Expert Rev Ophthalmol

Introduction:Non-adherence to glaucoma medication and poor follow-up is a global health concern.Areas covered:Glaucoma remains one of the largest causes of irreversible blindness worldwide. Traditional treatment guidelines suggest topical eye drop medication as first line therapy followed by addition of supplementary medications before proceeding to more invasive glaucoma surgeries. Unfortunately, poor glaucoma self-management remains high, leading to disease progression and blindness. Recent advancements in the field of pharmacotherapies, surgeries, and behavioral approaches have taken aim at increasing support for glaucoma self-management. We review the current and emerging approaches towards glaucoma management, with the exception of bleb-based surgical approaches, to investigate if they have had an impact on adherence. Literature searches were conducted via MEDLINE (PubMed), Embase (Elsevier), Cochrane Library (Wiley), and Preprints from January 1st, 2018, to January 26th, 2023.Expert opinion:The ability to offer patients a multitude of choices enables patients to tailor their glaucoma treatment to their values and lifestyle. Offering personalized patient education and coaching to support chronic glaucoma self-management would better enable patient engagement in whichever treatment path is chosen. Currently, literature regarding the impact of these new advancements on treatment engagement is lacking; this field is ripe for additional intervention and assessment.R01 EB032328/EB/NIBIB NIH HHSUnited States/R01 EY031337/EY/NEI NIH HHSUnited States/U01 DP006442/DP/NCCDPHP CDC HHSUnited States

A Comparison Of Clinical Trial And Model-Based Cost Estimates In Glaucoma – The Case Of Repeat Laser Trabeculoplasty In Ontario

Background and objective: For cost-effectiveness analyses (CEA) of glaucoma interventions to be of use they require valid and accurate cost and effectiveness data. Costs remain understudied relative to effectiveness. The impact of cost estimation methods on resultant estimates is unknown in glaucoma. Direct measurement of costs is labour-intensive and expensive. Decision-analytic modelling of costs using literature sources, expert opinion, institutional experience and assumptions provides a quicker, less laborious alternative to empirical costing. A lack of long-term effectiveness data in chronic diseases like glaucoma means that modelling is widespread and inevitable, both for CEAs and budget impact projections. The same problem precludes validation of models and there are concerns about their validity and possible arbitrariness given the discretionary nature of their construction. In this thesis we investigate whether costs from a decision-analytic model of repeat laser trabeculoplasty among glaucoma patients provide a valid alternative to direct measurement of costs alongside an effectiveness trial. Secondary aims were to compare the ministry and societal perspective and to identify main cost drivers for repeat laser trabeculoplasty. Methods: Trial-based costing was conducted as part of an effectiveness trial comparing argon- and selective-laser trabeculoplasty (ALT and SLT) after previous SLT among glaucoma patients at an ophthalmologic clinic in Ontario. For model-based costing a decision tree was formulated and populated with parameter estimates based on previous literature supplemented with assumptions. Mean trial and model cost were compared for ALT and SLT. Results: Model and trial cost estimates differed minimally for the ministry perspective (4% and 8% for SLT and ALT respectively) – this in spite of large differences in modelled and observed parameter values. Labour accounted for almost 90% of total cost. Model and trial costs were also similar for the societal perspective (8% and 1% for ALT and SLT), although there was more sensitivity to assumptions about patient time loss. Indirect and patient costs were at least as large as direct medical costs. Our results indicate that modelled costs are an acceptable substitute for directly measured costs for some clinical scenarios – glaucoma interventions in Ontario possibly being such a case

A Systematic Approach to Big Data Analysis in Cataract Patients In Telangana State, India

