Schools are an important avenue to tackle the rising prevalence of uncorrected refractive error among children. School-based vision programs are an innovative approach of vision care delivery in the urban school setting in the United States. These programs are effective in improving vision outcomes and advancing health equity, especially among the disadvantaged school districts. While most school-based vision programs provide vision screening, eye examinations, and eyeglasses prescription to students directly in schools, different mechanisms and models have been reported. In this paper, we describe two large-scale school-based vision programs, Vision for Baltimore and Helen Keller International’s United States Vision Program, representing national and regional efforts to partner with local communities in improving access to pediatric vision care. These programs also serve as data collection platforms and provide evidence to inform public health policy and guide best practice. Collectively, these two programs showed that one in three students failed vision screening. The prevalence of uncorrected refractive error was high and the demand for eyeglasses was great among those who failed vision screening. While most of the students’ uncorrected refractive errors could be addressed in the school setting, one in seven needed additional eye care. We found that schools with more socioeconomically disadvantaged students had greater needs of school-based vision program services. We hope this knowledge helps to maximize the impact of school-based vision programs and promote a system that ensures better health outcomes for all children.

Schools are an important avenue to tackle the rising prevalence of uncorrected refractive error among children. School-based vision programs are an innovative approach of vision care delivery in the urban school setting in the United States. These programs are effective in improving vision outcomes and advancing health equity, especially among the disadvantaged school districts. While most school-based vision programs provide vision screening, eye examinations, and eyeglasses prescription to students directly in schools, different mechanisms and models have been reported. In this paper, we describe two large-scale school-based vision programs, Vision for Baltimore and Helen Keller International’s United States Vision Program, representing national and regional efforts to partner with local communities in improving access to pediatric vision care. These programs also serve as data collection platforms and provide evidence to inform public health policy and guide best practice. Collectively, these two programs showed that one in three students failed vision screening. The prevalence of uncorrected refractive error was high and the demand for eyeglasses was great among those who failed vision screening. While most of the students’ uncorrected refractive errors could be addressed in the school setting, one in seven needed additional eye care. We found that schools with more socioeconomically disadvantaged students had greater needs of school-based vision program services. We hope this knowledge helps to maximize the impact of school-based vision programs and promote a system that ensures better health outcomes for all children.

Achieving universal eye health remains a global challenge, particularly in low- and middle-income countries where visual impairment and blindness are prevalent. While advances in tertiary eye care have improved outcomes, access to primary eye care (PEC) continues to be inadequate in rural and underserved regions. This gap necessitates innovative, scalable models that provide accessible, affordable, and comprehensive eye care.

The Vision Centre (VC) model, pioneered by the Aravind Eye Care System (AECS), exemplifies a sustainable approach to delivering PEC. Designed as permanent facilities in rural communities, VCs are equipped with state-of-the-art diagnostic tools and staffed by trained allied ophthalmic personnel. The integration of teleophthalmology, electronic medical records, and artificial intelligence enhances the model’s capacity to address complex conditions like diabetic retinopathy and glaucoma.

VCs have demonstrated significant impact in improving accessibility, reducing financial burdens, and increasing utilization of eye care services. In the fiscal year 2023–24, AECS VCs recorded nearly one million outpatient visits, achieving a 25% population coverage rate and generating substantial cost savings of ₹647 million (US$7.8 million) for patients. The model's success is underpinned by community engagement, a focus on operational excellence, and a robust referral system to tertiary hospitals.

This review explores the evolution, implementation, and impact of the AECS VC model, emphasizing its alignment with the Sustainable Development Goals and Universal Health Coverage. By addressing accessibility and affordability, the VC model serves as a scalable template for primary eye care delivery in resource-limited settings globally.

Achieving universal eye health remains a global challenge, particularly in low- and middle-income countries where visual impairment and blindness are prevalent. While advances in tertiary eye care have improved outcomes, access to primary eye care (PEC) continues to be inadequate in rural and underserved regions. This gap necessitates innovative, scalable models that provide accessible, affordable, and comprehensive eye care.

The Vision Centre (VC) model, pioneered by the Aravind Eye Care System (AECS), exemplifies a sustainable approach to delivering PEC. Designed as permanent facilities in rural communities, VCs are equipped with state-of-the-art diagnostic tools and staffed by trained allied ophthalmic personnel. The integration of teleophthalmology, electronic medical records, and artificial intelligence enhances the model’s capacity to address complex conditions like diabetic retinopathy and glaucoma.

