Faculty Bibliography

OBJECTIVE:To assess the feasibility of remotely training glaucoma patients to take a 10-session clustered virtual reality (VR) visual field (VF) test (Vivid Vision Perimetry [VVP-10]) at home, analyze results for test-retest variability, and assess correspondence with conventional perimetry. DESIGN/METHODS:Cross-sectional study. SUBJECTS/METHODS:Twenty-one subjects with glaucoma were enrolled and included in the feasibility assessment of remote training. Thirty-six eyes were used for test-retest analysis and determination of concordance with the Humphrey Field Analyzer (HFA). METHODS:Subjects were provided with a mobile VR headset containing the VVP-10 test software and trained remotely via video conferencing. Subjects were instructed to complete 10 sessions over a 14-day period. MAIN OUTCOME MEASURES/METHODS:Feasibility was determined by the number of subjects who were able to independently complete VVP-10 over the 14-day period after 1 remote training session. The intraclass correlation coefficient (ICC) for average fraction seen across 10 sessions and the standard error (SE) of the mean were primary outcome measures for assessing test-retest variability. Correlation with HFA mean sensitivity (MS) across eyes, was a secondary outcome measure. RESULTS:Twenty subjects (95%) successfully completed the VVP-10 test series after 1 training session. The ICC for VVP-10 was 0.95 (95% confidence interval [CI], 0.92-0.97). The mean SE in units of fraction seen was 0.012. The Spearman correlations between VVP-10 average fraction seen and HFA MS were 0.87 (95% CI, 0.66-0.98) for moderate-to-advanced glaucoma eyes, and decreased to 0.67 (95% CI, 0.28-0.94) when all eyes were included. CONCLUSIONS:Remote training of patients at home is feasible, and subsequent remote clustered VF testing using VVP-10 by patients on their own, without any further interactions with caregivers or study staff, was possible. At-home VVP-10 results demonstrated low test-retest variability. Future studies must be conducted to determine if VVP-10, taken at home as convenient for the patient, may be a viable supplement to provide equivalent or complementary results to that of standard in-clinic assessment of visual function in glaucoma. FINANCIAL DISCLOSURE(S)/BACKGROUND:Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

OBJECTIVE:To examine the longitudinal postoperative outcomes of open versus closed conjunctiva implantation of the XEN45 gel stent. DESIGN/METHODS:Retrospective multicenter study. SUBJECTS/METHODS:One hundred ninety-three patients with glaucoma underwent XEN45 implantation via an open or closed conjunctiva approach. METHODS:Data on patient demographics; diagnoses; preoperative and postoperative clinical data; outcome measures, including intraocular pressure (IOP); use of glaucoma medications; visual acuity; and complications were collected. Statistical analyses were performed with P < 0.05 as significant. MAIN OUTCOME MEASURES/METHODS:Failure was defined as < 20% reduction in IOP from the medicated baseline or a IOP of > 21 mmHg at 2 consecutive visits at postoperative month 1 and beyond, the need for subsequent operative intervention or additional glaucoma surgery, or a catastrophic event, such as loss of light perception. Eyes that had not failed by these criteria and were not on glaucoma medications were considered complete successes. Overall success was defined as those who achieved success either with or without topical medications. RESULTS:Patients were followed for an average of 17 months. Complete success was achieved in 42.5% and 24.7% of the open and closed groups, respectively (P = 0.01). Overall success was achieved in 64.2% and 37.0% of the open and closed groups, respectively (P < 0.001) at the last follow-up. Bleb needling was performed in 12.4% of eyes in the open group compared with 40% of eyes in the closed group. An IOP spike of ≥ 10 mmHg was twice as likely to occur in the closed group compared with the open group during the postoperative period (40% vs. 18%; P = 0.001). CONCLUSIONS:Implantation of XEN45 with opening of the conjunctiva resulted in a lower IOP with greater success and lower needling rate compared with those achieved with the closed conjunctiva technique. Similar rates of postoperative complications and vision loss were noted in each group. Although both procedures provide substantial IOP reduction, the open technique appears to result in higher success rates and fewer postoperative interventions. FINANCIAL DISCLOSURE(S)/BACKGROUND:Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

PURPOSE/UNASSIGNED:Race disparities in the healthcare system and the resulting inequality in clinical data among different races hinder the ability to generate equitable prediction results. This study aims to reduce healthcare disparities arising from data imbalance by leveraging advanced transfer learning (TL) methods. METHOD/UNASSIGNED:We examined the ophthalmic healthcare disparities at a population level using electronic medical records data from a study cohort (N = 785) receiving care at an academic institute. Regression-based TL models were usesd, transferring valuable information from the dominant racial group (White) to improve visual field mean deviation (MD) rate of change prediction particularly for data-disadvantaged African American (AA) and Asian racial groups. Prediction results of TL models were compared with two conventional approaches. RESULTS/UNASSIGNED:Disparities in socioeconomic status and baseline disease severity were observed among the AA and Asian racial groups. The TL approach achieved marked to comparable improvement in prediction accuracy compared to the two conventional approaches as evident by smaller mean absolute errors or mean square errors. TL identified distinct key features of visual field MD rate of change for each racial group. CONCLUSIONS/UNASSIGNED:The study introduces a novel application of TL that improved reliability of the analysis in comparison with conventional methods, especially in small sample size groups. This can improve assessment of healthcare disparity and subsequent remedy approach. TRANSLATIONAL RELEVANCE/UNASSIGNED:TL offers an equitable and efficient approach to mitigate healthcare disparities analysis by enhancing prediction performance for data-disadvantaged group.

