British Journal of Ophthalmology

After rejection, resubmission of scientific manuscripts often requires substantial journal-specific reformatting. We compared systematic review submission policies across high-impact ophthalmology journals and quantified policy similarity to support resubmission planning. We identified the top 50 ophthalmology journals by SCImago Journal Rank that publish systematic reviews and are not invite-only, extracted policies from author instructions using an a priori data dictionary, and computed pairwise similarity on a 0 to 1 scale using the Gower coefficient across mixed policy variables with available-case denominators for unstated fields. Policies were heterogeneous and frequently unstated. Only 29 of 50 journals (58%) stated a main-text word limit; among journals with numeric limits, the median was 4000 words (interquartile range 3500 to 5500; n = 23). Preferred Reporting Items for Systematic Reviews and Meta-Analyses compliance was explicitly required by 35 of 50 journals (70%), and prospective registration by 6 of 50 journals (12%). Across 1225 journal pairs, similarity was modest, with a median of 0.64 (interquartile range 0.57 to 0.71; range 0.05 to 0.98). Similarity among the top 5 highest-ranking journals ranged from 0.62 to 0.90 (median 0.75). Systematic review submission policies vary widely across high-impact ophthalmology journals, and most journal pairs show only modest similarity. Similarity-based guidance may help identify policy-aligned resubmission targets while anticipating common sources of reformatting burden.

Purpose: To evaluate the incidence and baseline predictors of intraocular pressure (IOP)-lowering treatment following detection of referable glaucoma by teleretinal screening. Design: Retrospective cohort study. Methods: Participants were derived from a safety-net teleretinal diabetic retinopathy screening program (2013-2024). Participants included individuals who screened positive for referable glaucoma (cup-to-disc ratio [CDR] [&ge;]0.6 or CDR asymmetry [&ge;]0.2) and completed in-office diagnostic evaluation. The primary outcome was initiation of IOP-lowering treatment (medication, laser, or surgery) and the secondary outcome was intervention with surgery. Cumulative incidence functions were estimated, accounting for loss to follow-up. Fine-Gray models were used to identify baseline screening predictors to risk stratify each outcome. Glaucoma diagnosis was approximated using diagnostic codes and chart review. Results: 2,367 participants were included. The cumulative incidence of treatment was 19.6% (95% CI: 18.0-21.2) at Year 1 and 45.1% (42.1-48.1) at Year 8. Early treatment occurred primarily in glaucoma cases, whereas treatment accumulated longitudinally in glaucoma suspects, reaching 36.5% (31.6-41.5) by Year 8. Surgery was less common (8-year incidence: 5.3%). Baseline screening data predicted treatment and surgery, enabling risk stratification. At Year 8, cumulative incidence differed substantially between high- and low-risk groups (treatment: 59.9% vs. 31.2%; surgery: 9.7% vs. 1.0%). Older age (sub-distribution hazard ratio [SHR] 1.03 per year, p<0.001), Black race (SHR 1.50, p<0.001), and personal history of glaucoma (SHR 1.90, p<0.001) were associated with treatment; Asian race was protective (0.71, p=0.03). Older age (SHR 1.06, p<0.001), worse visual acuity (SHR 5.11 per logMAR unit, p<0.001), and screening at a hospital-based site (SHR 2.46, p=0.003) were associated with surgical treatment. Conclusion: Nearly half of safety-net diabetic patients screening positive for referable glaucoma initiated IOP-lowering treatment over 8 years, while few received surgery. Baseline screening characteristics enabled risk stratification of treatment and surgery. These findings address an evidence gap about longitudinal consequences of screening and suggest that its impact extends beyond detection of prevalent glaucoma to include identification of high-risk glaucoma suspects who warrant ongoing surveillance.

ObjectiveTo evaluate outcomes of lower-energy selective laser trabeculoplasty (SLT) using a titrated energy-pigmentation (TAPE) construct. MethodsThis retrospective study analyzed de-identified clinical data of 62 eyes undergoing lower-energy SLT as part of routine care. Laser energy was titrated relative to trabecular meshwork (TM) pigmentation grade and quantified as the product of the two (TAPE score). For example, grade 2 pigmentation x 40 mJ total energy yields a TAPE score of 80. The primary outcome was intraocular pressure (IOP) at 2 months, with adjustment for baseline maximum IOP (Tmax) using analysis of covariance (ANCOVA). Durability was assessed using Kaplan-Meier survival analysis and Cox proportional hazards modeling. ResultsAfter adjustment for baseline Tmax, higher TAPE scores ([&ge;]70) were associated with lower 2-month IOP (p < 0.01) and greater likelihood of achieving [&ge;]20% IOP reduction. Over longer follow-up, higher TAPE scores were associated with fewer treatment escalation events and improved survival free of additional therapy. Low-grade anterior chamber inflammation was common, transient, and self-limited. At 3 years, 85% of eyes in the high-TAPE group remained drop-free, accounting for retreatment where applicable. No clinically significant IOP spikes or sight-threatening adverse events were observed. ConclusionsHigher energy-pigmentation (TAPE) scores were associated with improved short-term IOP reduction and greater durability following lower-energy SLT. These findings are hypothesis-generating and suggest that TM pigmentation-adjusted energy delivery may enhance biologic engagement of the trabecular outflow pathway and support prospective evaluation of individualized SLT dosing strategies.

