Impact of Vision Impairment and Ocular Morbidity and Their Treatment on Quality of Life in Children: A Systematic Review.

TOPIC: This review summarizes existing evidence of the impact of vision impairment and ocular morbidity and their treatment on children's quality of life (QoL). CLINICAL RELEVANCE: Myopia and strabismus are associated with reduced QoL among children. Surgical treatment of strabismus significantly improves affected children's QoL. METHODS: We conducted a systematic review and meta-analysis by screening articles in any language in 9 databases published from inception through August 22, 2022, addressing the impact of vision impairment, ocular morbidity, and their treatment on QoL in children. We reported pooled standardized mean differences (SMDs) using random-effects meta-analysis models. Quality appraisal was performed using Joanna Briggs Institute and National Institutes of Health tools. This study was registered with the International Prospective Register of Systematic Reviews (identifier, CRD42021233323). RESULTS: Our search identified 29 118 articles, 44 studies (0.15%) of which were included for analysis that included 32 318 participants from 14 countries between 2005 and 2022. Seventeen observational and 4 interventional studies concerned vision impairment, whereas 10 observational and 13 interventional studies described strabismus and other ocular morbidities. Twenty-one studies were included in the meta-analysis. The QoL scores did not differ between children with and without vision impairment (SMD, -1.04; 95% confidence interval [CI], -2.11 to 0.03; P = 0.06; 9 studies). Myopic children demonstrated significantly lower QoL scores than those with normal vision (SMD, -0.60; 95% CI, -1.09 to -0.11; P = 0.02; 7 studies). Children with strabismus showed a significantly lower QoL score compared with those without (SMD, -1.19; 95% CI, -1.66 to -0.73; P < 0.001; 7 studies). Strabismus surgery significantly improved QoL in children (SMD, 1.36; 95% CI, 0.48-2.23; P < 0.001; 7 studies). No randomized controlled trials (RCTs) concerning refractive error and QoL were identified. Among all included studies, 35 (79.5%) were scored as low to moderate quality; the remaining met all quality appraisal tools criteria. DISCUSSION: Reduced QoL was identified in children with myopia and strabismus. Surgical correction of strabismus improves the QoL of affected children, which supports insurance coverage of strabismus surgery. Further studies, especially RCTs, investigating the impact of correction of myopia on QoL are needed. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Impact of Vision Impairment and Ocular Morbidity and Their Treatment on Depression and Anxiety in Children: A Systematic Review.

TOPIC: This systematic review and meta-analysis summarizes existing evidence to establish whether vision impairment, ocular morbidity, and their treatment are associated with depression and anxiety in children. CLINICAL RELEVANCE: Understanding and quantifying these associations support early detection and management of mental health symptoms in children with vision impairment and ocular morbidity. Additionally, this review provides evidence in favor of insurance coverage for timely strabismus surgery. METHODS: We searched 9 electronic databases from inception through February 18, 2021, including observational and interventional studies assessing whether vision impairment, ocular morbidity, or both and their treatment are associated with depression, anxiety, or both in children. We used narrative synthesis and meta-analysis with the residual maximum likelihood method. A protocol was registered and published on The International Prospective Register of Systematic Reviews (identifier: CRD42021233323). RESULTS: Among 28 992 studies, 28 956 studies (99.9%) were excluded as duplicates or unrelated content. Among 36 remaining studies, 21 studies (58.3%) were observational studies concerning vision impairment, 8 studies (22.2%) were observational studies concerning strabismus, and 7 studies (19.4%) were interventional studies. Vision impaired children demonstrated significantly higher scores of depression (standard mean difference [SMD], 0.57; 95% confidence interval [CI], 0.26-0.89; 11 studies) and anxiety (SMD, 0.62; 95% CI, 0.40-0.83; 14 studies) than normally sighted children. In particular, children with myopia demonstrated higher scores of depression (SMD, 0.58; 95% CI, 0.36-0.81; 6 studies) than normally sighted children. Strabismus surgery significantly improved symptoms of depression (SMD, 0.59; 95% CI, 0.12-1.06; 3 studies) and anxiety (SMD, 0.69; 95% CI, 0.25-1.14; 4 studies) in children. CONCLUSION: Among children, vision impairment is associated with greater symptoms of depression and anxiety. Surgical treatment of strabismus improved these symptoms. Further randomized controlled trials exploring the impact of public health measures for myopia correction on mental health in children are needed. Scaling up access to strabismus surgery could improve the mental health of affected children.

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

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.

Feasibility and acceptance of artificial intelligence-based diabetic retinopathy screening in Rwanda.

BACKGROUND: Evidence on the practical application of artificial intelligence (AI)-based diabetic retinopathy (DR) screening is needed. METHODS: Consented participants were screened for DR using retinal imaging with AI interpretation from March 2021 to June 2021 at four diabetes clinics in Rwanda. Additionally, images were graded by a UK National Health System-certified retinal image grader. DR grades based on the International Classification of Diabetic Retinopathy with a grade of 2.0 or higher were considered referable. The AI system was designed to detect optic nerve and macular anomalies outside of DR. A vertical cup to disc ratio of 0.7 and higher and/or macular anomalies recognised at a cut-off of 60% and higher were also considered referable by AI. RESULTS: Among 827 participants (59.6% women (n=493)) screened by AI, 33.2% (n=275) were referred for follow-up. Satisfaction with AI screening was high (99.5%, n=823), and 63.7% of participants (n=527) preferred AI over human grading. Compared with human grading, the sensitivity of the AI for referable DR was 92% (95% CI 0.863%, 0.968%), with a specificity of 85% (95% CI 0.751%, 0.882%). Of the participants referred by AI: 88 (32.0%) were for DR only, 109 (39.6%) for DR and an anomaly, 65 (23.6%) for an anomaly only and 13 (4.73%) for other reasons. Adherence to referrals was highest for those referred for DR at 53.4%. CONCLUSION: DR screening using AI led to accurate referrals from diabetes clinics in Rwanda and high rates of participant satisfaction, suggesting AI screening for DR is practical and acceptable.

