Abstract: Diabetic retinopathy (DR) remains a leading cause of irreversible vision loss in adult populations around the globe. Despite growing evidence of the effectiveness of routine assessments and early intervention, DR screening strategies are not widely implemented largely due to an inadequate availability of resources to cope with the growing burden of diabetes. Advances in technology in the field of DR screening are clearly warranted and the recent emergence of deep learning-based artificial intelligence (AI) grading of retinal pathology offers significant potential benefits including an increased efficiency, accessibility and affordability of screening programmes.

Abstract: The disease burden of diabetic retinopathy (DR) is tremendous around the world. While DR is correlated with hemoglobin A1c (HbA1c) and duration of diabetes, genetic differences likely account for variation in susceptibility to DR. DR is a polygenic disorder with demonstrated heritability. However, linkage and admixture analyses, candidate gene association studies, and genome-wide association studies (GWAS) have not identified many loci for DR that can be consistently replicated. Larger, collaborative, multi-ethnic GWAS are needed to identify common variants with small effects. Rigorous defining of controls groups as patients with a long duration of diabetes without DR, and case groups as patients with severe DR will also aid in finding genes associated with DR. Replication in independent cohorts will be key to establishing associated loci for DR. Investigations of mitochondrial DNA and epigenetics in DR are ongoing. Whole exome sequencing presents new opportunities to identify rare variants that might be implicated in DR development. Continued research in the genetic epidemiology of DR is needed, with the potential to elucidate pathogenesis and treatment of an important disease.

Abstract: Despite appropriate management of the systemic disease, patients with diabetes may develop severe forms of diabetic retinopathy that require surgery. Non-clearing vitreous haemorrhage (VH), traction retinal detachment involving the macula, combined traction and rhegmatogenous retinal detachment, progressive fibrovascular proliferation (PFP) and rubeosis with acute VH represent the main indications for surgery. Vitrectomy techniques and surgical tools have developed dramatically in the last decade in order to help the surgeon succeed in these challenging cases.

Abstract: Diabetic retinopathy (DR) is the most common microvascular complication in patients with diabetes mellitus (DM), and remains the single greatest cause of blindness in working age adults around the world. In this article, we review the evolution of pharmacotherapies for both diabetic macular edema (DME) and DR such as anti-vascular endothelial growth factor inhibitors and various steroid formulations, as well as other emerging pharmacotherapies currently in late stage clinical testing for this disease.

Abstract: Several factors drive the need for increased efficiency in telemedicine screening programs directed toward diabetic retinopathy: continually increasing prevalence of diabetes worldwide, growing awareness among physicians and patients of the importance of early detection of retinal damage, and emerging technology in artificial intelligence that enables rapid identification of vision-threatening fundus features. In this context, optimizing workflows in teleretinopathy programs becomes a priority. Recent work has revealed opportunities for improvement in areas of logistics, in particular in finding the best way to get diabetic patients in front of screening cameras as conveniently as possible, as this improves compliance and, ultimately, achieves the widest reach for detection programs. The present review discusses particular aspects of mobile screening programs in which specialized retinal cameras are deployed in a van or similar type of vehicle so that they can reach patients anywhere in order to reduce barriers to access. The rationale for implementing such programs and practical considerations are presented, along with a view toward future expansion of screening and integration with artificial intelligence platforms. Lacking standardization of format and quality control among smartphone-linked approaches at present, translation of eye clinic-based photographic techniques to community-based screening offers a means of expanding the scope of impactful screening programs without the need for adoption of significantly new technology.