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PurposeTo report a case of systemic diffuse large B cell lymphoma presenting with ocular manifestations and neurologic findings resembling Vogt-Koyanagi-Harada syndrome.ObservationsA 51-year-old Caucasian man presented with headache, ear pain, and blurry vision in both eyes. He was found to have bilateral exudative retinal detachments. After a short period of initial improvement with high dose systemic corticosteroid, his condition significantly worsened. An extensive work-up, including a kidney biopsy, led to a diagnosis of systemic diffuse large B cell lymphoma. He had excellent recovery following treatment with appropriate chemotherapy.Conclusions and importanceSystemic malignancy may present with ocular manifestations and may masquerade as another diagnosis. An unexpected clinical course may suggest an alternative diagnosis. A broad systemic work-up including an evaluation for malignancy should be considered for patients presenting with unexplained exam or systemic findings.

To identify functionally related genes associated with diabetic retinopathy (DR) risk using gene set enrichment analyses applied to genome-wide association study meta-analyses.MethodsWe analyzed DR GWAS meta-analyses performed on 3246 Europeans and 2611 African Americans with type 2 diabetes. Gene sets relevant to 5 key DR pathophysiology processes were investigated: tissue injury, vascular events, metabolic events and glial dysregulation, neuronal dysfunction, and inflammation. Keywords relevant to these processes were queried in 4 pathway and ontology databases. Two GSEA methods, Meta-Analysis Gene set Enrichment of variaNT Associations (MAGENTA) and Multi-marker Analysis of GenoMic Annotation (MAGMA), were used. Gene sets were defined to be enriched for gene associations with DR if the P value corrected for multiple testing (Pcorr) was

PurposeTo investigate the natural history and genetic associations of drusenoid pigment epithelial detachment (DPED) associated with age-related macular degeneration (AMD).DesignRetrospective analysis of a prospective cohort study.ParticipantsOf the 4203 Age-Related Eye Disease Study 2 (AREDS2) participants, 391 eyes (325 participants) had DPED without late AMD at the time of DPED detection. Genetic analyses included 120 white AREDS2 participants and 145 Age-Related Eye Disease Study (AREDS) participants with DPED.MethodsBaseline and annual stereoscopic fundus photographs were graded centrally to detect DPED, a well-defined yellow elevated mound of confluent drusen ≥433 μm in diameter, and to evaluate progression rates to late AMD: geographic atrophy (GA) and neovascular (NV)-AMD. Five single nucleotide polymorphisms (CFH [rs10611670], C3 [rs2230199], CFI [rs10033900], C2/CFB [rs114254831], ARMS2 [rs10490924]) and genetic risk score (GRS) group were investigated for association with DPED development. Kaplan-Meier analyses and multivariable proportional hazard regressions were performed.Main outcome measuresProgression rates to late AMD and decrease of ≥3 lines in visual acuity (VA) from the time of DPED detection; association of rate of DPED development with genotype.ResultsMean (standard deviation [SD]) follow-up time from DPED detection was 4.7 (0.9) years. DPED was associated with increased risk of progression to late AMD (hazard ratio [HR], 2.36; 95% confidence interval [CI], 1.98-2.82; P < 0.001); 67% of eyes progressed to late AMD 5 years after DPED detection. Drusenoid pigment epithelial detachment was associated with increased risk of ≥3 lines of VA loss (HR, 3.08; CI, 2.41-3.93; P < 0.001) with 46% of eyes experiencing vision loss at 5 years (with or without progression to late AMD). ARMS2 risk alleles (1 vs. 0: HR, 2.72, CI, 1.58-4.70; 2 vs. 0: HR, 3.16, CI, 1.60-6.21, P < 0.001) and increasing GRS group (4 vs. 1) (HR, 12.17, CI, 3.66-40.45, P < 0.001) were significantly associated with DPED development in AREDS. There were no significant genetic results in AREDS2.ConclusionsThis study replicates the results of previous natural history studies of eyes with DPED including the high rates of progression to late AMD and vision loss (regardless of progression to late AMD). The genetic associations are consistent with genes associated with AMD progression.

