Increasing the diagnostic yield of childhood glaucoma cases recruited into the 100,000 Genomes Project.

Childhood glaucoma (CG) encompasses a heterogeneous group of genetic eye disorders that is responsible for approximately 5% of childhood blindness worldwide. Understanding the molecular aetiology is key to improving diagnosis, prognosis and unlocking the potential for optimising clinical management. In this study, we investigated 86 CG cases from 78 unrelated families of diverse ethnic backgrounds, recruited into the Genomics England 100,000 Genomes Project (GE100KGP) rare disease cohort, to improve the genetic diagnostic yield. Using the Genomics England/Genomic Medicine Centres (GE/GMC) diagnostic pipeline, 13 unrelated families were solved (13/78, 17%). Further interrogation using an expanded gene panel yielded a molecular diagnosis in 7 more unrelated families (7/78, 9%). This analysis effectively raises the total number of solved CG families in the GE100KGP to 26% (20/78 families). Twenty-five percent (5/20) of the solved families had primary congenital glaucoma (PCG), while 75% (15/20) had secondary CG; 53% of this group had non-acquired ocular anomalies (including iris hypoplasia, megalocornea, ectopia pupillae, retinal dystrophy, and refractive errors) and 47% had non-acquired systemic diseases such as cardiac abnormalities, hearing impairment, and developmental delay. CYP1B1 was the most frequently implicated gene, accounting for 55% (11/20) of the solved families. We identified two novel likely pathogenic variants in the TEK gene, in addition to one novel pathogenic copy number variant (CNV) in FOXC1. Variants that passed undetected in the GE100KGP diagnostic pipeline were likely due to limitations of the tiering process, the use of smaller gene panels during analysis, and the prioritisation of coding SNVs and indels over larger structural variants, CNVs, and non-coding variants.

Automated AI labeling of optic nerve head enables insights into cross-ancestry glaucoma risk and genetic discovery in >280,000 images from UKB and CLSA.

Cupping of the optic nerve head, a highly heritable trait, is a hallmark of glaucomatous optic neuropathy. Two key parameters are vertical cup-to-disc ratio (VCDR) and vertical disc diameter (VDD). However, manual assessment often suffers from poor accuracy and is time intensive. Here, we show convolutional neural network models can accurately estimate VCDR and VDD for 282,100 images from both UK Biobank and an independent study (Canadian Longitudinal Study on Aging), enabling cross-ancestry epidemiological studies and new genetic discovery for these optic nerve head parameters. Using the AI approach, we perform a systematic comparison of the distribution of VCDR and VDD and compare these with intraocular pressure and glaucoma diagnoses across various genetically determined ancestries, which provides an explanation for the high rates of normal tension glaucoma in East Asia. We then used the large number of AI gradings to conduct a more powerful genome-wide association study (GWAS) of optic nerve head parameters. Using the AI-based gradings increased estimates of heritability by ∼50% for VCDR and VDD. Our GWAS identified more than 200 loci associated with both VCDR and VDD (double the number of loci from previous studies) and uncovered dozens of biological pathways; many of the loci we discovered also confer risk for glaucoma.

Glaucoma: now and beyond.

The glaucomas are a group of conditions leading to irreversible sight loss and characterised by progressive loss of retinal ganglion cells. Although not always elevated, intraocular pressure is the only modifiable risk factor demonstrated by large clinical trials. It remains the leading cause of irreversible blindness, but timely treatment to lower intraocular pressure is effective at slowing the rate of vision loss from glaucoma. Methods for lowering intraocular pressure include laser treatments, topical medications, and surgery. Although modern surgical innovations aim to be less invasive, many have been introduced with little supporting evidence from randomised controlled trials. Many cases remain undiagnosed until the advanced stages of disease due to the limitations of screening and poor access to opportunistic case finding. Future research aims to generate evidence for intraocular pressure-independent neuroprotective treatments, personalised treatment through genetic risk profiling, and exploration of potential advanced cellular and gene therapies.

Central Visual Field Testing in Early Glaucoma: A Report by the American Academy of Ophthalmology.

