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Purpose: To develop an algorithm for the diagnosis of Behçet's disease (BD) uveitis based on ocular findings. Methods: Following an initial survey among uveitis experts, we collected multi-center retrospective data on 211 patients with BD uveitis and 207 patients with other uveitides, and identified ocular findings with a high diagnostic odds ratio (DOR). Subsequently, we collected multi-center prospective data on 127 patients with BD uveitis and 322 controls and developed a diagnostic algorithm using Classification and Regression Tree (CART) analysis and expert opinion. Results: We identified 10 items with DOR >5. The items that provided the highest accuracy in CART analysis included superficial retinal infiltrate, signs of occlusive retinal vasculitis, and diffuse retinal capillary leakage as well as the absence of granulomatous anterior uveitis or choroiditis in patients with vitritis. Conclusion: This study provides a diagnostic tree for BD uveitis that needs to be validated in future studies. [ABSTRACT FROM AUTHOR]

Behçet disease is a chronic relapsing multisystem inflammatory disorder. Ocular involvement is characterized by a bilateral recurrent non-granulomatous panuveitis and retinal vasculitis. Posterior segment findings vary during the course of the disease, in parallel with the relapsing and remitting intraocular inflammation. Structural alterations occur with increased disease duration. Fluorescein angiography is the gold standard in revealing the extent and severity as well as the leaky and/or occlusive nature of retinal vasculitis. Multimodal imaging using color fundus photography, fluorescein angiography, and optical coherence tomography is essential in visualizing diagnostic features, detecting structural changes, and monitoring disease activity and response to treatment in patients with Behçet uveitis. [ABSTRACT FROM PUBLISHER]