Big data is the new gold, especially in healthcare. Advances in collecting and processing Electronic Medical Records (EMRs), coupled with increasing computer capabilities have resulted in an increased interest in the use of big data in healthcare. Big data require collection and analysis of data at an unprecedented scale and represents a paradigm shift in healthcare, offering on one hand the capacity to generate new knowledge more quickly than traditional scientific approaches, and, on the other hand, a holistic understanding of specific illnesses when socio-demographics are incorporated in the analysis. Big data promises more personalized and precision medicine for patients with improved accuracy and earlier diagnosis, and therapy geared to an individual’s unique combination of genes, environmental risk, and precise disease phenotype. Ophthalmology has been an area of focus where results have shown to be promising. The objective of this study was to determine whether the EMR record in LV Prasad Eye Institute (LVPEI), based in Hyderabad, India, can contribute to the management of patient care, through studying how climatic and socio-demographic factors relate to cataracts, clouding of the lens – turning the lens from clear to yellow, brown or even milky white, which cause visual impairment and blindness if left untreated. The study was designed by merging a dataset obtained from the Telangana State Development Society to an existing EMR of approximately 1 million patients, who presented themselves with different eye symptoms and were diagnosed with several ocular diseases from the years (2011-2019), a timeframe of 8 years. The dataset obtained included climatic variables to be tested alongside the development of cataracts in patients. Microsoft Power BI was used to analyze the data through prescriptive and descriptive data analysis techniques to read patterns that can dig deeper into high-risk climatic and socio-demographic factors that correlate to the development of cataract. Our findings revealed that there is a high presence of cataract in the state of Telangana, mostly in rural areas and throughout the different weather seasons in India. Women tend to be the most affected as per the number of visits to the clinic, while home makers make the most visit to the hospital, in addition to employees, students, and laborers. While cataract is most dominant in the older age population, diseases such as astigmatism and conjunctivitis, are more present in the younger age population. The study appeared useful for taking preventive measures in the future to manage the treatment of patients who present themselves with cataracts in Telangana. In addition, this research created a pathway for new methods in the study of how EMRs contribute to new knowledge in ophthalmology. Results indicated that cultural upbringing, climatic factors, and proximity to the state-run thermal plant play a significant role in the presence of cataracts. Through testing the methodology used, observations indicate that the AI technique used is only effective when variables are minimized. Reflections suggest that studying patients through a more holistic and systematic approach can reveal new insights that can help bridge the gap between existing knowledge and practice for an aim to provide enhanced ophthalmic care in India

Modulation of Inflammation Driven Wound Healing after Glaucoma Surgery

Dysregulated wound healing contributes to most currently unanswered ophthalmological morbidity. Opacification and structure altering contractures compromise the delicate ocular anatomy upon which ocular function and healthy vision are reliant. Glaucoma filtration surgery, corneal stromal injury, proliferative vitreoretinopathy and age-related macular degeneration are major contributors to ocular morbidity – all with myofibroblast transdifferentiation and pathognomonic scarring activity at their core. This thesis aims to revaluate the means by which dysregulated ocular wound healing is combated with evidence describing a novel strategy to mitigate its effects. A translational approach was used. An initial retrospective analysis of over ten thousand glaucoma surgeries found that perioperative NSAID exposure was significantly associated with surgical success. The current standard of care, corticosteroids, showed no such association. This was surprising and provided impetus to evaluate these clinical findings within the basic science lab. The subsequent project examined the relative effects of NSAIDs to that of corticosteroids on the in vitro wound healing activity of ocular fibroblasts. Relative to steroids, NSAID exposure resulted in more ordered extracellular matrix remodelling, less cell-mediated collagen contraction and greater impairment of myofibroblast associated protein expression. We hypothesized that these differences were due to NSAIDs more specific targeting of COX enzyme activity. By sparing lipoxygenase activity, competitive NSAIDs leave intact the biosynthetic machinery responsible for signaling the endogenous resolution of inflammation. This system involves the collective effects of the pro-resolving superfamily of lipid mediators and promotes the active resolution of inflammatory processes. To assess the anti-fibrotic potential of inducing resolution within inflammation-induced ocular fibroblasts, two COX2 Ser516 acetylating molecules were utilized to modify the COX2 enzyme such that it: 1) ceases prostaglandin production, and 2) gains the capacity to produce pro-resolving lipid mediators. When applied to inflammation-induced ocular fibroblasts, a reduction in in vitro wound healing phenomena was observed with a corresponding shift in pro-/anti-fibrogenic transcription factor expression and downregulation of myofibroblast associated proteins. Together these findings suggest that the resolution of inflammation and the resolution of fibroproliferation may be controlled by a common signaling system, and that interventions promoting the production of resolving lipid mediators could have significant anti-cicatrizing properties

