Does semaglutide increase the risk of non-arteritic anterior ischemic optic neuropathy? A systematic review and meta-analysis of emerging evidence
Bibliographic record
Abstract
BACKGROUND: Semaglutide, a GLP-1 receptor agonist widely prescribed for type 2 diabetes and obesity, has recently been linked to rare ocular adverse events, including non-arteritic anterior ischemic optic neuropathy (NAION). Given the growing concerns and limited clarity, this systematic review and meta-analysis aims to critically assess the potential association between semaglutide use and NAION risk. OBJECTIVES: To evaluate the association between semaglutide use and the development of NAION. METHODS: A comprehensive literature search was conducted via different databases from inception to June 3rd, 2025. A reviewer screened the potential articles against prespecified eligibility criteria. The risk of bias in the eligible studies was then evaluated using the Newcastle Ottawa Scale (NOS). Data were then systematically extracted and analyzed. RESULTS: The database search yielded 3539 records, of which 10 research articles investigating the association between Semaglutide and NAION were included in this study. Semaglutide use was associated with a significantly increased risk of NAION compared to control medications, with a pooled hazard ratio of 2.620 (95 % CI: 1.808-3.795, P < 0.001). Risk elevation showed time-dependency, becoming statistically significant after 2 years of exposure. Identified risk factors included older age, male sex, prolonged diabetes duration, elevated HbA1c, diabetic retinopathy, and obesity. Among GLP-1 receptor agonists, semaglutide accounted for 86.5 % of reported NAION cases. Clinical presentations featured optic disc edema, intraretinal fluid on OCT, and crowded optic discs. Cumulative incidence rates were substantially higher in semaglutide users versus non-GLP-1 receptor agonist comparators. CONCLUSIONS: Semaglutide use shows association with increased NAION risk, particularly with prolonged exposure and in patients with predisposing factors. Risk-benefit assessment and targeted ophthalmologic monitoring are recommended while maintaining appropriate therapeutic use.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".