British Journal of Ophthalmology

This prospective, multicenter, real-world evidence study evaluates the 12-month safety and effectiveness of standalone cyclodialysis with AlloFlo cleft reinforcement for intraocular pressure (IOP) reduction in open-angle glaucoma (OAG). AlloFlo represents the worlds first acellular, allogenic scleral tissue implant, and data from this CREST Study cohort (NCT05506423) contribute critical long-term safety and effectiveness knowledge to the field of extracellular matrix biomaterials research, in addition to describing a novel procedure for surgical management of OAG. Eyes with investigator-confirmed inadequately controlled OAG were treated with standalone cyclodialysis using a microsurgical cannula (CycloPen), followed by uveoscleral cleft reinforcement with AlloFlo. Eyes were followed prospectively for 12 months. Key outcomes included changes in medicated IOP, number of glaucoma medications, adverse events, and progression to subsequent glaucoma procedures. Forty-one eyes of 38 patients were included. Most eyes (66%) were considered treatment-refractory, defined as having any of: failed [&ge;] 1 incisional surgery or cilioablative procedure; condition in which incisional surgery would be more likely to fail than in eyes with uncomplicated OAG. At 12 months, mean IOP decreased 31% to 14.7 {+/-} 6.9 mmHg (within the normal IOP range of 10-20 mmHg, p < 0.001); mean number of glaucoma medications decreased 32% to 1.9 {+/-} 1.6 (p < 0.001). Seventy-one percent of eyes achieved [&ge;] 20% IOP reduction (a clinically meaningful benchmark set by the FDA). More than half of eyes (53%) achieved [&ge;] 20% IOP reduction without increasing medication. Three eyes (7.2%) progressed to incisional glaucoma surgery. Postoperative IOP elevations [&ge;] 10 mmHg occurred in 17% of eyes, most of which resolved within 30 days of the procedure. No persistent inflammation, implant rejection, clinically significant hyphema, or scaffold migration occurred. These findings suggest that uveoscleral outflow enhancement with AlloFlo provides a safe, conjunctiva-sparing option for IOP reduction in OAG, including eyes with prior surgical interventions.

BackgroundAchieving precise postoperative refractive outcomes remains a significant challenge in cataract surgery. While advanced intraocular lens (IOL) power calculation formulas exist, they are constrained by their singular algorithmic structures. This study investigated whether a stacking ensemble machine learning approach could overcome these limitations. MethodsA dataset of 1,710 eyes from patients who underwent cataract surgery with monofocal IOL implantation (Vivinex or SA60AT) was utilized. Following rigorous preprocessing and feature engineering, a stacking ensemble architecture was developed comprising three diverse base learners (Multi-Layer Perceptron, Support Vector Regressor with RBF kernel, and SplineTransformer with Linear Regression) and a Ridge Regressor meta-learner. The model was trained on 80% of the data using 5-fold cross-validation and evaluated on an independent 20% test set (n=341). Performance was compared against six standard IOL formulas. ResultsThe stacking ensemble model demonstrated excellent predictive accuracy, achieving a Mean Absolute Error (MAE) of 0.272 D on the independent test set (n=341). The model achieved lower MAE compared to all six standard IOL formulas, including Kane (MAE 0.295 D) and Barrett Universal II (MAE 0.318 D). Clinically, 85.1% of eyes achieved predictions within {+/-}0.50 D, compared to 82.5% for Kane formula and 81.8% for Barrett Universal II. ConclusionThe stacking ensemble machine learning model significantly enhances postoperative refraction prediction accuracy compared to established IOL calculation formulas. By leveraging algorithmic diversity and data-driven learning, this approach represents a promising advancement toward reducing refractive surprises and improving patient satisfaction in cataract surgery. External validation on independent datasets is required to confirm generalizability.

PurposeThe interpupillary distance is a measure of the width of the orbit and is important for spectacle design and proper head-mounted displays in virtual reality. Extreme interpupillary distances may predispose to horizontal strabismus. The interpupillary distance is thought to differ between ethnicities, but global data on this parameter have not been systematically explored, mapped and compared. MethodologyWe performed a systematic review that compiled 242 studies reporting the interpupillary distance and mapped the data geographically. We then compared the regional distribution of the mean interpupillary distance with the distribution of horizontal strabismus patterns. The strabismus data, obtained from our previous systematic review of the literature, were used to map the relative frequency of esotropia and exotropia according to 301 population-based studies. The mean interpupillary distance and esotropia/exotropia ratio of major ethnicities were then analyzed by meta-regression analyses to determine an association between the two parameters. ResultsInterpupillary distances are larger in Western Africa, South India, East Asia, in Latinos/Hispanics, in Native and African Americans, and they are smaller in Europe, North Africa, the Middle East, Northwestern India, and in Inuit populations. Regression analyses revealed an association between the interpupillary distance and the esotropia/exotropia ratio with R2 values of 0.320 (major ethnicities) and 0.410 (populations at higher resolution). ConclusionThe mean interpupillary distance varies significantly between ethnicities. Orbital anatomical parameters contribute to diverse horizontal strabismus patterns. Our findings may aid in the design of appropriate spectacles and the optimal size of head-mounted displays, and help to better understand the pathogenesis of horizontal strabismus. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/25343217v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@14cf7d6org.highwire.dtl.DTLVardef@232e5aorg.highwire.dtl.DTLVardef@1b82f66org.highwire.dtl.DTLVardef@12ffd81_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

