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1.
Optical Coherence Tomography (Angiography) Biomarkers in the Assessment and Monitoring of Diabetic Macular Edema.
Suciu, CI, Suciu, VI, Nicoara, SD
Journal of diabetes research. 2020;:6655021
Abstract
Retinopathy is one of the most severe diabetes-related complications, and macular edema is the major cause of central vision loss in patients with diabetes mellitus. Significant progress has been made in recent years in optical coherence tomography and angiography technology. At the same time, various parameters have been attributed the role of biomarkers creating the frame for new monitoring and treatment strategies and offering new insights into the pathogenesis of diabetic retinopathy and diabetic macular edema. In this review, we gathered the results of studies that investigated various specific OCT (angiography) parameters in diabetic macular edema, such as central subfoveal thickness (CST), cube average thickness (CAT), cube volume (CV), choroidal thickness (CT), retinal nerve fiber layer (RNFL), retinal thickness at the fovea (RTF), subfoveal choroidal thickness (SFCT), central macular thickness (CMT), choroidal vascularity index (CVI), total macular volume (TMV), central choroid thickness (CCT), photoreceptor outer segment (PROS), perfused capillary density (PCD), foveal avascular zone (FAZ), subfoveal neuroretinal detachment (SND), hyperreflective foci (HF), disorganization of the inner retinal layers (DRIL), ellipsoid zone (EZ), inner segment/outer segment (IS/OS) junctions, vascular density (VD), deep capillary plexus (DCP), and superficial capillary plexus (SCP), in order to provide a synthesis of biomarkers that are currently used for the early diagnosis, assessment, monitoring, and outlining of prognosis.
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2.
NOD-like Receptors in the Eye: Uncovering Its Role in Diabetic Retinopathy.
Lim, RR, Wieser, ME, Ganga, RR, Barathi, VA, Lakshminarayanan, R, Mohan, RR, Hainsworth, DP, Chaurasia, SS
International journal of molecular sciences. 2020;(3)
Abstract
Diabetic retinopathy (DR) is an ocular complication of diabetes mellitus (DM). International Diabetic Federations (IDF) estimates up to 629 million people with DM by the year 2045 worldwide. Nearly 50% of DM patients will show evidence of diabetic-related eye problems. Therapeutic interventions for DR are limited and mostly involve surgical intervention at the late-stages of the disease. The lack of early-stage diagnostic tools and therapies, especially in DR, demands a better understanding of the biological processes involved in the etiology of disease progression. The recent surge in literature associated with NOD-like receptors (NLRs) has gained massive attraction due to their involvement in mediating the innate immune response and perpetuating inflammatory pathways, a central phenomenon found in the pathogenesis of ocular diseases including DR. The NLR family of receptors are expressed in different eye tissues during pathological conditions suggesting their potential roles in dry eye, ocular infection, retinal ischemia, cataract, glaucoma, age-related macular degeneration (AMD), diabetic macular edema (DME) and DR. Our group is interested in studying the critical early components involved in the immune cell infiltration and inflammatory pathways involved in the progression of DR. Recently, we reported that NLRP3 inflammasome might play a pivotal role in the pathogenesis of DR. This comprehensive review summarizes the findings of NLRs expression in the ocular tissues with special emphasis on its presence in the retinal microglia and DR pathogenesis.
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3.
Artificial Intelligence in the assessment of diabetic retinopathy from fundus photographs.
Gilbert, MJ, Sun, JK
Seminars in ophthalmology. 2020;(7-8):325-332
Abstract
Background: Over the next 25 years, the global prevalence of diabetes is expected to grow to affect 700 million individuals. Consequently, an unprecedented number of patients will be at risk for vision loss from diabetic eye disease. This demand will almost certainly exceed the supply of eye care professionals to individually evaluate each patient on an annual basis, signaling the need for 21st century tools to assist our profession in meeting this challenge. Methods: Review of available literature on artificial intelligence (AI) as applied to diabetic retinopathy (DR) detection and predictionResults: The field of AI has seen exponential growth in evaluating fundus photographs for DR. AI systems employ machine learning and artificial neural networks to teach themselves how to grade DR from libraries of tens of thousands of images and may be able to predict future DR progression based on baseline fundus photographs. Conclusions: AI algorithms are highly promising for the purposes of DR detection and will likely be able to reliably predict DR worsening in the future. A deeper understanding of these systems and how they interpret images is critical as they transition from the bench into the clinic.
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4.
Artificial Intelligence: The Future for Diabetes Care.
