Abstract: Abstract Background Landmark studies reported on faricimab efficacy and safety predominantly in treatment naïve patients, but outcomes following switch from other anti-VEGF therapies are lacking. We evaluated patients switched to faricimab who had previously shown a partial response to other anti-VEGF injections for neovascular age-related macular degeneration (nAMD) and diabetic macular oedema (DMO). Methods Retrospective study at the Oxford Eye Hospital. Patients switched to faricimab from January to April 2023 with six months follow-up were identified via electronic medical records. Results A total of 116 patients (151 eyes) were included. In 88 patients with nAMD (107 eyes), mean visual acuity remained stable: 62±17 ETDRS letters at baseline; 62±18 at six months ( p > 0.05). Central subfield thickness (CST) reduced from 294 ± 73 μm to 270 ± 53 μm ( p < 0.05) at six months. Subretinal or intraretinal fluid was present in 102 eyes (95%) at baseline and 75 eyes (70%) at follow-up ( p < 0.05). Pigment epithelial detachment height decreased from 233 ± 134 μm to 188 ± 147 μm ( p < 0.05). Mean treatment interval increased by 1.7 weeks ( p < 0.05) and was extended in 61 eyes (57%) at six months. In 28 patients with DMO (44 eyes), visual acuity remained stable: 69 ± 15 letters at baseline; 70±15 at six months ( p > 0.05). CST reduced from 355 ± 87 μm to 317 ± 82 μm ( p < 0.05). Mean treatment interval increased by 1.4 weeks ( p < 0.05) and was extended in 21 eyes (46%) by six months. Conclusions Switching to faricimab in treatment resistant eyes led to improved anatomical response and extended treatment interval in a significant proportion of patients. Ongoing review of real-world data will inform longer-term outcomes of safety and effectiveness.

Abstract: Abstract Background We aimed to update estimates of global vision loss due to age-related macular degeneration (AMD). Methods We did a systematic review and meta-analysis of population-based surveys of eye diseases from January, 1980, to October, 2018. We fitted hierarchical models to estimate the prevalence of moderate and severe vision impairment (MSVI; presenting visual acuity from <6/18 to 3/60) and blindness ( < 3/60) caused by AMD, stratified by age, region, and year. Results In 2020, 1.85 million (95%UI: 1.35 to 2.43 million) people were estimated to be blind due to AMD, and another 6.23 million (95%UI: 5.04 to 7.58) with MSVI globally. High-income countries had the highest number of individuals with AMD-related blindness (0.60 million people; 0.46 to 0.77). The crude prevalence of AMD-related blindness in 2020 (among those aged ≥ 50 years) was 0.10% (0.07 to 0.12) globally, and the region with the highest prevalence of AMD-related blindness was North Africa/Middle East (0.22%; 0.16 to 0.30). Age-standardized prevalence (using the GBD 2019 data) of AMD-related MSVI in people aged ≥ 50 years in 2020 was 0.34% (0.27 to 0.41) globally, and the region with the highest prevalence of AMD-related MSVI was also North Africa/Middle East (0.55%; 0.44 to 0.68). From 2000 to 2020, the estimated crude prevalence of AMD-related blindness decreased globally by 19.29%, while the prevalence of MSVI increased by 10.08%. Conclusions The estimated increase in the number of individuals with AMD-related blindness and MSVI globally urges the creation of novel treatment modalities and the expansion of rehabilitation services.

Abstract: Abstract Background/Aims To identify the domains of quality of life (QoL) in people with keratoconus. Methods Semi structured in-depth in person and telephone interviews were conducted with participants diagnosed with keratoconus and recruited from the Sydney Eye Hospital, Sydney, Australia. Thematic analysis of interview content was conducted using inductive and deductive processes. Data was collected until thematic saturation was obtained. Results 33 patients with keratoconus with median age 37 (range 18 to 65) years and majority male ( n = 25; 75.8%) were interviewed and a total of 2551 quotes coded. Thematic analysis resulted in 7 broad themes, Driving (199 references), Career (259 references), Symptoms (647 references), Enjoyment (149 references), Relationships (250 references), Financial (104 references) and Healthcare (881 references). Most references described a negative relationship between keratoconus and these 7 domains. The diverse QoL issues expressed included frustration with treatment effectiveness, fear of disease progression, inconvenience with contact lenses, forced career changes and job loss, cost of contact lenses, and feelings of isolation and discrimination. Themes and subthemes described a complex and varied relationship between keratoconus and QoL. Conclusion Severe quality of life impairment was experienced by keratoconus patients despite treatment. Keratoconus diminishes various aspects of individual’s QoL. Therapies able to improve QoL are still needed for keratoconus.