PURPOSE: To evaluate the current published literature on the utility of the 10-2 visual field (VF) testing strategy for the evaluation and management of early glaucoma, defined here as mean deviation (MD) better than -6 decibels (dB). METHODS: A search of the peer-reviewed literature was last conducted in June 2023 in the PubMed database. Abstracts of 986 articles were examined to exclude reviews and non-English-language articles. After inclusion and exclusion criteria were applied, 26 articles were selected, and the panel methodologist rated them for strength of evidence. Thirteen articles were rated level I, and 8 articles were rated level II. The 5 level III articles were excluded. Data from the 21 included articles were abstracted and reviewed. RESULTS: The central 12 locations on the 24-2 VF test grid lie within the central 10 degrees covered by the 10-2 VF test. In early glaucoma, defects detected within the central 10 degrees generally agree between the 2 tests. Defects within the central 10 degrees of the 24-2 VF test can predict defects on the 10-2 VF test, although the 24-2 may miss defects detected on the 10-2 VF test. In addition, results from the 10-2 VF test show better association with findings from OCT scans of the macular ganglion cell complex. Modifications of the 24-2 test that include extra test locations within the central 10 degrees improve detection of central defects found on 10-2 VF testing. CONCLUSIONS: Evidence to date does not support routine testing using 10-2 VF for patients with early glaucoma. However, early 10-2 VF testing may provide sufficient additional information for some patients, particularly those with a repeatable defect within the central 12 locations of the standard 24-2 VF test or who have inner retinal layer thinning on OCT scans of the macula. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Quantification and Predictors of Visual Field Variability in Healthy, Glaucoma Suspect, and Glaucomatous Eyes Using SITA-Faster.

PURPOSE: The newly released Swedish Interactive Thresholding Algorithm (SITA)-Faster (SFR) has significantly shorter testing durations compared with older SITA algorithms, but its variability is uncertain. This study quantified and established threshold limits of test-retest variability across the 24-2 test grid using SFR. DESIGN: Cross-sectional study with prospective longitudinal arm. PARTICIPANTS: 1426 eyes of 787 patients with healthy, suspected glaucoma, or manifest glaucoma eyes from hospital- and university- eye clinics. METHODS: Two SFR tests per eye at a baseline visit and at two follow-up visits. MAIN OUTCOME MEASURES: Pointwise variability measured by test-retest difference in pointwise sensitivity between tests one and two, mean global variability (test-retest variance) measured by average of pointwise variability for each participant, global sensitivity, and reliability indices of each eye. RESULTS: Of the 1426 eyes, 540 eyes (37.9%) had a diagnosis of glaucoma, 753 eyes (52.8%) were suspected of having glaucoma, and the remaining 133 eyes (9.3%) were healthy. Of 74 152 pointwise sensitivities obtained, the mean test-retest difference was 2.17 ± 2.9 dB, whereas the mean test-retest variance for each participant was 2.17 ± 1.2 dB. Pointwise and global variability increased with worsening threshold sensitivity and (MD), respectively, and was greater for peripheral compared with central test locations. In the longitudinal cohort, no significant difference in mean test-retest variance was found across the 3 visits (mean variability, 2.10 dB vs. 2.16 dB vs. 2.16 dB at visits F0 vs. F1 vs. F2; P = 0.53, repeated-measures analysis of variance). Baseline MD (-0.19 dB; 95% CI, -0.22 to 0.16 dB; P < 0.0001) and abnormally high sensitivity on glaucoma hemifield test (1.14 dB; 95% CI, 0.78-1.51 dB; P < 0.0001) were significantly associated with increased variability. Finally, test-retest MD showed minimal change around the recommended 15% false-positive cutoff threshold. CONCLUSIONS: The variability of SFR increases with worsening threshold sensitivity, is stable over time, and is greater for peripheral compared with central test locations. Worse baseline MD and abnormally high sensitivity are significant predictors of increased variability. A cutoff of 15% in false-positive results may be inappropriate as a threshold for judging test reliability in SFR. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Statistical performance review on diagnosis of leukemia, glaucoma and diabetes mellitus using AI.

The growth of artificial intelligence (AI) in the healthcare industry tremendously increases the patient outcomes by reshaping the way we diagnose, treat and monitor patients. AI-based innovation in healthcare include exploration of drugs, personalized medicine, clinical diagnosis investigations, robotic-assisted surgery, verified prescriptions, pregnancy care for women, radiology, and reviewed patient information analytics. However, prediction of AI-based solutions are depends mainly on the implementation of statistical algorithms and input data set. In this article, statistical performance review on various algorithms, Accuracy, Precision, Recall and F1-Score used to predict the diagnosis of leukemia, glaucoma, and diabetes mellitus is presented. Review on statistical algorithms' performance, used for individual disease diagnosis gives a complete picture of various research efforts during the last two decades. At the end of statistical review on each disease diagnosis, we have discussed our inferences that will give future directions for the new researchers on selection of AI statistical algorithm as well as the input data set.