ObjectiveTo describe the ophthalmic examination protocol within the German National Cohort (NAKO) / NAKO Gesundheitsstudie, to report the baseline profile of participants undergoing ophthalmological assessment, and to illustrate the potential of these data as a population-based open resource for artificial intelligence (AI) research in eye health. DesignBaseline analysis of ophthalmic data within the nationwide, population-based multicenter prospective NAKO study. Participants48,460 adults in the ophthalmological level 2 module of 205,053 adults enrolled in NAKO, aged 19-74 years, with mean age 48.9 {+/-} 12.5 years and 52.7% male. MethodsAll participants underwent standardized assessments of a wide range of biomedical examinations and detailed questionnaire-based data collection, including non-dilated color fundus imaging, visual acuity testing, recording of a brief ocular history. Ocular and systemic health measures were summarized using descriptive statistics. Fundus image quality and morphological features (e.g. cup-to-disc ratio, ateriole-to-venule-ratio) were assessed using open-source deep learning models. Standard deep learning architectures were trained on the fundus images to predict age, sex and blood pressure. Main Outcome MeasuresPercentage of fundus images graded as good quality; mean absolute error for age and blood pressure prediction; accuracy for sex prediction. ResultsThe analysis includes 48,460 participants who successfully completed the level 2 ophthalmological baseline examination across 18 study sites in Germany. Mean visual acuity (logMAR) was 0.01 {+/-} 0.20 (left eye) and 0.03 {+/-} 0.21 (right eye). Self-reported ocular disease prevalence was 4.2% for cataract, 2.0% for glaucoma, and 0.9% for macular degeneration. 68.2% of fundus images were classified as gradable as a consensus of four deep learning-based quality grading models Morphological features such as cup-to-disc ratio and arteriole-to-venule-ratio showed systematic differences across age groups. Standard deep learning architectures showed comparative performance to the state-of-the-art for age, sex and blood pressure prediction (2.96 MAE for age prediction, 0.84 accuracy for sex prediction, 10.78 and 7.01 MAE for systolic and diastolic blood pressure prediction). ConclusionsNAKO provides a large-scale, nationwide population-based resource with visual acuity measurements and systemic health indicators, as well as color fundus images in about 50,000 NAKO participants. The data sets the ground for studying eye health in the general adult population in Germany and can serve as a strong foundation for developing and validating AI tools in eye health research.

Purpose:To improve determination of the treatment area for the personalization of subliminal transscleral cyclophotocoagulation (SL-TSCPC) procedures in glaucoma treatment, we designed a biometry based model of the human eye to find the estimated cilary body (CB) arc length (ECBAL) and the calculated CB distance (CCBD). Methods: We developed a rotationally symmetric modified two-sphere eye model based on axial length (AL), mean keratometry (mean K), anterior chamber depth (ACD), lens thickness (LT), and white-to-white (WTW). ECBAL and CCBD were calculated for each eye. Fluence was calculated with standardized parameters. Results: Publicly accessible biometric measurements for 24,001 eyes were pooled for analysis. The mean ECBAL was 23.99+-1.8 mm. The correlations of ECBAL with AL and ACD were 0.723 and 0.754 respectively (p < 0.01). The number of eyes with an ECBAL 21.7-22.0 mm was 131 of 24,001 (0.55%). The mean CCBD was 4.21+-0.8 mm. The number of eyes with a CCBD of 3.8 mm was 1,445 of 24,001 (6.02%). Mean fluence was 120.33+-9.0 J/cm2. A mean difference of -8.18+-6.9%, ranging from -22.66% to +29.07% in fluence was observed with treating only the recommended 22 mm versus the ECBAL. Conclusions: This study demonstrated that use of 22.0 mm as the standard treatment arc length may under or overdose laser treatment in many eyes. Precise estimation or exact localization of the CB treatment area is required to accurately calculate fluence. Translational Relevance:The model proves that CB arc length is a variable while current guidelines consider it a constant

