TY - JOUR
T1 - An Algorithm for the Diagnosis of Behçet Disease Uveitis in Adults
AU - Tugal-Tutkun, Ilknur
AU - Onal, Sumru
AU - Stanford, Miles
AU - Akman, Mehmet
AU - Twisk, Jos W R
AU - Boers, Maarten
AU - Oray, Merih
AU - Özdal, Pinar Çakar
AU - Kadayifcilar, Sibel
AU - Amer, Radgonde
AU - Rathinam, Sivakumar R
AU - Vedhanayaki, Rajesh
AU - Khairallah, Moncef
AU - Akova, Yonca
AU - Yalcindag, Fatime Nilüfer
AU - Kardes, Esra
AU - Basarir, Berna
AU - Altan, Çigdem
AU - Özyazgan, Yilmaz
AU - Gül, Ahmet
N1 - Funding Information: The authors thank the uveitis experts who answered the questionnaire on diagnostic features of BD uveitis: Yonca Akova (Turkey), Sibel Kadayifcilar (Turkey), Gungor Sobaci (Turkey), Merih Soylu (Turkey), Sumru Onal (Turkey), Pinar Ozdal (Turkey), Yilmaz Ozyazgan (Turkey), Nilufer Yalcindag (Turkey), Nida Sen (USA), Narsing Rao (USA), Emmett Cunningham (USA), Andrew Dick (UK), Miles Stanford (UK), Arnd Heiligenhaus (Germany), Uwe Pleyer (Germany), Luca Cimino (Italy), Pia Allegri (Italy), Soon Phaik Chee (Singapore), Radgonde Amer (Israel), Khalid Tabbara (Saudi Arabia), and Moncef Khairallah (Tunisia). Publisher Copyright: © 2020, © 2020 Taylor & Francis Group, LLC.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Behçet disease
KW - classification and regression tree (CART) analysis
KW - classification criteria
KW - diagnosis
KW - uveitis
UR - http://www.scopus.com/inward/record.url?scp=85083581112&partnerID=8YFLogxK
U2 - https://doi.org/10.1080/09273948.2020.1736310
DO - https://doi.org/10.1080/09273948.2020.1736310
M3 - Article
C2 - 32286112
SN - 0927-3948
SP - 1
EP - 10
JO - Ocular Immunology and Inflammation
JF - Ocular Immunology and Inflammation
ER -