Artificial intelligence for glaucoma: state of the art and future perspectives.

PURPOSE OF REVIEW: To address the current role of artificial intelligence (AI) in the field of glaucoma. RECENT FINDINGS: Current deep learning (DL) models concerning glaucoma diagnosis have shown consistently improving diagnostic capabilities, primarily based on color fundus photography and optical coherence tomography, but also with multimodal strategies. Recent models have also suggested that AI may be helpful in detecting and estimating visual field progression from different input data. Moreover, with the emergence of newer DL architectures and synthetic data, challenges such as model generalizability and explainability have begun to be tackled. SUMMARY: While some challenges remain before AI is routinely employed in clinical practice, new research has expanded the range in which it can be used in the context of glaucoma management and underlined the relevance of this research avenue.

Recent developments of telemedicine in glaucoma.

PURPOSE OF REVIEW: Telemedicine has an increasingly significant role in the fields of ophthalmology and glaucoma. This review covers recent advancements in the development and optimization of teleglaucoma techniques and applications. RECENT FINDINGS: Glaucoma monitoring and diagnosis via remote tonometry, perimetry, and fundus imaging have become a possibility based on recent developments. Many applications work in combination with smart devices, virtual reality, and artificial intelligence and have been tested in patient populations against conventional "reference-standard" measurement tools, demonstrating promising results. Of note, there is still much progress to be made in teleglaucoma and telemedicine at large, such as accessibility to internet, broadband, and smart devices, application affordability, and reimbursement for remote services. However, continued development and optimization of these applications suggest that the implementation of remote monitoring will be a mainstay for glaucoma patient care. SUMMARY: Especially since the beginning of the COVID-19 pandemic, remote patient care has taken on an important role in medicine and ophthalmology. Remote versions of tonometry, perimetry, and fundus imaging may allow for a more patient-centered and accessible future for glaucoma care.

Sensitivity and specificity of the uniform field electroretinogram in glaucoma detection in comparison to the pattern electroretinogram.

PURPOSE: To determine the ability of the photopic negative response (PhNR) of the uniform field electroretinogram (UF-ERG) to identify early glaucomatous changes in comparison to the checkerboard and bar stimuli of the pattern electroretinogram (PERG). METHODS: Forty-nine glaucoma patients were classified into two groups: glaucoma-suspect (23 eyes) and early to moderate glaucoma (30 eyes), based on their clinical examination and the results of standard automated perimetry. Thirty patients (30 eyes) with intraocular pressures (IOP) of 21 mmHg or less, with no history of reported high IOP, were included as controls. PERG and UF-ERG recordings were obtained on a Diagnosys D-341 Attaché-Envoy System. Visual field testing was done only for glaucoma-suspect and glaucoma patients. RESULTS: All three tests (PERG bar stimulus, PERG checkerboard stimulus and PhNR) displayed significantly prolonged peak times for glaucoma and glaucoma-suspect patients, with delays ranging from 7.8 to 14.8%, depending on the test. The PERG bar stimulus also showed a significantly lower N95 amplitude for both glaucoma groups (with reductions of 26.0% and 33.0% for glaucoma-suspect and glaucoma groups, respectively). The PERG checkerboard N95 amplitude component had high sensitivity for detecting glaucoma patients but a low specificity (97% and 37%, respectively; AUC = 0.61). Overall, the PhNR peak time showed the highest sensitivity and specificity (77% and 90%, respectively; AUC = 0.87). CONCLUSIONS: PERG bar stimuli and the PhNR of the UF-ERG can be used in the clinical setting to detect glaucoma-related changes in glaucoma-suspect and glaucoma patients. However, our data confirm that the PhNR peak time has the best combined sensitivity and specificity.

Objective detection of visual field defects with multifrequency VEPs.

