Purpose: To conduct a review to systematically evaluate the use of anterior segment opticalcoherence tomography (AS-OCT) in measuring anterior scleral thickness across diverse ocularconditions and its clinical implications. Methods: Literature search was conducted across electronicdatabases, including PubMed, Scopus, and Embase, to identify relevant studies. The risk of biaswas assessed, and the main characteristics of each  studies were analyzed. We calculated theoverall mean anterior scleral thickness using the data which have measurement at the same locations. Results: A total of 32 studies were included that utilized AS-OCT to measure anterior scleralthickness in both healthy subjects and individuals with ocular disorders such as myopia, keratoconus, scleritis, and others , The review found that anterior scleral thickness is signiicantly influenced by age, diurnal variation, and specific ocular conditions. For example, myopic eyes mayexhibit thinner sclera, particularly along certain meridians, while conditions like scleritis showecincreased scleral thickness due to inflammation, However, some studies have inconsistent resultsAdditionally, AS-OCT proved effective in detecting subtle variations in anterior scleral thickness. which could be linked to the progression of ocular diseases. Conclusions: Anterior scleral thicknessvaries considerably depending on age, time of day, and ocular health, making it a valuable parameterin the assessment of eye conditions. AS-OCT's ability to measure these variations non-invasivelybroadens its application in both clinical practice and research, offering new insights into thebiomechanical properties of the sclera and their implications for ocular diseases.

Purpose: To conduct a review to systematically evaluate the use of anterior segment opticalcoherence tomography (AS-OCT) in measuring anterior scleral thickness across diverse ocularconditions and its clinical implications. Methods: Literature search was conducted across electronicdatabases, including PubMed, Scopus, and Embase, to identify relevant studies. The risk of biaswas assessed, and the main characteristics of each  studies were analyzed. We calculated theoverall mean anterior scleral thickness using the data which have measurement at the same locations. Results: A total of 32 studies were included that utilized AS-OCT to measure anterior scleralthickness in both healthy subjects and individuals with ocular disorders such as myopia, keratoconus, scleritis, and others , The review found that anterior scleral thickness is signiicantly influenced by age, diurnal variation, and specific ocular conditions. For example, myopic eyes mayexhibit thinner sclera, particularly along certain meridians, while conditions like scleritis showecincreased scleral thickness due to inflammation, However, some studies have inconsistent resultsAdditionally, AS-OCT proved effective in detecting subtle variations in anterior scleral thickness. which could be linked to the progression of ocular diseases. Conclusions: Anterior scleral thicknessvaries considerably depending on age, time of day, and ocular health, making it a valuable parameterin the assessment of eye conditions. AS-OCT's ability to measure these variations non-invasivelybroadens its application in both clinical practice and research, offering new insights into thebiomechanical properties of the sclera and their implications for ocular diseases.

Abstract: Retinal degeneration, a leading cause of irreversible blindness, often results from photoreceptor deterioration due to genetic mutations or damage to retinal pigment epithelial (RPE) cells. Emerging research highlights the gut-eye axis, a connection between gut microbiota and eye diseases. Our recent findings demonstrate that bacterial translocation from the gut to the retina contributes to Crb1-associated retinal degeneration. This review explores the relationship between the gut microbiome and retinal degeneration, focusing on inherited retinal degeneration (IRD) and age-related macular degeneration (AMD).

Abstract: Retinal degeneration, a leading cause of irreversible blindness, often results from photoreceptor deterioration due to genetic mutations or damage to retinal pigment epithelial (RPE) cells. Emerging research highlights the gut-eye axis, a connection between gut microbiota and eye diseases. Our recent findings demonstrate that bacterial translocation from the gut to the retina contributes to Crb1-associated retinal degeneration. This review explores the relationship between the gut microbiome and retinal degeneration, focusing on inherited retinal degeneration (IRD) and age-related macular degeneration (AMD).

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.

