Introduction The macula is a pigmented area located at the centre of the retina, responsible for central, high-resolution colour vision. Previous research has demonstrated that oral carotenoid supplementation can enhance contrast sensitivity (CS) in European populations. This study aims to investigate whether carotenoid supplementation can also improve visual function in the Chinese population.Methods and analysis The Contrast Sensitivity Vision (CSV) trial is a double-blind, randomised controlled trial conducted at the Zhongshan Ophthalmic Center in Guangzhou, China. 220 eligible Chinese adults will be randomised in a 1:1 ratio to receive either oral supplementation of 10 mg lutein, 10 mg meso-zeaxanthin and 2 mg zeaxanthin in a formula-based oil suspension (administered as one soft gel capsule) or a placebo oil soft gel capsule daily for 1 year. Participants in both groups will undergo ophthalmological study procedures including best-corrected visual acuity (BCVA), contrast sensitivity, optical coherence tomography, fundus photography and skin carotenoid examinations at baseline and at 3-month, 6-month and 12-month follow-up visits. Blood tests and a Dietary Carotenoid Screening Questionnaire will be administered at baseline and at the 12-month follow-up. Subjective visual function questionnaire interviews will be administered at baseline and at the 3-month, 6-month and 12-month follow-ups. The primary outcome will assess change in CS at 6 cycles per degree (cpd) over the 1-year study intervention. Secondary outcomes will examine CS at 6 cpd at the 3-month and 6-month follow-up, CS at other cpd, BCVA, subjective visual function and skin carotenoid levels as measured at baseline, 3-month, 6-month and 12-month follow-ups.Ethics and dissemination The CSV trial was approved by the Ethics Committee of the Zhongshan Ophthalmic Center, Guangzhou, China (No. KYPJ141-4). Participants will have the opportunity to ask questions about the trial, and written informed consent will be obtained from all participants prior to their involvement in the study. Results will be disseminated through peer-reviewed publication and conference presentations.Trial registration number NCT06098677.

Purpose:The parapapillary gamma zone is a hallmark structural change of the optic nerve head (ONH) in pathological myopia and is closely linked to axial elongation. Cross-sectional studies suggest strong correlations between gamma zone and axial length (AL), but longitudinal data characterizing gamma zone progression and its impact on AL are scarce. Methods:In this 10-year prospective study, 205 participants with bilateral high myopia (spherical equivalent ≤ -6.0 diopter [D]) from the Zhongshan High Myopia cohort were followed. A novel swept-source optical coherence tomography (SS-OCT)-based algorithm was developed for automated three-dimensional quantification of Bruch's membrane opening (BMO) displacement and gamma zone parameters, including area, angular extent, maximal radial extent, and spatial distribution. Associations among BMO and gamma zone metrics and myopia progression (AL, spherical equivalent, and AL change rate) were analyzed using linear and nonlinear regression. Results:The study included 205 individuals (mean age = 14.84 ±2 .26 years). In multivariate analysis, a larger area of BMO (mean = 3.65 ± 1.06 mm²) was associated with greater AL (P = 0.039) and inversely related with spherical equivalent (SE; P = 0.001). The gamma zone area (mean = 1.71 ± 2.20 mm²) was significantly correlated with AL (P < 0.001) and SE (P = 0.003) after adjusting for confounders. The gamma zone area was used to stratify the participants into four quartiles (Q1-Q4). Quartile Q4 showed a markedly greater rate of AL change than each of the lower quartiles (P < 0.0001), which remained evident even after Q1 to Q3 were merged. Conclusions:Progressive gamma zone enlargement is strongly associated with axial elongation in high myopia. Once the gamma zone exceeds a critical area threshold, the AL accelerates rapidly, likely reflecting compromised biomechanical counterforce from Bruch's membrane (BM). Longitudinal gamma zone monitoring may provide a valuable prognostic marker for identifying eyes at risk of accelerated and potentially irreversible myopic progression.

