Search Results (154)

Establishing baseline ultrasound biomicroscopy (UBM) measurements of the feline anterior segment is essential for accurate evaluation of ocular diseases. This study aimed to establish normative UBM parameters in clinically normal cats and to assess the influence of sex, body weight, and age on these measurements. Twenty eyes from twenty healthy adult cats were examined using a standardized UBM protocol under general anesthesia to ensure consistent positioning and optimal visualization. Quantitative measurements were obtained for corneal, anterior chamber, iris, ciliary cleft, and ciliary body parameters. The mean perilimbal corneal thickness was 0.59 mm, anterior chamber depth was 4.11 mm, and peripheral anterior chamber depth was 3.11 mm. The angle-opening distance and iridocorneal angle measured 1.73 mm and 28.89°, respectively. Ciliary cleft parameters included a width of 1.22 mm, length of 2.07 mm, and area of 1.10 mm². Longitudinal and combined longitudinal–radial ciliary body thicknesses were 0.52 mm and 0.78 mm, respectively, while ciliary body axial length and ciliary process scleral angle averaged 2.01 mm and 58.98°. Iris base width and iris middle width measured 0.35 mm and 0.54 mm, respectively. Sex-based analysis revealed significant differences in peripheral anterior chamber depth and ciliary cleft width, whereas body weight showed positive correlations with iris thickness parameters. No significant associations were identified between age and any anterior segment measurements. These findings establish comprehensive normative UBM reference values for the feline anterior segment and provide a quantitative anatomical framework for future clinical and disease-oriented studies in feline ophthalmology. Full article

Diabetes mellitus and its microvascular complications, including diabetic retinopathy (DR), present significant health challenges. DR is a leading cause of vision impairment and blindness among working-age individuals in developed countries. The prevalence of DR continues to rise, underscoring the need for more precise diagnostic and therapeutic strategies. Due to its multifactorial nature and despite advancements in understanding DR pathophysiology, predicting its onset and progression remains challenging. Traditional screening and treatment methods often fall short of addressing the heterogeneous nature of the disease, underscoring the need for personalised therapeutic strategies. Recent research has highlighted the vital role of genetic biomarkers in the development and progression of DR, paving the way for a precision medicine approach. Personalised eye care in patients with diabetes aims to accurately predict the risk of DR progression and visual loss in real time. A precision medicine approach that utilises genetic biomarkers offers a promising pathway for personalised diagnosis and treatment strategies. Each DR case is distinct in phenotype, genotype, and therapeutic response, making personalised therapy crucial for optimising outcomes. Advancements in genomics, including genome-wide association studies (GWAS) and next-generation sequencing (NGS), have identified numerous genetic markers associated with DR susceptibility and severity. Emerging evidence underscores the critical role of genetic factors, which account for 25–50% of the risk of developing DR. Advances in identifying genetic markers, such as gene polymorphisms and human leukocyte antigen associations, along with the development of targeted drugs, highlight a promising future for personalised medicine in DR. By identifying specific genetic variants associated with DR, we can enhance prevention and early diagnosis, tailor personalised treatment plans, and more accurately predict disease progression. This represents a critical step toward personalised medicine in DR management. Integrating genetic and epigenetic biomarkers into clinical models may transform DR care through earlier diagnosis and precision-guided interventions, gearing it toward precision ophthalmology. Full article