Abstract: This article describes the main visual electrodiagnostic tests relevant to neuro-ophthalmology practice, including the visual evoked potential (VEP), and the full-field, pattern and multifocal electroretinograms (ffERG; PERG; mfERG). The principles of electrophysiological interpretation are illustrated with reference to acquired and inherited optic neuropathies, and retinal disorders that may masquerade as optic neuropathy, including ffERG and PERG findings in cone and macular dystrophies, paraneoplastic and vascular retinopathies. Complementary VEP and PERG recordings are illustrated in demyelinating, ischaemic, nutritional (B12), and toxic (mercury, cobalt, and ethambutol-related) optic neuropathies and inherited disorders affecting mitochondrial function such as Leber hereditary optic neuropathy and dominant optic atrophy. The value of comprehensive electrophysiological phenotyping in syndromic diseases is highlighted in cases of SSBP1-related disease and ROSAH (Retinal dystrophy, Optic nerve oedema, Splenomegaly, Anhidrosis and Headache). The review highlights the value of different electrophysiological techniques, for the purposes of differential diagnosis and objective functional phenotyping.

Abstract: Abstract Objectives To compare rates of change in peripapillary retinal nerve fibre layer (pRNFL) and macular ganglion cell-inner plexiform layer (mGCIPL) parameters among different race-ethnicities from a large electronic health record database of subjects with or suspected of glaucoma. Methods In this retrospective cohort study, rates of change were obtained using joint longitudinal linear mixed models for eyes with ≥3 visits and ≥1 year of follow-up, adjusting for age, sex, intraocular pressure, central corneal thickness, and baseline pRNFL and mGCIPL thickness. Best linear unbiased predictor estimates of various parameters were stratified by baseline glaucoma severity and analysed by racial-ethnic group. Results A total of 21,472 spectral domain optical coherence tomography (OCT) pRNFL scans and 14,431 mGCIPL scans from 2002 eyes were evaluated. A total of 200 (15.6%) and 601 (46.8%) subjects identified as non-Hispanic Black (NHB) and Hispanic, respectively. NHB eyes exhibited faster rates of change in pRNFL among glaucoma suspect (global pRNFL −0.57 ± 0.55 µm/year vs. −0.37 ± 0.62 µm/year among Hispanics, p < 0.001), mild glaucoma (superior pRNFL quadrant −1.20 ± 1.06 µm/year vs. −0.75 ± 1.51 µm/year among non-Hispanic Whites (NHW), p = 0.043), and moderate glaucoma eyes (superior pRNFL quadrant −1.31 ± 1.49 µm/year vs. −0.52 ± 1.26 µm/year among Hispanics, p = 0.003). NHB eyes exhibited faster rates of mGCIPL loss corresponding to pRNFL rates. Global pRNFL and mGCIPL rates were strongly correlated (R 2 = 0.70). Conclusions Adjusted rates of pRNFL and mGCIPL loss significantly differed between racial-ethnic groups when stratified by glaucoma severity, with faster rates among NHB patients. These differences highlight key racial-ethnic disparities in adjusted rates of glaucoma OCT parameters.

Abstract: The natural history of neovascular age-related macular degeneration (nAMD) leads to scarring and loss of vision. Since the advent of anti-VEGF therapies, which are very effective for controlling exudation, large disciform scars are rarely encountered in the clinic. However long term studies show that smaller and less severe fibrotic scars are not uncommon and develop over time despite optimal treatment. This means that additional mechanisms of action may be required to completely address this condition. To permit new treatments, a proper understanding of the clinical impact of fibrosis is required. This review is focused on clinical aspects of fibrosis and summarises recent data on biomarkers, prevalence, causes, consequences, and therapies, highlighting the most important and urgent topics to tackle in order to advance in the treatment of fibrosis.

Abstract: To evaluate the relationship between the development of retinopathy of prematurity (ROP) and neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR).

Abstract: Abstract Multiple Sclerosis (MS) is a chronic autoimmune demyelinating disease of the central nervous system (CNS) characterized by inflammation, demyelination, and axonal damage. Early recognition and treatment are important for preventing or minimizing the long-term effects of the disease. Current gold standard modalities of diagnosis (e.g., CSF and MRI) are invasive and expensive in nature, warranting alternative methods of detection and screening. Oculomics, the interdisciplinary combination of ophthalmology, genetics, and bioinformatics to study the molecular basis of eye diseases, has seen rapid development through various technologies that detect structural, functional, and visual changes in the eye. Ophthalmic biomarkers (e.g., tear composition, retinal nerve fibre layer thickness, saccadic eye movements) are emerging as promising tools for evaluating MS progression. The eye’s structural and embryological similarity to the brain makes it a potentially suitable assessment of neurological and microvascular changes in CNS. In the advent of more powerful machine learning algorithms, oculomics screening modalities such as optical coherence tomography (OCT), eye tracking, and protein analysis become more effective tools aiding in MS diagnosis. Artificial intelligence can analyse larger and more diverse data sets to potentially discover new parameters of pathology for efficiently diagnosing MS before symptom onset. While there is no known cure for MS, the integration of oculomics with current modalities of diagnosis creates a promising future for developing more sensitive, non-invasive, and cost-effective approaches to MS detection and diagnosis.