PurposeAspheric planning in laser refractive surgery remains difficult: surgeons often rely on empirical nomo-grams or simple linear regression for defocus and astigmatism, while console Q-factor modulation yields a variably predictable effect on asphericity and an inconsistent cross-effect on defocus. This translational methods proof-of-concept frames planning as supervised prediction of console-programmable inputs (de-focus, astigmatism, Q-factor) and evaluates competing models; it is not a clinical effectiveness study. MethodsWe analyzed an anonymized, retrospective, single-platform dataset of 2,448 complete-case treatments. Multi-output regressors (linear and nonlinear) were trained and compared using prespecified metrics (R2, MAE/MSE) and residual-distribution visualization/calibration. Actuator-response checks related programmed inputs to changes in defocus (Z20) and primary spherical aberration (Z40). External validation used a temporally later, device-shift cohort (n=147). ResultsLinear regression predicted defocus and astigmatism well (e.g., defocus R2=0.98) but degraded for Q-factor (R2=0.47), whereas nonlinear models improved Q-factor error and calibration. Actuator-response analyses showed strong coupling for defocus input (R2=0.97), moderate coupling of Q-factor to {Delta}Z40 (R2=0.51), and a weak Q[-&gt;]defocus cross-effect (R2=0.12). On external validation, the best model generalized: Defocus MAE 0.22 D (R2=0.98) and Q-factor MAE 0.21 (R2=0.81). ConclusionsSupervised nonlinear multi-output models achieve lower error and better calibration for Q-factor than linear baselines, supporting a metric-driven pathway toward more reliable control of low-order refractive targets and primary asphericity. Potential clinical implications include tissue sparing, improved contrast, and near-vision gains. Prospective, human-in-the-loop evaluation with safety and patient-reported endpoints is warranted.

ImportanceEarly intraoperative warning signs of zonular instability during cataract surgery, such as anterior capsular radial folds, are subtle and easily missed but are clinically important for preventing surgical complications. Whether current artificial intelligence (AI) systems can reliably detect such subtle warning signs in real-world surgical video remains unknown. Recently, automated AI model generators have become available, enabling the automatic construction of task-specific AI models for individual clinical tasks. ObjectiveTo evaluate the diagnostic performance of general-purpose and automated task-specific artificial intelligence systems for detecting anterior capsular radial folds during cataract surgery and to compare their performance with human clinicians. Design, Setting, and ParticipantsThis retrospective diagnostic study used 537 continuous curvilinear capsulorhexis (CCC) video clips collected from Beijing Tongren Hospital (China), National University Hospital (Singapore), and the OphNet-APTOS public dataset. ExposurePresence or absence of anterior capsular radial folds during CCC, annotated at both clip and frame levels by senior glaucoma surgeons based on expert consensus. Main Outcomes and MeasuresDiscrimination between fold-positive and fold-negative cases was assessed using macro-averaged precision, recall, and F1 score at the frame and clip levels. Performance was compared among general-purpose AI systems, task-specific models generated by an automated AI model generator, and human graders with different levels of clinical experience. ResultsAmong 537 video clips (mean 7.32 seconds), 156 (29.1%) were fold-positive. General-purpose AI systems showed limited and inconsistent performance; the best-performing model achieved a mean F1 score of 0.519, and fine-tuned models remained inferior to human graders (maximum F1 score, 0.606). In contrast, task-specific models generated by an automated AI model generator achieved substantially higher performance (F1 score, 0.869; area under the receiver operating characteristic curve, 0.958). In head-to-head comparison with clinicians, the top automated task-specific model (F1 score, 0.835) matched the performance of junior specialists (mean F1 score, 0.829) but remained below that of senior specialists. Conclusions and RelevanceGeneral-purpose artificial intelligence systems do not reliably detect subtle intraoperative warning signs during cataract surgery and consistently underperform human clinicians. In contrast, recently available automated AI model generators enable the creation of task-specific models with near-junior specialist performance. These findings suggest that clinically reliable surgical AI is more likely to be achieved through automated generation of task-specific models rather than through general-purpose AI systems. Although evaluated in cataract surgery, these findings highlight a broader challenge for artificial intelligence in detecting brief, low-contrast intraoperative warning signs in surgical video. Key PointsO_ST_ABSQuestionC_ST_ABSHow reliably can general-purpose artificial intelligence (AI) systems and task-specific AI models generated by an automated AI model generator detect subtle intraoperative warning signs during cataract surgery compared with human clinicians? FindingsIn this multicenter diagnostic study of 537 cataract surgery video clips, general-purpose AI systems were unreliable and consistently underperformed human clinicians in detecting anterior capsular radial folds. In contrast, task-specific AI models generated by an automated AI model generator--a technology that has only recently become available--achieved substantially higher diagnostic performance and matched the performance of junior specialists. MeaningGeneral-purpose AI systems show limited reliability for detecting subtle intraoperative warning signs during cataract surgery. The recent availability of automated AI model generators enables a new paradigm of task-specific model development and represents a more clinically viable path for surgical decision support.

