Effect of providing near glasses on productivity among rural Indian tea workers with presbyopia (PROSPER) a randomised trial

BACKGROUND: Presbyopia, age-related decline in near vision, is the most common cause of vision impairment globally, but no trials have assessed its workplace effects. We aimed to study the effect of near glasses on the productivity of tea workers with presbyopia.METHODS: This randomised trial was done in tea pickers aged 40 years or older in Assam, India, with unaided near visual acuity (NVA) lower than 6/12 in both eyes, correctable to 6/7·5 with near glasses; unaided distance vision 6/7·5 or greater; and no eye disease. Participants were randomly assigned (1:1) to receive free glasses optimising NVA at working distance (cost including delivery US$10·20 per person), either immediately (intervention group) or at closeout (control group). Participants were stratified by age, sex, and productivity. The primary outcome (investigator-masked) was the difference between groups in the change in mean daily weight of tea picked (productivity), between the 4-week baseline period (June, 2017) and the 11-week evaluation period (July 24, 2017, to Oct 7, 2017). Workers' income was tied to their productivity. Compliance with study glasses was assessed at seven unannounced visits. Results were analysed on an intention-to-treat basis. This trial is registered with ClinicalTrials.gov, number NCT03228199.FINDINGS: Between July 3, 2017, and July 15, 2017, 1297 (48·1%) of 2699 permanent workers met the age criteria and consented for eye examinations. 751 (57·9%) fulfilled vision criteria and were randomly assigned to the intervention (n=376) or control (n=375) groups. Groups did not differ substantially in baseline characteristics. No participants owned glasses at baseline, 707 (94·1%) received the allocated intervention, and all were followed up and analysed. Between the baseline and evaluation periods, mean productivity in the intervention group increased from 25·0 kg per day to 34·8 kg per day (an increase of 9·84 kg per day), a significantly higher increase than in the control group (from 26·0 kg per day to 30·6 kg per day; an increase of 4·59 kg per day), corresponding to a between-group difference of 5·25 kg per day (95% CI 4·50-5·99; 21·7% relative productivity increase; effect size 1·01 [95% CI 0·86-1·16]; p&lt;0·0001). Intervention-group compliance with study glasses reached 84·5% by closeout. Regression model predictors of greater productivity increase included intervention group membership (5·25 kg per day [95% CI 4·60-5·91], p&lt;0·0001) and, among intervention participants, older age (p=0·039) and better compliance with the intervention (p&lt;0·0001).INTERPRETATION: A substantial productivity increase was achieved in this rural cohort by providing glasses to correct presbyopia, with little cost and high intervention uptake.FUNDING: Clearly.</p

Burden of eye disease and demand for care in the Bangladesh Rohingya displaced population and host community: A cohort study.

BackgroundThere 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 findingsOrbis 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 ConclusionsThe 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

Impact of artificial intelligence assessment of diabetic retinopathy on referral service uptake in a low resource setting: The RAIDERS randomized trial

PURPOSE: This trial was designed to determine if artificial intelligence (AI)-supported diabetic retinopathy (DR) screening improved referral uptake in Rwanda. DESIGN: The Rwanda Artificial Intelligence for Diabetic Retinopathy Screening (RAIDERS) study was an investigator-masked, parallel-group randomized controlled trial. PARTICIPANTS: Patients ≥ 18 years of age with known diabetes who required referral for DR based on AI interpretation. METHODS: The RAIDERS study screened for DR using retinal imaging with AI interpretation implemented at 4 facilities from March 2021 through July 2021. Eligible participants were assigned randomly (1:1) to immediate feedback of AI grading (intervention) or communication of referral advice after human grading was completed 3 to 5 days after the initial screening (control). MAIN OUTCOME MEASURES: Difference between study groups in the rate of presentation for referral services within 30 days of being informed of the need for a referral visit. RESULTS: Of the 823 clinic patients who met inclusion criteria, 275 participants (33.4%) showed positive findings for referable DR based on AI screening and were randomized for inclusion in the trial. Study participants (mean age, 50.7 years; 58.2% women) were randomized to the intervention (n = 136 [49.5%]) or control (n = 139 [50.5%]) groups. No significant intergroup differences were found at baseline, and main outcome data were available for analyses for 100% of participants. Referral adherence was statistically significantly higher in the intervention group (70/136 [51.5%]) versus the control group (55/139 [39.6%]; P = 0.048), a 30.1% increase. Older age (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.02–1.05; P < 0.0001), male sex (OR, 2.07; 95% CI, 1.22–3.51; P = 0.007), rural residence (OR, 1.79; 95% CI, 1.07–3.01; P = 0.027), and intervention group (OR, 1.74; 95% CI, 1.05–2.88; P = 0.031) were statistically significantly associated with acceptance of referral in multivariate analyses. CONCLUSIONS: Immediate feedback on referral status based on AI-supported screening was associated with statistically significantly higher referral adherence compared with delayed communications of results from human graders. These results provide evidence for an important benefit of AI screening in promoting adherence to prescribed treatment for diabetic eye care in sub-Saharan Africa

CHILDSTAR: CHIldren Living With Diabetes See and Thrive with AI Review

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