In this review we highlight emerging immune regulatory functions of lumican, keratocan, fibromodulin, biglycan and decorin, which are members of the small leucine-rich proteoglycans (SLRP) of the extracellular matrix (ECM). These SLRPs have been studied extensively as collagen-fibril regulatory structural components of the skin, cornea, bone and cartilage in homeostasis. However, SLRPs released from a remodeling ECM, or synthesized by activated fibroblasts and immune cells contribute to an ECM-free pool in tissues and circulation, that may have a significant, but poorly understood foot print in inflammation and disease. Their molecular interactions and the signaling networks they influence also require investigations. Here we present studies on the leucine-rich repeat (LRR) motifs of SLRP core proteins, their evolutionary and functional relationships with other LRR pathogen recognition receptors, such as the toll-like receptors (TLRs) to bring some molecular clarity in the immune regulatory functions of SLRPs. We discuss molecular interactions of fragments and intact SLRPs, and how some of these interactions are likely modulated by glycosaminoglycan side chains. We integrate findings on molecular interactions of these SLRPs together with what is known about their presence in circulation and lymph nodes (LN), which are important sites of immune cell regulation. Recent bulk and single cell RNA sequencing studies have identified subsets of stromal reticular cells that express these SLRPs within LNs. An understanding of the cellular source, molecular interactions and signaling consequences will lead to a fundamental understanding of how SLRPs modulate immune responses, and to therapeutic tools based on these SLRPs in the future.

Lumican is an extracellular matrix proteoglycan known to regulate toll-like receptor (TLR) signaling in innate immune cells. In experimental settings, lumican suppresses TLR9 signaling by binding to and sequestering its synthetic ligand, CpG-DNA, in non-signal permissive endosomes. However, the molecular details of lumican interactions with CpG-DNA are obscure. Here, the 3-D structure of the 22 base-long CpG-DNA (CpG ODN_2395) bound to lumican or TLR9 were modeled using homology modeling and docking methods. Some of the TLR9-CpG ODN_2395 features predicted by our model are consistent with the previously reported TLR9-CpG DNA crystal structure, substantiating our current analysis. Our modeling indicated a smaller buried surface area for lumican-CpG ODN_2395 (1803 Ų) compared to that of TLR9-CpG ODN_2395 (2094 Ų), implying a potentially lower binding strength for lumican and CpG-DNA than TLR9 and CpG-DNA. The docking analysis identified 32 amino acids in lumican LRR1-11 interacting with CpG ODN_2395, primarily through hydrogen bonding, salt-bridges, and hydrophobic interactions. Our study provides molecular insights into lumican and CpG-DNA interactions that may lead to molecular targets for modulating TLR9-mediated inflammation and autoimmunity.

Glaucoma causes progressive visual field deterioration and is the leading cause of blindness worldwide. Glaucomatous damage is irreversible and greatly impacts quality of life. Therefore, it is critically important to detect glaucoma early and closely monitor progression to preserve functional vision. Glaucoma is routinely monitored in the clinical setting using optical coherence tomography (OCT) for derived measures such as the thickness of important visual structures. There is not a consensus of what measures represent the most relevant biomarkers of glaucoma progression. Further, despite the increasing availability of longitudinal OCT data, a quantitative model of 3D structural change over time associated with glaucoma does not exist. In this paper we present an algorithm that will perform hierarchical geodesic modeling at the imaging level, considering 3D OCT images as observations of structural change over time. Hierarchical modeling includes subject-wise trajectories as geodesics in the space of diffeomorphisms and population level (glaucoma vs control) trajectories are also geodesics which explain subject-wise trajectories as deviations from the mean. Our preliminary experiments demonstrate a greater magnitude of structural change associated with glaucoma compared to normal aging. Our algorithm has the potential application in patient-specific monitoring and analysis of glaucoma progression as well as a statistical model of population trends and population variability.