PURPOSE: To correlate multifrequency pattern reversal VEPs in quadrants (QmfrVEPs) with perimetric field losses for objective detection of visual field losses. METHODS: QmfrVEP measurements were performed using four LED-based checkerboard stimulators to stimulate the four quadrants of the visual field. QmfrVEPs were measured monocularly in 5 normal subjects and in 5 glaucoma patients who showed losses in conventional Octopus perimetry. The pattern reversal frequency varied slightly between the stimulators: (11.92, 12.00, 12.08 and 12.16 reversals/sec). The responses to the different stimuli were identified by discrete Fourier analysis. VEPs were recorded using different electrode configurations, and the recording with the highest signal-to-noise ratio (SNR) was used for further analysis. RESULTS: QmfrVEP responses from the different quadrants can be reliably measured and separated using the 0.08 reversals/sec interstimulus reversal frequency differences. The signal-to-noise ratio in the four quadrants was significantly correlated with the equivalent visual field losses obtained with perimetry (Spearman rank correlation: P < 0.001). In the five glaucoma patients, the SNR was reduced in 15 out of the 16 quadrants with a perimetric defect, in comparison to the results in quadrants of healthy subjects. This confirms the sensitivity of the procedure. CONCLUSION: QmfrVEP responses can be measured reliably. This pilot study suggests that high SNR values exclude visual field defects and that focal defects can be identified in glaucoma patients. TRIAL REGISTRATION: www. CLINICALTRIALS: gov . NCT00494923.

The associations of self-perception, movement competence, and clinical features of young school-aged children with glaucoma.

The purpose of the study was to determine the associations of self-perception, motor skills, and clinical features of young school-age children with glaucoma (CG). This is a cross-sectional observational study. Children from preschool to second grade, including CG (N = 19), children with amblyopia (CA, N = 28), and controls (N = 32), completed the Manual Dexterity and Aiming and Catching Scales of the Movement Assessment Battery for Children-2nd edition (MABC-2), including Manual Dexterity, Aiming and Catching, and Balance. CG, CA, and their parent completed the Pictorial Scale of Perceived Competence and Social Acceptance for Young Children, respectively, assessing the child's cognitive competence, peer acceptance, physical competence, and maternal acceptance. The Kruskal-Wallis H test and Bonferroni post hoc test compared motor skills among groups. Spearman's correlation analysis evaluated the correlations between motor skills, self-perception, and clinical features. The CG reported lower peer acceptance than CA (P = 0.040), and the parents of CG reported lower cognitive competence than CG reported (P = 0.046). Compared with controls, CG had worse performance of Aiming and Catching, and Balance (P = 0.018 and P = 0.001), and CA had worse performance of Balance (P = 0.009). The motor skills were comparable between CG and CA. For CG, older age correlated with worse competence of Aiming and Catching (r = - 0.620, P = 0.005), better best-corrected visual acuity of better-seeing eye correlated with higher competence of Manual Dexterity and Balance (r = - 0.494, P = 0.032, and r = - 0.516, P = 0.024), and longer duration of glaucoma correlated with worse competence of Manual Dexterity (r = - 0.487, P = 0.034). CONCLUSION:  Glaucoma and amblyopia have significant negative impacts on children's daily motor skills. The acuity of a better-seeing eye is an important factor influencing motor movement. TRIAL REGISTRATION: ClinicalTrials.gov identifier, ChiCTR2100050415. WHAT IS KNOWN: • The state of mental health in early childhood influences the development of their future personality and physical development. The prognosis and management of glaucoma may seriously impair the mental health development of the affected children. However, the exploration of psychological aspects and motor movement of childhood glaucoma was limited. WHAT IS NEW: • Children with glaucoma have impaired motor skills and self-perception development, especially in terms of peer socialization.

Posture-related fluctuations of intraocular pressure in healthy children with suspicion of glaucoma.

PURPOSE: Currently, there are no specific data on the circadian course of intraocular pressure (IOP) in children, especially for IOP measurements in the supine position. The study aimed to characterize the diurnal and nocturnal IOP fluctuations in supine and sitting positions in patients less than 18 years of age. METHODS: Seventy-nine eyes of 79 patients under 18 years of age with suspicious optic nerve heads or ocular hypertension could be included in this study. All included patients showed an inconspicuous retinal nerve fiber layer thickness and Bruch's membrane minimum rim width by coherence tomography. IOP measurements during the 24-h IOP profile were retrospectively evaluated. Measurements were taken at 10:00, 16:00, 20:00, and 23:00 h in the sitting position and at 6:00 h in the morning in the supine position using iCare rebound tonometry on 2 consecutive days. RESULTS: Thirty-four of 79 children (43.0%) had peak nocturnal IOP values > 25 mmHg. The mean daily IOP was 18.8 ± 5.6 mmHg, and the mean daily fluctuation was 6.1 ± 4.0 mmHg. At 6 am, supine measurements were elevated to 25.1 ± 8.0 mmHg. Extensive fluctuations with values > 40 mmHg in the nocturnal supine measurement occurred in a relevant share of patients (n = 5). CONCLUSION: There appear to be relevant diurnal and nocturnal IOP fluctuations in healthy children (< 18 years). Nocturnal IOP measurements in supine patients with risk factors for glaucoma may provide important additional information to identify critical patients for further follow-up.

