Standardization of Uveitis Nomenclature (SUN) Working Group, .; (2021) Classification Criteria for Sympathetic Ophthalmia. American Journal of Ophthalmology , 228 pp. 212-219. 10.1016/j.ajo.2021.03.048.

Preview

Text SUN_SO_classification_criteria_2020.pdf - Accepted Version Download (353kB) | Preview

Abstract

PURPOSE: To determine classification criteria for sympathetic ophthalmia DESIGN: Machine learning of cases with sympathetic ophthalmia and 5 other panuveitides. METHODS: Cases of panuveitides 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 panuveitides. The resulting criteria were evaluated on the validation set. RESULTS: One thousand twelve cases of panuveitides, including 110 cases of sympathetic ophthalmia, were evaluated by machine learning. The overall accuracy for panuveitides was 96.3% in the training set and 94.0% in the validation set (95% confidence interval 89.0, 96.8). Key criteria for sympathetic ophthalmia included bilateral uveitis with 1) a history of unilateral ocular trauma or surgery and 2) an anterior chamber and vitreous inflammation or a panuveitis with choroidal involvement. The misclassification rates for sympathetic ophthalmia were 4.2 % in the training set and 6.7% in the validation set, respectively. CONCLUSIONS: The criteria for sympathetic ophthalmia had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.

Download activity - last month

Export as CSVXMLJSON

Download activity - last 12 months

Export as CSVXMLJSON

Downloads by country - last 12 months

Export as JSONXMLCSV

Archive Staff Only

View Item