METHODS: Patients with newly diagnosed AAC were identified prospectively over a 12-month period (November 2011 to October 2012) by active surveillance through the Scottish Ophthalmic Surveillance Unit reporting system. Data were collected at case identification and at 6 months follow-up.
RESULTS: There were 114 cases (108 patients) reported, giving an annual incidence of 2.2 cases (95% CI 1.8 to 2.6) or 2 patients (95% CI 1.7 to 2.4) per 1 00 000 in the whole population in Scotland. Precipitating factors were identified in 40% of cases. Almost one in five cases was associated with topical dilating drops. Best-corrected visual acuity (BCVA) at presentation ranged from 6/6 to perception of light. The mean presenting intraocular pressure (IOP) was 52 mm Hg (SD 11). Almost 30% cases had a delayed presentation of 3 or more days. At 6 months follow-up, 75% had BCVA of 6/12 or better and 30% were found to have glaucoma at follow-up. Delayed presentation (≥3 days) was associated with higher rate of glaucoma at follow-up (22.6% vs 60.8%, p<0.001), worse VA (0.34 vs 0.74 LogMAR, p<0.0001) and need for more topical medication (0.52 vs 1.2, p=0.003) to control IOP.
CONCLUSION: The incidence of AAC in Scotland is relatively low compared with the Far East countries, but in line with previous European data. Almost one in five cases were associated with pupil dilation for retinal examination.
METHODS: In this work, we present a bit-plane slicing (BPS) and local binary pattern (LBP) based novel approach for glaucoma diagnosis. Firstly, our approach separates the red (R), green (G), and blue (B) channels from the input color fundus image and splits the channels into bit planes. Secondly, we extract LBP based statistical features from each of the bit planes of the individual channels. Thirdly, these features from the individual channels are fed separately to three different support vector machines (SVMs) for classification. Finally, the decisions from the individual SVMs are fused at the decision level to classify the input fundus image into normal or glaucoma class.
RESULTS: Our experimental results suggest that the proposed approach is effective in discriminating normal and glaucoma cases with an accuracy of 99.30% using 10-fold cross validation.
CONCLUSIONS: The developed system is ready to be tested on large and diverse databases and can assist the ophthalmologists in their daily screening to confirm their diagnosis, thereby increasing accuracy of diagnosis.
METHODS: All diabetic patients were screened in Retinal Disease Awareness Programme (RDAP) and those who had significant DR changes were referred to the hospital for further management. Descriptive analyses were done to determine the prevalence of DR and sociodemographic characteristics among patients with diabetic. Univariate and multivariable analysis using Logistic regression were performed to find association and predictor factors in this screening.
RESULTS: A total of 3305 patients aged 40y and above were screened for DR. Of the patients screened, 9% patients were found to have DR and other visual complication such as maculopathy (0.9%), cataract (4.8%) and glaucoma (0.4%). The mean age of patients without retinopathy was 57.82±8.470y and the mean age of patients with DR was 63.93±9.857y. About 61.5% of the patients screened were aged below 60y and 38.5% were aged 60y and above. Majority of the patients screened were women 58.5% and Malay in the age group of 50-59y, while 27% were aged 60-69y. Significant association were found between age, sex, race, visual loss and DR.
CONCLUSION: Although the prevalence of DR among patients is not alarming, effective interventions need to be implemented soon to avert a large burden of visual loss from DR.