Purpose: The purpose of this study is to describe the characteristics and prognostic factors of pediatric uveitis in a French university referral hospital.
Methods: We performed a retrospective study of all cases of all pediatric uveitis seen at our institution over a 7-year period.
Results: A total of 141 eyes of 86 children were included. The mean age was 10.7 years, and 61.6% were girls. The uveitis was bilateral in 64.0% of cases. Anterior uveitis (41.0%) and intermediate uveitis (32.0%) were the most frequent forms. The most frequent etiologies were idiopathic (27.9%), juvenile idiopathic arthritis (25.6%) and pars planitis (18.6%). During the follow-up period, systemic corticosteroids were received by 43.0% of children, immunosuppressive drugs by 31.4% and biological agents by 18.6%. At the final examination, complications were present in 67.0% of patients: 18.0% had cataracts, and 11.3% had intraocular hypertension. Posterior synechiae were present in 27.6% of eyes, optic disc edema in 10.5% and macular edema in 16.2%. At the last visit, visual acuity was better than 20/200 in 97.0% of cases. The presence of band keratopathy, cataract or glaucoma was an independent predictor of impaired visual outcomes at follow-up.
Conclusion: Juvenile idiopathic arthritis is one of the most frequent and severe pediatric uveitides. Close monitoring and early treatment could prevent complications.
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http://dx.doi.org/10.1016/j.jfo.2022.08.005 | DOI Listing |
Turk J Ophthalmol
December 2024
Uvea Academy Eye Clinic, Ankara, Türkiye.
Objectives: To evaluate the clinical features of pediatric non-infectious uveitis (NIU) patients treated with adalimumab (ADA) and the efficacy of ADA in patients unresponsive to conventional immunosuppressive therapy.
Materials And Methods: The records of 91 NIU patients aged ≤16 years who received ADA therapy were evaluated retrospectively. The patients' demographic and clinical characteristics and treatment approaches were recorded.
Sci Rep
December 2024
Department of Ophthalmology, China Medical University Hospital, China Medical University, Taichung, Taiwan.
To investigate for the risk of uveitis among such patients. A retrospective cohort study utilized the TriNetX database and recruited pediatric autoimmune patients diagnosed between January 1st 2004 and December 31st 2022. The non-autoimmune cohort were randomly selected control patients matched by sex, age, and index year.
View Article and Find Full Text PDFJ Family Med Prim Care
November 2024
Flinders University College of Medicine and Public Health, Adelaide, Australia.
Up to 10% of uveitis cases occur in children, with notable implications due to the risk of chronicity and vision loss. It can result from infections, autoimmune and autoinflammatory diseases, trauma, or masquerade syndromes. Primary care providers are vital in early detection, symptom management, and timely specialist referral.
View Article and Find Full Text PDFClin Exp Rheumatol
December 2024
Division of Rheumatology, Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Children's Hospital of Philadelphia, PA, USA.
Objectives: Treatment with tumour necrosis factor inhibitors (TNFi) has significantly improved outcomes in uveitis associated with juvenile idiopathic arthritis (JIA-U). This study examines a CARRA Registry cohort of JIA-U patients on TNFi to analyse utilisation patterns and identify factors associated with response.
Methods: This retrospective cohort study used CARRA Registry data for subjects aged 0-25 with JIA-U who had uveitis onset before the age of 19, and ever used TNFi.
Clin Ophthalmol
December 2024
Department of Cataract, Cornea and Refractive Surgery, Gomabai Netralaya and Research Centre, Neemuch, Madhya Pradesh, 458441, India.
In the dynamic field of ophthalmology, artificial intelligence (AI) is emerging as a transformative tool in managing complex conditions like uveitis. Characterized by diverse inflammatory responses, uveitis presents significant diagnostic and therapeutic challenges. This systematic review explores the role of AI in advancing diagnostic precision, optimizing therapeutic approaches, and improving patient outcomes in uveitis care.
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