Economic Aspects in the Management of Diabetic Macular Edema in Italy

Background

Diabetic Macular Edema (DME) is the most common cause of vision loss in diabetic patients. Currently, the Vascular Endothelial Growth Factor inhibitors (anti-VEGFs) are used as the first line of DME treatment and corticosteroid implants are usually used as a second-line treatment. These implants are a safe and effective therapeutic option that can improve the quality of life of DME patients by reducing the intravitreal injections number. We determined the economic impact related to DME, also from the social perspective, and the consequences of the increased use of the dexamethasone implant.

Methods

The analysis compares two scenarios: the first based on the current rate of recourse to the therapeutic alternatives available in the Italian healthcare setting (as is) and the second based on the assumption of an increased recourse to dexamethasone implants (to be). The results are expressed both in terms of the resource absorption associated with the two scenarios and in terms of the cost differential yielded by their comparison.

Results

The increased use of the dexamethasone implant allows considerable savings in terms of healthcare professionals' time, follow-up and productivity lost by patients/caregivers. These savings would reduce healthcare costs for the management of DME patients in Italy by €2,058,238 in 5 years.

Conclusions

To optimize the healthcare resources allocation, it is necessary to implement treatments that yield not only cost reductions but also a clinical benefit for patients. The dexamethasone implant use is an example of DME management that generates value for patients, health system and society.

Association Between Diabetic Retinopathy, Brain Structural Abnormalities, and Cognitive Impairment for Accumulated Evidence in Observational Studies

PURPOSE

To evaluate the association between diabetic retinopathy (DR) and cerebral disease or cognitive impairment.

DESIGN

Systematic review and meta-analysis.

METHOD

The hypothesis was formulated prior to data collection. Cross-sectional studies and cohort studies that assessed the association between any measure of DR and cerebral small vessel disease or any type of cognitive impairment in diabetic participants were included. The data were independently extracted by two investigators. This systematic review and meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses and Meta-analysis of Observational Studies in Epidemiology guidelines RESULTS: A total of 27 studies were included. The combined odds ratio of 5 cross-sectional/cohort studies that reported that the associations between DR and cerebral structural changes was 1.75 (95% confidence interval [CI]: 1.36-2.25). The combined hazard ratio of 4 cohort studies that examined the association between DR and cognitive impairment events was 1.47 (95% CI: 1.22-1.78). The combined odds ratio of 14 cross-sectional/cohort studies that examined the association between DR and different cognitive impairment events was 1.43 (95% CI: 1.06-1.93). The overall coefficient (β) of 4 studies that examined the relationship between DR and specific cognitive performance was 0.09 (95% CI: 0.00-0.18). Considering the quality of the data, we have performed subgroup analysis in studies scored >7 and studies scored ≤7, respectively, according to the Newcastle-Ottawa scale.

CONCLUSION

The present meta-analysis suggests that DR is associated with an increased risk of structural abnormalities in the brain and cognitive impairment. This association remained significant after adjusting for blood glucose, and the presence of hypertension, indicating that DR is an important danger signal for cerebral abnormalities.

A computer-aided diagnosis system for detecting various diabetic retinopathy grades based on a hybrid deep learning technique

Diabetic retinopathy (DR) is a serious disease that may cause vision loss unawares without any alarm. Therefore, it is essential to scan and audit the DR progress continuously. In this respect, deep learning techniques achieved great success in medical image analysis. Deep convolution neural network (CNN) architectures are widely used in multi-label (ML) classification. It helps in diagnosing normal and various DR grades: mild, moderate, and severe non-proliferative DR (NPDR) and proliferative DR (PDR). DR grades are formulated by appearing multiple DR lesions simultaneously on the color retinal fundus images. Many lesion types have various features that are difficult to segment and distinguished by utilizing conventional and hand-crafted methods. Therefore, the practical solution is to utilize an effective CNN model. In this paper, we present a novel hybrid, deep learning technique, which is called E-DenseNet. We integrated EyeNet and DenseNet models based on transfer learning. We customized the traditional EyeNet by inserting the dense blocks and optimized the resulting hybrid E-DensNet model's hyperparameters. The proposed system based on the E-DenseNet model can accurately diagnose healthy and different DR grades from various small and large ML color fundus images. We trained and tested our model on four different datasets that were published from 2006 to 2019. The proposed system achieved an average accuracy (ACC), sensitivity (SEN), specificity (SPE), Dice similarity coefficient (DSC), the quadratic Kappa score (QKS), and the calculation time (T) in minutes (m) equal [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], 0.883, and 3.5m respectively. The experiments show promising results as compared with other systems.

