Classification Criteria for Birdshot Chorioretinitis
| Autor: | Russell W. Read, Jennifer E. Thorne, Antoine P. Brézin, Neal Oden, Douglas A. Jabs, Albert T. Vitale, Alan G. Palestine, Brett Trusko, Peter McCluskey, Ralph D. Levinson, Susan E Wittenberg |
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| Rok vydání: | 2021 |
| Předmět: |
Male
medicine.medical_specialty Consensus Training set Choroid Fundus Oculi business.industry Indocyanine green angiography Birdshot Chorioretinopathy Birdshot chorioretinitis Middle Aged Retina Article Confidence interval Multifocal choroiditis Machine Learning Ophthalmology medicine Humans Female Fluorescein Angiography business |
| Zdroj: | Am J Ophthalmol |
| ISSN: | 0002-9394 |
| DOI: | 10.1016/j.ajo.2021.03.059 |
| Popis: | Purpose To determine classification criteria for birdshot chorioretinitis. Design Machine learning of cases with birdshot chorioretinitis and 8 other posterior uveitides. Methods Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on 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 infectious posterior/panuveitides. The resulting criteria were evaluated on the validation set. Results One thousand sixty-eight cases of posterior uveitides, including 207 cases of birdshot chorioretinitis, were evaluated by machine learning. Key criteria for birdshot chorioretinitis included a multifocal choroiditis with: 1) the characteristic appearance a bilateral multifocal choroiditis with cream-colored or yellow-orange, oval or round choroidal spots ("birdshot" spots); 2) absent to mild anterior chamber inflammation; and 3) absent to moderate vitreous inflammation; or multifocal choroiditis with positive HLA-A29 testing and either: 1) classic "birdshot spots" or 2) characteristic imaging on indocyanine green angiography. Overall accuracy for posterior uveitides was 93.9% in the training set and 98.0% (95% confidence interval 94.3, 99.3) in the validation set. The misclassification rates for birdshot chorioretinitis were 10% in the training set and 0% in the validation set. Conclusions The criteria for birdshot chorioretinitis had a low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research. |
| Databáze: | OpenAIRE |
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