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  • Title: Classification Criteria for Fuchs Uveitis Syndrome.
    Author: Standardization of Uveitis Nomenclature (SUN) Working Group.
    Journal: Am J Ophthalmol; 2021 Aug; 228():262-267. PubMed ID: 33845007.
    Abstract:
    PURPOSE: To determine classification criteria for Fuchs' uveitis syndrome. DESIGN: Machine learning of cases with Fuchs' uveitis syndrome and 8 other anterior uveitides. METHODS: Cases of anterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the anterior uveitides. The resulting criteria were evaluated on the validation set. RESULTS: One thousand eighty-three cases of anterior uveitides, including 146 cases of Fuchs' uveitis syndrome, were evaluated by machine learning. The overall accuracy for anterior uveitides was 97.5% in the training set and 96.7% in the validation set (95% confidence interval 92.4, 98.6). Key criteria for Fuchs' uveitis syndrome included unilateral anterior uveitis with or without vitritis and either: 1) heterochromia or 2) unilateral diffuse iris atrophy and stellate keratic precipitates. The misclassification rates for Fuchs' uveitis syndrome were 4.7% in the training set and 5.5% in the validation set, respectively. CONCLUSIONS: The criteria for Fuchs' uveitis syndrome had a low misclassification rate and appeared to perform well enough for use in clinical and translational research.
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