Purpose: This review consolidates current evidence on how chronic kidney disease (CKD)-especially end-stage kidney disease (ESKD) and its treatments-alters choroidal and retinal vascular permeability, leading to changes in intraocular fluid homeostasis. Methods: A literature search of Medical Literature Analysis and Retrieval System Online (MEDLINE), reference lists, and key ophthalmology-nephrology texts was performed for studies published between 1980 and 2025. One-hundred-forty-four articles (clinical trials, observational cohorts, and case reports) met the inclusion criteria. Data were abstracted on choroidal thickness changes, blood-retinal barrier integrity, incidence of Central Serous Chororioretinopathy (CSCR) and Serous Retinal Detachment (SRD) in dialysis and transplant populations, and systemic variables such as oncotic pressure, hypertension, and corticosteroid exposure, with special attention to retinal pigment epithelium (RPE) pump function. Findings were synthesized qualitatively and tabulated where appropriate. Results: ESKD induces a triad of lowered plasma oncotic pressure, fluctuating hydrostatic forces, and impaired RPE pump function that collectively drive subretinal fluid accumulation. Hemodialysis acutely reduces sub-foveal choroidal thickness by a mean of ≈15–25 µm yet shows inconsistent effects on retinal thickness. Large population data demonstrate a three- to four-fold higher SRD risk and ~1.5-fold higher CSCR risk in dialysis patients versus controls, with peritoneal dialysis conferring the greatest hazard. After kidney transplantation, CSCR prevalence approaches 6%, driven by combined stresses of surgery, hypertension, and long-term corticosteroid or calcineurin-inhibitor therapy. Most reported SRDs resolve as systemic parameters normalize, underscoring the importance of promptly identifying systemic drivers. Conclusions: Systemic fluid-pressure imbalances and treatment-related factors in CKD significantly perturb the outer blood-retinal barrier. Regular ophthalmic surveillance, early visual-symptom screening (e.g., Amsler grid), and close nephrologist-ophthalmologist collaboration are essential for timely detection and management. Future research should quantify the relative contribution of hypoalbuminemia, hypertension, and immunosuppression to ocular permeability changes, and evaluate preventive strategies tailored to high-risk CKD subgroups. Full article

This paper provides an overview of artificial intelligence (AI) applications in ophthalmology, with a focus on diagnosing dry eye disease (DED). We aim to synthesize studies that explicitly compare AI-based diagnostic models with clinical tests employed by ophthalmologists, examine results obtained using similar imaging modalities, and identify recurring limitations to propose recommendations for future work. We conducted a systematic literature search following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines across four databases: Google Scholar, PubMed, ScienceDirect, and the Cochrane Library. We targeted studies published between 2020 and 2025 and applied predefined inclusion criteria to select 30 original peer-reviewed articles. We then analyzed each study based on the AI models used, development strategies, diagnostic performance, correlation with clinical parameters, and reported limitations. The imaging modalities covered include videokeratography, smartphone-based imaging, tear film interferometry, anterior segment optical coherence tomography, infrared meibography, in vivo confocal microscopy, and slit-lamp photography. Across modalities, deep learning models (e.g., U-shaped Convolutional Network (U-Net), Residual Network (ResNet), Densely Connected Convolutional Network (DenseNet), Generative Adversarial Networks (GANs), transformers) demonstrated promising performance, often matching or surpassing clinical assessments, with reported accuracies ranging from 82% to 99%. However, few studies performed external validations or addressed inter-expert variability. The findings confirm AI’s potential in DED diagnosis, but emphasize gaps in data diversity, clinical use, and reproducibility. It offers practical recommendations for future research to bridge these gaps and support AI deployment in routine eye care. Full article

Background: Hypochlorous acid (HOCl) is an integral component of the human innate immune system. It possesses antimicrobial properties and is available in solution, dermal spray, and scar gel forms. Objectives/Methods: This review presents data from studies on the clinical use of HOCl in various specialties, including dermatology, surgery, dentistry, ophthalmology, and rhinology. Results: Due to its anti-inflammatory/antimicrobial/immunomodulatory and healing properties, HOCl is advantageous in treating various skin disorders: ulcus cruris (and wound care), diabetic ulcers, atopic dermatitis, seborrheic dermatitis, pruritus, acne vulgaris, etc. Also, the application of a HOCl spray/gel after surgical procedures may prevent infection, reduce inflammation, and accelerate healing. HOCl is also effective and safe for the prevention and treatment of hypertrophic and keloid scars. Growing evidence shows a broader role for HOCl in limiting cancer cell survival and slowing tumor growth. It is also important in treating various viral infections like SARS-CoV-2 (coronavirus), influenza, and herpes, thereby helping to prevent the spread of aerosols. In addition, since HOCl is an endogenous compound naturally present in mammals with a high safety profile, it may be an effective bacterial disinfectant in dental waterlines. In ophthalmology, adjuvant treatment with HOCl ophthalmic spray can reduce the duration of antibiotic/corticosteroid use, even in severe blepharitis. To fully harness the protective/therapeutic properties of HOCl, future advancements will rely on the development of new chemical compounds and sophisticated pharmaceutical formulations. Conclusions: The majority of clinical studies have confirmed that HOC1 is useful in therapy, although the results are not entirely consistent. Further research is essential to optimize HOCl dosing and to develop controlled-release systems aimed at maximizing its anti-inflammatory and photoprotective effects while minimizing tissue irritation and damage. Full article