Amblyopia is a neurodevelopmental vision disorder resulting from abnormal visual input during the critical period of visual development, such as strabismus, uncorrected anisometropia, high refractive errors, and form deprivation. It is frequently associated with reduced visual acuity and deficits in binocular vision. Traditional occlusion therapy for amblyopia has typically been restricted to infants and young children during the critical period of visual development, as it is believed to be ineffective for older children and adults due to the decreased plasticity of the mature brain. Our research group has concentrated on pivotal scientific issues in amblyopia, including quantitative methods for detecting binocular vision, especially interocular visual suppression, the mechanisms underlying binocular vision impairment in amblyopia,treatment methods and their evaluations for amblyopia, and visual plasticity and its neural mechanismsin amblyopia. This paper summarizes the visual mechanisms and treatment modalities of amblyopia based on our research and both domestic and foreign sources, while also looking forward to the future development of this field in light of existing problems.

Amblyopia is a neurodevelopmental vision disorder resulting from abnormal visual input during the critical period of visual development, such as strabismus, uncorrected anisometropia, high refractive errors, and form deprivation. It is frequently associated with reduced visual acuity and deficits in binocular vision. Traditional occlusion therapy for amblyopia has typically been restricted to infants and young children during the critical period of visual development, as it is believed to be ineffective for older children and adults due to the decreased plasticity of the mature brain. Our research group has concentrated on pivotal scientific issues in amblyopia, including quantitative methods for detecting binocular vision, especially interocular visual suppression, the mechanisms underlying binocular vision impairment in amblyopia,treatment methods and their evaluations for amblyopia, and visual plasticity and its neural mechanismsin amblyopia. This paper summarizes the visual mechanisms and treatment modalities of amblyopia based on our research and both domestic and foreign sources, while also looking forward to the future development of this field in light of existing problems.

Objective: 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 = 1,739.97, 95% CI: 423.13-3,056.82) with low heterogeneity. From a societal perspective, AI-based DR screening was generally cost-effective (INB= 5,102.33, 95% CI: -815.47-11,020.13), 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: 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 = 1,739.97, 95% CI: 423.13-3,056.82) with low heterogeneity. From a societal perspective, AI-based DR screening was generally cost-effective (INB= 5,102.33, 95% CI: -815.47-11,020.13), 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.

Aims: To identify the characteristic retinal neurovascular changes in patients in different stages of nondiabetic chronic kidney disease (CKD) and to develop a model for the accurate diagnosis of nondiabetic CKD.
Methods: Peripapillary retinal nerve fiber layer (pRNFL) thickness and average macular ganglion cell-inner plexiform layer (GC-IPL) thickness of nondiabetic CKD patients and healthy controls (HC) were evaluated by spectral-domain optical coherence tomography (OCT). The vessel density (VD) and perfusion density (PD) of the macula were obtained from optical coherence tomography angiography (OCTA). The estimated glomerular filtration rate (eGFR) was obtained to access the kidney function of CKD patients. Multiple linear regression models were used to adjust for confounding factors in statistical analyzes. The diagnostic capabilities of the parameters were evaluated by logistic regression models.
Results: 131 nondiabetic CKD patients and 62 HC entered the study. eGFR was found significantly associated with parafoveal VD and PD (average PD: β = 0.000 4, P_adjusted < 0.001) in various sectors. Thinning of pRNFL (β = -6.725, P_adjusted < 0.001) and GC-IPL (β = -4.542, P_adjusted < 0.001), as well as decreased VD (β = -2.107, P_- adjusted < 0.001) and PD (β = -0.057, P_adjusted = 0.032 8) were found in CKD patients. Thinning of pRNFL and deteriorated perifoveal vasculature were found in early CKD, and the parafoveal and foveal VD significantly declined in advanced CKD. Logistic regression models were employed, and selected neurovascular parameters showed an AUC of 0.853 (95% Confidence Interval [CI]: 0.795 to 0.910) in distinguishing CKD patients from HC.
Conclusions: Distinctive retinal neurovascular characteristics could be observed in nondiabetic CKD patients of different severities. Our results suggest that retinal manifestations could be valuable in the screening, diagnosis, and follow-up evaluation of patients with CKD.