AIMS:To investigate retinal vascular geometric alterations following intraocular pressure (IOP)-lowering surgery in patients with primary angle closure disease (PACD) and determine associations between IOP reduction magnitude and retinal vascular parameters. METHODS:This retrospective, self-controlled study included patients with PACD who underwent IOP-lowering surgery at Beijing Tongren Hospital. Retinal vascular parameters were quantitatively measured from fundus photographs before and after surgery using a validated deep learning-based analysis system. Main outcomes included retinal arteriolar and venular calibre, tortuosity, fractal dimension (FD), segment number (N_seg) and vascular density. Linear mixed-effects models, adjusted for age, follow-up interval and PACD subtype, assessed associations between IOP reduction magnitude and vascular parameter changes. RESULTS:Among 126 eyes (112 patients), surgery decreased IOP from 35.0±9.9 to 16.7±5.7 mm Hg (p<0.001). Venous FD increased from 1.52±0.06 to 1.53±0.05 (p=0.003), N_seg from 123.50 (IQR: 61.75-182.50) to 153.00 (88.50-185.00) (p=0.007), vessel area density (VAD) from 6.13±1.56 to 6.50±1.34 (p=0.006) and vessel skeleton density (VSD) from 1.24±0.35 to 1.35±0.31 (p=0.003). Vessel calibre and tortuosity showed no significant changes. IOP reduction magnitude was independently associated with changes in venous FD (p=0.023), N_seg (p=0.031), VAD (p=0.012) and VSD (p=0.030). CONCLUSIONS:Surgical IOP reduction in PACD patients produces selective retinal venous alterations with increased complexity and density. These pressure-responsive changes may provide complementary, non-invasive information regarding vascular response after surgery.

PURPOSE:To establish a longitudinal, school-based cohort to investigate physiological and pathological ocular changes and identify associated risk factors in children and adolescents with high myopia in South China. METHODS:This three-year cohort recruits students aged 6-18 years from 1,438 schools in Guangzhou, China (April 2018-August 2024). Eligible participants have a cycloplegic spherical equivalent (SE) ≤-3.00 D (ages 6-8) or ≤-6.00 D (ages 9-18). Annual follow-up includes demographic, behavioural, and familial questionnaires and comprehensive ophthalmic assessments, including visual acuity, ocular biometry, cycloplegic refraction, fundus photography, and optical coherence tomography/angiography. The study adheres to the Declaration of Helsinki and was approved by the Ethics Committee of Zhongshan Ophthalmic Centre (approval number: 2017KYPJ100). Written informed consent is obtained from all participants and their guardians. Generalized estimating equations and mixed-effect models assess ocular changes and associations with environmental and biometric factors. RESULTS:1,331 participants were enrolled at baseline (mean SE= -7.34 ± 2.38 D; axial length = 26.21 ± 1.30 mm). Older age was associated with more myopic SE (β= -0.26, p < 0.001) and longer axial length (β = 0.18, p < 0.001). Males had longer axial length (β = 0.42, p < 0.001), and higher corneal power was linked to shorter axial length (β= -0.29, p < 0.001). Behavioural factors showed no significant associations with SE or axial length. CONCLUSIONS:These baseline preliminary analyses show that demographic factors and corneal power, rather than behavioural factors, are significantly associate with ocular dimensions in early-onset high myopia. This longitudinal cohort provides a vital platform to track ocular growth, early pathological changes, and progression risk factors.

