Association of ocular adverse events with varenicline solution use: a population-based study
Bibliographic record
Abstract
Background Approved by the FDA in 2021, varenicline solution is the first nasal spray specifically designed to enhance basal tear film production for treating dry eye disease (DED). However, there is a lack of data comprehensively comparing its safety profile to conventional DED therapies. Herein, we assess whether ocular adverse events (AEs) are disproportionately reported with the real-world use of varenicline solution.Research design and methods This observational, population-based pharmacovigilance study analyzed the Food and Drug Administration Adverse Event Reporting System (FAERS) data (inception-April 2024) using reporting odds ratio (ROR), with significance defined as a 95% CI lower bound > 1.0. Nasal saline and systane were the controls.Results A total of 1,125 AE reports were associated with varenicline solution. No disproportionate reporting of specific ocular AEs was observed when comparing varenicline solution with nasal saline. However, when compared with systane, varenicline solution showed higher odds of lacrimation (ROR = 2.18, 95%CI = 1.46–3.26, p < 0.0001), visual impairment (ROR = 2.27, 95%CI = 1.24–4.16, p = 0.0085), and photophobia (ROR = 7.50, 95%CI = 3.68–15.27, p < 0.0001).Conclusions Although a direct causal relationship for higher RORs cannot be established for varenicline solution compared to systane, our findings provide evidence for potential risk signals and highlight the crucial role of post-marketing pharmacovigilance in monitoring long-term safety.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".