VCs have demonstrated significant impact in improving accessibility, reducing financial burdens, and increasing utilization of eye care services. In the fiscal year 2023–24, AECS VCs recorded nearly one million outpatient visits, achieving a 25% population coverage rate and generating substantial cost savings of ₹647 million (US$7.8 million) for patients. The model's success is underpinned by community engagement, a focus on operational excellence, and a robust referral system to tertiary hospitals.

This review explores the evolution, implementation, and impact of the AECS VC model, emphasizing its alignment with the Sustainable Development Goals and Universal Health Coverage. By addressing accessibility and affordability, the VC model serves as a scalable template for primary eye care delivery in resource-limited settings globally.

Virtual Reality (VR) technology is widely recognized as a prominent technological paradigm. Its potential and promise in the domain of ophthalmology are substantial, and the evolution of VR technology has significantly influenced the contemporary landscape of ophthalmology. Numerous empirical studies have validated the practical utility of VR technology in domains such as ophthalmic disease treatment and surgery training. This paper offers a comprehensive overview of VR technology's utilization in ophthalmic disease treatment, student education, and surgery training, expands the application of VR technology in ophthalmic evaluation and disease diagnosis, discusses the challenges and limitations of VR technology in ophthalmology, and expounds on emerging trends and future developments of VR technology in ophthalmology. This endeavor aims to provide readers with an in-depth comprehension of the current status and future prospects of VR technology application in ophthalmology, with the ultimate objective of fostering more effective advancements and applications of VR technology in the realm of ophthalmology.

Virtual Reality (VR) technology is widely recognized as a prominent technological paradigm. Its potential and promise in the domain of ophthalmology are substantial, and the evolution of VR technology has significantly influenced the contemporary landscape of ophthalmology. Numerous empirical studies have validated the practical utility of VR technology in domains such as ophthalmic disease treatment and surgery training. This paper offers a comprehensive overview of VR technology's utilization in ophthalmic disease treatment, student education, and surgery training, expands the application of VR technology in ophthalmic evaluation and disease diagnosis, discusses the challenges and limitations of VR technology in ophthalmology, and expounds on emerging trends and future developments of VR technology in ophthalmology. This endeavor aims to provide readers with an in-depth comprehension of the current status and future prospects of VR technology application in ophthalmology, with the ultimate objective of fostering more effective advancements and applications of VR technology in the realm of ophthalmology.

Myopia, a common cause of visual impairment, together with the global decline in physical fitness and increasing prevalence of childhood obesity, has become a prominent global health problem. The beneficial effect of increasing the time of outdoor activities on the incidence of myopia and physical well-being in children has been widely recognized. However, in countries with highly competitive education systems, such as China, parents and school administrators may be reluctant to increase their children's time for extracurricular outdoor activities for fear of affecting their academic performance. Therefore, it is crucial to accurately assess the role of after-school outdoor activities in preventing and controlling myopia, as well as in promoting the physical and mental development of adolescents. Schools and families should be encouraged to collaboratively support children’s engagement in outdoor activities to foster their healthy growth. 

Given the dual benefits of outdoor activities—improving visual health and promoting overall physical and mental well-being—it is essential to encourage schools and families to work together to support children's engagement in such activities. By doing so, it is hoped that a balanced environment can be created, one that values both academic achievement and healthy development. Policymakers, educators, and parents must recognize the long-term advantages of integrating outdoor activities into children's daily lives, as this approach can help alleviate the burden of myopia, enhance physical fitness, and support emotional and cognitive development. Ultimately, fostering a culture that views outdoor activities as an essential component of education and health will be key to ensuring the well-rounded development of future generations.

Myopia, a common cause of visual impairment, together with the global decline in physical fitness and increasing prevalence of childhood obesity, has become a prominent global health problem. The beneficial effect of increasing the time of outdoor activities on the incidence of myopia and physical well-being in children has been widely recognized. However, in countries with highly competitive education systems, such as China, parents and school administrators may be reluctant to increase their children's time for extracurricular outdoor activities for fear of affecting their academic performance. Therefore, it is crucial to accurately assess the role of after-school outdoor activities in preventing and controlling myopia, as well as in promoting the physical and mental development of adolescents. Schools and families should be encouraged to collaboratively support children’s engagement in outdoor activities to foster their healthy growth.

