Incidence of sight-threatening diabetic retinopathy in an established urban screening programme: An 11-year cohort study

Evolution of ophthalmological care in adult with diabetes in France between 2010 and 2022: a nationwide study

PURPOSE

The aim of this study is to describe ophthalmological care of adults with diabetes in France and its evolution between 2010 and 2022.

METHODS

In this study, we used the ESND, a representative permanent random sample of 2/100th of the entire French population. Ophthalmological care was defined by the combination of ophthalmological procedures (fundus examination, color fundus photography, Optical Coherence Tomography..) and/or ophthalmological treatment (intravitreal injection or laser treatment) during the year. Changes in annual rates during the study period were assessed using linear regression models excluding 2020.

RESULTS

From 2010 to 2022, the number of adults treated for diabetes in the ENSD increased from 48 329 patients (mean age 65.3 ± 13.0, 46.3% women) to 68 397 patients (mean age 67.0 ± 13.2, 44.8% women). Among them, the annual rate of ophthalmological care was stable (46.5% in 2010 and 48.5% in 2022) and the difference was not significant (β = 0.10% per year, p = 0.11). The yearly ophthalmological treatment rate increased significantly (3.3% in 2010 and 5.3% in 2022, β = 0.2% per year, p < 0.0001). Rates were lower during the COVID-19 outbreak in 2020.Women, individuals aged between 66-80 years, those living in the least deprived areas and those treated with combined insulin and non-insulin treatment had higher yearly ophthalmological care rate.

CONCLUSION

In this large nationwide representative study with recent and updated data, although ophthalmological treatment rate has increased over the decade mainly due to intravitreal injections, less than half of the diabetic patients receive yearly ophthalmological care.

Microglia in retinal angiogenesis and diabetic retinopathy

Diabetic retinopathy has a high probability of causing visual impairment or blindness throughout the disease progression and is characterized by the growth of new blood vessels in the retina at an advanced, proliferative stage. Microglia are a resident immune population in the central nervous system, known to play a crucial role in regulating retinal angiogenesis in both physiological and pathological conditions, including diabetic retinopathy. Physiologically, they are located close to blood vessels and are essential for forming new blood vessels (neovascularization). In diabetic retinopathy, microglia become widely activated, showing a distinct polarization phenotype that leads to their accumulation around neovascular tufts. These activated microglia induce pathogenic angiogenesis through the secretion of various angiogenic factors and by regulating the status of endothelial cells. Interestingly, some subtypes of microglia simultaneously promote the regression of neovascularization tufts and normal angiogenesis in neovascularization lesions. Modulating the state of microglial activation to ameliorate neovascularization thus appears as a promising potential therapeutic approach for managing diabetic retinopathy.

Five-year outcomes of digital diabetic eye screening in individuals aged 80 and 85 years

OBJECTIVE

To assess the incidence of referable diabetic retinopathy (DR) in patients aged 80 and 85 years to determine whether screening interval can be extended safely in this age group.

METHODS

Patients who were aged 80 and 85 years when they attended digital screening during April 2014-March 2015 were included. Screening results at baseline and over the next four years were analysed.

RESULTS

1880 patients aged 80 and 1105 patients aged 85 were included. Patients referred to hospital eye service (HES) for DR ranged from 0.7% to 1.4% in the 80-year-old cohort over 5 years. In this cohort a total of 76 (4%) were referred to HES for DR, of which 11 (0.6%) received treatment. Over the course of the follow up (FU), 403 (21%) died. In the 85-year-old cohort, referral to HES for DR each year ranged from 0.1% to 1.3%. In this cohort a total of 27 (2.4%) were referred to HES for DR, of which 4 (0.4%) received treatment. Over the course of follow-up 541(49%) died. All treated cases were for maculopathy in both cohorts and there were no cases of proliferative diabetic retinopathy requiring treatment.

CONCLUSION

This study showed that the risk of progression of retinopathy is quite low in this age group and only a small proportion of patients developed referable retinopathy requiring treatment. This suggests relooking at the need for screening and ideal screening intervals in patients aged 80 years and over with no referable DR as they can be potentially classed as a group with low risk of sight loss.

Changes in the Epidemiology of Diabetic Retinopathy in Spain: A Systematic Review and Meta-Analysis

Background. The aim of the present study was to determine the prevalence and incidence of diabetic retinopathy (DR) and its changes in the last 20 years in type 2 diabetes mellitus (T2DM) patients in Spain. Methods. A systematic review with a meta-analysis was carried out on the studies published between 2001–2020 on the prevalence and incidence of DR and sight-threatening diabetic retinopathy (STDR) in Spain. The articles included were selected from four databases and publications of the Spanish Ministry of Health and Regional Health Care System (RHCS). The meta-analysis to determine heterogeneity and bias between studies was carried out with the MetaXL 4.0. Results. Since 2001, we have observed an increase in the detection of patients with DM, and at the same time, screening programs for RD have been launched; thus, we can deduce that the increase in the detection of patients with DM, many of them in the initial phases, far exceeds the increased detection of patients with DR. The prevalence of DR was higher between 2001 and 2008 with values of 28.85%. These values decreased over the following period between 2009 and 2020 with a mean of 15.28%. Similarly the STDR prevalence decrease from 3.67% to 1.92% after 2008. The analysis of the longitudinal studies determined that the annual DR incidence was 3.83%, and the STDR annual incidence was 0.41%. Conclusion. In Spain, for T2DM, the current prevalence of DR is 15.28% and 1.92% forSTDR. The annual incidence of DR is 3.83% and is 0.41% for STDR.

Multiple Ocular Disease Diagnosis Using Fundus Images Based on Multi-Label Deep Learning Classification

Designing computer-aided diagnosis (CAD) systems that can automatically detect ocular diseases (ODs) has become an active research field in the health domain. Although the human eye might have more than one OD simultaneously, most existing systems are designed to detect specific eye diseases. Therefore, it is crucial to develop new CAD systems that can detect multiple ODs simultaneously. This paper presents a novel multi-label convolutional neural network (ML-CNN) system based on ML classification (MLC) to diagnose various ODs from color fundus images. The proposed ML-CNN-based system consists of three main phases: the preprocessing phase, which includes normalization and augmentation using several transformation processes, the modeling phase, and the prediction phase. The proposed ML-CNN consists of three convolution (CONV) layers and one max pooling (MP) layer. Then, two CONV layers are performed, followed by one MP and dropout (DO). After that, one flatten layer is performed, followed by one fully connected (FC) layer. We added another DO once again, and finally, one FC layer with 45 nodes is performed. The system outputs the probabilities of all 45 diseases in each image. We validated the model by using cross-validation (CV) and measured the performance by five different metrics: accuracy (ACC), recall, precision, Dice similarity coefficient (DSC), and area under the curve (AUC). The results are 94.3%, 80%, 91.5%, 99%, and 96.7%, respectively. The comparisons with the existing built-in models, such as MobileNetV2, DenseNet201, SeResNext50, InceptionV3, and InceptionresNetv2, demonstrate the superiority of the proposed ML-CNN model.