To identify genetic variants associated with diabetic retinopathy (DR), we performed a large multiethnic genome-wide association study. Discovery included eight European cohorts (n = 3,246) and seven African American cohorts (n = 2,611). We meta-analyzed across cohorts using inverse-variance weighting, with and without liability threshold modeling of glycemic control and duration of diabetes. Variants with a P value

Objectives To develop, validate, and implement algorithms to identify diabetic retinopathy (DR) cases and controls from electronic health care records (EHRs). Materials and Methods We developed and validated electronic health record (EHR)-based algorithms to identify DR cases and individuals with type I or II diabetes without DR (controls) in 3 independent EHR systems: Vanderbilt University Medical Center Synthetic Derivative (VUMC), the VA Northeast Ohio Healthcare System (VANEOHS), and Massachusetts General Brigham (MGB). Cases were required to meet 1 of the following 3 criteria: (1) 2 or more dates with any DR ICD-9/10 code documented in the EHR, (2) at least one affirmative health-factor or EPIC code for DR along with an ICD9/10 code for DR on a different day, or (3) at least one ICD-9/10 code for any DR occurring within 24 hours of an ophthalmology examination. Criteria for controls included affirmative evidence for diabetes as well as an ophthalmology examination. Results The algorithms, developed and evaluated in VUMC through manual chart review, resulted in a positive predictive value (PPV) of 0.93 for cases and negative predictive value (NPV) of 0.91 for controls. Implementation of algorithms yielded similar metrics in VANEOHS (PPV = 0.94; NPV = 0.86) and lower in MGB (PPV = 0.84; NPV = 0.76). In comparison, the algorithm for DR implemented in Phenome-wide association study (PheWAS) in VUMC yielded similar PPV (0.92) but substantially reduced NPV (0.48). Implementation of the algorithms to the Million Veteran Program identified over 62 000 DR cases with genetic data including 14 549 African Americans and 6209 Hispanics with DR. Conclusions/Discussion We demonstrate the robustness of the algorithms at 3 separate healthcare centers, with a minimum PPV of 0.84 and substantially improved NPV than existing automated methods. We strongly encourage independent validation and incorporation of features unique to each EHR to enhance algorithm performance for DR cases and controls. [ABSTRACT FROM AUTHOR]

Purpose: To assess the diagnostic performance of two chatbots, ChatGPT and Glass, in uveitis diagnosis compared to renowned uveitis specialists, and evaluate clinicians' perception about utilizing artificial intelligence (AI) in ophthalmology practice. Methods: Six cases were presented to uveitis experts, ChatGPT (version 3.5 and 4.0) and Glass 1.0, and diagnostic accuracy was analyzed. Additionally, a survey about the emotions, confidence in utilizing AI-based tools, and the likelihood of incorporating such tools in clinical practice was done. Results: Uveitis experts accurately diagnosed all cases (100%), while ChatGPT achieved a diagnostic success rate of 66% and Glass 1.0 achieved 33%. Most attendees felt excited or optimistic about utilizing AI in ophthalmology practice. Older age and high level of education were positively correlated with increased inclination to adopt AI-based tools. Conclusions: ChatGPT demonstrated promising diagnostic capabilities in uveitis cases and ophthalmologist showed enthusiasm for the integration of AI into clinical practice. [ABSTRACT FROM AUTHOR]

Introduction: Accurate diagnosis and timely management are vital for favorable uveitis outcomes. Artificial Intelligence (AI) holds promise in medical decision-making, particularly in ophthalmology. Yet, the diagnostic precision and management advice from AI-based uveitis chatbots lack assessment. Methods: We appraised diagnostic accuracy and management suggestions of an AI-based chatbot, ChatGPT, versus five uveitis-trained ophthalmologists, using 25 standard cases aligned with new Uveitis Nomenclature guidelines. Participants predicted likely diagnoses, two differentials, and next management steps. Comparative success rates were computed. Results: Ophthalmologists excelled (60–92%) in likely diagnosis, exceeding AI (60%). Considering fully and partially accurate diagnoses, ophthalmologists achieved 76–100% success; AI attained 72%. Despite an 8% AI improvement, its overall performance lagged. Ophthalmologists and AI agreed on diagnosis in 48% cases, with 91.6% exhibiting concurrence in management plans. Conclusions: The study underscores AI chatbots' potential in uveitis diagnosis and management, indicating their value in reducing diagnostic errors. Further research is essential to enhance AI chatbot precision in diagnosis and recommendations. [ABSTRACT FROM AUTHOR]