Transcription factor FOXP1 mediates vascular endothelial dysfunction in diabetic retinopathy

BACKGROUND

Diabetic retinopathy (DR) is still the fastest growing cause of blindness in working aged adults, and its typical characteristics are endothelial cell dysfunction and pericytes loss. Transcription factor fork head box P1 (FOXP1) is a member of FOX family involved in diabetes progression and is expressed in endothelial cells. The purpose of this study was to investigate the role and mechanism of FOXP1 in DR.

METHODS

The vitreous of DR patients and non-DR patients were collected, and the expression of FOXP1 was detected by real-time polymerase chain reaction (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA). Human umbilical vein endothelial cells (HUVECs) cultured in high glucose simulated DR environment, and the expressions of FOXP1, vascular endothelial growth factor (VEGF), and pigment epithelium derived factor (PEDF) were detected by RT-qPCR and western blot (WB) after transfection of small interfering RNA (siRNA) to knock out FOXP1. At the same time, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay (MTT), 5-ethynyl-2'-deoxyuridine assay (EDU), flow cytometry, Transwell assay, and tube-forming experiment were performed to determine cell proliferation, migration, and tube-forming ability.

RESULTS

We found that FOXP1 was highly expressed in the vitreous of DR patients and HUVECs under high glucose condition. After FOXP1 was decreased, the activation of VEGF expression and inhibition of PEDF expression in HUVECs induced by high glucose were reversed; meanwhile, cell proliferation, migration, and tube formation decreased, and apoptosis was promoted.

CONCLUSION

Generally, FOXP1 is highly expressed in the vitreous of DR patients, and its silence prevented VEGF/PEDF signaling pathway stimulated by high glucose and also reduced the proliferation, migration, and tube formation of endothelial cell, thus improving vascular endothelial dysfunction caused by DR. The results indicate that FOXP1 may be a therapeutic target of DR.

Gene Biomarkers Related to Th17 Cells in Macular Edema of Diabetic Retinopathy: Cutting-Edge Comprehensive Bioinformatics Analysis and In Vivo Validation

Background

Previous studies have shown that T-helper 17 (Th17) cell-related cytokines are significantly increased in the vitreous of proliferative diabetic retinopathy (PDR), suggesting that Th17 cells play an important role in the inflammatory response of diabetic retinopathy (DR), but its cell infiltration and gene correlation in the retina of DR, especially in diabetic macular edema (DME), have not been studied.

Methods

The dataset GSE160306 was downloaded from the Gene Expression Omnibus (GEO) database, which contains 9 NPDR samples and 10 DME samples. ImmuCellAI algorithm was used to estimate the abundance of Th17 cells in 24 kinds of infiltrating immune cells. The differentially expressed Th17 related genes (DETh17RGs) between NPDR and DME were documented by difference analysis and correlation analysis. Through aggregate analyses such as gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis, a protein-protein interaction (PPI) network was constructed to analyze the potential function of DETh17RGs. CytoHubba plug-in algorithm, Lasso regression analysis and support vector machine recursive feature elimination (SVM-RFE) were implemented to comprehensively identify Hub DETh17RGs. The expression archetypes of Hub DETh17RGs were further verified in several other independent datasets related to DR. The Th17RG score was defined as the genetic characterization of six Hub DETh17RGs using the GSVA sample score method, which was used to distinguish early and advanced diabetic nephropathy (DN) as well as normal and diabetic nephropathy. Finally, real-time quantitative PCR (qPCR) was implemented to verify the transcription levels of Hub DETh17RGs in the STZ-induced DR model mice (C57BL/6J).