Purpose: Psychological distress is highly prevalent in glaucoma and is associated with worse adherence, reduced quality of life, and faster disease progression. However, distress is rarely assessed in ophthalmology settings due to time, workflow, and staffing constraints. We evaluated two artificial intelligence (AI)-based screening strategies, designed to efficiently identify distressed primary open angle glaucoma (POAG) patients during routine care, aiming to achieve effective, resource conscious, low burden clinical screening. Design: Hybrid retrospective cohort and prospective cross-sectional study. Participants: The retrospective cohort included >3,000 POAG patients from the Duke Ophthalmic Registry. Prospective validation was conducted in a separate 300 POAG patient cohort who completed patient-reported distress screening. Methods: Using retrospective data, a neural network model was trained to predict an electronic health record (EHR)-derived computable phenotype of distress ("silver standard"). Prospective validation used the 8-item Patient Health Questionnaire (PHQ-8) as the "gold standard." Three screening strategies were compared against PHQ-8: (1) universal PHQ-2 screening (two-item screener administered to all patients), (2) AI-only screening (fully automated EHR-based screener), and (3) sequential screening, (only patients flagged as high risk by AI screener completed the PHQ-2). Performance metrics included sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and screening burden. Main Outcome Measures: Sensitivity; specificity; PPV; NPV; accuracy; proportion of patients requiring secondary screening (screening burden). Results: Distress prevalence was 17% (PHQ-8 > 6). Universal PHQ-2 screening (> 0) achieved high sensitivity (0.96) but lower specificity (0.73) and PPV (0.41), while requiring screening of all patients. The AI-assisted sequential approach substantially reduced screening burden while maintaining strong diagnostic performance. By administering PHQ-2 to ~25% of patients, sequential screening achieved sensitivity 0.64, specificity 0.93, PPV 0.64, NPV 0.93, and accuracy 0.88, representing a ~50% increase in PPV compared to PHQ-2 alone. AI-only screening reduced burden further but did not achieve comparable sensitivity or predictive performance. Conclusions: AI-assisted sequential screening enables scalable, resource efficient identification of psychological distress in glaucoma care, substantially reducing screening burden while preserving clinically meaningful performance. This framework offers a practical pathway for integrating distress screening into routine ophthalmology workflows and improving the identification and referral of at-risk patients.

ObjectiveTo assess how whole genome sequencing and varying phenotype definitions influence genetic discovery for primary open-angle glaucoma (POAG) in a diverse population. DesignAncestry-stratified genome-wide association studies (GWASs) and cross-ancestry meta-analyses of POAG cases and controls using two phenotype definitions. ParticipantsCases (age>40) and controls (age>65) were identified in the National Institutes of Health All of Us Research Program v8 data release and sub-divided into genetically inferred ancestral groups. Using the relaxed phenotype (ICD codes only), case/control counts were: European (1,846/84,654), African (1,042/15,966), and Latino/Admixed American (305/10,167). Using the stringent phenotype (ICD codes and evidence of glaucoma treatment in the electronic health record), case/control counts were: European (1,528/79,276), African (862/14,076), and Latino/Admixed American (250/9,668). Cross-ancestry meta-analyses included 3,193 cases/110,787 controls for the relaxed phenotype and 2,640 cases/103,020 controls for the stringent phenotype. MethodsGWASs were conducted within European, African, and Latino/Admixed American ancestry groups individually using firth logistic regression with age, sex, and the top 10 genotype principal components included as covariates. The ancestry-stratified GWASs were then meta-analyzed using a fixed-effects, inverse variance-weighted approach. Main Outcome MeasuresIdentification of genome-wide significant loci (P < 5x10-8) for POAG using different phenotype definitions and ancestry groups. ResultsKnown POAG risk loci (e.g., TMCO1, CDKN2B-AS1, and GMDS) reached genome-wide significance in both the European GWASs and cross-ancestry meta-analyses (odds ratio (OR) range: 1.19-1.38). A novel risk locus near CYP2A7 (rs76935404[T], OR = 1.35) was identified in the African ancestry GWAS using the stringent phenotype definition. Effect sizes for known POAG risk loci from prior large-scale meta-analyses strongly correlated with effect sizes in this study (Pearson r = 0.75-0.84, P < 1 x 10- for all). The strength and consistency of these correlations support the robustness of the findings. ConclusionsThis study demonstrates the value of whole genome sequencing, diverse ancestry inclusion, and phenotypic refinement in uncovering novel POAG genetic risk loci. The findings underscore the need to prioritize both genetic diversity and refined case/control definitions to advance understanding of this complex ocular disease. PrecisThis study identifies a novel primary open-angle glaucoma risk locus in individuals of African ancestry using whole genome sequencing and varying phenotype definitions in the diverse All of Us Research Program dataset.

