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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]

Since there is no pathognomonic clinical sign or laboratory test to distinguish Behçet disease from other uveitic entities, the diagnosis must be made based on characteristic ocular and systemic findings in the absence of evidence of other disease that can explain the findings. Ancillary tests, including ocular and brain imaging studies, are used to assess the severity of intraocular inflammation and systemic manifestations of Behçet disease, to identify latent infections and other medical conditions that might worsen with systemic treatment, and to monitor for adverse effects of drugs used. There are two diagnostic or classification criteria in general use by the uveitis community, one from Japan and one from an international group; both rely on a minimum number and/or combination of clinical findings to identify Behçet disease. Finally, several grading schemes have been proposed to assess severity of ocular disease and response to treatment. [ABSTRACT FROM AUTHOR]