ArticleAsia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Big Data-Based Epidemiology of Uveitis and Related Intraocular Inflammation.
Article in Asia-Pacific journal of ophthalmology (Philadelphia, Pa.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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Who cites it
4 citing papers in PubMed, 16 citations in OpenAlex.
- Epidemiology of Uveitis from a Tertiary Referral Hospital in Bulgaria over a 13-Year Period.Diagnostics (Basel, Switzerland) · 2025Article
- Comprehensive single-cell profiling of monocytes in HLA-B27-positive ankylosing spondylitis with acute anterior uveitis.MedComm · 2024Article
- Ophthalmic surgery in New Zealand: analysis of 410,099 surgical procedures and nationwide surgical intervention rates from 2009 to 2018.Eye (London, England) · 2023Review
- Colombian Ocular Diseases Epidemiology Study (CODES): incidence and sociodemographic characterisation of keratoconus between 2015 and 2020.BMJ open ophthalmology · 2023Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
abstractLarge administrative health databases, nationwide surveys, and the widespread adoption of electronic medical records have led to an increasing availability of health-related data on ocular inflammatory disease, allowing us to elucidate the real-world epidemiology of uveitis and examine patient and systems-level risk factors for the incidence of specific etiologies of uveitis and its complications. Despite the many advantages to using big databases, there are also limitations that clinicians must be aware of when making conclusions and extrapolating to the general population, such as the lack of standardization of nomenclature and coding. As the availability of even more robust datasets increases, clinicians and scientists should be prepared to leverage these tools to improve our understanding of disease pathophysiology and our ability to manage patients with ocular inflammatory disease.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.