Purpose: To evaluate the impact of ''not commonly considered risk factors '' on glaucoma surgical outcomes. Methods: This study included 339 eyes that underwent glaucoma surgery. Surgical procedures included microhook ab-interno trabeculotomy (TLO), Preserflo ab-externo microshunt implantation, trabeculectomy (Trab), and Ahmed Glaucoma Valve (AGV) implantation. In addition to conventional background factors, we examined a set of ''not commonly considered risk factors, '' including very elderly age ([&ge;]85 years), avitreous status, aphakia, use of antithrombotic agents, difficulty attending frequent postoperative visits, small palpebral fissure, corneal endothelial dysfunction, poor vision in the fellow eye, dementia, hearing loss, mental illness, atopic dermatitis, pseudophacodonesis, glaucoma eye drop allergy, and conditions contraindicating {beta}-blocker use. Surgical success was defined as intraocular pressure (IOP) [&le;]21 mmHg, [&ge;]20% reduction from baseline, and no additional glaucoma surgery at 1 year. Logistic regression was performed to identify potential risk factors; significant factors were further evaluated using propensity score matching. Results: Of the 339 cases, surgical success rates were 65% for TLO, 82% for Preserflo, 91% for Trab, and 82% for AGV. Multivariate logistic regression identified two independent predictors of surgical failure: small palpebral fissure (odds ratio 2.52, p < 0.01) and hearing loss (odds ratio 3.94, p = 0.04). Propensity score matching of patients with small versus large palpebral fissures (111 per group) confirmed significantly worse postoperative outcomes in the small-palpebral-fissure group despite balanced baseline characteristics. Conclusion: Small palpebral fissure is an independent and previously unnoticed risk factor for glaucoma surgical failure, affecting both minimally invasive and filtration procedures.

Purpose To investigate the relative efficacy of nine distinct visual field (VF) denoising artificial intelligence (AI) methods and a pathology-aware AI strategy to discourage over-correction of glaucomatous defects. Design Retrospective study. Participants 87,940 paired visual field (VF) and optical coherence tomography (OCT) samples from a tertiary academic center. Methods Denoising models were trained on a separate VF-only dataset and evaluated on an independent structure-function dataset of paired VF-OCT samples. We implemented and evaluated nine distinct VF denoising strategies representing three broad categories: baseline measurements, self-supervised and image restoration models (including Noise2Noise, Noise2Void, and NAFNet), and latent variable compression-based models (autoencoders and variational autoencoders). All models were designed to reconstruct VF sensitivity maps. We then predicted retinal nerve fiber layer thickness (RNFLT) maps from the denoised VFs using a fixed, independently trained VF-to-RNFLT prediction model. Main Outcome Measures Predicted VF and RNFLT maps and resultant evaluation metrics. Results The raw VF baseline achieved a global R2 of 0.5468 and MAE of 16.83 um. Restoration-based models maintained or slightly improved concordance, with the pathology-aware NAFNet achieving the highest global R2 of 0.5485 and a comparable MAE of 16.82 um. In contrast, compression-based models degraded concordance, with CNN-VAE showing a significant reduction (R2 approximately 0.50). In severe glaucoma, concordance decreased across all methods; however, compression architectures exhibited disproportionately greater degradation compared with restoration-based approaches. Conclusions We present a comparative benchmark of AI-based VF denoising strategies paired with structure-function evaluation. While restoration-based models can reduce variability without loss of biological signal, latent compression risks attenuating clinically meaningful defects. Visually smoother fields are not necessarily more biologically accurate.