AimTo assess the relationship between pointwise visual field (VF) sensitivity fluctuation and localised glaucoma progression. MethodsRetrospective observational analysis of prospective cohort data from 399 participants (641 eyes) in the African Descent and Glaucoma Evaluation Study (ADAGES). Glaucoma, glaucoma suspect, and control participants underwent annual examinations including VF testing. VF fluctuation was evaluated using the pointwise standard deviation (SD) of total deviation (TD) residuals during the early 30-month period. Pointwise progression was defined independently at each location as a confirmed sensitivity loss >7 dB. The primary outcome was the association between early fluctuation and subsequent pointwise progression. We additionally evaluated whether the early pointwise rate of change (slope) strengthened this association. ResultsOf 33,332 VF points, 5.8% showed progression over 12.2 {+/-} 3.1 years. Progression occurred more frequently in glaucoma (15.6%) than in suspects (1.6%) or controls (0.4%) (p<0.0001). In glaucomatous eyes, progressive points demonstrated greater early fluctuation (median 1.75 dB; IQR 1.52-2.00) than non-progressive points (1.14 dB; IQR 0.97-1.34; p<0.0001) and faster early slopes (-0.65 vs 0.08 dB/year; p<0.0001). In multivariable mixed-effects models, higher early fluctuation ({beta} = 0.40 {+/-} 0.02; p<0.0001) and faster early slopes ({beta} = - 0.40 {+/-} 0.02; p<0.0001), but not baseline TD (p=0.92), were associated with progression. Conclusions: Greater early pointwise VF fluctuation independently predicted future localised progression. The slope analysis mirrored these findings, indicating that early functional variability reflects underlying local instability. These results support early pointwise fluctuation as a predictor of glaucoma progression and a potential endpoint for clinical trials.

PurposeTo systematically evaluate ocular biometric and systemic laboratory factors associated with cataract in highly myopic eyes and to characterize potential nonlinear associations using an interpretable machine learning approach, thereby providing deeper mechanistic insights into the pathogenesis of highly myopic cataract. DesignA cross-sectional study encompassed 770 eyes of 594 patients with high myopia from Eye & ENT Hospital of Fudan University. SubjectsThe non-cataract control group included 458 eyes while the cataract group contained 312 eyes. MethodsDemographic traits, ocular biometric and systemic laboratory factors were gathered while features with over 30% of missing data were excluded. Composite indices were obtained through calculation. Multiple machine learning models were compared to investigate the association between features and highly myopic cataract, and the random forest (RF) model was chosen and fine-tuned. Feature selection was carried out by means of Shapley additive explanations (SHAP) and non-linear relationships were probed using SHAP dependence diagrams and confirmed with partial dependence plots. Main Outcome Measures(1) The Area Under the Curve (AUC) and other metrics of multiple machine learning models; (2) Top feature importance of the final simplified RF model; (3) Overall trends between features and highly myopic cataract; (4) Potential inflection points of top continuous features. ResultsA simplified fine-tuned RF model with 17 features reached stable discriminative performance, with a mean AUC of 0.762 (95%CI: [0.731, 0.794]) among 10 independent testing sets. Age and axial length (AL) turned out to be the most influential features which had non-linear relationships highly myopic cataract, with an inflection point seen around 65.75 (95%CI: [63.72, 67.79]) years for age and 30.55 (95% CI: [29.22, 31.88]) mm for axial length respectively, while the ratio of anterior chamber depth to axial length (ACD/AL) was associated with highly-myopic cataract in a U-shape. Ocular biometric factors were more strongly related to highly myopic cataract than systemic laboratory factors. ConclusionsOcular biometric factors, especially age, AL, and composite indices like ACD/AL, have strong and non-linear connections with highly myopic cataract. These results emphasize the significance of ocular structural arrangement in cataract within highly myopic eyes and indicate that interpretable data-driven methods could offer clinically relevant understandings regarding its phenotypic description.

The prevalence of the two types of horizontal strabismus, esotropia and exotropia, varies considerably between studies. This variability has been attributed to factors such as geography/environment, research methodology, age of study subjects, and/or ethnicity. Comprehensive estimates of regional and global prevalences of esotropia and exotropia are lacking, making it difficult to recognize true patterns, trends, and etiologies. Our systematic review compiles prevalences and ratios of esotropia to exotropia from 315 population-based studies and 374 clinic-based studies. We analyze data to assess effects of ethnicity, geography, age, and identify generational changes of horizontal strabismus. Major ethnicities differ in patterns and ratios of esotropia and exotropia prevalence, not only Caucasians and East Asians, but also Latinos/Hispanics, South Asians, Africans, and Native Americans. Compared to population-based studies, clinic-based studies underestimate exotropia frequency. By weighing prevalences according to the population size of ethnicities, we estimate the worldwide prevalence of horizontal strabismus in the current generation at 1.81% (138.5 million), comprising 60.0 million people with esotropia (0.67%) and 87.5 million with exotropia (1.14%). In the previous generation, the worldwide prevalence of horizontal strabismus was 1.64% (86.5 million people), comprising 50.5 million with esotropia (0.96%) and 36.0 million with exotropia (0.68%). Generational trends in esotropia and exotropia prevalences differ between ethnicities, indicating that extrinsic factors can modify the underlying intrinsic (genetic) disposition.