Results

238 DETh17RGs were identified, of which 212 genes were positively correlated while only 26 genes were negatively correlated. Six genes (CD44, CDC42, TIMP1, BMP7, RHOC, FLT1) were identified as Hub DETh17RGs. Because DR and DN have a strong correlation in clinical practice, the verification of multiple independent datasets related to DR and DN proved that Hub DETh17RGs can not only distinguish PDR patients from normal people, but also distinguish DN patients from normal people. It can also identify the initial and advanced stages of the two diseases (NPDR vs DME, Early DN vs Advanced DN). Except for CDC42 and TIMP1, the qPCR transcription levels and trends of other Hub DETh17RGs in STZ-induced DR model mice were consistent with the human transcriptome level in this study.

Conclusion

This study will improve our understanding of Th17 cell-related molecular mechanisms in the progression of DME. At the same time, it also provides an updated basis for the molecular mechanism of Th17 cell crosstalk in the eye and kidney in diabetes.

A Hybrid Deep Learning-Metaheuristic Model for Diagnosis of Diabetic Retinopathy

International Diabetes Federation (IDF) reports that diabetes is one of the rapidly growing illnesses. About 463 million adults between 20-79 years have diabetes. There are also millions of undiagnosed patients. It is estimated that there will be about 578 million diabetics by 2030 [1]. Diabetes reasons different eye diseases. Diabetic retinopathy (DR) is one of them and is also one of the most common vision loss or blindness worldwide. DR progresses slowly and has few indicators in the early stages. It makes the diagnosis of DR a problematic task. Automated systems promise to support the diagnosis of DR. Many deep learning-based models have been developed for DR classification. This study aims to support ophthalmologists in the diagnosis process and increase the diagnosis performance of DR through a hybrid model. A publicly available Messidor-2 dataset was used in this study, comprised of retinal images. In the proposed model, first, images were pre-processed and a deep learning model, namely, InceptionV3 was used in feature extraction where a transfer learning approach is applied. Next, the number of features in obtained feature vectors was decreased with feature selection by Simulated Annealing (SA). Lastly, the best representation features were used in XGBoost model. The XGBoost algorithm gives an accuracy of 92.26% in a binary classification task. This study shows that a pre-trained ConvNet with a metaheuristic algorithm for feature selection gives a satisfactory result in the diagnosis of DR.

EDR-Net: Lightweight Deep Neural Network Architecture for Detecting Referable Diabetic Retinopathy

Present architecture of convolution neural network for diabetic retinopathy (DR-Net) is based on normal convolution (NC). It incurs high computational cost as NC uses a multiplicative weight that measures a combined correlation in both cross-channel and spatial dimension of layer's inputs. This might cause the overall DR-Net architecture to be over-parameterised and computationally inefficient. This paper proposes EDR-Net - a new end-to-end, DR-Net architecture with depth-wise separable convolution module. The EDR-Net architecture was trained with DRKaggle-train dataset (35,126 images), and tested on two datasets, i.e. DRKaggle-test (53,576 images) and Messidor-2 (1,748 images). Results showed that the proposed EDR-Net achieved predictive performance comparable with current state-of-the-arts in detecting referable diabetic retinopathy (rDR) from fundus images and outperformed other light weight architectures, with at least two times less computation cost. This makes it more amenable for mobile device based computer-assisted rDR screening applications.

