Association of Glucagon-Like Peptide-1 Receptor Agonists With Optic Nerve and Retinal Adverse Events: A Population-Based Observational Study Across 180 Countries
Bibliographic record
Abstract
Purpose : Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are important therapeutic options for type 2 diabetes and obesity; however, concerns about ophthalmic safety persist. This study examined associations between GLP-1 RAs and ocular adverse events (AEs). Design : Global observational pharmacovigilance study. Methods : We searched the US FAERS database (via OpenVigil 2.1) and WHO's VigiBase (via VigiAccess) for optic nerve and retinal AEs associated with semaglutide and tirzepatide, covering the period from their respective approval dates—December 2017 for semaglutide and May 2022 for tirzepatide—through September 2024. In FAERS, all other drugs were compared, while in VigiBase, metformin, empagliflozin, dulaglutide, and insulin served as controls. Disproportionality metrics included reporting odds ratios (RORs) with 95% confidence intervals. Results : Semaglutide and tirzepatide accounted for 76,444 cases (0.59%) in FAERS ( n =12,936,341) and 118,639 cases (0.34%) in VigiBase ( n >35,000,000). Semaglutide showed significantly higher odds of ischemic optic neuropathy (ION) (FAERS: ROR=11.12, 95%CI=8.15-15.16; VigiBase: ROR=68.58, 95%CI=16.75-280.67), diabetic retinopathy (DR) (FAERS: ROR=17.28, 95%CI=13.62-21.91; VigiBase: ROR=7.81, 95%CI=5.60-10.90), as well as retinal/vitreous detachment, retinal/vitreous hemorrhage, and retinal tear (FAERS: ROR=2.44–5.89, 95%CI=1.70–8.97, all p<0.001, IC 025 =0.49, compared to all other drugs. VigiBase: ROR=5.49-20.91, 95%CI=2.71-90.11, all p≤0.0001, IC 025 ≥0.53, compared to metformin). Unique to VigiBase were macular edema (ROR=3.87, 95%CI=1.89-7.92), macular hole (ROR=20.90, 95%CI=2.65-165.01), and papilledema (ROR=6.97, 95%CI=2.53-19.17) (all p≤0.004, IC 025 ≥0.27, compared to metformin). Sensitivity analyses using empagliflozin and dulaglutide revealed significant associations with ION and DR, while vitreous detachment and hemorrhage were significant when compared to dulaglutide. Additionally, when insulin was used as a comparator, semaglutide showed a higher ROR for ION (ROR=9.84, 95%CI=4.25–22.81, P<0.0001, IC025=0.42). However, tirzepatide was only significantly associated with DR in FAERS. Conclusions Given the widespread use of semaglutide, its association with ocular AEs highlight the need for global pharmacovigilance and post-marketing surveillance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".