Objective. To describe the patterns of clinical presentation in a series of 407 patients with uveitis and to establish the relationship between these patterns and the final diagnosis. Methods. Patients were referred to the Uveitis Clinic of a tertiary hospital from January 1992 to January 1996. All patients received a complete ophthalmologic examination, and a general clinical history was obtained. The current International Uveitis Study Group classification system was used for anatomic classification. To establish the final diagnosis of the most common entities causing uveitis, current diagnostic criteria were used. A discriminant analysis, with diagnostic grouping as the outcome variable and the clinical presentation features as discriminating variables, was performed. Results. With our classification system, 66.5% of the cases could be correctly classified according to the clinical pattern and morphologic findings. By diagnostic groups, discriminant analysis showed that 75% of patients with Behçet's disease, 77.1% of those with spondylarthropathy (including inflammatory bowel disease), 33.3% of those with sarcoidosis, 97.9% of those with toxoplasmosis, 85.7% of those with Vogt‐Koyanagi‐Harada syndrome, 100% of those with herpes, and 50.4% of those with idiopathic uveitis were correctly classified. In the miscellaneous group, which included disease entities with fewer than 5 cases, 42.9% were correctly classified. Conclusion. Rheumatologic evaluation of the patient with uveitis can be more cost‐effective if the referring ophthalmologist follows the classification system described herein, allowing a tailored approach in which only specific and necessary diagnostic tests are used.

Purpose: To establish a retinal blood flow database in normal human eyes using the Canon Laser Blood Flowmeter (CLBF). Method: Fourteen healthy subjects (7 males, 7 females) between the ages of 24 and 33 underwent birectional laser Doppler velocimetry (BLDV) in one eye using the CLBF. Measurements consisting of blood vessel diameter (D) in micrometers, velocity (V) in millimeters per second, and flow (F) in microliters per minute were recorded at sites along the major retinal veins. Four to six veins were measured in each eye. Total volumetric blood flow was calculated as the sum of the venous flow rates in the major veins. Results: Total retinal blood flow could be reliably determined on 5 of the subjects (1 male, 4 females). Venous blood vessel diameter ranged from 84 to 177 µm. The correlations between D and F, as well as D and V were found to be significant. Specifically, the correlation coefficient between D and F was 0.885 (p ≤ 0.001), while the log-log regression coefficient was 3.35 ± 0.23 (p ≤ 0.001). The correlation coefficient between D and V was 0.694 (p ≤ 0.001), while the log-log regression coefficient was 1.43 ± 0.27 (p ≤ 0.001). Total venous blood flow showed a mean of 64.9 ± (SD) 12.8 µl/min (range: 50.9–80.6 µl/min). Venous blood flow averaged 44.1 ± 4.5 µl/min temporally and 20.8 ± 9.2 µl/min nasally, showing a temporal retinal blood flow approximately twice that of the nasal retina (p < 0.001). On the other hand, venous blood flow averaged 30.6 ± 9.8 µl/min superiorly and 34.3 ± 8.0 µl/min inferiorly. These values showed no statistical difference. Conclusion: The average total retinal blood flow in 5 healthy subjects using the CLBF was 64.9 ± 12.8 µl/min. Venous blood flow at the temporal retina was about twice that of the nasal retina, whereas flow at the superior and inferior retina showed no statistical difference. Our findings are comparable with studies done using a different BLDV system.

AS-OCT is indicated for imaging the conjunctiva, sclera, cornea, and iris, screening the angle, and visualizing subconjunctival, corneal, and anterior chamber implants. Coronal imaging, unique to AC Cornea OCT (Ophthalmic Technologies Inc., Toronto, Ontario, Canada), graphically defines structures viewed on cross-sectional OCT. Ultrasound biomicroscopy is indicated for imaging the conjunctiva, sclera, iris, lens, and ciliary body, for tumor measurements, for light-and-dark tests in glaucoma, and for viewing subconjunctival, anterior chamber, posterior chamber, and pars plana implants.

Cross-sectional AS-OCT adequately imaged the components of the assembled KPro in vivo, as well as its interaction with surrounding anterior-segment structures. It allowed visualization of the anterior chamber, iris, and angle, essential in the postoperative care of these patients. Coronal AS-OCT showed graphic en face images of the KPro device and suspected retrokeratoprosthetic membranes. UBM, on the other hand, adequately imaged glaucoma tube shunts and PCIOL haptics beneath the iris plane.

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