Classification Criteria for Intermediate Uveitis, Non-Pars Planitis Type

Douglas A Jabs, Alastair K Denniston, Andrew D Dick, James P Dunn, Michal Kramer, Neal Oden, Annabelle A Okada, Alan G Palestine, Russell W Read, Jennifer E Thorne, Brett E Trusko, Steven Yeh

Research output: Contribution to journalArticle (Academic Journal)peer-review

17 Citations (Scopus)


PURPOSE: To determine classification criteria for intermediate uveitis, non-pars planitis type (IU- NPP, also known as undifferentiated intermediate uveitis) DESIGN: : Machine learning of cases with IU-NPP and 4 other intermediate uveitides.

METHODS: Cases of intermediate 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 intermediate uveitides. The resulting criteria were evaluated on the validation set.

RESULTS: Five hundred eighty-nine of cases of intermediate uveitides, including 114 cases of IU-NPP, were evaluated by machine learning. The overall accuracy for intermediate uveitides was 99.8% in the training set and 99.3% in the validation set (95% confidence interval 96.1, 99.9). Key criteria for IU-NPP included unilateral or bilateral intermediate uveitis with neither 1) snowballs in the vitreous nor 2) snowbanks on the pars plana. Other key exclusions included: 1) multiple sclerosis, 2) sarcoidosis, and 3) syphilis. The misclassification rates for pars planitis were 0 % in the training set and 0% in the validation set, respectively.

CONCLUSIONS: The criteria for IU-NPP had a low misclassification rate and appeared to perform well enough for use in clinical and translational research.

Original languageEnglish
Pages (from-to)159-164
Number of pages6
JournalAmerican Journal of Ophthalmology
Early online date8 Apr 2021
Publication statusPublished - Aug 2021

Bibliographical note

Funding Information:
Funding/Support: Supported by grant R01 EY026593 from the National Eye Institute, National Institutes of Health, Bethesda, Maryland, USA; the David Brown Fund, New York, New York, USA; the Jillian M. and Lawrence A. Neubauer Foundation, New York, New York, USA; and the New York Eye and Ear Foundation, New York, New York, USA.

Publisher Copyright:
© 2021 Elsevier Inc.


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