Department of Ophthalmology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey.
Department of Ophthalmology, School of Medicine, Koc University, Istanbul, Turkey.
Ocul Immunol Inflamm. 2021 Aug 18;29(6):1154-1163. doi: 10.1080/09273948.2020.1736310. Epub 2020 Apr 14.
: To develop an algorithm for the diagnosis of Behçet's disease (BD) uveitis based on ocular findings.: 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.: 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.: This study provides a diagnostic tree for BD uveitis that needs to be validated in future studies.
:开发一种基于眼部表现的贝赫切特病(BD)葡萄膜炎诊断算法:在对葡萄膜炎专家进行初步调查后,我们收集了 211 例 BD 葡萄膜炎患者和 207 例其他葡萄膜炎患者的多中心回顾性数据,并确定了具有高诊断比值比(DOR)的眼部表现。随后,我们收集了 127 例 BD 葡萄膜炎患者和 322 例对照患者的多中心前瞻性数据,并使用分类和回归树(CART)分析和专家意见制定了诊断算法。:我们确定了 10 项 DOR>5 的项目。在 CART 分析中提供最高准确性的项目包括浅层视网膜浸润、闭塞性视网膜血管炎的迹象以及弥漫性视网膜毛细血管渗漏,以及患有玻璃体炎症的患者中无肉芽肿性前葡萄膜炎或脉络膜炎。:本研究提供了一种 BD 葡萄膜炎的诊断树,需要在未来的研究中进行验证。