Background/Aims: Neovascular glaucoma (NVG) is an aggressive secondary glaucoma with limited longitudinal data. This study reports the aetiologies, treatments, and longitudinal outcomes in NVG. Methods: Patients with NVG were identified through electronic medical record review. Inclusion required documented rubeosis of the iris and/or anterior chamber angle, intraocular pressure (IOP) [&ge;]25 mmHg, diagnosis during 2008-2024, and follow-up at Helsinki University Hospital. Baseline data and all follow-up visits were included. Results: Of 919 patients identified, 626 met inclusion criteria, with a median follow-up of 24 months. The estimated NVG incidence was 2.2/100,000/year. The most common aetiology was central retinal vein occlusion (CRVO; 45%), followed by diabetic retinopathy (DR; 14%), central retinal artery occlusion (CRAO; 11%), and ocular ischaemic syndrome (8%). Half of patients had hand motion vision or worse at baseline, with 18% at no light perception (NLP). At 5 years, 13% of patients had Snellen 6/60 vision or better. Visual outcomes differed by aetiology, with median time to NLP ranging from 1.6 (CRAO) to 9.1 (DR) years (log-rank p=0.002). Median baseline IOP was 40 mmHg, decreasing to 21 mmHg by 1 year. Ocular pain fell from 43% at baseline to 11% at last follow-up. Structural eye loss (e.g., enucleation or phthisis) occurred in 3% by 5 years. Conclusion: The estimated incidence was lower than previously reported elsewhere. Unlike other cohorts where DR predominates, CRVO was the most common aetiology, and visual prognosis was strongly aetiology-dependent. Glaucoma drainage device surgery reached 7.6% at 3 years, despite the severity and refractory nature of NVG.

BackgroundNeurotrophic keratopathy (NK) is a rare degenerative corneal disease caused by impaired trigeminal innervation, resulting in reduced corneal sensation, impaired epithelial healing, ulceration, and risk of perforation or vision loss. Corneal innervation is essential for protective reflexes, epithelial maintenance, and ocular surface homeostasis. Conventional medical therapies may promote epithelial healing but do not directly restore corneal innervation. Corneal neurotization (CN) has emerged as a surgical strategy in which healthy donor sensory axons are transferred to denervated corneas to provide innervation. Multiple procedural variations now exist, including differences in donor nerve selection, graft use, and methods of limbal nerve insertion. A broad variety of NK etiologies is also being treated, including congenital, infectious, tumor, or other causes. However, published evidence remains limited by small case series, heterogeneous surgical methods, short follow-up periods, and inconsistent outcome reporting. ObjectiveTo address the need for standardized long-term outcome data in CN, we established the Corneal Neurotization Assessment (CorNeA) Registry, an international multicenter observational registry designed to evaluate patients undergoing CN. MethodsThe CorNeA Registry captures demographic characteristics, disease etiology, surgical technique, and longitudinal ocular outcomes in patients with NK treated with CN. Data are recorded in REDCap and include both retrospective and prospective patient enrollment across participating centers. Patients are followed longitudinally after surgery without a predefined endpoint to permit long-term assessment of corneal sensation recovery, ulcer recurrence, and visual outcomes. At the time of reporting, the registry includes 58 patients from multiple international centers, with active expansion ongoing. ConclusionBecause NK is rare and CN remains an evolving surgical field, long-term comparative data are lacking. The CorNeA Registry provides the first international platform to characterize patient selection, procedural variation, and long-term outcomes after CN, with the goal of informing future surgical decision-making and outcome standardization.

ObjectiveThe study aims to evaluate the real-world effectiveness of Highly Aspherical Lenslets spectacle (HAL; Essilor(R) Stellest(R)) in slowing myopia progression among Indian children and adolescents aged between 4 and 16 years. Methods and analysisThis was a multicentre retrospective study conducted across 10 leading ophthalmic centers. The study participants comprised children aged between 4 and 16 years who were prescribed HAL spectacles (Essilor(R) Stellest(R)). Data were extracted from electronic medical records at three time points: T1: One year prior to intervention; T2: Baseline at HAL spectacle prescription; T3: 6 to 24 months after prescription. The primary endpoint was the myopia progression and axial elongation in the year following prescription, compared with the untreated year and with published meta-regression models. Only data from the right eye were analysed, with the expected physiological progression estimated based on the individual progression trajectory after adjusting for age-related slowing as reported in published meta-regression models. ResultsA total of 372 myopic children were included in the study. The annual myopia progression was -0.72 {+/-} 0.47 D/year during the untreated period, reducing to -0.11 {+/-} 0.29 D/year with HAL spectacle wear. The expected progression without treatment was -0.65 D/year, based on trajectory-adjusted modelling, indicating a treatment effect of 0.54 D/years and an estimated 83% slowing in myopia progression compared to expected progression. The expected axial elongation under physiological conditions was 0.29 mm/year, estimated using age-adjusted meta-regression models; with HAL lens wear, axial elongation was 0.11 {+/-} 0.16 mm/year, corresponding to a [~]62% relative slowing of elongation. ConclusionThe present study demonstrates the real-world evidence validating the efficacy of HAL lenses as an effective myopia control intervention in Indian children and adolescents. The retrospective design and limited follow-up period warrant future prospective, long-term studies to validate these findings.

