OBJECTIVE: To assess the adequacy of image agreement regarding uveitis based on color fundus and fluorescein angiography images alone, and to use free and open source applications to conduct an image agreement study. DESIGN: Cross-sectional agreement study. PARTICIPANTS: Baseline fundus and fluorescein images of patients with panuveitis, posterior, or intermediate uveitis enrolled in the Multi-center Uveitis Steroid Treatment (MUST) trial. METHODS: Three fellowship-trained specialists in uveitis independently reviewed patient images using ClearCanvas™ and responded using Epi Info™. The diagnoses of the 3 reviewers were compared with the MUST clinician as a gold standard. A rank transformation adjusted for the possible variation in number of responses per patient. Chance-corrected interobserver agreement among the 3 reviewers was estimated with the ι coefficient. Confidence interval (CI) and SE were bootstrapped. RESULTS: Agreement between the diagnoses of the respondents and the baseline MUST clinician's diagnosis was poor across all diagnostic categories, ι = 0.09 (95% CI, 0.07-0.11). The agreement among respondents alone also was poor, ι = 0.11 ± 0.02 (95% CI, 0.08-0.13). The specialists requested more patient historical and clinical information to make a diagnosis on all patients. CONCLUSIONS: The role in distinguishing the multiple conditions in uveitis appears to be limited when based on fundus imaging alone. Future studies should investigate different categories of clinical data to supplement image data. Freely available applications have excellent utility in ophthalmic imaging agreement studies. Published by Elsevier Inc.
RCT Entities:
OBJECTIVE: To assess the adequacy of image agreement regarding uveitis based on color fundus and fluorescein angiography images alone, and to use free and open source applications to conduct an image agreement study. DESIGN: Cross-sectional agreement study. PARTICIPANTS: Baseline fundus and fluorescein images of patients with panuveitis, posterior, or intermediate uveitis enrolled in the Multi-center Uveitis Steroid Treatment (MUST) trial. METHODS: Three fellowship-trained specialists in uveitis independently reviewed patient images using ClearCanvas™ and responded using Epi Info™. The diagnoses of the 3 reviewers were compared with the MUST clinician as a gold standard. A rank transformation adjusted for the possible variation in number of responses per patient. Chance-corrected interobserver agreement among the 3 reviewers was estimated with the ι coefficient. Confidence interval (CI) and SE were bootstrapped. RESULTS: Agreement between the diagnoses of the respondents and the baseline MUST clinician's diagnosis was poor across all diagnostic categories, ι = 0.09 (95% CI, 0.07-0.11). The agreement among respondents alone also was poor, ι = 0.11 ± 0.02 (95% CI, 0.08-0.13). The specialists requested more patient historical and clinical information to make a diagnosis on all patients. CONCLUSIONS: The role in distinguishing the multiple conditions in uveitis appears to be limited when based on fundus imaging alone. Future studies should investigate different categories of clinical data to supplement image data. Freely available applications have excellent utility in ophthalmic imaging agreement studies. Published by Elsevier Inc.
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