Purpose:To investigate retinomic changes preceding glaucoma onset and explore their predictive value. Design:A population-based, prospective cohort study. Participants:A total of 40 949 adults from the UK Biobank, all with eligible color fundus photography (CFP) data and OCT data and without baseline glaucoma, were included in this study. Methods:We used baseline values of retinomics, a composite set of quantitative retinal imaging biomarkers including 135 retinal vascular measurements extracted with the Retina-based Microvascular Health Assessment System from CFP and 21 OCT-derived retinal layer measurements. After least absolute shrinkage and selection operator feature selection, Cox regression was used to assess associations with incident glaucoma, and a gradient boosting machine model was applied to evaluate predictive performance. Main Outcome Measures:Glaucoma status. Results:During a median follow-up of 12.49 years, 653 of 40 949 participants developed glaucoma. After adjusting for age, sex, ethnicity, education, smoking behavior, alcohol consumption, physical activity, hypertension, obesity, glycated hemoglobin, and intraocular pressure, 18 of the 48 least absolute shrinkage and selection operator-identified retinal parameters showed statistically significant associations with incident glaucoma, with each standard deviation change associated with 8.2% to 26.4% increased risk. These findings highlighted novel predictors beyond conventional parameters, including vascular network simplification and inner nuclear layer-related thickening. For a 12.49-year incident glaucoma prediction, simply using age, sex, and retinomic features, we achieved a concordance index of 0.767. After being stratified into 3 risk groups, the highest risk group showed a hazard ratio of 8.72 (95% confidence interval: 6.59-11.54) against the lowest risk group. Conclusions:Our study revealed retinal vascular and neural alterations associated with increased risk of incident glaucoma. In addition, our study showed that retinomics can serve as an effective biomarker for identifying individuals at high risk of developing glaucoma. The simplicity (age, sex, and basic imaging) of our model along with its satisfactory risk stratification performance for long-term incident glaucoma suggest that it can be used to distinguish those patients who are most suitable for early therapeutic intervention to prevent blindness or severe visual impairment at a population level. Financial Disclosures:Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Purpose:To translate and validate a Chinese version of the Low Luminance Questionnaire (LLQ). Methods:The original LLQ was translated into Chinese by two ophthalmologists and back-translated by a professional translator. Between 2022 and 2023, participants with visual impairment were recruited from Zhongshan Ophthalmic Center. The method of successive dichotomizations (MSD) was used to assess the separation index, reliability, item misfit, and differential item functioning (DIF) of the questionnaire; principal component analysis was also used to assess unidimensionality. Linear regression analyzed the relationship between participant demographics and MSD person measures based on the Chinese LLQ. Results:A total of 173 participants (67.05% female) with an average age of 65.73 years were included, and all completed the Chinese version of the LLQ. After taking into account item fit, content validity, targeting, and cultural adaptation to the Chinese context, eight items were removed, yielding a final 24-item Chinese LLQ (LLQ-24). This version showed good separation (person, 3.47; item, 7.61) and reliability (person, 0.92; item, 0.98), although person-item targeting was suboptimal, with person measures averaging 1.63 logits higher than item measures. A few items showed DIF across age and gender. Participants with worse visual acuity and those with cataract had lower scores on the LLQ-24. Conclusions:The 24-item Chinese LLQ provides a useful tool with fair validity and reliability to assess low luminance visual difficulties in the Chinese population. Translational Relevance:The Chinese LLQ enables eyecare professionals to more accurately assess and manage vision-related conditions in low-light environments.

Clinical Relevance:The retina is a unique and accessible window to the central nervous system and its vasculature. Ocular fundus examination is crucial for identifying diagnostic red flags indicative of life- and sight-threatening conditions, such as papilledema and central retinal artery occlusion. In the emergency department (ED), prompt recognition of these conditions is essential to reduce the risk of vision loss and serious complications. Methods:This review summarizes advances in ocular fundus examination, imaging, and artificial intelligence (AI) for emergency care. Results:The direct ophthalmoscope, a traditional tool for ocular fundus examination by nonophthalmology providers in the ED, is rarely utilized due to technical limitations and lack of user skill and confidence. Recent advancements in retinal imaging technologies have introduced ocular fundus cameras with OCT as valuable alternatives. The advent of nonmydriatic and portable imaging devices has significantly expanded accessibility, enabling remote image interpretation and facilitating teleophthalmology consultations. Moreover, AI, especially deep-learning technology, has demonstrated considerable potential for automated ocular image interpretation. The latest developments in large language models show promise in providing aids in diagnosis and management. Conclusions:Further research is needed to validate the reliability of AI-powered ocular fundus assessment and to explore how these emerging technologies can be effectively integrated into ED practice to enhance ocular fundus examination and improve patient care.

