ArticleFrontiers in medicine2026
Signals of drug-related retinal artery occlusion: a multi-country retrospective study from a spontaneous reporting system.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to systematically identify systemic drugs associated with retinal artery occlusion (RAO) using real-world data from the US FDA Adverse Event Reporting System (FAERS). Methods: FAERS reports from January 2004 to December 2024 were analyzed. Disproportionality analyses (ROR, PRR, BCPNN, and MGPS) were applied to detect signals of disproportionate reporting. Drugs were further evaluated based on signal strength and time-to-onset characteristics. Results: A total of 626 drugs were initially screened, among which 36 drugs were identified as having significant disproportionality signals for RAO. These drugs were categorized into several pharmacological classes, including antineoplastic agents, anti-VEGF agents, reproductive system medications, anesthetics, anti-inflammatory drugs, hormonal agents, and others. Strong signals, as indicated by the BCPNN algorithm, were observed for mepivacaine, brolucizumab, and pegaptanib. Anesthetic agents exhibited the shortest median time to onset. Conclusion: This study characterizes the reporting patterns and signal strength of RAO across multiple drug classes using pharmacovigilance data. These findings provide real-world evidence to enhance clinical awareness and support safer prescribing practices, while emphasizing the need for further validation in controlled studies.
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