An auxiliary diagnostic tool for common fundus diseases based on fundus color photography and light-weight classification models.

OBJECTIVE: To evaluate the performance of two lightweight neural network models in the diagnosis of common fundus diseases and make comparison to another two classical models. METHODS: A total of 16,000 color fundus photography were collected, including 2000 each of glaucoma, diabetic retinopathy (DR), high myopia, central retinal vein occlusion (CRVO), age-related macular degeneration (AMD), optic neuropathy, and central serous chorioretinopathy (CSC), in addition to 2000 normal fundus. Fundus photography was obtained from patients or physical examiners who visited the Ophthalmology Department of Beijing Tongren Hospital, Capital Medical University. Each fundus photography has been diagnosed and labeled by two professional ophthalmologists. Two classical classification models (ResNet152 and DenseNet121), and two lightweight classification models (MobileNetV3 and ShufflenetV2), were trained. Area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were used to evaluate the performance of the four models. RESULTS: Compared with the classical classification model, the total size and number of parameters of the two lightweight classification models were significantly reduced, and the classification speed was sharply improved. Compared with the DenseNet121 model, the ShufflenetV2 model took 50.7% less time to make a diagnosis on a fundus photography. The classical models performed better than lightweight classification models, and Densenet121 showed highest AUC in five out of the seven common fundus diseases. However, the performance of lightweight classification models is satisfying. The AUCs using MobileNetV3 model to diagnose AMD, diabetic retinopathy, glaucoma, CRVO, high myopia, optic atrophy, and CSC were 0.805, 0.892, 0.866, 0.812, 0.887, 0.868, and 0.803, respectively. For ShufflenetV2model, the AUCs for the above seven diseases were 0.856, 0.893, 0.855, 0.884, 0.891, 0.867, and 0.844, respectively. CONCLUSION: The training of light-weight neural network models based on color fundus photography for the diagnosis of common fundus diseases is not only fast but also has a significant reduction in storage size and parameter number compared with the classical classification model, and can achieve satisfactory accuracy.

A deep learning approach to investigate the filtration bleb functionality after glaucoma surgery: a preliminary study.

PURPOSE: To distinguish functioning from failed filtration blebs (FBs) implementing a deep learning (DL) model on slit-lamp images. METHODS: Retrospective, cross-sectional, multicenter study for development and validation of an artificial intelligence classification algorithm. The dataset consisted of 119 post-trabeculectomy FB images of whom we were aware of the surgical outcome. The ground truth labels were annotated and images splitted into three outcome classes: complete (C) or qualified success (Q), and failure (F). Images were prepared implementing various data cleaning and data transformations techniques. A set of DL models were trained using different ResNet architectures as the backbone. Transfer and ensemble learning were then applied to obtain a final combined model. Accuracy, sensitivity, specificity, area under the ROC curve, and area under the precision-recall curve were calculated to evaluate the final model. Kappa coefficient and P value on the accuracy measure were used to prove the statistical significance level. RESULTS: The DL approach reached good results in unraveling FB functionality. Overall, the model accuracy reached a score of 74%, with a sensitivity of 74% and a specificity of 87%. The area under the ROC curve was 0.8, whereas the area under the precision-recall curve was 0.74. The P value was equal to 0.00307, and the Kappa coefficient was 0.58. CONCLUSIONS: All considered metrics supported that the final DL model was able to discriminate functioning from failed FBs, with good accuracy. This approach could support clinicians in the patients' management after glaucoma surgery in absence of adjunctive clinical data.

Factors associated with intrachoroidal cavitation and sinkhole formation in eyes with glaucomatous visual-field defects.