A transcriptomics and molecular biology based investigation reveals the protective effect and mechanism of carnosol on t-BHP induced HRMECs via Nrf2 signaling pathway

Human retinal microvascular endothelial cells (HRMECs) injury plays an essential role in the pathogenesis of diabetic retinopathy (DR). As one of the crucial pathogenetic factors, oxidative stress induces HRMECs apoptosis and microvascular lesions. Nuclear factor erythroid 2-related factor 2 (Nrf2) acts as a molecular switch in oxidative stress-induced HRMECs injury. The present study was designed to investigate the protective effect and underlying mechanism of carnosol, a potential Nrf2 agonist, in tert-butyl hydroperoxide (t-BHP) induced HRMECs oxidative stress injury. In this study, carnosol was found to inhibit HRMECs injury induced by t-BHP. Transcriptomics and molecular biology illustrated that the mechanism was associated with oxidative stress, vascular system development, apoptosis, cell cycle, cell adhesion, cytoskeleton, and nitric oxide biosynthesis. Carnosol directly scavenged free radicals or activated the Nrf2 signaling pathway to alleviate HRMECs oxidative stress. ML385 pretreatment or Nrf2 small interference RNA (siRNA) inhibited the protective effect of carnosol on HRMECs injury. Moreover, the apoptosis and cell cycle arrest in HRMECs were suppressed by carnosol. Treatment with carnosol could also effectively regulate the adhesion and cytoskeleton. Overall, our data provide a systematic perspective for the mechanism of carnosol against HRMECs oxidative stress injury and reveal that carnosol may be a candidate drug for DR therapy.

Metabolism Dysregulation in Retinal Diseases and Related Therapies

The human retina, which is part of the central nervous system, has exceptionally high energy demands that requires an efficient metabolism of glucose, lipids, and amino acids. Dysregulation of retinal metabolism disrupts local energy supply and redox balance, contributing to the pathogenesis of diverse retinal diseases, including age-related macular degeneration, diabetic retinopathy, inherited retinal degenerations, and Macular Telangiectasia. A better understanding of the contribution of dysregulated metabolism to retinal diseases may provide better therapeutic targets than we currently have.

Deep Learning to Detect OCT-derived Diabetic Macular Edema from Color Retinal Photographs: A Multicenter Validation Study

PURPOSE

To validate the generalizability of a deep learning system (DLS) that detects diabetic macular edema (DME) from 2-dimensional color fundus photographs (CFP), for which the reference standard for retinal thickness and fluid presence is derived from 3-dimensional OCT.

DESIGN

Retrospective validation of a DLS across international datasets.

PARTICIPANTS

Paired CFP and OCT of patients from diabetic retinopathy (DR) screening programs or retina clinics. The DLS was developed using data sets from Thailand, the United Kingdom, and the United States and validated using 3060 unique eyes from 1582 patients across screening populations in Australia, India, and Thailand. The DLS was separately validated in 698 eyes from 537 screened patients in the United Kingdom with mild DR and suspicion of DME based on CFP.

METHODS

The DLS was trained using DME labels from OCT. The presence of DME was based on retinal thickening or intraretinal fluid. The DLS's performance was compared with expert grades of maculopathy and to a previous proof-of-concept version of the DLS. We further simulated the integration of the current DLS into an algorithm trained to detect DR from CFP.

MAIN OUTCOME MEASURES

The superiority of specificity and noninferiority of sensitivity of the DLS for the detection of center-involving DME, using device-specific thresholds, compared with experts.

RESULTS

The primary analysis in a combined data set spanning Australia, India, and Thailand showed the DLS had 80% specificity and 81% sensitivity, compared with expert graders, who had 59% specificity and 70% sensitivity. Relative to human experts, the DLS had significantly higher specificity (P = 0.008) and noninferior sensitivity (P < 0.001). In the data set from the United Kingdom, the DLS had a specificity of 80% (P < 0.001 for specificity of >50%) and a sensitivity of 100% (P = 0.02 for sensitivity of > 90%).