PurposeTo analyze the prevalence, incidence, and clinical characteristics of eyes with geographic atrophy (GA) in age-related macular degeneration (AMD), including clinical and genetic factors affecting enlargement.DesignProspective cohort study within a controlled clinical trial.ParticipantsAge-Related Eye Disease Study 2 (AREDS2) participants, aged 50-85 years.MethodsBaseline and annual stereoscopic color fundus photographs were evaluated for GA presence and area. Analyses included GA prevalence and incidence rates, Kaplan-Meier rates, mixed-model regression, and multivariable analysis of the square root of GA, area adjusted for covariates, including clinical/imaging characteristics and genotype.Main outcome measures(1) Presence or development of GA; (2) change in the square root of GA area over time.ResultsAt baseline, 517 eyes (6.2%) of 411 participants (9.8%) had pre-existing GA (without neovascular AMD), with the following characteristics: 33% central, 67% noncentral; and the following configurations: 36% small, 26% solid/unifocal, 24% multifocal, 9% horseshoe/ring, and 6% indeterminate. Of the remaining 6530 eyes at risk, 1099 eyes (17.3%) of 883 participants developed incident GA without prior neovascular disease during mean follow-up of 4.4 years. The Kaplan-Meier rate of incident GA was 19% of eyes at 5 years. In eyes with incident GA, 4-year risk of subsequent neovascular AMD was 29%. In eyes with incident noncentral GA, 4-year risk of central involvement was 57%. GA enlargement rate (following square root transformation) was similar in eyes with pre-existing GA (0.29 mm/year; 95% confidence interval 0.27-0.30) and incident GA (0.28 mm/year; 0.27-0.30). In the combined group, GA enlargement was significantly faster with noncentrality, multifocality, intermediate baseline size, and bilateral GA (P < 0.0001 for interaction in each case) but not with AREDS2 treatment assignment (P = 0.33) or smoking status (P = 0.05). Enlargement was significantly faster with ARMS2 risk (P < 0.0001), C3 non-risk (P = 0.0002), and APOE non-risk (P = 0.001) genotypes.ConclusionsAnalyses of AREDS2 data on natural history of GA provide representative data on GA evolution and enlargement. GA enlargement, which was influenced by lesion features, was relentless, resulting in rapid central vision loss. The genetic variants associated with faster enlargement were partially distinct from those associated with risk of incident GA. These findings are relevant to further investigations of GA pathogenesis and clinical trial planning.

PurposeDiabetic retinopathy is the most common eye complication in patients with diabetes. The purpose of this study is to identify genetic factors contributing to severe diabetic retinopathy.MethodsA genome-wide association approach was applied. In the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) datasets, cases of severe diabetic retinopathy were defined as type 2 diabetic patients who were ever graded as having severe background retinopathy (Level R3) or proliferative retinopathy (Level R4) in at least one eye according to the Scottish Diabetic Retinopathy Grading Scheme or who were once treated by laser photocoagulation. Controls were diabetic individuals whose longitudinal retinopathy screening records were either normal (Level R0) or only with mild background retinopathy (Level R1) in both eyes. Significant Single Nucleotide Polymorphisms (SNPs) were taken forward for meta-analysis using multiple Caucasian cohorts.ResultsFive hundred and sixty cases of type 2 diabetes with severe diabetic retinopathy and 4,106 controls were identified in the GoDARTS cohort. We revealed that rs3913535 in the NADPH Oxidase 4 (NOX4) gene reached a p value of 4.05 × 10-9 . Two nearby SNPs, rs10765219 and rs11018670 also showed promising p values (p values = 7.41 × 10-8 and 1.23 × 10-8 , respectively). In the meta-analysis using multiple Caucasian cohorts (excluding GoDARTS), rs10765219 and rs11018670 showed associations for diabetic retinopathy (p = 0.003 and 0.007, respectively), while the p value of rs3913535 was not significant (p = 0.429).ConclusionThis genome-wide association study of severe diabetic retinopathy suggests new evidence for the involvement of the NOX4 gene.