Given the dual benefits of outdoor activities—improving visual health and promoting overall physical and mental well-being—it is essential to encourage schools and families to work together to support children's engagement in such activities. By doing so, it is hoped that a balanced environment can be created, one that values both academic achievement and healthy development. Policymakers, educators, and parents must recognize the long-term advantages of integrating outdoor activities into children's daily lives, as this approach can help alleviate the burden of myopia, enhance physical fitness, and support emotional and cognitive development. Ultimately, fostering a culture that views outdoor activities as an essential component of education and health will be key to ensuring the well-rounded development of future generations.

Background: Diabetic retinopathy (DR) screening using artificial intelligence (AI) has evolved significantly over the past decade. This study aimed to analyze research trends, developments, and patterns in AI-based fundus image DR screening from 2014 to 2024 through bibliometric analysis.Methods: The study used CiteSpace and Microsoft Excel to analyze 1,172 publications from the Web of Science Core Collection database. The analysis included publication trends over time, citation patterns, institutional collaborations, and the emergence of keywords. Results: From 2014-2022, there was a steady increase in the number of publications, reaching a peak in 2021. India (26%), China (20.05%), and the USA (9.98%) were the major contributors to research output in this field. Among the publication venues, IEEE ACCESS stood out as the leading one, with 44 articles published. The research landscape has evolved from traditional image processing techniques to deep learning approaches. In recent years, there has been a growing emphasis on multimodal AI models. The analysis identified three distinct phases in the development of AI-based DR screening: CNN-based systems (2014-2020), Vision Transformers and innovative learning paradigms (2020-2022), and large foundation models (2022-2024). Conclusions: The field has demonstrated a mature development in traditional AI approaches and is currently in the process of transitioning toward multimodal learning technologies. Future directions suggest an increased focus on the integration of telemedicine, innovative AI algorithms, and real-world implementation of these technologies in real-world settings.

Background: Diabetic retinopathy (DR) screening using artificial intelligence (AI) has evolved significantly over the past decade. This study aimed to analyze research trends, developments, and patterns in AI-based fundus image DR screening from 2014 to 2024 through bibliometric analysis. Methods: The study used CiteSpace and Microsoft Excel to analyze 1,172 publications from the Web of Science Core Collection database. The analysis included publication trends over time, citation patterns, institutional collaborations, and the emergence of keywords. Results: From 2014-2022, there was a steady increase in the number of publications, reaching a peak in 2021. India (26%), China (20.05%), and the USA (9.98%) were the major contributors to research output in this field. Among the publication venues, IEEE ACCESS stood out as the leading one, with 44 articles published. The research landscape has evolved from traditional image processing techniques to deep learning approaches. In recent years, there has been a growing emphasis on multimodal AI models. The analysis identified three distinct phases in the development of AI-based DR screening: CNN-based systems (2014-2020), Vision Transformers and innovative learning paradigms (2020-2022), and large foundation models (2022-2024). Conclusions: The field has demonstrated a mature development in traditional AI approaches and is currently in the process of transitioning toward multimodal learning technologies. Future directions suggest an increased focus on the integration of telemedicine, innovative AI algorithms, and real-world implementation of these technologies in real-world settings.

Background: Diabetic retinopathy (DR) is a top leading cause of blindness worldwide, requiring early detection for timely intervention. Artificial Intelligence (AI) has emerged as a promising tool to improve DR screening efficiency, accessibility, and cost-effectiveness. This study conducted a systematic review of literature and meta-analysis on the economic outcomes of AI-based DR screening. Methods: A systematic review of studies published before September 2024 was conducted throughout PubMed, Scopus, Embase, the Cochrane Library, the National Health Service Economic Evaluation Database, and the Cost-Effectiveness Analysis Registry. Eligible studies were included if they were (1) conducted among type 1 diabetes mellitus or type 2 diabetes mellitus  adult diabetic population; (2) studies compared AI-based DR screening strategy to non-AI screening; and (3) performed a cost-effectiveness analysis. Meta-analysis was applied to pool incremental net benefit (INB) across studies stratified by country income and study perspective using a random-effects model. Statistical heterogeneity among studies was assessed using the I² statistic, Cochrane Q statistics, and meta regression. Results: Nine studies were included in the analysis. From a healthcare system/payer perspective, AI-based DR screening was significantly cost-effective compared to non-AI-based screening, with a pooled INB of 615.77 (95% confidence interval [CI]: 558.27, 673.27). Subgroup analysis showed robust cost-effectiveness of AI-based DR screening in high-income countries (INB = 613.62, 95% CI: 556.06, 671.18) and upper-/lower- middle income countries (INB = 1739.97, 95% CI: 423.13, 3056.82) with low heterogeneity. From a societal perspective, AI-based DR screening was generally cost-effective (INB= 5102.33, 95% CI: -815.47, 11020.13), though the result lacked statistical significance and showed high heterogeneity. Conclusions: AI-based DR screening is generally cost-effective from a healthcare system perspective, particularly in high-income countries. Heterogeneity in cost-effectiveness across different perspectives highlights the importance of context-specific evaluations, to accurately evaluate the potential of AI-based DR screening in reducing global healthcare disparities.