CONCLUSIONS

The DLS can generalize to multiple international populations with an accuracy exceeding that of experts. The clinical value of this DLS to reduce false-positive referrals, thus decreasing the burden on specialist eye care, warrants a prospective evaluation.

Three-dimensional spheroids of choroid-retinal vascular endothelial cells as an in-vitro model for diabetic retinopathy: Proof-of-concept investigation

Diabetic retinopathy (DR) is a primary microvascular complication of diabetes mellitus and a vision-threatening condition. Vascular endothelial growth factor (VEGF) induces neovascularization and causes metabolic damage to the retinal and choroidal vasculature in diabetic patients. Existing drug screening models and treatment strategies for DR need to be refined through the establishment of relevant pre-clinical models, which may enable development of effective and safe therapies. The present study discusses the development of an in-vitro three-dimensional (3D) spheroid model, using RF/6A choroid-retinal vascular endothelial cells, to closely mimic the in-vivo disease condition. Compact, reproducibly-sized, viable and proliferating RF/6A spheroids were fabricated, as confirmed by microscopy, live/dead assay, cell proliferation assay and histological staining. In-vitro angiogenesis was studied by evaluating individual effects of VEGF and an anti-VEGF monoclonal antibody, Bevacizumab, and their combination on cellular proliferation and 3D endothelial sprout formation. VEGF stimulated angiogenic sprouting while Bevacizumab demonstrated a dose-dependent anti-angiogenic effect, as determined from the cellular proliferation observed and extent and length of sprouting. These investigations validated the potential of RF/6A spheroids in providing an alternative-to-animal, pathophysiologically-relevant model to facilitate pre-clinical and biomedical research related to DR.

•

Matrix-free three-dimensional RF/6A spheroids were developed and characterized.

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VEGF-induced sprouting in RF/6A spheroids mimicked in-vivo vascular angiogenesis.

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Bevacizumab showed clinically-relevant anti-angiogenic responses in spheroid model.

•

Proof-of-concept for in-vitro diabetic retinopathy model was developed.

Treatment of chronic diabetic macular oedema with intravitreal fluocinolone acetonide implant; real-life analysis of outcomes during overall treatment period

PURPOSE

To assess the clinical efficacy of the fluocinolone acetonide (FA) intravitreal implant (Iluvien, Alimera Sciences) over a 12-month period in a population resistant to treatment with first-line anti-VEGF agents.

METHODS

This study is a retrospective cohort study assessing functional and anatomical outcomes in 13 eyes of 12 patients treated for diabetic macular oedema (DMO) with a single fluocinolone implant (FA) (Iluvien) under real-world conditions. The follow-up period includes the time of first intravitreal treatment (incl anti-VEGF or short-lasting steroids) given until 12 months post FA implant insertion. Primary outcomes were best corrected visual acuity (BCVA), measured using the modified Early Treatment Diabetic Retinopathy Study (ETDRS) grading scale, and central foveal thickness (CFT), measured using Topcon 3DOCT-2000 (Topcon Inc) SD-OCT imaging. Mean BCVA and CFT were measured before anti-VEGF treatment, after anti-VEGF treatment, at the time of Iluvien implant insertion, and 6 and 12 months after Iluvien implant insertion. The t-paired sample test was used to ascertain statistical significance of changes in comparison of two samples while the ANOVA analysis was used in comparison of three or more samples.

RESULTS

The baseline BCVA (SD) of the cohort prior to initiation of anti-VEGF treatment was 47.45 (12.27) ETDRS letters whilst the mean CFT (SD) was 579 (203) microns. Following completion of anti-VEGF therapy, the mean improvement in vision was 8.9 ETDRS letters (p = 0.1) whilst the mean reduction in CFT was 197 microns (p = 0.028). Mean BCVA (SD) at the time of insertion of the FA implant was 55.15 (11.16) ETDRS letters and mean (SD) CFT at time of insertion of the FA was 454.62 μm (109.51). Following the 12-month treatment period with the FA implant, BCVA (SD) was 62.15 (10.25) ETDRS letters (p = 0.0331) and the mean (SD) CFT was 404.36 μm (142.92), a change of -50.26 μm from baseline (p = 0.0369).