BACKGROUND:Despite over 90% of vision impairment (VI) being preventable, in China, a routine screening programme is currently unavailable in primary healthcare. Robust epidemiological evidence is needed to guide national strategies. METHOD:Using Global Burden of Disease 2021 data, we estimated prevalence, years lived with disability (YLDs), and age-standardized rates of VI by cause and severity. Temporal changes were decomposed into contributions from population growth, ageing, and shifts in age-specific prevalence. Estimated annual percentage changes (EAPCs) assessed trends, and Bayesian age-period-cohort models projected burden to 2040. RESULTS:In 2021, China had 767.4 million (95% UI 576.6 to 1009.3) VI cases, comprising: 324.4 million (237.7 to 435.4) uncorrected presbyopia, 4.1 million (3.4 to 5.0) moderate VI, 46.7 million (39.4 to 55.3) severe VI and 8.6 million (7.0 to 10.2) blindness. Population ageing emerged as the predominant driver, accounting for 164.25% of the cataract-related burden increase. Women had a higher burden than men (53.79% of cases; 54.87% of YLDs), and the burden peaked at older ages. Uncorrected refractive errors and cataracts were the leading aetiologies, constituting 50.65% of moderate VI and 35.08% of blindness. Projections indicate that by 2040, the age-standardised YLD rate for VI may nearly double from 2021 levels, reaching 596.4 (95% UI 72.0 to 1240.4) per 100 000 population. CONCLUSIONS:VI is a growing public health challenge in China, driven primarily by ageing. Many cases are preventable, underscoring the need for targeted interventions, particularly among women and older adults.

Artificial intelligence (AI) tools are rapidly reshaping ophthalmology by improving screening and diagnosis for diabetic retinopathy, age-related macular degeneration, glaucoma, and increasingly retina-based systemic risk assessment. This narrative review provides a comparative assessment of regulatory pathways governing ophthalmic AI and software as a medical device (SaMD) across the United States, European Union, United Kingdom, Australia, China, Japan, Canada, India, and selected emerging jurisdictions.We used a structured search of public regulator databases, guidance documents, manufacturer disclosures, and peer-reviewed literature to assemble a representative sample of marketed or authorized devices through August 2025; the device inventory is illustrative rather than exhaustive. Key differences persist in device classification, evidence expectations, change management for adaptive algorithms, and post-market oversight. Examples such as LumineticsCore, EyeArt, DrNoon for CVD, CLAiR, and EyeWisdom illustrate how risk-based approaches vary across jurisdictions.These inconsistencies can delay multi-region deployment and complicate implementation, supporting the need for lifecycle-focused and internationally aligned standards for safe, transparent, and equitable use of ophthalmic AI.

Proteomics represents a powerful but underutilized approach for characterizing eye aging. Here, leveraging data from three large-scale, cross-national cohorts of over 55,000 transethnic participants, we demonstrate the ability of high-throughput proteomics combined with deep learning (DL) phenotyping to track eye aging and disease in both discovery and external validation settings. Proteomic aging driven by machine learning modeling closely aligns with signals of eye aging and DL aging phenotypes. We identifiy and validate premature proteomic aging in individuals with major age-related eye diseases (AREDs), including cataract, diabetic retinopathy, age-related macular degeneration, and glaucoma, and propose evidence supporting proteomic aging acceleration as a robust biomarker for predicting these conditions beyond chronological age, with adaptability across sexes and ethnicities. We also develop a streamlined, cost-effective proteomic aging clock that preserves predictive performance while reducing assay complexity. By integrating advanced tomographic and angiographic imaging, we derive structural and functional biomarkers through DL-driven pipelines and link accelerated proteomic aging to both neuroretinal degeneration and microvascular rarefaction in the Guangzhou Diabetic Eye Study (GDES) and the High-definition Oculo-Phenomic Evaluation (HOPE) study, highlighting coupled neural-vascular decline in eye aging. Our findings position proteomic aging combined with AI as a scalable tool for tracking eye health and disease, and provides new insights into shared aging pathways underlying multiple ocular pathologies.