Background: INPP5E-related retinopathy (INPP5E-RR) is a rare genetic disorder caused by biallelic pathogenic variants in the INPP5E gene, which encodes an enzyme critical for phosphoinositide signaling. While early-onset rod–cone dystrophy is a hallmark feature, detailed longitudinal data on the phenotype are scarce. This study aims to report a 6-year longitudinal assessment of retinal structure and function in a case of non-syndromic INPP5E-RR. Methods: A 42-year-old female proband with compound heterozygous pathogenic missense variants in INPP5E (p.Arg486Cys and p.Arg378Cys) was monitored from 2019 to 2025. She underwent serial comprehensive ophthalmologic evaluations, including optical coherence tomography (OCT), fundus autofluorescence, adaptive optics transscleral flood illumination, full-field 30Hz flicker electroretinography (ERG), and macular frequency-doubling technology perimetry. Results: Over the 6-year follow-up, OCT imaging revealed a progressive decline in the ellipsoid zone (EZ) width, from 1220 µm to 720 µm (~80 µm/year), and in the inner nuclear layer (INL) thickness. The central outer nuclear layer (ONL) thickness was preserved, but intraretinal cysts developed. Functional testing revealed a progressive decline in cone flicker ERG amplitudes, while visual acuity and macular perimetry remained stable. Conclusions: In this genotypically confirmed case, the longitudinal data identify EZ width, INL thickness, and cone flicker ERG as robust biomarkers of disease progression in INPP5E-RR. These parameters are ideal candidates for monitoring therapeutic outcomes in future clinical trials. Full article

Ophthalmic drug delivery encounters unique challenges due to the anatomical and physiological ocular barriers, necessitating the development of novel drug delivery systems (NDDSs). This review focuses on emerging therapeutic platforms, including nanoemulsions (NEs), microemulsions (MEs), self-emulsifying drug delivery systems (SEDDSs) such as self-nano emulsifying drug delivery systems (SNEDDSs) and self-micro emulsifying drug delivery systems (SMEDDSs), emulgels, and in situ-forming emulgels, as novel strategies for enhancing ocular drug delivery. NEs and MEs, due to their small globule size, excellent drug solubility, stability, and bioavailability, offer promising solutions for effective ocular therapy. SEDDSs further enhance the stability and bioavailability of hydrophobic drugs through self-emulsification in aqueous environments. Emulgels, combining the benefits of emulsions and gels, provide sustained and controlled release of therapeutic agents, improving the ocular retention time and therapeutic efficacy. Additionally, in situ-forming emulgels offer the advantage of liquid-to-gel transition upon contact with ocular surfaces, optimizing drug delivery. The review discusses various ocular diseases, challenges for ocular delivery of conventional formulations, updates on emulsion-based novel drug delivery systems for ophthalmic drug delivery, mechanisms of enhanced ocular permeation, formulation strategies, advantages, and challenges, design-of-experiment considerations for optimization, characterizations, and recent advancements in these systems including patents and clinical trials, highlighting their potential for improving the treatment of various ocular diseases. Furthermore, this review explores marketed ophthalmic emulsions and future prospects for integrating these NDDSs into clinical ophthalmology, emphasizing their ability to overcome ocular barriers and enhance therapeutic efficacy. Full article