PURPOSE:Cost-effectiveness analyses (CEAs) quantify and compare both costs and measures of efficacy for different interventions. As the costs of glaucoma management to patients, payers, and physicians are increasing, we seek to investigate the role of CEAs in the field of glaucoma and how such studies impact clinical management. METHODS:We adhered to the "Preferred Reporting Items for Systematic Reviews and Meta-analyses" guidelines for our systematic review structure. Eligible studies included any full-text articles that investigated cost-effectiveness or cost-utility as it relates to the field of open angle glaucoma management in the United States. Risk of bias assessment was conducted using the validated Joanna Briggs Institute Critical Appraisal Checklist for Economic Evaluations. RESULTS:Eighteen studies were included in the review. Dates of publication ranged from 1983 to 2021. Most of the studies were published in the 2000s and performed CEAs in the domains of treatment/therapy, screening, and adherence for patients with primary angle open glaucoma. Of the 18 articles included, 14 focused on treatment, 2 on screening, and 2 on adherence. Most of these studies focused on the cost-effectiveness of different topical medical therapies, whereas only a few studies explored laser procedures, surgical interventions, or minimally invasive procedures. Economic models using decision analysis incorporating state-transition Markov cycles or Montecarlo simulations were widely used, however, the methodology among studies was variable, with a wide spectrum of inputs, measures of outcomes, and time horizons used. CONCLUSION:Overall, we found that cost-effectiveness research in glaucoma in the United States remains relatively unstructured, resulting in unclear and conflicting implications for clinical management.

PURPOSE:The presence of imbalanced datasets in medical applications can negatively affect deep learning methods. This study aims to investigate how the performance of convolutional neural networks (CNNs) for glaucoma diagnosis can be improved by addressing imbalanced learning issues through utilizing glaucoma suspect samples, which are often excluded from studies because they are a mixture of healthy and preperimetric glaucomatous eyes, in a semi-supervised learning approach. METHODS:A baseline 3D CNN was developed and trained on a real-world glaucoma dataset, which is naturally imbalanced (like many other real-world medical datasets). Then, three methods, including reweighting samples, data resampling to form balanced batches, and semi-supervised learning on glaucoma suspect data were applied to practically assess their impacts on the performances of the trained methods. RESULTS:The proposed method achieved a mean accuracy of 95.24%, an F1 score of 97.42%, and an area under the curve of receiver operating characteristic (AUC ROC) of 95.64%, whereas the corresponding results for the traditional supervised training using weighted cross-entropy loss were 92.88%, 96.12%, and 92.72%, respectively. The obtained results show statistically significant improvements in all metrics. CONCLUSIONS:Exploiting glaucoma suspect eyes in a semi-supervised learning method coupled with resampling can improve glaucoma diagnosis performance by mitigating imbalanced learning issues. TRANSLATIONAL RELEVANCE:Clinical imbalanced datasets may negatively affect medical applications of deep learning. Utilizing data with uncertain diagnosis, such as glaucoma suspects, through a combination of semi-supervised learning and class-imbalanced learning strategies can partially address the problems of having limited data and learning on imbalanced datasets.

BACKGROUND:Environmental factors have been implicated in various eye pathologies. The purpose of this review is to synthesise the published research on environmental effects on eye disease. METHODS:Four databases were searched for terms relating to environmental exposures and ophthalmic disease. Titles and abstracts were screened followed by full-text review. Data was extracted from 118 included studies. Quality assessment was conducted for each study. RESULTS:Air pollutants, including nitrogen dioxide, nitrites, sulphur dioxide, particulate matter, carbon monoxide, ozone and hydrocarbons are associated with ocular conditions ranging from corneal damage to various retinopathies, including central retinal artery occlusion. Certain chemicals and metals, such as cadmium, are associated with increased risk of age-related macular degeneration. Climate factors, such as sun exposure, have been associated with the development of cataracts. Living in rural areas was associated with various age-related eye diseases whereas people living in urban settings had higher risk for dry eye disease and uveitis. CONCLUSION/CONCLUSIONS:Environmental exposures in every domain are associated with various ophthalmic conditions. These findings underscore the importance of continued research on the interplay between the environment and eye health.

TOPIC/OBJECTIVE:Understanding approaches to sustainability in cataract surgery and their risks and benefits CLINICAL RELEVANCE: In the United States, healthcare is responsible for approximately 8.5% of greenhouse gas (GHG), and cataract surgery is one of the most commonly performed surgical procedures. Ophthalmologists can contribute to reducing GHG emissions, which lead to a steadily increasing list of health concerns ranging from trauma to food instability. METHODS:We conducted a literature review to identify the benefits and risks of sustainability interventions. We then organized these interventions into a decision tree for use by individual surgeons. RESULTS:Identified sustainability interventions fall into the domains of advocacy and education, pharmaceuticals, process, and supplies and waste. Existing literature shows certain interventions may be safe, cost-effective, and environmentally friendly. These include dispensing medications home to patients after surgery, multi-dosing appropriate medications, training staff to properly sort medical waste, reducing the number of supplies used during surgery, and implementing immediate sequential bilateral cataract surgery where clinically appropriate. The literature was lacking on the benefits or risks for some interventions, such as switching specific single use supplies to reusables or implementing a hub-and-spoke style theatre setup. Many of the advocacy and education interventions have inadequate literature specific to ophthalmology but are likely to have minimal risks. CONCLUSIONS:Ophthalmologists can engage in a variety of safe and effective approaches to reduce or eliminate dangerous GHG emissions associated with cataract surgery.