Background: Diabetic retinopathy (DR) is a top leading cause of blindness worldwide, requiring early detection for timely intervention. Artificial Intelligence (AI) has emerged as a promising tool to improve DR screening efficiency, accessibility, and cost-effectiveness. This study conducted a systematic review of literature and meta-analysis on the economic outcomes of AI-based DR screening. Methods: A systematic review of studies published before September 2024 was conducted throughout PubMed, Scopus, Embase, the Cochrane Library, the National Health Service Economic Evaluation Database, and the Cost-Effectiveness Analysis Registry. Eligible studies were included if they were (1) conducted among type 1 diabetes mellitus or type 2 diabetes mellitus  adult diabetic population; (2) studies compared AI-based DR screening strategy to non-AI screening; and (3) performed a cost-effectiveness analysis. Meta-analysis was applied to pool incremental net benefit (INB) across studies stratified by country income and study perspective using a random-effects model. Statistical heterogeneity among studies was assessed using the I² statistic, Cochrane Q statistics, and meta regression. Results: Nine studies were included in the analysis. From a healthcare system/payer perspective, AI-based DR screening was significantly cost-effective compared to non-AI-based screening, with a pooled INB of 615.77 (95% confidence interval [CI]: 558.27, 673.27). Subgroup analysis showed robust cost-effectiveness of AI-based DR screening in high-income countries (INB = 613.62, 95% CI: 556.06, 671.18) and upper-/lower- middle income countries (INB = 1739.97, 95% CI: 423.13, 3056.82) with low heterogeneity. From a societal perspective, AI-based DR screening was generally cost-effective (INB= 5102.33, 95% CI: -815.47, 11020.13), though the result lacked statistical significance and showed high heterogeneity. Conclusions: AI-based DR screening is generally cost-effective from a healthcare system perspective, particularly in high-income countries. Heterogeneity in cost-effectiveness across different perspectives highlights the importance of context-specific evaluations, to accurately evaluate the potential of AI-based DR screening in reducing global healthcare disparities.

Objective: Evidence pertaining to the associations between hyperuricemia and diabetic microvascular complications is limited and inconclusive. In this study, we aimed to prospectively investigate the independent associations of hyperuricemia and retinopathy, nephropathy and neuropathy in individuals with type 2 diabetes mellitus (T2DM). Methods: This cohort study enrolled 25,094 participants from UK Biobank with T2DM and without microvascular complications at baseline. Hyperuricemia was defined as serum uric acid (SUA) higher than 420 μmol/L. The incidence of diabetic microvascular complications was identified from hospital inpatient records that were coded according to the International Classification of Diseases (ICD)-10 coding system. Multivariable adjusted Cox proportional hazards regression models were used to calculate adjusted hazard ratios (aHR). Results: Among all participants, 3,844 (15.3%) were classified as having hyperuricemia at baseline. During a median follow-up of 14.0 years, 555 (14.4%) individuals with hyperuricemia developed diabetic microvascular complications, compared with 12.6% of individuals without hyperuricemia (P=0.002). In the multivariable-adjusted model accounted for socioeconomic status, lifestyle factors, physical and biochemical measurements, and medication use, when compared with individuals of T2DM who had a normal SUA level, those with hyperuricemia had an 82.9% higher risk of developing diabetic nephropathy (95%CI: 1.41-2.38, P<0.001), and a 30.2% higher risk of diabetic neuropathy (95%CI: 1.06-1.60, P=0.011). However, the association between hyperuricemia and diabetic retinopathy was not statistically significant (aHR:1.070, 95%CI: 0.94-1.22, P=0.320). Conclusions: Hyperuricemia was independently associated with diabetic nephropathy and neuropathy but not retinopathy in individuals with T2DM. These findings underscore the importance of monitoring SUA level in prevention of certain microvascular complications.