PurposeTo evaluate the diagnostic performance of anterior segment optical coherence tomography (ASOCT) compared to slit lamp examination for identification of corneal perforation in microbial keratitis, and to assess ASOCT grading reproducibility. MethodsWe conducted a diagnostic concordance study of 150 eyes with microbial keratitis at a tertiary eye hospital in India. Two masked graders independently evaluated ASOCT scans for perforation, with disagreements resolved by consensus. We calculated Cohens kappa for inter-grader concordance and intra-grader repeatability. Sensitivity and specificity of slit lamp examination were calculated using ASOCT as the reference standard. Logistic regression identified factors associated with disagreement between modalities. ResultsInter-grader agreement for ASOCT was near-perfect ({kappa}=0.98; 95% CI, 0.92-1.00). ASOCT identified perforation in 24 eyes (16.0%) compared to 12 eyes (8.0%) by slit lamp examination. Using ASOCT as reference, slit lamp examination demonstrated 33.3% sensitivity (95% CI, 14.9-52.2%) and 96.8% specificity (95% CI, 93.4-99.2%). Odds of disagreement were significantly higher for eyes with stromal thinning (OR=8.19; 95% CI, 2.27-29.54), mid-stromal involvement (OR=4.44; 95% CI, 1.08-18.30), and infection within 2mm of the limbus (OR=8.81; 95% CI, 1.77-43.80). ConclusionsASOCT enables highly reproducible perforation grading and detects substantially more perforations than slit lamp examination, particularly in severe disease. These findings support ASOCT as an objective tool for clinical assessment and outcome ascertainment in microbial keratitis.

PurposeTo evaluate the three-year efficacy and safety of compound trabeculectomy for uveitic glaucoma (UG). MethodsThis retrospective study enrolled 51 patients (53 eyes) requiring compound trabeculectomy, divided into UG (25 eyes) and non-UG groups (28 eyes). Outcomes including intraocular pressure (IOP), medication use, surgical success rates, and complications were analyzed over 3 years. ResultsBaseline characteristics including age, sex, preoperative IOP and medication use were comparable (all P>0.05). At 36 months, postoperative IOP was showed no significant differences, which was 15.4{+/-}8.4 mmHg and 14.6{+/-}3.3 mmHg (P=0.73) with 54% and 55% reduction (P=0.88) in UG and non-UG groups respectively. The qualified success rate was 76.0% and 85.7% at 36 months in UG and non-UG group, and Kaplan-Meier analysis showed no significant difference. Medication reduction of UG group was significant lower than non-UG group (P=0.0058). Comparable complication rates were observed between groups (all P>0.05), yet bleb scarring and cataract progression showed elevated incidence in both cohort. ConclusionCompound trabeculectomy effectively reduced IOP and medications use in UG and non-UG. There was no significant difference in both qualified and completed success rate between UG and non-UG. Complications of filtering bleb fibrosis and cataract progression should be pay close attention for both groups.