Purpose:The purpose of this study was to compare longitudinal changes in three-dimensional (3D) macular morphology between repeated low-level red-light (RLRL) therapy and 0.01% low-dose atropine (LDA) treatment in myopic children. Methods:This secondary analysis of a randomized controlled trial (RCT) included 50 myopic children (aged 7-15 years) randomized to receive either RLRL therapy (650 ± 10 nm) or 0.01% atropine eye drops. Spectral-domain optical coherence tomography (OCT) was performed at baseline and 1, 3, 6, and 12 months. Custom software was used to perform distortion correction and quantify macular curvature (MC; mm-1), macular outward scleral height (MOSH; µm), and their respective asymmetry indices. Primary outcomes were 12-month changes in average regional macular curvature. Secondary outcomes included changes in MOSH, asymmetry indices, and retinal layer thicknesses. Linear mixed-effects models analyzed longitudinal changes. Results:At 12 months, RLRL showed greater macular flattening than 0.01% atropine across all regions (mean differences, × 10-3 mm-1): central (9.0, 95% confidence interval [CI] = 4.4-13.6, P < 0.01), temporal (9.7, 95% CI = 6.7-12.8, P < 0.001), inferior (8.4, 95% CI = 5.2-11.6, P < 0.001), superior (7.0, 95% CI = 4.0-9.9, P < 0.001), and nasal (3.7, 95% CI = 0.8-6.7, P < 0.05). The inter-group difference was most pronounced centrally and decreased with eccentricity. MOSH decreased superiorly and increased inferiorly in the RLRL group at 12 months, whereas the LDA group showed minimal change. Both nasal-temporal and superior-inferior macular curvature asymmetry indices increased significantly more in the RLRL group (P < 0.001 and P < 0.05, respectively). No inter-group differences in retinal layer thickness changes were observed. Conclusions:Over 12 months, RLRL showed broader macular flattening and more region-specific MOSH changes compared with 0.01% atropine in this cohort. However, the underlying mechanisms and the independent contribution of myopic progression to these morphological differences require further study.

This scoping review examines the existing literature on the application of artificial intelligence (AI) in screening for eye diseases, with a focus on evaluating whether AI-assisted diagnostic technologies enhance the availability, accessibility, acceptability and quality of screening services. 42 original studies were selected for in-depth analysis, including those employing health economic evaluations. Methodological quality was assessed using the Mixed Methods Appraisal Tool, with the majority of studies demonstrating high quality—24 scored 5/5, 15 scored 4/5 and the rest scored 3/5. Among the included studies, 34 compared manual screening with either AI-assisted or fully AI-driven approaches. Availability was the most frequently studied aspect (28 studies), followed by acceptability (12 studies), whereas accessibility and service quality were less commonly addressed. Overall, AI shows significant potential to improve the cost-effectiveness of eye care services and enhance patient access, particularly in remote or underserved regions. It was also well-accepted by patients, with high satisfaction and improved referral compliance. The findings suggest that AI holds promise for advancing eye disease screening, although large-scale, long-term trials are needed to effectively integrate AI into the reconstruction of screening processes and the reshaping of eye health service systems.