CONCLUSIONS

This study has shown that statistically significant improvements in BCVA and CFT can be achieved over a 12-month period with the Iluvien implant. The implant has been shown to be a safe option in the treatment of DMO and may have a role to play in achieving good functional and anatomical outcomes in DMO while also reducing the frequency of follow-up appointments required to maintain stable vision in the working-age population.

tiRNA-Val promotes angiogenesis via Sirt1–Hif-1α axis in mice with diabetic retinopathy

Background

Diabetic retinopathy (DR) is a specific microvascular complication arising from diabetes, and its pathogenesis is not completely understood. tRNA-derived stress-induced RNAs (tiRNAs), a new type of small noncoding RNA generated by specific cleavage of tRNAs, has become a promising target for several diseases. However, the regulatory function of tiRNAs in DR and its detailed mechanism remain unknown.

Results

Here, we analyzed the tiRNA profiles of normal and DR retinal tissues. The expression level of tiRNA-Val was significantly upregulated in DR retinal tissues. Consistently, tiRNA-Val was upregulated in human retinal microvascular endothelial cells (HRMECs) under high glucose conditions. The overexpression of tiRNA-Val enhanced cell proliferation and inhibited cell apoptosis in HRMECs, but the knockdown of tiRNA-Val decreased cell proliferation and promoted cell apoptosis. Mechanistically, tiRNA-Val, derived from mature tRNA-Val with Ang cleavage, decreased Sirt1 expression level by interacting with sirt1 3'UTR, leading to the accumulation of Hif-1α, a key target for DR. In addition, subretinal injection of adeno-associated virus to knock down tiRNA-Val in DR mice ameliorated the symptoms of DR.

Conclusion

tiRNA-Val enhance cell proliferation and inhibited cell apoptosis via Sirt1/Hif-1α pathway in HRMECs of DR retinal tissues.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40659-022-00381-7.

Cost-effectiveness of artificial intelligence screening for diabetic retinopathy in rural China

BACKGROUND

Diabetic retinopathy (DR) has become a leading cause of global blindness as a microvascular complication of diabetes. Regular screening of diabetic retinopathy is strongly recommended for people with diabetes so that timely treatment can be provided to reduce the incidence of visual impairment. However, DR screening is not well carried out due to lack of eye care facilities, especially in the rural areas of China. Artificial intelligence (AI) based DR screening has emerged as a novel strategy and show promising diagnostic performance in sensitivity and specificity, relieving the pressure of the shortage of facilities and ophthalmologists because of its quick and accurate diagnosis. In this study, we estimated the cost-effectiveness of AI screening for DR in rural China based on Markov model, providing evidence for extending use of AI screening for DR.

METHODS

We estimated the cost-effectiveness of AI screening and compared it with ophthalmologist screening in which fundus images are evaluated by ophthalmologists. We developed a Markov model-based hybrid decision tree to analyze the costs, effectiveness and incremental cost-effectiveness ratio (ICER) of AI screening strategies relative to no screening strategies and ophthalmologist screening strategies (dominated) over 35 years (mean life expectancy of diabetes patients in rural China). The analysis was conducted from the health system perspective (included direct medical costs) and societal perspective (included medical and nonmedical costs). Effectiveness was analyzed with quality-adjusted life years (QALYs). The robustness of results was estimated by performing one-way sensitivity analysis and probabilistic analysis.

RESULTS

From the health system perspective, AI screening and ophthalmologist screening had incremental costs of $180.19 and $215.05 but more quality-adjusted life years (QALYs) compared with no screening. AI screening had an ICER of $1,107.63. From the societal perspective which considers all direct and indirect costs, AI screening had an ICER of $10,347.12 compared with no screening, below the cost-effective threshold (1-3 times per capita GDP of Chinese in 2019).

