Background: The concordance of microalbuminuria and diabetic retinopathy (DR) has been well reported in persons with type 1 diabetes; however, for type 2 diabetes, there is paucity of data especially from population-based studies. The aim of this study was to estimate the prevalence of albuminuria (micro - and macroalbuminuria) among persons with type 2 diabetes and determine its role as a risk factor for presence and severity of DR. Methods: A population-based cross sectional study was conducted in cohort of 1414 subjects with type 2 diabetes from Chennai metropolis. All the subjects underwent comprehensive eye examination including 45 degrees four-field stereoscopic digital photography. DR was clinically graded using Early Treatment Diabetic Retinopathy Study scales. A morning urine sample was tested for albuminuria. Subjects were considered to have microalbuminuria, if the urinary albumin excretion was between 30 and 300 mg/24 hours, and macroalbuminuria at more than 300 mg/24 hours. The statistical software used was SPSS for Windows, Chicago, IL. Student t-test for comparing continuous variables, and χ ² test, to compare proportions amongst groups were used. Results: The prevalence of microalbuminuria in the study subjects was 15.9% (226/1414), and that of macroalbuminuria, 2.7% (38/1414). Individuals with macroalbuminuria in comparison to micro- or normoalbuminuria showed a greater prevalence of DR (60.5% vs. 31.0% vs. 14.1%, p < 0.001), and also a greater severity of the disease (60.9% vs. 21.4 vs. 9.9, p < 0.001). Conclusions: Every 6^th individual in the population of type 2 diabetes is likely to have albuminuria. Subjects with microalbuminuria were around 2 times as likely to have DR as those without microalbuminuria, and this risk became almost 6 times in the presence of macroalbuminuria.

RRH: Rural and Remote Health. Published article number: 4304 - Knowledge, attitude and practices on diabetes, hypertension and diabetic retinopathy and the factors that motivate screening for diabetes and diabetic retinopathy in a pyramidal model of eye health care

Purpose: The aim of this study was to analyze the cost and factors affecting diabetic retinopathy (DR) care in a tertiary eye care facility in South India. Methods: In a retrospective, observational study, we evaluated the costs incurred in DR management in each stage of retinopathy from electronic medical records. Both medical and indirect costs (transportation and boarding) were calculated. Results: The study evaluated 1000 consecutive patients (2000 eyes) with DR, from January to June 2019. One-third (32%; n = 321) patients were females. The median cost per patient was INR 8,214 (IQR 2,812-29,748). Cost of care was higher in patients with sight-threatening DR (STDR) compared to non-STDR (INR 31,820 vs INR 14,356, P < 0.001). Among 57.3% (n = 573;1137 eyes) of subjects who completed treatment, there was a statistically significant reduction in visual impairment (427 to 355 eyes) and blindness (<3/60) (132 to 103 eyes) from baseline (P < 0.001). The number of follow-up visits had a negative association with travel distance and socioeconomic status (P < 0.001); the positive association was seen with DR severity (P = 0.002) and total cost (P < 0.001) on regression analysis. There was a nearly 3-fold difference in the average medical cost per eye for subjects with severe visual loss (<3/60) (INR 26,270) compared to those with good vision (≥6/12) (INR 8,510). Conclusion: Treatment of DR benefits, but the cost of care increases with disease severity and visual impairment. Compliance to care was related to DR severity and treatment cost. Some of the barriers could be reduced with greater advocacy and reduced travel distance.

Purpose: The objective of this study was to identify and validate smartphone-based visual acuity (VA) apps that can be used in a teleophthalmology portal. Methods: The study was conducted in three phases: A survey to investigate if the SmartOptometry App was easy to download, understand and test (phase I), an in-clinic comparison of VA measured in a random testing order with four tools namely COMPlog, Reduced Snellen near vision, Peek Acuity (Distance VA) and SmartOptometry (Near VA) (phase II) and a repeatability study on these 4 tools by measuring VA again (phase III). The study recruited the employees of our institute and adhered to the strict COVID-19 protocols of testing. Results: Phase I Survey (n = 40) showed 90% of participants used android phones, 60% reported that instructions were clear, and all users were able to self-assess their near VA with SmartOptometry App. Phase II (n = 68) revealed that Peek Acuity was comparable to COMPlog VA (P = 0.31), however SmartOptometry was statistically significantly different (within 2 log MAR lines) from Reduced Snellen near vision test, particularly for young (n = 44, P = 0.004) and emmetropic (n = 16, P = 0.04) participants. All the 4 tests were found to be repeatable in phase III (n = 10) with a coefficient of repeatability ≤0.14. Conclusion: Smartphone-based apps were easy to download and can be used for checking patient's distance and near visual acuity. An effect of age and refractive error should be considered when interpreting the results. Further studies with real-time patients are required to identify potential benefits and challenges to solve.

The burden of diabetes mellitus (DM) and diabetic retinopathy (DR) is at alarming proportions in India and around the globe. The number of people with DM in India is estimated to increase to over 134 million by 2045. Screening and early identification of sight-threatening DR are proven ways of reducing DR-related blindness. An ideal DR screening model should include personalized awareness, targeted screening, integrated follow-up reminders, and capacity building. The DR screening technology is slowly shifting from direct examination by an ophthalmologist to remote screening using retinal photographs, including telescreening and automated grading of retinal images using artificial intelligence. The ophthalmologist-to-patient ratio is poor in India, and there is an urban–rural divide. The possibility of screening all people with diabetes by ophthalmologists alone is a remote possibility. It is prudent to use the available nonophthalmologist workforce for DR screening in tandem with the technological advances. Capacity-building efforts are based on the principle of task sharing, which allows for the training of a variety of nonophthalmologists in DR screening techniques and technology. The nonophthalmologist human resources for health include physicians, optometrists, allied ophthalmic personnel, nurses, and pharmacists, among others. A concurrent augmentation of health infrastructure, conducive health policy, improved advocacy, and increased people’s participation are necessary requirements for successful DR screening. This perspective looks at the characteristics of various nonophthalmologist DR screening models and their applicability in addressing DR-related blindness in India.