Antimicrobial resistance (AMR) is a growing global health concern with profound implications for ophthalmology, where it compromises the management of ocular infections such as bacterial keratitis, conjunctivitis, endophthalmitis, and postoperative complications. Resistance in common ocular pathogens, including Staphylococcus aureus (S. aureus), Streptococcus pneumoniae (S. pneumoniae), Pseudomonas aeruginosa (P. aeruginosa), and coagulase-negative staphylococci (CoNS) emerge through genetic mutations, horizontal gene transfer, and biochemical mechanisms such as enzymatic degradation, target modification, efflux pumps, and reduced membrane permeability. Biofilm formation further complicates eradication on the ocular surface and interior. The key drivers of resistance include inappropriate or prolonged topical antibiotic use, routine prophylaxis in ocular surgery, subtherapeutic dosing, and cross-resistance with systemic antimicrobials. The rise in multidrug-resistant strains, particularly methicillin-resistant S. aureus, fluoroquinolone-resistant P. aeruginosa, and drug-resistant S. pneumoniae has been linked to delayed treatment response, increased healthcare costs, and sight-threatening outcomes. Recent advances in rapid diagnostics, molecular assays, and point-of-care testing support earlier and more precise detection of resistance, enabling timely therapeutic decisions. Promising strategies to address AMR in ophthalmology include antimicrobial stewardship, novel drug delivery platforms, and alternative approaches such as bacteriophage therapy and antimicrobial peptides. Emerging tools, including genomic surveillance, artificial intelligence (AI)-driven resistance prediction, and personalized antimicrobial regimens, further expand opportunities for innovation. Collectively, this review synthesizes current evidence on AMR in ocular disease, summarizing patterns of resistance, underlying mechanisms, and clinical consequences, while highlighting strategies for mitigation and underscoring the need for global awareness and collaboration among clinicians, researchers, and policymakers to safeguard vision. Full article

Hydrogel films have emerged as versatile platforms in biomedical engineering due to their unique physicochemical properties, biocompatibility, and adaptability to diverse therapeutic needs. This review provides a comprehensive overview of hydrogel film materials, including natural biopolymers, synthetic polymers, and multifunctional composites, highlighting their structural and functional diversity. We examine key fabrication techniques—ranging from solvent casting and photopolymerization to advanced methods like microfluidics and 3D printing—and discuss how these influence film architecture and performance. The biomedical applications of hydrogel films span wound healing, drug delivery, tissue engineering, ophthalmology, and implantable biosensors, with recent innovations enabling stimuli-responsive behavior, multi-drug loading, and integration with wearable electronics. Despite their promise, hydrogel films face persistent challenges in mechanical durability, sterilization, storage stability, regulatory approval, and scalable manufacturing. We conclude by identifying critical research gaps and outlining future directions, including AI-guided design, sustainable material development, and the establishment of standardized, regulatory-aligned, and industrially scalable fabrication strategies to accelerate clinical translation. Full article

Background: Refractive errors are a common ophthalmological complaint, with a significant potential on the quality of life of our patients—myopia in particular has a growing incidence worldwide. Recent research focused on the ratio between the axial length of the eye (AL) and the corneal radius of curvature (CR), as it had proven valuable in refractive error diagnosis, and risk of progression and of complications. The objective of the study is to compare young emmetropic, hyperopic, and myopic eyes in terms of corneal biomechanics and ocular biometry, focusing on the AL/CR ratio. Methods: This cross-sectional study included 144 myopic eyes, 92 emmetropic eyes, and 47 hyperopic eyes. Measurements included cycloplegic autorefractometry (SE—spherical equivalent), Ocular Response Analyzer (CH—corneal hysteresis, CRF—corneal resistance factor), Aladdin biometry (AL, CR, ACD—anterior chamber depth, CCT—central corneal thickness, AL/CR ratio). Results: ACD, AL, and AL/CR were significantly higher and CCT, SE, CH, and CRF were lower in myopia. The AL/CR ratio correlated positively with AL and ACD and negatively with SE and CR in myopes and hyperopes, and correlated positively with AL and negatively with SE, CH, CRF, and CCT in emmetropes. Conclusions: The AL/CR ratio is significantly higher in myopes and significantly lower in hyperopes, compared to emmetropes, with differences also being in biomechanical properties (CH, CRF) and morphological ones (AL, CCT, ACD). This suggests the AL/CR ratio as a future potential biomarker for refractive errors, particularly for their risk of progression and complications. Full article