PURPOSE: To investigate factors associated with intrachoroidal cavitation (ICC) and sinkhole formation in eyes with glaucomatous visual-field defects. METHODS: This retrospective, cross-sectional study enrolled a total of 2808 eyes of 1482 patients who were diagnosed/treated for glaucoma and underwent swept-source optical coherence tomography (OCT). We first determined the prevalence of ICCs and sinkholes and their locations. Next, we selected one eye from each patient and compared the clinical characteristics of eyes with and without ICCs. Finally, in eyes with ICCs, we compared the clinical characteristics of eyes with and without sinkholes. Blood flow (BF), represented by laser speckle flowgraphy-measured tissue-area mean blur rate (MBR), was measured in the temporal optic nerve head (ONH), temporal peripapillary chorioretinal atrophy (PPA) zone, and in the ICC zone. ICC area and angle were analyzed in OCT en-face images. Mean deviation and total deviation in the central area (TD-central) were measured with Humphrey visual-field testing. RESULTS: A total of 86 eyes (3.1%) had ICCs and 52 eyes (1.9%) had sinkholes. ICC eyes had a lower spherical equivalent and longer axial length (AL) than non-ICC eyes (P < 0.05). Patients with eyes with sinkholes were more elderly and had worse best-corrected visual acuity, worse TD-central, a larger ICC, and lower tissue-area MBR in the temporal ONH, temporal PPA zone, and ICC zone (P < 0.05). CONCLUSION: In eyes with glaucoma, AL elongation might be linked to ICC formation. Sinkhole formation might be associated with ICC enlargement, impaired ocular BF, and impaired retinal structure and function involving the central area.

An eternal hunt for glaucoma.

In the first issue of Graefe's Archive from 1854, Albrecht von Graefe wrote about glaucoma. Glaucoma comes from the Greek word "glaukos," gleaming, which was first used by Homer around 800 BCE. Since then, glaukos and glaucoma have taken on many different meanings. The terms blindness, cataract and glaucoma were used interchangeably and twisted together in incomprehensible contexts. Over 2500 years of glaucoma theories were upset by the discovery of the ophthalmoscope in 1851. The first reports of increased intraocular pressure appeared in the mid-seventeenth century, but it took over 200 years for this elevated pressure to be accepted by the ophthalmological community. The discovery of glaucoma simplex in 1861 was an important step forward. What did doctors know about glaucoma before 1850 and why did it take so long to classify glaucoma in its various categories? And why is it that we still do not know what the cause is for primary open angle glaucoma? I will try to answer some of these questions after a historical overview.

A multi-label transformer-based deep learning approach to predict focal visual field progression.

PURPOSE: Tracking functional changes in visual fields (VFs) through standard automated perimetry remains a clinical standard for glaucoma diagnosis. This study aims to develop and evaluate a deep learning (DL) model to predict regional VF progression, which has not been explored in prior studies. METHODS: The study included 2430 eyes of 1283 patients with four or more consecutive VF examinations from the baseline. A multi-label transformer-based network (MTN) using longitudinal VF data was developed to predict progression in six VF regions mapped to the optic disc. Progression was defined using the mean deviation (MD) slope and calculated for all six VF regions, referred to as clusters. Separate MTN models, trained for focal progression detection and forecasting on various numbers of VFs as model input, were tested on a held-out test set. RESULTS: The MTNs overall demonstrated excellent macro-average AUCs above 0.884 in detecting focal VF progression given five or more VFs. With a minimum of 6 VFs, the model demonstrated superior and more stable overall and per-cluster performance, compared to 5 VFs. The MTN given 6 VFs achieved a macro-average AUC of 0.848 for forecasting progression across 8 VF tests. The MTN also achieved excellent performance (AUCs ≥ 0.86, 1.0 sensitivity, and specificity ≥ 0.70) in four out of six clusters for the eyes already with severe VF loss (baseline MD ≤ - 12 dB). CONCLUSION: The high prediction accuracy suggested that multi-label DL networks trained with longitudinal VF results may assist in identifying and forecasting progression in VF regions.

Pattern electroretinogram, blue-yellow visual evoked potentials and the risk of developing visual field defects in glaucoma suspects: a longitudinal "survival" analysis with a very long follow-up.

