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Classification criteria for Fuchs uveitis syndrome.

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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… Click to show full 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 overall accuracy for anterior uveitides was 97.5% in the training set (95% confidence interval [CI] 96.3, 98.4) and 96.7% in the validation set (95% CI 92.4, 98.6). The misclassification rates for FUS 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.

Keywords: criteria fuchs; anterior uveitides; training set; validation set; uveitis syndrome; fuchs uveitis

Journal Title: American journal of ophthalmology
Year Published: 2021

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