Aims: To identify the characteristic retinal neurovascular changes in patients in different stages of nondiabetic chronic kidney disease (CKD) and to develop a model for the accurate diagnosis of nondiabetic CKD.
Methods: Peripapillary retinal nerve fiber layer (pRNFL) thickness and average macular ganglion cell-inner plexiform layer (GC-IPL) thickness of nondiabetic CKD patients and healthy controls (HC) were evaluated by spectral-domain optical coherence tomography (OCT). The vessel density (VD) and perfusion density (PD) of the macula were obtained from optical coherence tomography angiography (OCTA). The estimated glomerular filtration rate (eGFR) was obtained to access the kidney function of CKD patients. Multiple linear regression models were used to adjust for confounding factors in statistical analyzes. The diagnostic capabilities of the parameters were evaluated by logistic regression models.
Results: 131 nondiabetic CKD patients and 62 HC entered the study. eGFR was found significantly associated with parafoveal VD and PD (average PD: β = 0.000 4, P_adjusted < 0.001) in various sectors. Thinning of pRNFL (β = -6.725, P_adjusted < 0.001) and GC-IPL (β = -4.542, P_adjusted < 0.001), as well as decreased VD (β = -2.107, P_adjusted < 0.001) and PD (β = -0.057, P_adjusted = 0.032 8) were found in CKD patients. Thinning of pRNFL and deteriorated perifoveal vasculature were found in early CKD, and the parafoveal and foveal VD significantly declined in advanced CKD. Logistic regression models were employed, and selected neurovascular parameters showed an AUC of 0.853 (95% Confidence Interval [CI]: 0.795 to 0.910) in distinguishing CKD patients from HC.
Conclusions: Distinctive retinal neurovascular characteristics could be observed in nondiabetic CKD patients of different severities. Our results suggest that retinal manifestations could be valuable in the screening, diagnosis, and follow-up evaluation of patients with CKD.

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 2023–2024, 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 2023–2024, 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.

Aims: To explore the point-wise correlations between 10-2 visual field (VF) metrics and macular vessel density, as measured by optical coherence tomography angiography (OCTA), in patients with early open-angle glaucoma (OAG) and healthy controls. Methods: This is a cross-sectional study that retrospectively analyzed data from 54 participants (18 eraly OAG patients and 36 healthy controls) from the Zhongshan Ophthalmic Center. All participants underwent comprehensive ophthalmic examinations, 10-2 VF, and macular OCTA imaging. The correlation between capillary density (CD) in macular subregions and light sensitivity (LS) at corresponding VF test points was analyzed using Pearson's correlation coefficients. Results: The analysis revealed a significant reduction in CD within the inferior macular regions of glaucomatous eyes. Notably, there were strong point-wise correlations between CD and 10-2 VF, particularly in the inferior region of outer ring (peak r = 0.534, P < 0.001). Conclusion: The point-wise correlation between 10-2 VF and macular CDdemonstrates the potential for using CD to predict central VF damage in glaucoma, emphasizing theimportance of macular microcirculation in early disease screening.

Aims: To explore the point-wise correlations between 10-2 visual field (VF) metrics and macular vessel density, as measured by optical coherence tomography angiography (OCTA), in patients with early open-angle glaucoma (OAG) and healthy controls. Methods: This is a cross-sectional study that retrospectively analyzed data from 54 participants (18 early OAG patients and 36 healthy controls) from the Zhongshan Ophthalmic Center. All participants underwent comprehensive ophthalmic examinations, 10-2 VF, and macular OCTA imaging. The correlation between capillary density (CD) in macular subregions and light sensitivity (LS) at corresponding VF test points was analyzed using Pearson's correlation coefficients. Results: The analysis revealed a significant reduction in CD within the inferior macular regions of glaucomatous eyes. Notably, there were strong point-wise correlations between CD and 10-2 VF, particularly in the inferior region of outer ring (peak r = 0.534, P < 0.001). Conclusion: The point-wise correlation between 10-2 VF and macular CDdemonstrates the potential for using CD to predict central VF damage in glaucoma, emphasizing theimportance of macular microcirculation in early disease screening.