Ellahham, S
The American journal of medicine. 2020;(8):895-900
Abstract
Artificial intelligence (AI) is a fast-growing field and its applications to diabetes, a global pandemic, can reform the approach to diagnosis and management of this chronic condition. Principles of machine learning have been used to build algorithms to support predictive models for the risk of developing diabetes or its consequent complications. Digital therapeutics have proven to be an established intervention for lifestyle therapy in the management of diabetes. Patients are increasingly being empowered for self-management of diabetes, and both patients and health care professionals are benefitting from clinical decision support. AI allows a continuous and burden-free remote monitoring of the patient's symptoms and biomarkers. Further, social media and online communities enhance patient engagement in diabetes care. Technical advances have helped to optimize resource use in diabetes. Together, these intelligent technical reforms have produced better glycemic control with reductions in fasting and postprandial glucose levels, glucose excursions, and glycosylated hemoglobin. AI will introduce a paradigm shift in diabetes care from conventional management strategies to building targeted data-driven precision care.
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5.
Targeting epigenetic modifications as a potential therapeutic option for diabetic retinopathy.
Kumari, N, Karmakar, A, Ganesan, SK
Journal of cellular physiology. 2020;(3):1933-1947
Abstract
Diabetic retinopathy (DR) is the leading cause of visual impairment in adults of working age (20-65 years) in developed countries. The metabolic memory phenomena (persistent effect of a glycemic insult even after retrieved) associated with it has increased the risk of developing the complication even after the termination of the glycemic insult. Hence, the need for finding early diagnosis and treatment options has been of great concern. Epigenetic modifications which generally occur during the beginning stages of the disease are responsible for the metabolic memory effect. Therefore, the therapy based on the reversal of the associated epigenetic mechanism can bring new insight in the area of early diagnosis and treatment mechanism. This review discusses the diabetic retinopathy, its pathogenesis, current treatment options, need of finding novel treatment options, and different epigenetic alterations associated with DR. However, the main focus is emphasized on various epigenetic modifications particularly DNA methylation which are responsible for the initiation and progression of diabetic retinopathy and the use of different epigenetic inhibitors as a novel therapeutic option for DR.
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6.
Artificial intelligence for diabetic retinopathy screening, prediction and management.
Gunasekeran, DV, Ting, DSW, Tan, GSW, Wong, TY
Current opinion in ophthalmology. 2020;(5):357-365
Abstract
PURPOSE OF REVIEW Diabetic retinopathy is the most common specific complication of diabetes mellitus. Traditional care for patients with diabetes and diabetic retinopathy is fragmented, uncoordinated and delivered in a piecemeal nature, often in the most expensive and high-resource tertiary settings. Transformative new models incorporating digital technology are needed to address these gaps in clinical care. RECENT FINDINGS Artificial intelligence and telehealth may improve access, financial sustainability and coverage of diabetic retinopathy screening programs. They enable risk stratifying patients based on individual risk of vision-threatening diabetic retinopathy including diabetic macular edema (DME), and predicting which patients with DME best respond to antivascular endothelial growth factor therapy. SUMMARY Progress in artificial intelligence and tele-ophthalmology for diabetic retinopathy screening, including artificial intelligence applications in 'real-world settings' and cost-effectiveness studies are summarized. Furthermore, the initial research on the use of artificial intelligence models for diabetic retinopathy risk stratification and management of DME are outlined along with potential future directions. Finally, the need for artificial intelligence adoption within ophthalmology in response to coronavirus disease 2019 is discussed. Digital health solutions such as artificial intelligence and telehealth can facilitate the integration of community, primary and specialist eye care services, optimize the flow of patients within healthcare networks, and improve the efficiency of diabetic retinopathy management.
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7.
Diabetic retinopathy, diabetic macular edema, and cardiovascular risk: the importance of a long-term perspective and a multidisciplinary approach to optimal intravitreal therapy.
Bandello, F, Toni, D, Porta, M, Varano, M
Acta diabetologica. 2020;(5):513-526
Abstract
Diabetic retinopathy (DR), diabetic macular edema (DME), and cardiovascular disease (CVD) resulting from vascular damage from persistently elevated blood glucose levels are among the serious secondary pathologies associated with long-standing diabetes mellitus. The established link between DR and CVD suggests the need for appropriate and early management of patients with diabetes to minimize CV risk. This is of particular importance in patients with recent, or a history of, major CV events. Early management of DR is a complex task that requires comprehensive evaluation and a multidisciplinary approach to manage complications, risk factors, and interactions between different aspects of the disease. Anti-vascular endothelial growth factor (VEGF) agents have become an important therapeutic modality in ophthalmology. However, their use is contraindicated in patients with DR and/or DME with a CV event in the previous 3 months. In patients with DME, corticosteroids target the multifaceted inflammatory pathways involved in the pathogenesis of DR, with a broader spectrum of action than anti-VEGF agents. In this context, recent guidelines suggest the use of corticosteroids, and in particular dexamethasone intravitreal implant, as a well-tolerated and efficacious first-line treatment in patients with high CV risk, such as a history of or recent major CV events. This review focuses on the subset of diabetic patients with a prior CV event, DR, and DME and discusses the need for a holistic approach in evaluating the optimal therapeutic choice for the care of the individual patient, supported by real-world clinical experience on long-term dexamethasone intravitreal implant therapy.
