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Purpose: To test an online training course for non-ophthalmic diabetic retinopathy (DR) graders for recognition of glaucomatous optic nerves in Vietnam., Methods: This was an uncontrolled, experimental, before-and-after study in which 43 non-ophthalmic DR graders underwent baseline testing on a standard image set, completed a self-paced, online training course and were retested using the same photographs presented randomly. Twenty-nine local ophthalmologists completed the same test without the training course. DR graders then underwent additional one-to-one training by a glaucoma specialist and were retested. Test performance (% correct, compared with consensus grades from four fellowship-trained glaucoma experts), sensitivity, specificity, positive and negative predictive value, and area under the receiver operating (AUC) curve, were computed., Results: Mean age of DR graders (32.6±5.5 years) did not differ from ophthalmologists (32.3±7.3 years, p=0.13). Online training required a mean of 297.9 (SD 144.6) minutes. Graders' mean baseline score (33.3%±14.3%) improved significantly after training (55.8%±12.6%, p<0.001), and post-training score did not differ from ophthalmologists (58.7±15.4%, p=0.384). Although grader sensitivity reduced before [85.5% (95% CI 83.5% to 87.3%)] versus after [80.4% (78.3% to 82.4%)] training, specificity improved significantly [47.8 (44.9 to 50.7) vs 79.8 (77.3 to 82.0), p<0.001]. Grader AUC also improved after training [66.6 (64.9 to 68.3)] to [80.1 (78.5 to 81.6), p<0.001]. Additional one-to-one grader training by a glaucoma specialist did not further improve grader scores., Conclusion: Non-ophthalmic DR graders can be trained to recognise glaucoma using a short online course in this setting, with no additional benefit from more expensive one-to-one training. After 5-hour online training in recognising glaucomatous optic nerve head, scores of non-ophthalmic DR graders doubled, and did not differ from local ophthalmologists. Intensive one-to-one training did not further improve performance., Competing Interests: Competing interests: Congdon serves as a paid consultant for Belkin Vision, a company selling devices for the treatment of glaucoma. Kahook has an equity interest in SpyGlass Pharma and receives royalties from New World Medical and Alcon. Olusola Olawoye is a Consortium for Advanced Research and Training in Africa (CARTA) Fellow., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Background: Artificial intelligence (AI) appears capable of detecting diabetic retinopathy (DR) with a high degree of accuracy in adults; however, there are few studies in children and young adults., Methods: Children and young adults (3-26 years) with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) were screened at the Dhaka BIRDEM-2 hospital, Bangladesh. All gradable fundus images were uploaded to Cybersight AI for interpretation. Two main outcomes were considered at a patient level: 1) Any DR, defined as mild non-proliferative diabetic retinopathy (NPDR or more severe; and 2) Referable DR, defined as moderate NPDR or more severe. Diagnostic test performance comparing Orbis International's Cybersight AI with the reference standard, a fully qualified optometrist certified in DR grading, was assessed using the Matthews correlation coefficient (MCC), area under the receiver operating characteristic curve (AUC-ROC), area under the precision-recall curve (AUC-PR), sensitivity, specificity, positive and negative predictive values., Results: Among 1274 participants (53.1% female, mean age 16.7 years), 19.4% (n = 247) had any DR according to AI. For referable DR, 2.35% (n = 30) were detected by AI. The sensitivity and specificity of AI for any DR were 75.5% (CI 69.7-81.3%) and 91.8% (CI 90.2-93.5%) respectively, and for referable DR, these values were 84.2% (CI 67.8-100%) and 98.9% (CI 98.3%-99.5%). The MCC, AUC-ROC and the AUC-PR for referable DR were 63.4, 91.2 and 76.2% respectively. AI was most successful in accurately classifying younger children with shorter duration of diabetes., Conclusions: Cybersight AI accurately detected any DR and referable DR among children and young adults, despite its algorithms having been trained on adults. The observed high specificity is particularly important to avoid over-referral in low-resource settings. AI may be an effective tool to reduce demands on scarce physician resources for the care of children with diabetes in low-resource settings., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Competing Interests: The authors declare that they have no conflicts of interest to disclose.

Competing Interests: J.P.C. Financial support from Genentech; Founder, Siloam Vision, LLC; R.V.P.C. Consultant, Alcon; Financial support, Genentech, Regeneron; Founder, Siloam Vision, LLC. The remaining authors declare that they have no conflicts of interest to disclose.