PurposeTo evaluate the performance of machine learning models for automated glaucoma detection using multimodal clinical, structural, and functional data from a West African clinical cohort. MethodsIn this retrospective observational study, we analyzed clinical records from two major eye care centers in Ghana. A total of 605 eyes from 417 patients who underwent comprehensive glaucoma evaluation were included. Extracted features included demographic data, intraocular pressure, optical coherence tomography (OCT) structural parameters, and Humphrey visual field indices. We assessed the diagnostic performance of individual parameters using receiver operating characteristic (ROC) analysis. Supervised machine learning classifiers, including support vector machine (SVM), random forest (RF), gradient boosting machine (GBM), and a multi-layer perceptron (MLP), were trained using a forward feature selection approach and evaluated using five-fold cross-validation. We assessed model performance by computing performance metrics like sensitivity, specificity, and area under the ROC curve (AUC). ResultsAmong the 605 eyes analyzed, 361 (59.7%) were glaucomatous, and 244 (40.3%) were healthy. Individual structural and functional parameters demonstrated moderate discriminative ability, while age showed no significant diagnostic value (AUC = 0.49, p = 0.841). Among machine learning models, the MLP achieved the highest diagnostic performance (AUC = 0.90 [95% CI: 0.86-0.92], sensitivity = 0.88, specificity = 0.86), outperforming SVM (AUC = 0.82), RF (AUC = 0.78), and GBM (AUC = 0.77). Multimodal integration of clinical, structural, and functional features improved discrimination compared with individual parameters. ConclusionsMultimodal machine learning models can effectively automate glaucoma detection using routinely collected clinical data. In this West African cohort, an MLP-based approach demonstrated superior diagnostic performance compared with traditional machine learning models and individual clinical metrics. These findings highlight the potential of clinically grounded artificial intelligence tools to support glaucoma diagnosis and triage in resource-constrained eye care settings.

PurposeConventional polygenic scores predict an individuals phenotype based on their genetics. By contrast, variance polygenic scores (vPGS) quantify genetic predisposition to phenotypic variance. We tested the hypothesis that a vPGS for refractive error can identify individuals with increased susceptibility to environmental risk factors for myopia. MethodsSix vPGS construction strategies were evaluated in UK Biobank participants: three variance heterogeneity genome-wide association studies (vGWAS) methods and two reweighting schemes. vPGS performance was assessed using two metrics: (i) Diff - difference in phenotypic variance in vPGS decile one vs. ten; (ii) Spearman correlation of phenotypic variance vs. vPGS decile. The optimal vPGS was used to test for vPGS x time spent reading or vPGS x time spent outdoors interactions in children aged 15 years (ALSPAC cohort; n=3471). ResultsOf the vGWAS methods, conditional quantile regression outperformed SCAMPI and Levenes Test. Of the re-weighting schemes, LDpred2 outperformed pruning and thresholding (P+T). In an independent sample of UK Biobank participants (n=19470), the top-performing vPGS successfully stratified individuals into groups with increasing variance in refractive error, even after adjusting for a conventional PGS (Diff: 2.55, 95% CI: 1.64-3.47; Spearman correlation: 0.87, 95% CI: 0.43-0.93). However, in ALSPAC participants, there was minimal support for vPGS interactions with time reading (P=0.80) or time outdoors (P=0.89). ConclusionA novel vPGS successfully stratified individuals into groups with relatively high or low genetic susceptibility to refractive error variance. However, the vPGS could not identify individuals at enhanced risk from lifestyle risk factors for myopia.

PurposeTo evaluate the retinal safety of repeated low-level red-light (RLRL) therapy using the Eyerising Myopia Management Device (EMMD) by analysing exposure parameters relative to established thermal and photochemical retinal injury thresholds and empirical human exposure data. MethodsEmission characteristics of the EMMD were measured in an accredited laboratory under worst-case conditions. Parameters assessed included wavelength, intraocular power, corneal irradiance, and retinal image characteristics across accommodative states. These measurements were compared with international safety standards, maximum permissible exposure limits, and experimentally derived retinal injury thresholds from animal studies and validated computational models. The effects of repeated exposures from RLRL therapy using the EMMD were evaluated using photochemical additivity principles and repair kinetics, and further contextualised using human volunteer exposure data. ResultsThe EMMD emitted red laser radiation at 654-655 nm with a maximum intraocular power of approximately 1 mW through a 7 mm pupil, placing it within Class 3R and marginally above the Class 2 limit. Corneal irradiance was approximately 26 W m- 2, well below conservative photochemical exposure limits. Thermal injury modelling indicated retinal damage thresholds above device exposure, including under worst-case assumptions of minimal retinal image size and absence of eye movements. Accounting for repeated daily exposures and photochemical additivity, safety margins remained approximately 3-fold for a 7 mm pupil and approximately 8-fold for a more realistic 4 mm pupil. Human volunteer studies demonstrated no detectable structural or functional retinal injury at exposure levels approximately five times higher than those produced by the EMMD. ConclusionExposure parameters of RLRL therapy using the EMMD remain well below conservative retinal injury thresholds under prescribed use conditions. Integration of experimental, modelling, and human data indicates substantial safety margins, supporting its safe clinical use.

