Classification Criteria for Multiple Sclerosis-Associated Intermediate Uveitis.

PURPOSE: The purpose of this study was to determine classification criteria for multiple sclerosis-associated intermediate uveitis. DESIGN: Machine learning of cases with multiple sclerosis-associated intermediate uveitis 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 in the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the intermediate uveitides. The resulting criteria were evaluated in the validation set. RESULTS: A total of 589 cases of intermediate uveitides, including 112 cases of multiple sclerosis-associated intermediate uveitis, 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 multiple sclerosis-associated intermediate uveitis included unilateral or bilateral intermediate uveitis and multiple sclerosis diagnosed by the McDonald criteria. Key exclusions included syphilis and sarcoidosis. The misclassification rates for multiple sclerosis-associated intermediate uveitis were 0 % in the training set and 0% in the validation set. CONCLUSIONS: The criteria for multiple sclerosis-associated intermediate uveitis had a low misclassification rate and appeared to perform sufficiently well enough for use in clinical and translational research.

Classification Criteria for Intermediate Uveitis, Non-Pars Planitis Type.

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 snowballs in the vitreous humor nor snowbanks on the pars plana. Other key exclusions included multiple sclerosis, sarcoidosis, and syphilis. The misclassification rates for IU-NPP were 0% in the training set and 0% in the validation set. CONCLUSIONS: The criteria for IU-NPP had a low misclassification rate and seemed to perform well enough for use in clinical and translational research.

Scale for photographic grading of vitreous haze in uveitis.

PURPOSE: To validate a scale for grading vitreous haze in uveitis using digitized photographs and standardized scoring. DESIGN: Evaluation of clinical research methodology. METHODS: Calibrated Bangerter diffusion filters inducing incremental decrements of spatial contrast were placed in front of the camera lens while photographing a normal eye to simulate vitreous haze. The photographs were digitized and an ordinal scale was created from 0 (none) to 8 (highest level of opacification at which fundus details could be seen). The scale steps correspond approximately to decimal Snellen visual acuities of 1.0, 0.8, 0.4, 0.2, 0.1, 0.04, 0.02, 0.01, and 0.002, with approximately 0.3 log step between each step. For validation, digitized fundus photographs of uveitis patients were displayed on a computer monitor for comparison with the standard photos. Three observers graded the test set twice under standard conditions. Interobserver and intraobserver variability and κ values for agreement greater than chance were calculated. RESULTS: Variance component analysis determined that 87.7% of the variance in grades was attributable to the test item rather than to grader or session. The intraclass correlation between graders and grading sessions varied from 0.84 to 0.91. Simple agreement within 1 grade between graders and sessions occurred in 90 ± 5.5% of gradings. κ values averaged 0.91, which is considered near perfect. CONCLUSIONS: A 9-step photographic scale was designed to standardize the grading of vitreous haze in uveitis patients using fundus photographs. The scale is potentially adaptable to clinical trials in uveitis.

Anterior and intermediate uveitis cases referred to a tertiary centre in Alberta.

BACKGROUND: We investigated the characteristics and causes of various uveitis subtypes in patients presenting to the Regional Eye Centre at the Royal Alexandra Hospital, University of Alberta, Edmonton, Alta., and estimated the incidence of anterior uveitis in northern Alberta. METHODS: A retrospective study was conducted of all patients presenting with uveitis to a single, full-time ophthalmologist at the Regional Eye Centre from September 2004 to June 2005. Uveitis was classified according to onset, severity, anatomical subtype, etiology, recurrence rate, and response to treatment. Statistical analysis was used to compare patients referred by ophthalmologists with those referred by non-ophthalmologists. RESULTS: Two hundred and nine eyes of 171 patients were included in the study. Ophthalmologist referrals consisted of 67.4% anterior, 14.0% intermediate, and 18.6% panuveitis, and non-ophthalmological referrals were 92.8% anterior, 5.4% intermediate, and 1.8% panuveitis. Referrals from ophthalmologists were significantly more likely to be chronic, recurrent, and (or) less responsive to treatment than referrals from other sources. INTERPRETATION: Referral bias strongly affects the proportions of uveitis subtypes seen. Human leukocyte antigen-B27-associated diseases (especially ankylosing spondylitis), sarcoidosis, and herpes infections should be considered among the most likely causes of uveitis to be diagnosed in this patient population.

[Uveitis intermedia in childhood]. / Uveitis intermedia im Kindesalter.

Round 10-12% of all children who present with signs of uveitis suffer from intermediate uveitis. Compared to uveitis anterior in children, the association of intermediate uveitis to a systemic disease is much more complicated. Most cases of uveitis intermedia are idiopathic and show the signs of a pars planitis. Post-infectious and immunological causes are difficult to detect. In cases of uveitis in children, it is necessary to know the specific symptoms of possible underlying systemic diseases. On this basis, an adequate and specific diagnosis will most probably be successful. This paper presents the different causes of uveitis intermedia in childhood and compares the incidence of the disease in comparison with adults as far as this is mentioned in the literature.