Purpose: To assess the prevalence of near and correctable distance visual impairment among screened participants in the garment industry and to explore associations with income, age, and urban versus rural residence., Methods: Vision screenings were conducted at 4 garment factories, 2 urban and 2 rural locations during September and October 2019. Distance vision impairment was the presence of uncorrected vision of <6/12 in either eye, correctable to ≥6/7.5 with distance refraction. Near vision impairment was defined as 1 or more of the following: 1) either eye with presenting near vision 6/12 in the same eye; 2) having been prescribed near add spectacle power in examination records; and/or 3) clinical diagnosis of presbyopia at the time of screening. Demographic information and monthly income were self-reported by questionnaire completion., Results: Among 915 participating workers (100% female, 18 to 70 years), 29.2% (n = 267) and 26.8% (n = 245) had correctable distance and near vision impairment respectively. Prevalence of near vision impairment was significantly higher among rural residents (34.2%, n = 160), compared to urban (19.0%, n = 85, P < 0.0001) with the largest differences in the 35 to 39 (68.2% vs 44.2%, P = 0.0019) and 40+ (85.9 vs 48.9%, P < 0.0001) year age ranges. Prevalence of near vision impairment was already high among urban (20.4%, n = 20) and rural (23.0%, n = 17) workers aged 30 to 34 years. In simple linear regression models, participants with near vision impairment earned $13.3 [standard error (SE) 2.44, P < 0.0001] less per month than those without, while urban residents earned $40.6 (SE 1.74, P < 0.0001) more than rural dwellers. In the final multivariate linear model, both near vision impairment ($6.51 lower monthly earnings, SE 1.84, P = 0.0004) and urban residence ($43.2 higher monthly earnings, SE 2.39, P < 0.0001) remained significantly associated with income., Conclusions: This study found high rates of near vision impairment among female garment workers, particularly rural dwellers, and at a younger age than expected. The high prevalence and association between near vision impairment and lower income suggest that focusing on industries with a high proportion of female workers, such as readymade garments, may be effective in addressing gender disparities in vision impairment and its economic impact., Competing Interests: The authors have no conflicts of interest to declare., (Copyright © 2022 Asia-Pacific Academy of Ophthalmology. Published by Wolters Kluwer Health, Inc. on behalf of the Asia-Pacific Academy of Ophthalmology.)

Background: There is a growing awareness that addressing chronic as well as acute health conditions may contribute importantly to the well-being of displaced populations, but eye care service has generally not been prioritized in crisis situations. We describe a replicable model of eye care provision as delivered by Orbis International and local partners to the Rohingya and host population in Cox's Bazar, Bangladesh, and characterize the burden of vision impairment and demand for sight-restoring services in this setting., Methods and Findings: Orbis International and local secondary facility Cox's Bazar Baitush Sharaf Hospital (CBBSH) provide eye care support to the Rohingya population and the host community of all ages in Cox's Bazar, Bangladesh, with fixed vision screening locations established in Camps 4 and 11 of the Kutupalong refugee settlement. Structured outreach targets these camps and four surrounding local subdistricts, with referrals made as needed for refraction (glasses measurement) and cataract surgery to CBBSH. Between February 2018 and March 2019, 48,105 displaced Rohingya (70.3%, among whom 71.6% were children and 46.5% women) and 20,357 local residents (29.7%, 88.5% children, 54.4% women) underwent vision screening. Displaced Rohingya sought services from a total of 12 surrounding camps, within which coverage was 17.3%, including 43.3% (27,027/62,424) of children aged 5-11 years and 60.0% (5,315/8,857) of adults ≥ 60 years old. The prevalence of blindness (presenting acuity < 3/60) among Rohingya patients exceeded that among local residents by 3- to 6-fold in each 10-year age group between 18 and 59 years (P < 0.001 comparing vision between the two groups in this age range), and the prevalence of cataract requiring surgery was also higher in Rohingya patients (18-29 years: 4.67% versus 1.80%, P = 0.0019; 30-39: 7.61% versus 2.39%, P < 0.001; and 40-49 years: 7.91% versus 3.77%, P = 0.0014). A limitation of the study is lack of data on population prevalence of eye disease., Conclusions: The burden of untreated eye disease is very high among the Rohingya, particularly those in their peak working years who could contribute most to the resiliency of their community. Demand for eye care service is also great among children and adults in this population with many competing healthcare priorities. Research is needed, building on strong evidence of benefit in settled populations, to explore the specific impact of vision care on the well-being of displaced populations., Competing Interests: The authors have declared that no competing interests exist.