Dry eye disease (DED) is a highly prevalent multifactorial disorder of the ocular surface that extends beyond local tear film pathology to involve systemic immune, neuroendocrine, and neurosensory mechanisms. Increasing evidence reveals a strong and bidirectional association between DED and psychiatric disorders, particularly depression, anxiety, post-traumatic stress disorder (PTSD), and sleep disturbances. This review synthesises the current knowledge on shared molecular, neuroimmune, and neuropathic pathways that underlie this comorbidity. Key mechanisms include hypothalamic–pituitary–adrenal (HPA) axis dysregulation, systemic and ocular inflammation, oxidative stress, mitochondrial dysfunction, and impaired neurotrophic signaling, especially reduced brain-derived neurotrophic factor (BDNF). Dysregulation of monoaminergic neurotransmitters such as serotonin and norepinephrine not only contributes to mood disturbances but also alters tear secretion and corneal pain perception. Corneal nerve changes and trigeminal–limbic sensitisation further reinforce the overlap between neuropathic ocular pain and affective dysregulation. Psychotropic medications, while essential for psychiatric care, may exacerbate ocular surface dysfunction through anticholinergic effects, altered neurotransmission, and tear film instability, highlighting the iatrogenic dimension of this interface. Conversely, tear-based biomarkers, including cytokines, serotonin, and BDNF, offer promising translational tools for patient stratification, diagnosis, and treatment monitoring across ocular and psychiatric domains. Recognising DED as part of a systemic, biopsychosocial continuum is critical for effective management. Multidisciplinary strategies that integrate ophthalmologic and psychiatric care, alongside novel therapies targeting shared molecular pathways, provide a framework for improving outcomes. Future research should prioritise longitudinal studies, biomarker validation, and personalised interventions to address this complex comorbidity. Full article

Intraocular neoplasia in horses is rare and only few case reports and small case series exist. Intraocular neoplasia has various clinical signs and includes important differential diagnoses in ocular disease. This narrative review of the current literature aims to provide a clinically relevant overview and classification of intraocular tumors in horses and adds a comparative oncological perspective concerning diagnosis, treatment and future considerations. The available clinical and imaging examination techniques allow for a reliable and differentiated investigation of the tumor, even in the standing horse, using high-frequency ultrasound or optical coherence tomography, which have gained importance in equine ophthalmology. Sectional imaging techniques, in particular computed tomography, are suitable for the examination of the peribulbar, retrobulbar and orbital structures. Differentiated diagnostics including precise tumor staging (TNM: tumor, node, metastasis) are essential for a general prognostic and therapeutic assessment. The embryologic and anatomic tissue origin of the neoplasm is the basis for clinicopathologic classification. Medulloepithelioma and uveal melanocytic neoplasia are the most common intraocular tissue formations occurring in horses. Whereas melanocytic neoplasia of the iris can be treated surgically, neuroepithelial tumors regularly lead to bulbus extirpation. Other primary intraocular neoplasms are sporadically reported, as well as intraocular metastasis of systemic neoplasia. Chemotherapy and radiation therapy are not currently used to treat intraocular neoplasia in horses and need to be further investigated, especially regarding the latest developments in human and small animal medicine. In addition, horses and dogs may serve as models for human oncologic research. Full article

Background: Papilledema, an ophthalmic finding associated with increased intracranial pressure, is often induced by dermatological medications, including corticosteroids, isotretinoin, and tetracyclines. Early detection is crucial for preventing irreversible optic nerve damage, but access to ophthalmologic expertise is often limited in rural settings. Artificial intelligence (AI) may enable the automated and accurate detection of papilledema from fundus images, thereby supporting timely diagnosis and management. Objective: The primary objective of this study was to explore the diagnostic capability of ChatGPT-4o, a general large language model with multimodal input, in identifying papilledema from fundus photographs. For context, its performance was compared with a ResNet-based convolutional neural network (CNN) specifically fine-tuned for ophthalmic imaging, as well as with the assessments of two human ophthalmologists. The focus was on applications relevant to dermatological care in resource-limited environments. Methods: A dataset of 1094 fundus images (295 papilledema, 799 normal) was preprocessed and partitioned into a training set and a test set. The ResNet model was fine-tuned using discriminative learning rates and a one-cycle learning rate policy. GPT-4o and two human evaluators (a senior ophthalmologist and an ophthalmology resident) independently assessed the test images. Diagnostic metrics including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and Cohen’s Kappa, were calculated for each evaluator. Results: GPT-4o, when applied to papilledema detection, achieved an overall accuracy of 85.9% with substantial agreement beyond chance (Cohen’s Kappa = 0.72), but lower specificity (78.9%) and positive predictive value (73.7%) compared to benchmark models. For context, the ResNet model, fine-tuned for ophthalmic imaging, reached near-perfect accuracy (99.5%, Kappa = 0.99), while two human ophthalmologists achieved accuracies of 96.0% (Kappa ≈ 0.92). Conclusions: This study explored the capability of GPT-4o, a large language model with multimodal input, for detecting papilledema from fundus photographs. GPT-4o achieved moderate diagnostic accuracy and substantial agreement with the ground truth, but it underperformed compared to both a domain-specific ResNet model and human ophthalmologists. These findings underscore the distinction between generalist large language models and specialized diagnostic AI: while GPT-4o is not optimized for ophthalmic imaging, its accessibility, adaptability, and rapid evolution highlight its potential as a future adjunct in clinical screening, particularly in underserved settings. These findings also underscore the need for validation on external datasets and real-world clinical environments before such tools can be broadly implemented. Full article