CONCLUSIONS

Our analysis demonstrates that AI-based screening is more cost-effective compared with conventional ophthalmologist screening and holds great promise to be an alternative approach for DR screening in the rural area of China.

Risk factors for epiretinal membrane in eyes with primary rhegmatogenous retinal detachment that received silicone oil tamponade

Background/aims

This study investigated the risk factors for epiretinal membrane (ERM) in eyes with primary rhegmatogenous retinal detachment (RRD) that received silicone oil (SO) tamponade.

Methods

This retrospective analysis included 1140 patients (1140 eyes) with RRD who underwent primary vitrectomy and SO tamponade. The prevalence of ERM was estimated and possible risk factors (eg, type 2 diabetes, proliferative vitreoretinopathy (PVR), SO tamponade time (SOTT), photocoagulation, vitreous haemorrhage, choroidal detachment, cryotherapy and retinal tear size) were analysed via multiple logistic regression.

Results

The prevalence of ERM was 12.3% (140/1140), and the accuracy of preoperative ERM diagnosis was 40.5%. Multivariate logistic regression analysis showed that risk factors for ERM in eyes with SO tamponade included preoperative PVR (OR=4.336, 95% CI 2.533 to 7.424, p<0.001), type 2 diabetes (OR=3.996, 95% CI 2.013 to 7.932, p<0.001), photocoagulation energy (OR=1.785, 95% CI 1.306 to 2.439, p<0.001) and SOTT (OR=1.523, 95% CI 1.261 to 1.840, p<0.001). No statistically significant associations were observed between the incidence of ERM and other risk factors. Preoperative PVR showed the strongest association with risk of ERM. The risk of ERM was positively associated with SOTT, photocoagulation energy and preoperative PVR grade.

Conclusion

In eyes with RRD that received SO tamponade, the prevalence of ERM was 12.3%, while the accuracy of preoperative ERM diagnosis was low. Preoperative PVR, type 2 diabetes, photocoagulation energy and SOTT were the main risk factors for ERM.

Mixed diabetic retinopathy screening coverage results in Indigenous Australian primary care settings: A nurse-led model of integrated diabetes care

AIMS

To determine eye screening coverage and adherence to national eye screening recommendations of a nurse-led retinal image-based model of diabetes education and eye screening in Indigenous primary care clinics.

DESIGN

A pre-post study.

METHODS

During January 2018-March 2020 Indigenous Australians with diabetes at three regional Australian clinics were offered eye screening by a nurse-diabetes educator/retinal imager. At the main site the nurse recruited/scheduled participants, and at satellite sites local clinic staff did so. Visual acuity was tested and digital retinal images acquired and graded. Participants were offered rescreening at or before 12-months based on baseline results.

RESULTS

In total 203 adults with diabetes attending Indigenous primary care clinics were screened, with divergent results based on the recruitment methods. At the main clinic 135 of 172 eligible adults (79%) were screened. At the satellite sites, 15 of 85 (18%) and 21 of 77 (27%) diabetes patients were screened. Combined coverage 51%.

CONCLUSION

A credentialed nurse-educator implemented a model of retinal image-based diabetes education, measured eye screening coverage and adherence to national eye screening guidelines, met the 'acceptable 75% eye screening coverage' benchmark and improved patient eye screening guideline adherence at the one site where the nurse-educator had access to patient recruitment and scheduling.

IMPACT

This novel nurse-led primary care iDEES model of retinal image-based diabetes education can improve the currently low Indigenous diabetes eye screening coverage in Australia. Importantly, the nurse-managed iDEES model of integrated diabetes care is readily adaptable to other settings and populations where access to and/or uptake of eye care is suboptimal.

CLINICAL TRIAL REGISTRATION

ANZCTRN1261800120435.