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8.
Fundamental principles of an effective diabetic retinopathy screening program.
Lanzetta, P, Sarao, V, Scanlon, PH, Barratt, J, Porta, M, Bandello, F, Loewenstein, A, ,
Acta diabetologica. 2020;(7):785-798
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Abstract
BACKGROUND Diabetic retinopathy (DR) is the leading cause of blindness among working-age adults worldwide. Early detection and treatment are necessary to forestall vision loss from DR. METHODS A working group of ophthalmic and diabetes experts was established to develop a consensus on the key principles of an effective DR screening program. Recommendations are based on analysis of a structured literature review. RESULTS The recommendations for implementing an effective DR screening program are: (1) Examination methods must be suitable for the screening region, and DR classification/grading systems must be systematic and uniformly applied. Two-field retinal imaging is sufficient for DR screening and is preferable to seven-field imaging, and referable DR should be well defined and reliably identifiable by qualified screening staff; (2) in many countries/regions, screening can and should take place outside the ophthalmology clinic; (3) screening staff should be accredited and show evidence of ongoing training; (4) screening programs should adhere to relevant national quality assurance standards; (5) studies that use uniform definitions of risk to determine optimum risk-based screening intervals are required; (6) technology infrastructure should be in place to ensure that high-quality images can be stored securely to protect patient information; (7) although screening for diabetic macular edema (DME) in conjunction with DR evaluations may have merit, there is currently insufficient evidence to support implementation of programs solely for DME screening. CONCLUSION Use of these recommendations may yield more effective DR screening programs that reduce the risk of vision loss worldwide.
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Widefield Optical Coherence Tomography Angiography in Diabetic Retinopathy.
Amato, A, Nadin, F, Borghesan, F, Cicinelli, MV, Chatziralli, I, Sadiq, S, Mirza, R, Bandello, F
Journal of diabetes research. 2020;:8855709
Abstract
PURPOSE To summarize the role of widefield optical coherence tomography angiography (WF-OCTA) in diabetic retinopathy (DR), extending from the acquisition strategies to the main clinical findings. METHODS A PubMed-based search was carried out using the terms "Diabetic retinopathy", "optical coherence tomography angiography", "widefield imaging", and "ultra-widefield imaging". All studies published in English up to August 2020 were reviewed. RESULTS WF-OCTA can be obtained with different approaches, offering advantages over traditional imaging in the study of nonperfusion areas (NPAs) and neovascularization (NV). Quantitative estimates and topographic distribution of NPA and NV are useful for treatment monitoring and artificial intelligence-based approaches. Curvature, segmentation, and motion artifacts should be assessed when using WF-OCTA. CONCLUSIONS WF-OCTA harbors interesting potential in DR because of its noninvasiveness and capability of objective metrics of retinal vasculature. Further studies will facilitate the migration from traditional imaging to WF-OCTA in both the research and clinical practice fields.
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Updates on the Management of Ocular Vasculopathies with VEGF Inhibitor Conbercept.
Liu, H, Ma, Y, Xu, HC, Huang, LY, Zhai, LY, Zhang, XR
Current eye research. 2020;(12):1467-1476
Abstract
Purpose: To provide a detailed review on the therapeutic efficacy of conbercept for the management of ocular vasculopathies. Methods: A comprehensive literature search of various electronic databases was performed. Results: Ocular vasculopathy is one of the major causes of visual impairment and blindness which includes a range of disorders. Vascular endothelial growth factor (VEGF) regulates angiogenesis, enhances vascular permeability, and drives the formation of neovascularization. Anti-VEGF therapy has been shown to prevent vision loss or potentially improve vision in patients with exudative or neovascular retinal disease. The most recent anti-VEGF drug in China is conbercept. In the USA and Europe, bevacizumab is the most recently approved anti-VEGF agent. Conclusions: Conbercept serves as another anti-VEGF option for patients with neovascular AMD and other retinal vascular disorders. There have not been many clinical trials that study conbercept as compared with other currently available anti-VEGF drugs. There is a need for large-scale, well-designed, randomized clinical trials to ensure its long-term safety and efficacy and to determine if it has any advantages over other anti-VEGF agents.