This study aimed to evaluate the performance of seven advanced AI Large Language Models (LLMs)—ChatGPT 4o, ChatGPT O3 Mini, ChatGPT O1, DeepSeek V3, DeepSeek R1, Gemini 2.0 Flash, and Grok-3—in answering multiple-choice questions (MCQs) in optics and refractive surgery, to assess their role in medical education for residents. The AI models were tested using 134 publicly available MCQs from national ophthalmology certification exams, categorized by the need to perform calculations, the relevant subspecialty, and the use of images. Accuracy was analyzed and compared statistically. ChatGPT O1 achieved the highest overall accuracy (83.5%), excelling in complex optical calculations (84.1%) and optics questions (82.4%). DeepSeek V3 displayed superior accuracy in refractive surgery-related questions (89.7%), followed by ChatGPT O3 Mini (88.4%). ChatGPT O3 Mini significantly outperformed others in image analysis, with 88.2% accuracy. Moreover, ChatGPT O1 demonstrated comparable accuracy rates for both calculated and non-calculated questions (84.1% vs. 83.3%). This is in stark contrast to other models, which exhibited significant discrepancies in accuracy for calculated and non-calculated questions. The findings highlight the ability of LLMs to achieve high accuracy in ophthalmology MCQs, particularly in complex optical calculations and visual items. These results suggest potential applications in exam preparation and medical training contexts, while underscoring the need for future studies designed to directly evaluate their role and impact in medical education. The findings highlight the significant potential of AI models in ophthalmology education, particularly in performing complex optical calculations and visual stem questions. Future studies should utilize larger, multilingual datasets to confirm and extend these preliminary findings. Full article

Background/Objectives: Patient education materials (PEMs) in ophthalmology often exceed recommended readability levels, limiting accessibility for many patients. While organizations like the AAO provide relatively easy-to-read resources, topics remain limited, and other associations’ PEMs are too complex. AI chatbots could help clinicians create more comprehensive, accessible PEMs to improve patient understanding. This study aims to compare the readability of patient education materials (PEMs) written by the American Academy of Ophthalmology (AAO) with those generated by large language models (LLMs), including ChatGPT-4o, Microsoft Copilot, and Meta-Llama-3.1-70B-Instruct. Methods: LLMs were prompted to generate PEMs for 15 common diagnoses relating to cornea and anterior chamber, which was followed by a follow-up readability-optimized (FRO) prompt to reword the content at a 6th-grade reading level. The readability of these materials was evaluated using nine different readability analysis python libraries and compared to existing PEMs found on the AAO website. Results: For all 15 topics, ChatGPT, Copilot, and Llama successfully generated PEMs, though all exceeded the recommended 6th-grade reading level. While initially prompted ChatGPT, Copilot, and Llama outputs were 10.8, 12.2, and 13.2, respectively, FRO prompting significantly improved readability to 8.3 for ChatGPT, 11.2 for Copilot, and 9.3 for Llama (p < 0.001). While readability improved, AI-generated PEMs were on average, not statistically easier to read than AAO PEMs, which averaged an 8.0 Flesch–Kincaid Grade Level. Conclusions: Properly prompted AI chatbots can generate PEMs with improved readability, nearing the level of AAO materials. However, most outputs remain above the recommended 6th-grade reading level. A subjective analysis of a representative subtopic showed that compared to AAO, there was less nuance, especially in areas of clinical uncertainty. By creating a blueprint that can be utilized in human–AI hybrid workflows, AI chatbots show promise as tools for ophthalmologists to increase the availability of accessible PEMs in ophthalmology. Future work should include a detailed qualitative review by ophthalmologists using a validated tool (like DISCERN or PEMAT) to score accuracy, bias, and completeness alongside readability. Full article