IntroductionAnti-vascular endothelial growth factor (anti-VEGF) therapies are standards of care for vision-threatening retinal diseases. This retrospective observational study describes demographics, utilization, best recorded visual acuity (BRVA), and safety among eyes with neovascular age-related macular degeneration (nAMD), diabetic retinopathy (DR), diabetic macular edema (DME), or retinal vein occlusion (RVO) treated with the biosimilar aflibercept-ayyh (PAVBLU(R)) in routine clinical practice. MethodsElectronic medical records from the Retina Consultants of America database of patients receiving aflibercept-ayyh (12/1/2024-10/31/2025) were analyzed, focusing on eyes with [&ge;]84 days of follow-up. The index date was the first documented aflibercept-ayyh injection. Postindex data were used to assess treatment patterns, BRVA (Wilcoxon signed rank test), and adverse events of special interest (AESIs). ResultsA total of 1,000 consecutive eyes from 989 patients received 3,730 injections of aflibercept-ayyh; most (91%) switched from prior anti-VEGF therapy and 9% were anti-VEGF treatment-naive. Disease distribution was 58% nAMD, 19% RVO, 16% DME, and 7% DR. Among switchers, median (IQR) number of prior injections was 21 (8-46). Median (IQR) follow-up was 6.0 months (4.6-7.1). Median (IQR) number of aflibercept-ayyh injections per eye was 4 (3-5). Among eyes with [&ge;]84 days of follow-up (n=889), mean BRVA expressed as logarithm of minimum angle of resolution (logMAR) remained stable for switchers (0.4 to 0.4; P=0.96) and improved from baseline in anti-VEGF-naive eyes (0.5 to 0.4; P<0.01). Confirmed AESIs included iritis (n=2; 0.05% of injections), with no events of vitreous cells, endophthalmitis, retinal detachment, retinal vasculitis, or vitreous hemorrhage. ConclusionIn this descriptive real-world analysis, aflibercept-ayyh was associated with stable visual acuity in previously treated eyes and vision improvement in treatment-naive eyes, with no new or unexpected safety findings, consistent with expectations for aflibercept. These findings add real-world experience to preexisting evidence demonstrating no clinically meaningful differences between aflibercept-ayyh (PAVBLU(R)) and reference aflibercept (EYLEA(R)). KEY SUMMARY POINTSO_ST_ABSWhy carry out this study?C_ST_ABSO_LIThe anti-vascular endothelial growth factor (VEGF) drug aflibercept, approved in 2011 and marketed in the United States as EYLEA(R),* has demonstrated efficacy in treating retinal diseases such as neovascular age-related macular degeneration (nAMD), diabetic retinopathy (DR), diabetic macular edema (DME), or retinal vein occlusion (RVO) and is a standard of care for these disorders. C_LIO_LIAflibercept-ayyh is a biosimilar to aflibercept that has demonstrated comparable efficacy and safety in the treatment of nAMD in a randomized controlled clinical trial. C_LIO_LIThis study describes the real-world use patterns, vision outcomes, and safety of aflibercept-ayyh in clinical settings in the United States for the treatment of nAMD, DR, DME, and RVO. C_LI What was learned from the study?O_LIIn this real-world study of 1,000 consecutive eyes treated with the biosimilar aflibercept-ayyh in patients with retinal diseases, we observed no new safety concerns and that aflibercept-ayyh maintained visual acuity in eyes switching anti-VEGF agents and improved vision in anti-VEGF-naive eyes, consistent with expected responses to aflibercept. C_LIO_LIThese findings support aflibercept-ayyh as a suitable treatment option when anti-VEGF therapy is indicated. *EYLEA(R) is a registered trademark of Regeneron Pharmaceuticals, Inc. PAVBLU(R) is a registered trademark of Amgen Inc. C_LI

BackgroundThe visual field (VF) test results of many eyes with glaucoma progress despite treatment. This suggests that some eyes are either untreated or that the management of intraocular pressure (IOP) does not influence the outcome. In this work, we explore whether future VF parameters can be predicted from a baseline optical coherence retinal nerve fibre layer (OCT-RNFL) scan using a deep learning model. MethodsThe model was developed using 1792 eyes from 1610 patients, and externally validated on 151 eyes from a second centre using the same Zeiss Cirrus machine and 281 eyes from a third centre using scans obtained from a different (Heidelberg Spectralis) machine. The Vision Transformers (ViT)-based regression model was trained on baseline OCT-RNFL scans to predict three key VF indices (follow-up interval: 4.74 {+/-} 2.59 years). Model performance was evaluated using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), with 95% confidence intervals (CI). ResultsThe model achieved an overall MAE of 2.07 (95% CI: 1.91-2.22) and RMSE of 2.87 (95% CI: 2.60-3.14) on the internal validation set. On external validation, the model showed comparable performance with an MAE of 2.07 (95% CI: 1.8-2.35) for the external validation (Zeiss OCT) cohort and 2.11 (95% CI: 1.93-2.31) for the external validation (Heidelberg OCT) cohort. Saliency maps revealed that the inner and outer RNFL layers were key structures in driving the models predictions. ConclusionsOur ViT-based regression model effectively predicts key VF indices objectively from a single OCT-RNFL scan, with strong performance across two OCT devices, offering a novel tool for predicting glaucoma progression.

ImportanceGenome-wide association studies have identified hundreds of common single nucleotide polymorphisms (SNPs) and small insertions/deletions (indels) associated with primary open-angle glaucoma (POAG) risk, though these variants have modest effect sizes and individually may have minor contributions to disease development. As whole-genome sequencing data is becoming more readily available, structural variants and other complex genomic features can be interrogated for contribution to disease risk. ObjectiveTest the association of structural variants in known glaucoma loci with disease risk. DesignCross-sectional study. SettingA multicenter cohort of individuals from the United States who contributed genomic and electronic health record data to the All of Us Research Program. ParticipantsPOAG case/control cohorts were generated in the All of Us Researcher Workbench using age (>40 for cases, >65 for controls) and ICD 9/10 diagnosis codes. Main Outcomes and MeasuresLogistic regression analyses adjusted for age, sex, and the top 10 principal components of ancestry were used to test association of structural variants within 500 kilobases of 309 known open-angle glaucoma risk loci. The significance threshold after Bonferroni correction was set at p<1.6x10-4. Results516 POAG cases and 18,716 controls of European ancestry from the All of Us v8 data release were included in the analysis. Mean age was 77.0 years among cases and 74.7 years among controls. Females comprised 45.7% of cases and 56.5% of controls. An 8,732 base pair deletion upstream of PITX2 (chr4:110680827-110689558) was associated with 7.3-fold higher odds of POAG (95% confidence interval: 2.9-18.5, p= 2.4x10-5, variant carrier frequency= 1.6% in cases and 0.25% in controls). Functional annotation identified multiple enhancers overlapping the deletion, suggesting that this structural variant likely impacts gene regulation and expression. Conclusion and RelevanceWhole genome sequencing data captures rare structural variants with large effect sizes that are missed by conventional SNP and indel genotyping approaches, enabling improved POAG risk stratification. These data also expand the phenotypic spectrum of structural variation in the PITX2 locus from childhood glaucoma to adult-onset disease, where age at diagnosis and clinical severity may be influenced by the extent of disrupted regulatory elements.

