Diabetic retinal disease is envisioned to become the plague of the coming decades with a steep increase of worldwide diabetes incidence followed by a substantial rise in retinal disease. Improvements in diagnostic and therapeutic care have to cope with this dilemma in a clinically and socioeconomically efficient manner. Laser treatment has found a less destructive competitor in pharmacological treatments. As a consequence of recent rigorous clinical trials, laser photocoagulation is no longer recommended for the treatment of diabetic macular edema (DME), and anti-vascular endothelial growth factor therapy has emerged as first-line therapy. Steroids have maintained a role in the management of chronically persistent DME. The paradigm shifts in therapy are accompanied by a substantial break-through in diagnostics. The following guidance for the management of DME has been composed from the best updated knowledge of leading experts in Europe and represents another volume in the series of EURETINA recommendations for the management of retinal disease.

Major advances in diagnostic technologies are offering unprecedented insight into the condition of the retina and beyond ocular disease. Digital images providing millions of morphological datasets can fast and non-invasively be analyzed in a comprehensive manner using artificial intelligence (AI). Methods based on machine learning (ML) and particularly deep learning (DL) are able to identify, localize and quantify pathological features in almost every macular and retinal disease. Convolutional neural networks thereby mimic the path of the human brain for object recognition through learning of pathological features from training sets, supervised ML, or even extrapolation from patterns recognized independently, unsupervised ML. The methods of AI-based retinal analyses are diverse and differ widely in their applicability, interpretability and reliability in different datasets and diseases. Fully automated AI-based systems have recently been approved for screening of diabetic retinopathy (DR). The overall potential of ML/DL includes screening, diagnostic grading as well as guidance of therapy with automated detection of disease activity, recurrences, quantification of therapeutic effects and identification of relevant targets for novel therapeutic approaches. Prediction and prognostic conclusions further expand the potential benefit of AI in retina which will enable personalized health care as well as large scale management and will empower the ophthalmologist to provide high quality diagnosis/therapy and successfully deal with the complexity of 21st century ophthalmology.

Deep learning in retinal image analysis achieves excellent accuracy for the differential detection of retinal fluid types across the most prevalent exudative macular diseases and OCT devices. Furthermore, quantification of fluid achieves a high level of concordance with manual expert assessment. Fully automated analysis of retinal OCT images from clinical routine provides a promising horizon in improving accuracy and reliability of retinal diagnosis for research and clinical practice in ophthalmology.

The high prevalence of cardiovascular disease particularly in the elderly population is associated with retinal vascular disease. Retinal vein occlusions represent severe disturbances of the hypoxia-sensitive neurosensory retina. Acute and excessive leakage leads to the diagnostic hallmarks of retinal hemorrhage and edema with substantial retinal thickening. Advanced diagnostic tools such as OCT angiography allow to evaluate retinal ischemia and identify the risk for late complications and will soon reach clinical routine besides fluorescein angiography. Accordingly, the duration of non-perfusion is a crucial prognostic factor requiring timely therapeutic intervention. With immediate inhibition of vascular leakage, anti-VEGF substances excel as treatment of choice. Multiple clinical trials with optimal potential for functional benefit or a lesser regenerative spectrum have evaluated aflibercept, ranibizumab, and bevacizumab. As retinal vein occlusion is a chronic disease, long-term monitoring should be individualized to combine maintenance with practicability. While steroids may be considered in patients with systemic cardiovascular risk, surgery remains advisable only for very few patients. Destructive laser treatment is an option if reliable monitoring is not feasible. Ophthalmologists are also advised to perform a basic systemic workup to recognize systemic concomitants. The current edition of the EURETINA guidelines highlights the state-of-the-art recommendations based on the literature and expert opinions in retinal vein occlusion.

Artificial intelligence with automated analysis of imaging biomarkers allows personalized prediction of AMD progression. Moreover, pathways of progression may be specific in respect to the neovascular/atrophic type.

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BackgroundChronic suppurative otitis media (CSOM) is frequently associated with symptoms of inflammation like discharge from the ear or pain. In many cases, patients suffer from hearing loss causing communication problems and social withdrawal. The objective of this work was to collect prospective audiological data and data on general and disease-specific quality of life with validated quality of life measurement instruments to assess the impact of the disease on health-related quality of life (HR-QOL).Methods121 patients were included in the study. Patients were clinically examined in the hospital before and 6 months after surgery including audiological testing. They filled in the quality of life questionnaires SF-36 and Chronic Otitis Media Outcome Test 15 (COMOT-15) pre-operatively and 6 and 12 months post-operatively, respectively.ResultsComplete data records from 90 patients were available for statistical analysis. Disease-specific HR-QOL in patients with CSOM improved after tympanoplasty in all the scales of the COMOT-15. There was no difference in HR-QOL assessment between patients with mesotympanic respectively epitympanic CSOM. However, we did find the outcome to be worse in patients who received revision surgery compared with those receiving primary surgery. Audiometric findings correlated very well with the subscale hearing function from the COMOT-15 questionnaire. General HR-QOL measured with the SF-36 was not significantly changed by tympanoplasty.ConclusionsTympanoplasty did lead to a significant improvement of disease-specific HR-QOL in patients with CSOM while general HR-QOL did not change. Very well correlations were found between the subscale hearing function from the COMOT-15 questionnaire and audiological findings. Revision surgery seems to be a predictor for a worse outcome.

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