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The number of people living with diabetes is expected to rise to 578 million by 2030 and to 700 million by 2045, exacting a severe socioeconomic burden on healthcare systems around the globe. This is also reflected in the increasing numbers of people with ocular complications of diabetes (namely, diabetic macular oedema (DMO) and diabetic retinopathy (DR)). In one study examining the global prevalence of DR, 35% of people with diabetes had some form of DR, 7% had PDR, 7% had DMO, and 10% were affected by these vision-threatening stages. In many regions of the world (Australia included), DR is one of the top three leading causes of vision loss amongst working age adults (20–74 years). In the management of DMO, the landmark ETDRS study demonstrated that moderate visual loss, defined as doubling of the visual angle, can be reduced by 50% or more by focal/grid laser photocoagulation. However, over the last 20 years, antivascular endothelial growth factor (VEGF) and corticosteroid therapies have emerged as alternative options for the management of DMO and provided patients with choices that have higher chances of improving vision than laser alone. In Australia, since the 2008 NHMRC guidelines, there have been significant developments in both the treatment options and treatment schedules for DMO. This working group was therefore assembled to review and address the current management options available in Australia.

Diagnosis and management of proliferative diabetic retinopathy are reliant upon retinal imaging. A systematic literature review of non-invasive imaging to guide diagnosis and treatment of proliferative diabetic retinopathy was performed. There is a trend of moving away from invasive (e.g., fundus fluorescein angiography) to non-invasive (e.g., wide-field optical coherence tomography (OCT), OCT angiography and colour fundus photography) imaging modalities to allow for more objective assessments that can be readily repeated in a time-efficient manner without compromising patient safety. Such quantitative assessments generating large amounts of data could benefit from artificial intelligence approaches to aid clinical decision making. These non-invasive imaging modalities continue to improve both in terms of the quality of image acquisition and progress in image interpretation. It is important that newer non-invasive imaging modalities are appropriately validated in large-scale prospective observational studies or randomised clinical trials.