PurposeMeasuring near vision provides clinicians with valuable insight into visual function. There is limited information on the accuracy of available reading charts frequently used in community practice. This study aimed to measure internationally available reading charts to determine how they compare to international standards, and develop a free chart, the UC/UWA Reading Chart, that conforms to these standards. MethodsCommercially and device manufacturer-provided reading charts were scanned at 600 dots per inch. Gaussian adaptive threshold was used to facilitate repeatable measurements. X-heights of letters were measured independently by three researchers. Other variables such as contrast levels and line spacing were also measured. Results for each chart were compared with ISO Standards. Intraclass correlation coefficient was used to assess intergrader agreement. ResultsOf the 19 reading charts that were measured, only one chart (5.26%) had text sizes that were all within tolerance. There was high variability in size observed between charts. Twelve charts (63.2%) used serif fonts and seven used sans-serif (36.8%). Text on serif charts tended to be smaller than required ({micro}=-9.65%) compared to sans-serif ({micro}=+4.96%). All charts met the line spacing requirements and minimum required contrast level; however, some charts were printed on laminated or satin plastic which does not meet the standard of using a matte surface. There was high interrater agreement (ICC(2,1) = 1.00), indicating a highly repeatable measurement technique. ConclusionThis study found that the tested reading charts displayed significant variability in text size. Although some charts had more lines of text within size tolerances than others, none met all the requirements of the International Standard. Clinicians and researchers should take care when interpreting changes in near reading acuity when multiple charts have been used, especially as part of shared care models or when monitoring progressive vision changes. Key pointsO_LINone of the measured reading charts met the requirements of the ISO 7921:2024 standard. C_LIO_LIThere is high variability in text size between reading charts. C_LIO_LIA new chart, the UC/UWA Reading Chart, has been developed to conform to the ISO standards. C_LI

PurposeQuantitative metrics obtained from retinal fundus images (such as vessel length, tortuosity and other scale-dependent measures) are increasingly used as potential biomarkers for systemic diseases, including cardio- and neurovascular conditions. However, with the increasing prevalence of myopia and related axial growth, this study aims to evaluate if axial length scaling significantly alters the overall distributions of the inferred biomarkers when compared to biomarker data obtained without axial length scaling and if these effects can be corrected. Methods2,309 clinic visits from patients aged [&le;]21 years were analysed and extracted for axial-length scaling analysis (range) 20 to 28 mm). The retinal fundus photographs were automatically segmented using Automorph to extract biometric data, including vascular metrics. The parameters were further corrected for axial length using correction factors based on the Bennett-Littmann formula and true axial length. ResultsAxial length significantly influenced biometric parameters (vessel metrics) derived from fundus photography. The magnitude of error in diameter and length of blood vessels was approximately 4-5% for each 1 mm deviation from the reference axial length of 24 mm, whereas the error in vessel area was approximately 9-10% per 1 mm, consistent with the geometric expectation that area scales with the square of linear dimensions. The scaling corrections for different axial lengths are presented. ConclusionsAxial-length-related magnification introduces systematic bias into retinal vascular metrics from fundus photographs. Bennett-Littmann correction using true axial length reduces these errors and should be adopted in quantitative fundus imaging and Al biomarker development.

