individuals with glaucoma, with 1-to-1 matching of patients (those with inconsistent follow-up) and controls (those with consistent follow-up). Data were collected via oral questionnaire. Survey results were correlated with attendance at follow-up examinations, using the t test, 2 test, and multivariate stepwise logistic regression analysis to calculate the odds ratios (ORs) and 95% confidence intervals. Results: After adjusting for covariates in the logistic regression analysis, factors independently associated with inconsistent follow-up included black race (adjusted OR, 7.16; 95% confidence interval, 1.64-31.24), Latino eth-nicity (adjusted OR, 4.77; 1.12-20.29), unfamiliarity with necessary treatment duration (adjusted OR, 3.54; 1.26-9.94), lack of knowledge of the permanency of glaucomainduced vision loss (adjusted OR, 3.09; 1.18-8.04), and perception that it is not important to attend all follow-up visits (adjusted OR, 3.54; 1.26-9.94). Conclusions: Demographic factors, including race and ethnicity, may directly or indirectly affect adherence to recommended glaucoma follow-up visits. Lack of information regarding irreversible vision loss from glaucoma, need for lifelong treatment, and lack of visual symptoms may be significant barriers to follow-up in this population. Targeted glaucoma education by physicians may improve follow-up, thereby decreasing the morbidity associated with glaucomatous disease.
The SUNDROP telemedicine screening initiative for ROP has proven to have a high degree of sensitivity and specificity for identification of referral warranted disease. These results indicate that telemedicine may improve accessibility of ROP screening.
PurposeTo compare grading of goniophotographic images and gonioscopy in assessing the iridocorneal angle.MethodsIn a population-based, cross-sectional study, participants underwent gonioscopy and goniophotographic imaging during the same visit. The iridocorneal angle was classified as closed if the posterior trabecular meshwork could not be seen. A single masked observer graded the goniophotographic images, and each eye was classified as having angle closure based on the number of closed quadrants. Agreement between the methods was analyzed by calculating kappa (κ) and first-order agreement coefficient (AC1) statistics and comparison of area under receiver operating characteristic curves (AUC).ResultsA total of 4149 Chinese Americans (3994 eyes) were included in this study. The agreement for angle closure diagnosis between gonioscopy and EyeCam was moderate to excellent (κ = 0.60, AC1 0.90, AUC 0.76–0.80).ConclusionsDetection of iridocorneal angle closure based on goniophotographic imaging shows moderate to very good agreement with angle closure assessment using gonioscopy.
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