetched live from OpenAlex

Objectives: Previous studies have shown conflicting results on the relationship between glucagon-like peptide-1 (GLP-1) receptor agonists and diabetic retinopathy (DR). This systematic review and meta-analysis aimed to clarify the association between GLP-1 receptor agonists use and the development or progression of DR. Methods: A comprehensive search of MEDLINE (via OVID and PubMed), Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov was conducted from inception to March 2025. We included randomized controlled trials (RCTs) and observational studies reporting on the association between GLP-1 receptor agonists and DR. Screening, data extraction, and quality appraisal were performed independently and in duplicate. We assessed study quality using the Cochrane risk-of-bias tool for RCTs and the Newcastle-Ottawa Scale for observational studies. Meta-analysis was conducted using Stata 17, following PRISMA and MOOSE guidelines. Results: The search identified 6,922 studies. Of these, 39 articles (24 RCTs and 15 observational studies) met the inclusion criteria and 23 were included in the meta-analysis. The pooled analysis showed that GLP-1 receptor agonists were not significantly associated with the risk of DR compared with comparators (pooled RR = 1.00, 95% CI 0.71-1.43). Subgroup analyses by study design yielded similar non-significant results, with a pooled RR of 0.91 (95% CI 0.73-1.14) for randomized controlled trials and 2.09 (95% CI 0.47-9.19) for observational studies. After excluding studies with a high risk of bias, the pooled estimate remained non-significant (RR = 1.06, 95% CI 0.67-1.67), supporting the robustness of the overall findings. The association remained non-significant when restricted to larger studies (>500 participants; RR = 1.13, 95% CI 0.70-1.84). Conclusion: In conclusions, this systematic review found no significant association between GLP-1 receptor agonists and DR risk, though a non-significant trend toward lower risk was observed in randomized trials. Given the limited number of long-term studies, the current evidence remains inconclusive. Future studies with longer follow-up period are warranted to clarify the long-term ocular safety of GLP-1 receptor agonists. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251007882.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.041
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0240.045
Bibliometrics0.0110.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.268
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in MedicineSame topicDiabetes Treatment and ManagementFrench-language works237,207