PurposeTo evaluate the intra- and inter-grader concordance of anterior segment optical coherence tomography (ASOCT) grading for detection of endothelial plaque in microbial keratitis, and to compare endothelial plaque detection via ASOCT grading versus in-person slit lamp examination. MethodsDiagnostic concordance study of 150 consecutive patients with microbiologically confirmed bacterial or fungal keratitis at a high-volume tertiary eye hospital in India. Two masked ophthalmologist graders independently evaluated ASOCT images for presence of two morphologically distinct endothelial plaque subtypes noted during image review (round and flat plaques). We assessed intra-grader and inter-grader concordance for each endothelial plaque morphology and for presence of either morphology. Diagnostic agreement between ASOCT and in-person slit lamp examination was evaluated using percent agreement, Cohens kappa, sensitivity, and specificity. Univariable and multivariable logistic regression was used to assess odds of disagreement between ASOCT and slit lamp examination for endothelial plaque detection. ResultsASOCT detection showed near perfect inter-grader agreement for round endothelial plaques (kappa 0.88, 94.7% agreement), flat endothelial plaques (kappa 0.84, 92.0% agreement), and either plaque (kappa 0.88, 94.0% agreement). Intra-grader agreement was substantial to near perfect for both graders across all plaque types (kappa 0.70-0.86). Ophthalmologist slit lamp examination identified endothelial plaque in 6.0% eyes, while ASOCT detected round plaques in 32.7%, flat plaques in 43.3%, and either plaque in 55.3% of eyes. Using ASOCT as reference, slit lamp examination demonstrated sensitivity of 16.3% for round plaques, 6.2% for flat plaques, and 9.6% for either plaque, with specificity exceeding 94% for all. Poor visual acuity (logMAR [&ge;]1.0) was associated with increased disagreement for round plaques (adjusted OR 5.04), flat plaques (adjusted OR 3.63), and either plaque (adjusted OR 3.98). Bacterial infection was associated with increased disagreement for any endothelial plaque (adjusted OR 4.56). ConclusionSlit lamp examination substantially under-detects endothelial plaque compared to ASOCT, while ASOCT enables reproducible detection with excellent intra- and inter-grader agreement. These findings support incorporation of ASOCT imaging into microbial keratitis evaluation protocols. Differences in round and flat endothelial plaque morphologies warrant further investigation.

PurposeGlaucoma, a leading cause of irreversible vision loss, often remains undiagnosed due to its asymptomatic progression and the limitations of existing screening methods. This study aimed to validate an artificial intelligence machine learning algorithm for the camera-agnostic detection of glaucomatous optic neuropathy using macula-centered fundus images. MethodsData were collected from EyePACS, a teleretinal screening system, comprising 25,000 macula-centered fundus images from 12,500 patients at U.S. primary care centers. A secondary dataset from the Philadelphia Telemedicine Glaucoma Follow-up Study was used for independent validation. A convolutional neural network was developed to detect glaucomatous optic neuropathy. Expert-graded fundus images served as the ground truth. Images underwent quality filtering to ensure the visibility of the optic nerve. Bilateral images were analyzed to produce patient-level diagnoses. Validation involved a secondary dataset of fundus images. ResultsThe sensitivity and specificity of the algorithm in detecting glaucomatous optic neuropathy is calculated in comparison to expert grading. From the EyePACS dataset, 21,792 images (10,986 subjects) met quality standards. The algorithm demonstrated a sensitivity of 90.6% and specificity of 90.5%. Validation on the secondary dataset (200 fundus images from 100 subjects) resulted in a sensitivity of 96.4% and specificity of 85.3%. ConclusionsThe algorithm achieved high sensitivity and specificity in detecting glaucomatous optic neuropathy using macula-centered fundus images, demonstrating its potential for integration into diverse clinical settings. Its camera-agnostic design and robust performance offer a scalable solution for improving glaucoma screening pathways, making them more accessible and efficient.

PurposeTo investigate the epidemiology of post-injection endophthalmitis (PIE) and evaluate the association of sociodemographic and clinical factors with incidence, timing of onset, and presenting visual acuity (VA) using the IRIS(R) Registry (Intelligent Research in Sight). DesignRetrospective cohort study. ParticipantsPatients with endophthalmitis after an intravitreal anti-VEGF injection in the IRIS(R) Registry from 2016-2023. MethodsOnly the first anti-VEGF injection per eye was included. Exclusion criteria were cataract surgery during the study, intravitreal corticosteroids within 30 days prior to PIE, uveitis, or cystoid macular edema. Mean best VA was recorded within 100 days prior to anti-VEGF treatment and at the time of PIE. Regression modeling evaluated associations between endophthalmitis and sociodemographic and clinical factors, and time to PIE. Linear regression assessed predictors of VA at the time of PIE, and descriptive statistics were used to analyze time to onset. Main Outcome MeasuresIncidence of post-injection endophthalmitis, time to symptom onset, and best VA at diagnosis. ResultsAmong 1,025,788 eyes treated, 600 (0.059%) developed endophthalmitis. Key risk factors included residence in U.S. territories (OR = 2.62; P = 0.038 vs. Northeast) and history of intravitreal corticosteroid injection (OR = 2.35; P = 0.004 vs. no history). The strongest protective factor was non-smoking (OR = 0.71; P = 0.023 vs. smokers). The median time from injection to onset of PIE was 5 days (interquartile range [IQR]: 3-8). The salient predictors of time to PIE included patient age (4.3 days sooner per decade older; P = 0.04), prior corticosteroid treatment (11.7 days sooner; P = 0.02), and a diagnosis of diabetic retinopathy (2.3 days sooner; P=0.03). Baseline VA before PIE was the only significant predictor of VA at the time of PIE diagnosis (0.67, P < 0.001). ConclusionPost-injection endophthalmitis was significantly associated with residence in U.S. territories and prior intravitreal corticosteroid exposure, while non-smoking status was protective. Most cases presented 3-8 days following anti-VEGF injection. Older age, history of prior corticosteroid treatment, and diabetic retinopathy were associated with earlier PIE. Baseline VA predicted VA at the time of PIE.