Purpose: To develop and evaluate a deep learning model that predicts optical coherence tomography (OCT)-equivalent retinal nerve fiber layer thickness (RNFLT) maps directly from color fundus photographs and to assess their diagnostic value for glaucoma detection. Design: Retrospective model development and evaluation study. Participants: 15,031 paired fundus photographs and spectral-domain OCT scans collected at Massachusetts Eye and Ear between 2011 and 2022. Methods: Paired fundus and OCT images were used to train a U-Net-based model to predict pixel-wise RNFLT maps with artifact-corrected supervision. Diagnostic performance was evaluated across single-modality models (fundus photos only, real RNFLT maps, predicted RNFLT maps) and multimodal fusion models (fundus + predicted RNFLT maps). Stratified analyses examined model performance across glaucoma severity and demographic subgroups. Glaucoma was defined based on standard criteria applied to Humphrey 24-2 visual field testing. Main Outcome Measures: Mean absolute error (MAE) and structural similarity index (SSIM) for RNFLT map prediction. Area under the ROC curve (AUC) and accuracy for glaucoma detection. Results: RNFLT map prediction achieved a MAE = 15.4 m and a SSIM = 0.65, measured against artifact-corrected RNFLT maps derived from OCT. For glaucoma detection, the predicted RNFLT-only classifier outperformed the fundus-only classifier (AUC 0.889 vs 0.883, p < 0.005; Accuracy 82.0% vs 78.0%), but performed worse than the real-RNFLT-only classifier (AUC 0.889 vs 0.903, p < 0.005). Multimodal fusion of fundus images with predicted RNFLT maps improved performance, achieving an AUC of 0.909, outperforming all single-modality inputs (p < 0.005 vs fundus-only, predicted-RNFLT-only, and real-RNFLT-only). Performance gains between the fundus-only and the multimodal classifier were greater in early-stage glaucoma compared to severe cases: accuracy increased from 55.3% to 64.0% in mild cases, from 71.5% to 80.4% in moderate cases, and from 90.0% to 94.6% in severe cases. Conclusions: Predicted RNFLT maps derived from fundus photographs provide quantitative, OCT-like structural information and improve glaucoma detection. Unlike prior work that predicted only summary RNFLT values, our model generates full RNFLT maps that better support glaucoma classification than fundus images alone. This approach offers a scalable pathway for early glaucoma screening and expands diagnostic access in resource-limited settings.

PurposeTo identify the ocular biometric parameters associated with refractive outcomes in Chinese Primary angle closure glaucoma (PACG) patients receiving phacoemulsification and intraocular lens (IOL) implantation (PEI) surgery. Methods165 Chinese PACG patients receiving PEI and goniosynechialysis (GSL) and 53 cataract patients as controls only receiving PEI surgery were recruited. The prediction accuracy of IOL power calculation was assessed by the prediction error (PE), mean absolute error (MAE), median absolute error (MedAE), and proportions of eyes with a PE within {+/-} 0.25 diopters (D), {+/-} 0.50 D, {+/-} 0.75 D, and {+/-} 1.00 D. The association of different ocular biometric parameters with the PE of IOL calculation were evaluated. ResultsThe PACG patients had significantly higher absolute of PE as compared to the control subjects, especially the acute PACG patients. The axial length (AL), changes in aqueous depth pre- and post-surgery ({bigtriangleup}AD), and the ratio of {bigtriangleup}AD/AL were significantly associated with the PE in acute PACG patients. The association of {bigtriangleup}AD with the PE of IOL power calculation was found in PACG patients with AL [&ge;] 22 mm. ConclusionsThis study revealed the association of AL and {bigtriangleup}AD with the PE of IOL calculation in Chinese PACG patients. Precisely predict the {bigtriangleup}AD is necessary for acute PACG patients, especially for those with AL [&ge;] 22 mm, to improve the refractive outcomes.