Abstract: Abstract Purpose To investigate the postoperative clinical outcomes and axial length (AL) growth of infants with congenital cataracts and microphthalmos following first-stage cataract surgery. Design Retrospective case-control study. Methods Setting: Single centre. Infants with congenital cataract that met the inclusion criteria were classified into two groups: the microphthalmos and comparison groups. All infants underwent a thorough ophthalmologic examination before surgery, and one week, 1 month, 3 months, and every 3 months after surgery. Results This study enrolled 21 infants (42 eyes) in the microphthalmos group and 29 infants (58 eyes) in the comparison group. More glaucoma-related adverse events were observed in the microphthalmos group (7 eyes, 16.7%) than in the comparison group (0 eyes, 0%) ( p < 0.001). At each subsequent follow-up, the comparison group had a greater AL than the microphthalmos group (all p < 0.001), and AL growth was significantly higher in the comparison group than in the microphthalmos group (all p = 0.035). Visual acuity improvement in the microphthalmos group was similar to that of the comparison group. Conclusion Early surgical intervention improves visual function in infants with congenital cataracts and microphthalmos although with a higher incidence of glaucoma-related adverse events. After cataract removal, the AL growth of microphthalmic eyes is slower than that of normally developed eyes.

Abstract: Abstract The human population is steadily growing with increased life expectancy, impacting the prevalence of age-dependent diseases, including age-related macular degeneration (AMD). Health care systems are confronted with an increasing burden with rising patient numbers accompanied by ongoing developments of therapeutic approaches. Concurrent advances in imaging modalities provide eye care professionals with a large amount of data for each patient. Furthermore, with continuous progress in therapeutics, there is an unmet need for reliable structural and functional biomarkers in clinical trials and practice to optimize personalized patient care and evaluate individual responses to treatment. A fast and objective solution is Artificial intelligence (AI), which has revolutionized assessment of AMD in all disease stages. Reliable and validated AI-algorithms can aid to overcome the growing number of patients, visits and necessary treatments as well as maximize the benefits of multimodal imaging in clinical trials. Therefore, there are ongoing efforts to develop and validate automated algorithms to unlock more information from datasets allowing automated assessment of disease activity and disease progression. This review aims to present selected AI algorithms, their development, applications and challenges regarding assessment and prediction of AMD progression.

Abstract: Abstract Importance Worldwide, glaucoma is a leading cause of irreversible blindness. Timely detection is paramount yet challenging, particularly in resource-limited settings. A novel, computer vision-based model for glaucoma screening using fundus images could enhance early and accurate disease detection. Objective To develop and validate a generalised deep-learning-based algorithm for screening glaucoma using fundus image. Design, setting and participants The glaucomatous fundus data were collected from 20 publicly accessible databases worldwide, resulting in 18,468 images from multiple clinical settings, of which 10,900 were classified as healthy and 7568 as glaucoma. All the data were evaluated and downsized to fit the model’s input requirements. The potential model was selected from 20 pre-trained models and trained on the whole dataset except Drishti-GS. The best-performing model was further trained to classify healthy and glaucomatous fundus images using Fastai and PyTorch libraries. Main outcomes and measures The model’s performance was compared against the actual class using the area under the receiver operating characteristic (AUROC), sensitivity, specificity, accuracy, precision and the F1-score. Results The high discriminative ability of the best-performing model was evaluated on a dataset comprising 1364 glaucomatous discs and 2047 healthy discs. The model reflected robust performance metrics, with an AUROC of 0.9920 (95% CI: 0.9920–0.9921) for both the glaucoma and healthy classes. The sensitivity, specificity, accuracy, precision, recall and F1-scores were consistently higher than 0.9530 for both classes. The model performed well on an external validation set of the Drishti-GS dataset, with an AUROC of 0.8751 and an accuracy of 0.8713. Conclusions and relevance This study demonstrated the high efficacy of our classification model in distinguishing between glaucomatous and healthy discs. However, the model’s accuracy slightly dropped when evaluated on unseen data, indicating potential inconsistencies among the datasets—the model needs to be refined and validated on larger, more diverse datasets to ensure reliability and generalisability. Despite this, our model can be utilised for screening glaucoma at the population level.