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.

Autonomous artificial intelligence increases real-world specialist clinic productivity in a cluster-randomized trial.

Autonomous artificial intelligence (AI) promises to increase healthcare productivity, but real-world evidence is lacking. We developed a clinic productivity model to generate testable hypotheses and study design for a preregistered cluster-randomized clinical trial, in which we tested the hypothesis that a previously validated US FDA-authorized AI for diabetic eye exams increases clinic productivity (number of completed care encounters per hour per specialist physician) among patients with diabetes. Here we report that 105 clinic days are cluster randomized to either intervention (using AI diagnosis; 51 days; 494 patients) or control (not using AI diagnosis; 54 days; 499 patients). The prespecified primary endpoint is met: AI leads to 40% higher productivity (1.59 encounters/hour, 95% confidence interval [CI]: 1.37-1.80) than control (1.14 encounters/hour, 95% CI: 1.02-1.25), p < 0.00; the secondary endpoint (productivity in all patients) is also met. Autonomous AI increases healthcare system productivity, which could potentially increase access and reduce health disparities. ClinicalTrials.gov NCT05182580.

Depression, anxiety, stress symptoms and their determinants among secondary students with vision impairment in rural Northwestern China during the COVID-19 pandemic.

Objective: The measures implemented to control the spread of Coronavirus disease 2019 (COVID-19) could affect children's mental and vision health. Youth particularly from minority and socioeconomically disadvantaged backgrounds were more likely to be impacted by these measures. This study aimed to examine the mental health of children with vision impairment and associated factors in North-western China during the COVID-19 pandemic. Methods: A cross-sectional study was conducted among 2,036 secondary school children living in Ningxia Hui Autonomous Region. Participants completed a survey on sociodemographic and lifestyle information and answered the Chinese version of the 21-item Depression Anxiety Stress Scales (DASS-21) questionnaire. Presenting visual acuity was measured by a trained enumerator. Multivariate logistic regression analysis was used to identify potential risk factors for mental health problems. Results: Responses from 1,992 (97.8%) children were included in the analysis after excluding those with incomplete mental health outcome data. The prevalence of depression, anxiety and stress symptoms within the dataset were 28.9, 46.4, and 22.3%, respectively. The distribution of children with different stress levels differed significantly between those with and without vision impairment (p = 0.03). Multivariable logistic regression analyses revealed that depression symptoms decreased with higher parental education (OR, 0.76, 95% confidence intervals (CI):0.63-0.96), longer sleep duration (OR, 0.90, 95% CI: 0.81-0.97) and longer study time (OR, 0.82, 95% CI: 0.74-0.91), whereas they increased with higher recreational screen time (OR, 1.19, 95% CI: 1.08-1.32). Anxiety symptoms decreased with higher parental education (OR, 0.80, 95% CI: 0.66-0.96) and increased with higher recreational screen time (OR, 1.15, 95% CI: 1.04-1.27) and being a left-behind child (OR, 1.26, 95% CI: 1.04-1.54). In addition, stress symptoms decreased with longer sleep duration (OR, 0.92, 95%CI: 0.85-0.99) and increased with higher number of siblings (OR, 1.10, 95% CI: 1.01-1.19), higher recreational screen time (OR, 1.15, 95% CI: 1.04-1.28) and older age (OR,1.12, 95% CI: 1.004-1.24). Conclusion: A considerable proportion of our sample experienced mental health problems during the pandemic. Healthcare planners in China should consider interventions such as reducing recreational screen time, ensuring sufficient sleep, and timely detection of mental health symptoms among socioeconomically disadvantaged groups.

Vision Impairment and Productivity Among Female Garment Workers in Bangladesh: A Cohort Study.

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.

Visual Impairment and Risk of Self-Reported Road Traffic Crashes Among Bus Drivers in Bangladesh.

PURPOSE: This study assesses the prevalence and the causes of visual impairment among bus drivers undergoing screening in Bangladesh and associations with self-reported crashes. METHODS: Eye health screenings including refraction and questionnaires were conducted at 10 bus terminals in 7 districts of Bangladesh from June through August 2019. Presenting near and distance visual impairment and self-reported road traffic crashes were recorded. RESULTS: Among 700 participants, nearly 1 in 5 (n = 126, 18.0%) had presented visual acuity (VA) in the better-seeing eye ≤6/9, not meeting the vision standard of Bangladesh for bus drivers. A majority of drivers (n = 492, 70.3%) had near or distance refractive error, and most who failed to reach the driving standard (88.1%, n = 111) could be improved with readily available treatment, either glasses or cataract surgery. A history of 1 or more road traffic crashes while driving a bus or minibus was reported by 62 (8.97%) participants. In multivariable models, factors significantly associated with near or distance visual impairment included older age [odds ratio (OR) per year 1.15, 95% confidence interval (CI): 1.12-1.18, P < 0.0001] and having no driver's license (OR 1.80, 95% CI: 1.04-3.13, P = 0.037). Self-reported history of a motor vehicle crash was associated with near or distance visual impairment (OR 2.45, 95% CI: 1.09-5.49, P = 0.030), even when adjusting for other factors such as age and weekly miles are driven. CONCLUSIONS: Ensuring that bus drivers are screened to meet the required visual standards for driving while referring those who do not for treatment, can contribute to safer roads in this high-risk setting.

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.