Personalized approaches for the management of glaucoma

Introduction: Personalized medicine is the future goal across all specialties. Accurate prediction of optimal treatment beneficial and adverse effects could transform patient management. This is of particular importance in chronic conditions, where a ‘trial and error’ approach over months and years can contribute to significant morbidity. Glaucoma is a chronic irreversible progressive optic neuropathy, a leading cause of blindness worldwide. An ideal personalized approach in glaucoma clinic would be to answer the inevitable question in a patient’s first visit: ‘Which treatment option will work best for me so that I won’t go blind?’ / Areas covered: This review will give an overview of the knowledge we have acquired to achieve this goal, particularly discussing using patient’s individual risk factors, their genetic profile, and different treatment modalities, including therapy compliance, to personalize care. / Expert opinion: Pharmacogenomics and genetic profiling are the most tangible ways in which glaucoma management can be personalized. Future challenges will include developing realistic animal models to reflect the underlying genetic patterns in glaucoma to investigate their interaction with different treatments

Quality Assurance and Quality Control in the Global Trachoma Mapping Project.

In collaboration with the health ministries that we serve and other partners, we set out to complete the multiple-country Global Trachoma Mapping Project. To maximize the accuracy and reliability of its outputs, we needed in-built, practical mechanisms for quality assurance and quality control. This article describes how those mechanisms were created and deployed. Using expert opinion, computer simulation, working groups, field trials, progressively accumulated in-project experience, and external evaluations, we developed 1) criteria for where and where not to undertake population-based prevalence surveys for trachoma; 2) three iterations of a standardized training and certification system for field teams; 3) a customized Android phone-based data collection app; 4) comprehensive support systems; and 5) a secure end-to-end pipeline for data upload, storage, cleaning by objective data managers, analysis, health ministry review and approval, and online display. We are now supporting peer-reviewed publication. Our experience shows that it is possible to quality control and quality assure prevalence surveys in such a way as to maximize comparability of prevalence estimates between countries and permit high-speed, high-fidelity data processing and storage, while protecting the interests of health ministries

Addressing Semantic Interoperability and Text Annotations. Concerns in Electronic Health Records using Word Embedding, Ontology and Analogy

Electronic Health Record (EHR) creates a huge number of databases which are being updated dynamically. Major goal of interoperability in healthcare is to facilitate the seamless exchange of healthcare related data and an environment to supports interoperability and secure transfer of data. The health care organisations face difficulties in exchanging patient’s health care information and laboratory reports etc. due to a lack of semantic interoperability. Hence, there is a need of semantic web technologies for addressing healthcare interoperability problems by enabling various healthcare standards from various healthcare entities (doctors, clinics, hospitals etc.) to exchange data and its semantics which can be understood by both machines and humans. Thus, a framework with a similarity analyser has been proposed in the thesis that dealt with semantic interoperability. While dealing with semantic interoperability, another consideration was the use of word embedding and ontology for knowledge discovery. In medical domain, the main challenge for medical information extraction system is to find the required information by considering explicit and implicit clinical context with high degree of precision and accuracy. For semantic similarity of medical text at different levels (conceptual, sentence and document level), different methods and techniques have been widely presented, but I made sure that the semantic content of a text that is presented includes the correct meaning of words and sentences. A comparative analysis of approaches included ontology followed by word embedding or vice-versa have been applied to explore the methodology to define which approach gives better results for gaining higher semantic similarity. Selecting the Kidney Cancer dataset as a use case, I concluded that both approaches work better in different circumstances. However, the approach in which ontology is followed by word embedding to enrich data first has shown better results. Apart from enriching the EHR, extracting relevant information is also challenging. To solve this challenge, the concept of analogy has been applied to explain similarities between two different contents as analogies play a significant role in understanding new concepts. The concept of analogy helps healthcare professionals to communicate with patients effectively and help them understand their disease and treatment. So, I utilised analogies in this thesis to support the extraction of relevant information from the medical text. Since accessing EHR has been challenging, tweets text is used as an alternative for EHR as social media has appeared as a relevant data source in recent years. An algorithm has been proposed to analyse medical tweets based on analogous words. The results have been used to validate the proposed methods. Two experts from medical domain have given their views on the proposed methods in comparison with the similar method named as SemDeep. The quantitative and qualitative results have shown that the proposed analogy-based method bring diversity and are helpful in analysing the specific disease or in text classification