AimsPrimary objective: To determine the minimum inhibitory concentration (MIC) of key antifungal drugs (natamycin, amphotericin B, voriconazole and econazole) against fungal isolates cultured from fungal keratitis patients in South India. Secondary objective: to ascertain correlations between antifungal resistance and patient outcome. MethodsIn this prospective observational study, MIC values were determined for fungal isolates cultured from 153 patients, with samples collected between May - August 2025. Clinical characteristics were collected at baseline, one-week and one-month following enrolment to the study. Mean antifungal MIC per fungi genera were compared. Statistical differences in MIC and patient characteristics were determined via multiple logistic or linear regression. Significance for participant outcome against resistant/non-resistant fungi were determined by Fishers exact test. ResultsResistance of Fusarium spp. isolates to: natamycin: 38.3%; amphotericin B: 93.8%; voriconazole: 97.5% and econazole: 76.5%. Resistance of Aspergillus spp. isolates to: natamycin: 66.7%; amphotericin B: 87.9%; voriconazole: 6.1%; and none were resistant to econazole. Natamycin MIC correlated with worse baseline (P[&le;]0.01) and one-week (P[&le;]0.05) visual acuity and ulcer severity. Poor patient outcomes (non-healing or therapeutic keratoplasty) were elevated 6.5x where the infection was caused by natamycin resistant Aspergillus, compared to sensitive Aspergillus strains (P[&le;]0.05). ConclusionThe majority of fungal isolates were resistant to multiple antifungals, none of the Fusarium isolates were sensitive to all four drugs, and 15% were resistant to all four drugs. Aspergillus isolates had high levels of resistance to the polyenes, but remained largely susceptible to the azoles. Overall, worse patient outcomes were associated with increased natamycin MIC. Key MessagesO_ST_ABSWhat is already known on this topicC_ST_ABSFungal keratitis is a major cause of blindness worldwide, disproportionately affecting those across the tropics, with incidence increasing across temperate climates. The majority of cases are caused by the filamentous fungi Fusarium spp. and Aspergillus spp.. Antifungal resistance is poorly characterised in fungal keratitis. What this study addsWe report the fungal aetiology and the minimum inhibitory concentration (MIC) against natamycin, amphotericin B, voriconazole and econazole of isolates cultured from 153 patient corneal scrape samples between May - August 2025 at a South Indian hospital. We found high levels of fungal resistance, with Fusarium isolates having high levels of resistance to both polyenes and azoles. Aspergillus isolates showed good azole sensitivity, but high levels of resistance to polyenes. Aspergillus resistance to natamycin correlated with worse clinical outcomes at one-month. Natamycin resistance contributed to worse visual acuity and ulcer severity at baseline and one-week follow-up across all fungi. How this study might affect research, practice or policyOur study confirmed that natamycin was best available first-line treatment for Fusarium. Aspergillus isolates were mostly resistant to natamycin and amphotericin B, and this impacted patient outcomes. SynopsisWe identified high incidence of multi-drug resistant fungi, and that patients were more likely to have a poor clinical outcome if the fungal isolate was resistant to natamycin. This was most pronounced for Aspergillus isolates.

PurposeTo investigate the association between glucagon-like peptide-1 receptor agonist (GLP-1RA) use and nonarteritic anterior ischaemic optic neuropathy (NAION) in type 2 diabetes, examining treatment recency and cumulative duration. MethodsThis nationwide registry-based nested case-control study utilised Danish health registries (1996-2023). Among 201,776 metformin-treated adults initiating second-line antihyperglycaemic therapy, 123 incident NAION cases were matched to 4,920 controls by birth year and sex (incidence-density sampling). Conditional logistic regression estimated adjusted hazard rate ratios (HRs) for GLP-1RA exposure by recency (current 0-90 days; recent 91-365 days) and cumulative duration, adjusting for socioeconomic factors, hypertension, hypercholesterolaemia, sleep apnoea, and diabetes duration. ResultsGLP-1RA use occurred in 63/123 cases (51.2%) and 1,688/4,920 controls (34.3%). Ever use was associated with a higher NAION rate than other second-line therapies (HR 2.13, 95% CI 1.43-3.18). Current use was associated with elevated rates (HR 2.28, 95% CI 1.49-3.48), whereas the estimate for recent use was imprecise (HR 1.69, 95% CI 0.88-3.25). By cumulative duration, no clear evidence of an increase was seen within 0-[1/2] years (HR 0.80, 95% CI 0.32-2.05), and rates were highest at [1/2]-1 year (HR 3.63, 95% CI 2.06-6.40) and 1-1[1/2] years (HR 3.52, 95% CI 1.73-7.17). Findings were consistent after HbA1c adjustment and in a new-user analysis. ConclusionGLP-1RA use is associated with a higher NAION rate in type 2 diabetes. This association appears time-dependent, being most pronounced during current treatment and peaking after 6-18 months of cumulative exposure.