Training medical vision-language models (VLMs) typically demands millions of image-text pairs to achieve versatility and reasoning, posing significant challenges in data acquisition. We propose ConceptVLM, a novel data-efficient fine-tuning paradigm that transforms general-domain VLMs into specialized medical ones with minimal labeled data, integrating medical knowledge without disrupting the model’s existing general capabilities. Central to our approach is a key concept-aware training strategy, building a structured medical concept dictionary and employing masked attention to guide the model’s focus toward essential clinical concepts. This focused fine-tuning enhances domain-specific comprehension while preserving the model’s reasoning abilities and response diversity. Experiments across multimodal medical benchmarks show ConceptVLM achieves state-of-the-art results using only 1% of the original training data, outperforming traditional methods reliant on large-scale QA datasets. These findings challenge the prevailing reliance on extensive annotated corpora, demonstrating key concept-guided tuning as a viable path to developing cognitively capable medical VLMs.

OBJECTIVE:Dry eye significantly impacts global quality of life and productivity, yet existing epidemiological data remain fragmented and outdated, hindering effective prevention and management strategies. This study aimed to estimate the global prevalence of dry eye and examine variations across regions, demographics, diagnostic criteria, study settings, and the COVID-19 pandemic. METHODS:A systematic search of PubMed, Web of Science, Embase, and Cochrane Library identified 119 cohort or cross-sectional studies involving 15,251,528 participants. Two reviewers independently screened records, extracted data, and assessed study quality using the Joanna Briggs Institute checklist. A random-effects model pooled prevalence estimates, with subgroup analyses exploring heterogeneity. RESULTS:The global pooled prevalence of dry eye was 34.6% (95% CI: 30.2%-39.4%). Regional disparities were pronounced, with the highest prevalence in Africa 43.9% (95% CI: 31.5%-57.2%) and the lowest in North America 20.9% (95% CI: 8.2%-43.8%). Higher rates were observed in females 39.1% (95% CI: 32.8%-45.8%) vs. males 30.8% (95% CI: 24.8%-37.7%), individuals aged > 40 years 37.0% (95% CI: 29.1%-45.7%) vs. ≤ 40 years 35.0% (95% CI: 25.4%-46.0%), institutional settings 45.2% (95% CI: 36.2%-54.5%), and during COVID-19 44.5% (95% CI: 28.0%-62.2%). Diagnostic criteria significantly influenced estimates, ranging from 6.9% (95% CI: 1.9%-21.7%) (ICD-9-based) to 53.8% (95% CI: 46.7%-60.8%) (OSDI ≥ 13). CONCLUSIONS:Dry eye represents a major global public health challenge, with prevalence shaped by geographic, demographic, environmental, and methodological factors. The pandemic exacerbated dry eye burden, underscoring the urgency for standardized diagnostic protocols and targeted interventions to mitigate its growing impact.

To investigate the association and potential causal relationship between accelerometer-assessed physical activity (PA) and the risk of senile cataract (SC). The study population was derived from the UK Biobank database. Triaxial accelerometer data from wearable devices, collected over a continuous 7-day wear period (accounting for potential seasonal variation), were used to define PA at light (LPA), moderate (MPA), and vigorous (VPA) intensities. Multivariable Cox proportional hazards models were used to examine the association between PA intensity-specific domains and SC incidence. Furthermore, two-sample Mendelian randomisation (MR) analyses were conducted using genome-wide association data from multiple large-scale prospective study cohorts (UK Biobank for PA and FinnGen for SC) to elucidate potential causality. The study ultimately enrolled 77,123 participants with a mean age of 55.67 ± 7.8 years. During a mean follow-up of 6.3 years (interquartile range [IQR]: 5.3–7.3 years), 1194 incident SC cases were identified. Compared with insufficient activity, achieving 150–600 min of moderate to vigorous-intensity PA (MVPA) per week was associated with a 21