To determine whether achieving normal corrected visual acuity independently influences myopia progression in school-aged children wearing single-vision spectacles. In a one-year real-world cohort study, 9-year-old myopic children were classified into three groups: uncorrected, adequately corrected (normal visual acuity), and under-corrected (subnormal visual acuity). One-to-one propensity score matching was used to balance baseline characteristics, and annual axial length growth was compared. The adequately corrected group showed the slowest axial elongation (0.23 {+/-} 0.14 mm/year), significantly less than both the under-corrected (0.35 &{+/-} 0.14 mm/year) and uncorrected groups (0.37 &{+/-} 0.16 mm/year) (all P < 0.001). Although the under-corrected group exhibited marginally slower progression than the uncorrected group, this minimal benefit was not sustained in semiannual analyses and lacked clinical relevance. Simply prescribing spectacles is insufficient for myopia control; achieving normal corrected visual acuity is essential to meaningfully slow axial elongation.

BackgroundEpidermal Growth Factor Receptor (EGFR) inhibitors, while effective in oncology, are associated with under-characterized ocular adverse events (AEs). Prior studies have been limited in scope, lacking a comprehensive, class-wide analysis of the full spectrum of ocular toxicity, particularly for newer agents. MethodsWe conducted a disproportionality analysis of the FDA Adverse Event Reporting System (FAERS) (2001-2025). Twelve EGFR-targeted agents were evaluated against a pre-specified set of ocular MedDRA Preferred Terms. To ensure robust signal detection, a significant association was defined by [&ge;]3 co-reported cases, a Proportional Reporting Ratio (PRR) [&ge;]2.0, and a false-discovery-rate adjusted p-value <0.05. ResultsAmong 6,976,462 drug-event combinations, 20 met all signal criteria for Eyelash Abnormalities, Ocular Surface Disease, or Vision-Threatening and Intraocular Events. Trichomegaly demonstrated extreme disproportionality (e.g., panitumumab PRR= 465.3, 95% Confidence Interval [CI], 247.7-874.3). A consistent pattern of ocular surface toxicity (conjunctivitis, keratitis, blepharitis) was observed across multiple tyrosine kinase inhibitors and monoclonal antibodies, indicating a class-wide effect. Signals for serious events included corneal perforation (erlotinib, n= 7, PRR=13.9, 95% CI= 6.6-29.4) and optic neuropathy (erlotinib, n= 6, PRR= 2.9, 95% CI= 1.3-6.4). ConclusionThis analysis confirms a strong, class-wide signal for ocular toxicity across the spectrum of EGFR inhibitors, from characteristic eyelid changes to sight-threatening complications. These findings underscore the necessity for proactive ophthalmologic monitoring, including baseline assessment, in patients receiving these therapies to preserve vision and maintain quality of life during cancer treatment.

Purpose: To quantify the binocular integrated visual field (IVF) loss patterns with archetypal (AT) analysis and their associations with patients' Quality of Life (QoL). Design: Retrospective study. Participants: Over 125,000 patients from three datasets from Massachusetts Eye and Ear and Glaucoma Research Network Consortium. Methods: We used: (1) the Glaucoma Research Network excluding the Massachusetts Eye and Ear subset for the binocular archetypal model training (77, 270 IVFs from 77 270 patients), (2) Massachusetts Eye and Ear dataset for demographic correlation analysis (47,965 IVFs from 47,965 patients), and (3) the MEE Quality of Life Survey dataset for QoL correlation analysis (75 IVFs from 75 patients). The whole study was restricted to the most recent VF measurements from each subject and binocular VFs were constructed by the integrated visual field method, which was taking the higher sensitivity at each test location. We first applied archetypal analysis to cluster 24-2 binocular VFs into archetypal patterns. The total number of patterns was determined by the Bayes factor. Pearson's correlations analyzed the associations between patients demographic information, binocular VF patterns and QoL scores, and the coefficients were set to 0 if p-values corrected by multiple comparisons < 0.05. Main Outcome Measures: A binocular VF archetypal patterns and its relationships with demographic divergences and QoL. Results: We identified 17 binocular VF loss patterns. Patterns with major vision impairment (AT10, AT12, AT13, AT14, and AT17) were more common in older patients, while Black or African Americans exhibited a broader spectrum of visual loss, notably AT5 and AT12, compared to Asian and White counterparts. 81 MEE patients with QoL survey data was analyzed to investigate the impact of demographic and vision-related variables on QoL. Older age and female gender were significantly associated with lower QoL. Binocular central vision loss (AT 5) and total vision loss (AT 12) had a significantly greater impact on QoL than binocular peripheral vision loss (AT 2, AT 5, AT 16). Conclusions: Individuals with central or total vision loss, as well as certain demographic groups, experience a significantly greater impact on quality of life. The quantifications of binocular VF loss patterns by archetypal analysis may help better understand glaucoma's impact on patients' quality of life.