PURPOSE: Estimating glaucoma suspects' risk for visual field defects helps to avoid under- and over-treatment. In this retrospective, longitudinal cohort study with a very long follow-up, we studied whether pattern electroretinograms (PERG) amplitudes and blue-on-yellow visual evoked potential (BY-VEP) latencies can predict visual field defects. METHODS: Participants of the Erlangen Glaucoma Study were examined with PERG and BY-VEP between 9/1991 and 8/2001. Stimuli were created using an optical bench with Maxwellian view and consisted of vertical gratings (0,88 cpd) in a 32° field for both PERG and BY-VEP. Patients were treated according to clinical standards and performed standard automated perimetry (SAP) annually. Retrospectively, patients with normal SAP at baseline were selected. Primary endpoint was conversion to perimetric glaucoma. Predictive value was modeled using Kaplan-Meier analyses and a multivariate cox proportional hazards model with the continuous variables PERG amplitude, BY-VEP peak time and SAP square-root of loss variance (sLV) after stratification for Jonas classification of the optic discs. RESULTS: Of 412 patients (288: Jonas 0, 103: I, and 21: II; baseline age: 20-60 years), 65 converted to perimetric glaucoma during follow-up (0.5-23.3 years; median 5.5 years). Optic disc classification was a strong risk factor for conversion (log rank p < 0.0001), and patients with more advanced changes progressed earlier. In the multivariate analysis (log rank p = 0.005), only PERG amplitude remained an independent risk factor after stratification for optic disc morphology (p = 0.021), with a ~ 30% higher risk per µV amplitude decrease. CONCLUSIONS: PERG helps to estimate glaucoma suspects' risk for visual field defects.

Aqueous misdirection syndrome: clinical outcomes and risk factors for treatment failure.

PURPOSE: To evaluate the outcomes of postoperative aqueous misdirection and factors predicting failure of interventions. METHODS: This retrospective study included 49 eyes from 47 patients with aqueous misdirection following glaucoma or cataract surgery. Resolution of aqueous misdirection (AM) was deepening of the central anterior chamber (AC) and intraocular pressure (IOP) ≤ 21 mmHg. The Cox proportional hazards regression model was used to evaluate risk factors for failure of various treatments. RESULTS: 10/49 eyes (20%) resolved with conservative management, and 39/49 eyes (80%) needed multiple intervention, of which 95% (37/39) eyes achieved resolution of aqueous misdirection. Pseudophakia predicted the need for multiple interventions with a hazard ratio of 2.391 (1.158-4.935), p = 0.02). Among the risk factors assessed for resolution of AM, longer axial length (HR: 0.61 (0.414-0.891), p < 0.01) and eyes with prior glaucoma surgery predicted resolution (HR: 0.142 (0.027-0.741), p < 0.01) and delayed presentation predicted failure (HR: 1.002 (1.0002-1.0031), p < 0.02). CONCLUSION: Pseudophakic eyes were more refractory and predicted the need for multiple interventions. Eyes with prior glaucoma surgery and those with longer axial length had achieved resolution faster, and delayed presentation was a risk factor for failure to resolve.

The correlation of anterior segment structures in primary congenital glaucoma by ultrasound biomicroscopy with disease severity and surgical outcomes.

PURPOSE: To evaluate the anterior segment structures using ultrasound biomicroscopy (UBM) in primary congenital glaucoma (PCG) and explore their correlation with disease severity and surgical outcomes. METHODS: Clinical information of PCG patients who underwent UBM prior to their first glaucoma surgeries from September 2014 to March 2021 were reviewed. The study included 214 UBM images of 154 PCG eyes and 60 fellow unaffected eyes. Anterior segment characteristics were analyzed. UBM parameters, including the iris thickness (IT) at variant distances from the pupil edge and iris root, anterior chamber depth (ACD), and pupil diameter (PD), were compared between two groups and their relationship with clinical factors and surgical outcomes were analyzed in PCG eyes. RESULTS: PCG eyes had unclear scleral spur, thin iris, wide anterior chamber angle, deep anterior chamber, rarefied ciliary body, elongated ciliary processes, and abnormal anterior iris insertion. ITs were thinner, ACD was deeper, and PD was larger in PCG eyes than fellow unaffected eyes (all P < 0.001). In PCG eyes, thinner ITs correlated with bilateral involvement and earlier age at presentation, and larger PD correlated with earlier age at presentation (P = 0.030) and higher intraocular pressure (P < 0.001). Thinner IT2 (P = 0.046) and larger PD (P = 0.049) were identified as risk factors for surgical failure. CONCLUSION: UBM is a powerful technique to exam anterior segment structures in PCG. The anatomical features are associated with disease severity and surgical outcomes, providing essential clinical insights.