AIMS:To investigate the use of retinomics as a composite biomarker for incident heart diseases, leveraging the multidimensional relationships between vascular parameters from colour fundus photography (CFP) and neural parameters from optical coherence tomography (OCT). METHODS AND RESULTS:Feature selection was performed using LASSO regression to minimize overfitting and multicollinearity. Subsequently, the predictive value of retinomics was assessed with the Gradient Boosting Machine model and compared with the widely used WHO-CVD risk score. Associations between retinomics and incident heart diseases were analysed using Cox regression. 39 450 participants, 3310 developed heart disease over 11.4 years. Retinomics with age and sex achieved a concordance index (C-index) of 0.731 for the entire follow-up duration and a C-index of 0.761 for 5-year incident events. For the 5-year follow-up, the high-risk group (the third tertile) had a hazard ratio of 9.30 compared with the low-risk group. Compared with the WHO-CVD risk score (C-index: 0.708), the retinomic model demonstrated significantly improved discrimination (C-index: 0.736; P < 0.001). Association analysis revealed 17 retinomic features associated with the risk of incident heart diseases, even after adjusting for age, sex, and the presence of hypertension, diabetes, and obesity. CONCLUSION:Our simple model incorporating neurovascular retinomics with age and sex demonstrated good predictive performance and effective risk stratification for incident heart disease. Notably, the age at which heart disease risk increases coincide with the age at which people get eye exams due to age-related ocular conditions, making this simple model a low-cost, timely, non-invasive, and highly feasible screening tool, especially in resource-limited settings.

Artificial intelligence (AI) shows growing potential, while exploration into human–AI collaboration to optimize health outcomes remains limited. Here we investigate human–AI collaboration strategies in disease screening from a health-economic perspective. We analyse eight AI-based screening strategies in 270 human–AI collaboration scenarios in a case study of a real-world diabetic retinopathy screening programme in China. We find that ‘copilot human–AI’ screening, leveraging both AI and human expertise, is the most cost-effective strategy. Implementing an annual ‘copilot’ strategy in all ages would save US$1.32 million while gaining 14.73 quality-adjusted life years over a lifetime, yielding health benefits equivalent to a net monetary benefit of US$1.88 million per 100,000 population compared with the status quo. This strategy effectively combines the advantages of both AI and human graders, maximizing the detection of positive cases and enabling timely intervention. Our findings demonstrate the indispensable role of human involvement in maximizing clinical benefits and cost-effectiveness in AI-driven medical applications. Exploring a broad range of 270 human–AI collaboration scenarios, this study presents which strategy would provide the best benefits in terms of gained quality-adjusted life years at lower costs, based on a case study of diabetic retinopathy screening.

Presbyopia is a common age-related condition and progressive addition lenses (PALs) are a primary corrective method. This systematic review synthesised recent evidence (2015–2025) on the technical design of PALs for presbyopia, focusing on key developments in design methodologies, performance evaluation and emerging lens concepts. A systematic search of six databases (PubMed, Embase, Web of Science, Cochrane Library, Scopus and SPIE Digital Library) was conducted following PRISMA guidelines. Eligible studies addressed PALs design principles, algorithms, methodologies or optical performance evaluation. Study quality was assessed using a customised 12-dimensional framework. The review included 17 eligible studies. Four major thematic areas of advancement were identified: the maturation of freeform surface design as the primary method for creating complex optical surfaces; the evolution of strategies for the control of surface astigmatism; the development of advanced optical performance quantification techniques enabling objective quantification of lens performance and the emergence of novel lens concepts expanding design possibilities beyond conventional refractive approaches. Key progress was noted in algorithmic optimisation for the control of surface astigmatism and the shift from subjective assessment to data-driven performance validation. PAL design has evolved significantly toward customised, algorithm-driven solutions. However, challenges remain in standardising clinical fitting, understanding neural adaptation and developing personalised designs for diverse presbyopic subpopulations. Future progress will hinge on deeper interdisciplinary integration and ongoing technological innovation to evolve PALs from standardised corrections into adaptive visual wearables.