Objective: Evidence pertaining to the associations between hyperuricemia and diabetic microvascular complications is limited and inconclusive. In this study, we aimed to prospectively investigate the independent associations of hyperuricemia and retinopathy, nephropathy and neuropathy in individuals with type 2 diabetes mellitus (T2DM). Methods: This cohort study enrolled 25,094 participants from UK Biobank with T2DM and without microvascular complications at baseline. Hyperuricemia was defined as serum uric acid (SUA) higher than 420 μmol/L. The incidence of diabetic microvascular complications was identified from hospital inpatient records that were coded according to the International Classification of Diseases (ICD)-10 coding system. Multivariable adjusted Cox proportional hazards regression models were used to calculate adjusted hazard ratios (aHR). Results: Among all participants, 3,844 (15.3%) were classified as having hyperuricemia at baseline. During a median follow-up of 14.0 years, 555 (14.4%) individuals with hyperuricemia developed diabetic microvascular complications, compared with 12.6% of individuals without hyperuricemia (P=0.002). In the multivariable-adjusted model accounted for socioeconomic status, lifestyle factors, physical and biochemical measurements, and medication use, when compared with individuals of T2DM who had a normal SUA level, those with hyperuricemia had an 82.9% higher risk of developing diabetic nephropathy (95%CI: 1.41-2.38, P<0.001), and a 30.2% higher risk of diabetic neuropathy (95%CI: 1.06-1.60, P=0.011). However, the association between hyperuricemia and diabetic retinopathy was not statistically significant (aHR:1.070, 95%CI: 0.94-1.22, P=0.320). Conclusions: Hyperuricemia was independently associated with diabetic nephropathy and neuropathy but not retinopathy in individuals with T2DM. These findings underscore the importance of monitoring SUA level in prevention of certain microvascular complications.

Objective: Fengqing County, situated in Yunnan Province, is a high-altitude regionknown for its ethnic diversity and a notably high prevalence of pterygium. As akey area for Sun Yat-sen University's poverty alleviation initiatives, this studyaims toinvestigate the unique characteristics of pterygiumin specific region. Methods: We analyzed data from hospitalized patients admitted to the Ophthalmology department of the People's Hospital of Fengqing in 2023. The data wereextracted from medical records through the hospital information system. The chi-square test was used for statistical comparison, and multivariate logistic regression analysiswas conduct to explorethefactors influencingthe onset ofpterygium.A significance level of P< 0.005 wasset. Results: In 2023,outof 1137 ophthalmic inpatients, 207 (18.2%) underwent pterygium surgery. There was asignificant female predominance, with a female-to-male ratio of6.67:1(P<0.001). However,nosignificantethnic variation was observed(P=0.57).The majority of patients were in the 46-55 age group (36.71%),and the recurrence rate was low at1.71%. Female gender,increasingage, diabetes mellitus, age-related cataract, and meibomian gland dysfunctionwere identified as independent risk factors for pterygium in this region. Conclusion:Fengqingislikelyto have intricate connections betweentheoccurrence andtreatment of perygium and its local geography, culture, and socio-economic conditions. Medical assistance programs should take these factors into account andprioritizethem in poverty alleviationinitiatives.

Objective: Fengqing County, situated in Yunnan Province, is a high-altitude regionknown for its ethnic diversity and a notably high prevalence of pterygium. As akey area for Sun Yat-sen University's poverty alleviation initiatives, this studyaims toinvestigate the unique characteristics of pterygiumin specific region. Methods: We analyzed data from hospitalized patients admitted to the Ophthalmology department of the People's Hospital of Fengqing in 2023. The data wereextracted from medical records through the hospital information system. The chi-square test was used for statistical comparison, and multivariate logistic regression analysiswas conduct to explorethefactors influencingthe onset ofpterygium.A significance level of P< 0.005 wasset. Results: In 2023,outof 1137 ophthalmic inpatients, 207 (18.2%) underwent pterygium surgery. There was asignificant female predominance, with a female-to-male ratio of6.67:1(P<0.001). However,nosignificantethnic variation was observed(P=0.57).The majority of patients were in the 46-55 age group (36.71%),and the recurrence rate was low at1.71%. Female gender,increasingage, diabetes mellitus, age-related cataract, and meibomian gland dysfunctionwere identified as independent risk factors for pterygium in this region. Conclusion:Fengqingislikelyto have intricate connections betweentheoccurrence andtreatment of perygium and its local geography, culture, and socio-economic conditions. Medical assistance programs should take these factors into account andprioritizethem in poverty alleviationinitiatives.