Single nucleotide variants of receptor for advanced glycation end-products (AGER) gene: is it a new opening in the risk assessment of diabetic retinopathy?-a review

Background

Diabetic retinopathy (DR) is a common microvascular complication of diabetes. There is strong evidence suggesting that DR has an inheritable component. The interaction between advanced glycation end products (AGEs) and their receptor is integral in the pathogenesis of diabetic retinopathy and its various complications, retinopathy being one of them.

Overview and methodology

This review discusses the existing literature on the association between single nucleotide variants (SNV) of AGER gene and the risk of DR. It also discusses the current understanding of the AGE-AGER pathway in diabetic retinopathy. Through our article we have tried to consolidate all the available information about these SNVs associated with diabetic retinopathy in a succinct tabular form. Additionally, a current understanding of the AGE-AGER interaction and its deleterious effects on the cells of the retina has been discussed in detail to provide comprehensive information about the topic to the reader. A literature review was performed on PubMed, Cochrane Library, and Google Scholar for studies to find existing literature on the association between AGER gene SNVs and the risk, progression and severity of developing DR. This article will encourage scientific communication and discussion about possibly devising genetic markers for an important cause of blindness both in developed and developing countries, i.e., diabetic retinopathy.

Result

Based on genetic studies done in Indian and Chinese population G82S(rs2070600) was positively associated with Diabetic Retinopathy. Patients of diabetic retinopathy in Caucasian population had −T374A(rs1800624) polymorphism. + 20T/A was found to be associated with the disease in a study done in UK. Association with G1704T(rs184003) was seen in Chinese and Malaysian population. A Chinese study found its association with CYB242T. -T429C(rs1800625) SNV was not associated with DR in any of the studies. G2245A(rs55640627) was positively associated with the disease process in Malaysian population. It was not associated in Malaysian and Chinese population. Promoter variant rs1051993 has also been found to a susceptible SNV in the Chinese population.

Conclusion

While providing a comprehensive review of the existing information, we would like to emphasize on a large, multi-centric, trial with a much larger and varied population base to definitely determine these single nucleotide variants predisposing diabetic individuals.

Prevalence of diabetic macular edema based on optical coherence tomography in people with diabetes: A systematic review and meta-analysis

Diabetic macular edema (DME) is a leading cause of vision loss among people with diabetes. Optical coherence tomography (OCT) allows for accurate assessment and early detection of DME. Meta-analyses on DME prevalence diagnosed with OCT are lacking. We performed a meta-analysis to assess the global prevalence of OCT-diagnosed DME. We searched five electronic databases (EMBASE, CINAHL, Web of Science, Scopus, and MEDLINE) on May 29, 2020 and updated the search on March 19 and June 22, 2021. The quality of retrieved studies was evaluated using the Joanna Briggs Institute Checklist for Prevalence Studies. A random-effects model was used to pool prevalence estimates. Countries were classified into low-to-middle-income and high-income countries using World Bank data for subgroup analyses. Seven studies were included in this meta-analysis. The pooled prevalence of DME was 5.47% (95% CI: 3.66%-7.62%) overall, 5.81% (95% CI: 0.07%-18.51%) in low-to-middle-income countries and 5.14% (95% CI: 3.44%-7.15%) in high-income countries. We reported approximately 5.5% of people with diabetes have DME, with a statistically non-significantly lower prevalence in high-income countries versus low-to-middle-income countries. Given the global pandemic of diabetes, there is a need to inform physicians and educate people with diabetes regarding early detection and treatment of DME using OCT.

Deep Learning Prediction of Response to Anti-VEGF among Diabetic Macular Edema Patients: Treatment Response Analyzer System (TRAS)

Diabetic macular edema (DME) is the most common cause of visual impairment among patients with diabetes mellitus. Anti-vascular endothelial growth factors (Anti-VEGFs) are considered the first line in its management. The aim of this research has been to develop a deep learning (DL) model for predicting response to intravitreal anti-VEGF injections among DME patients. The research included treatment naive DME patients who were treated with anti-VEGF. Patient’s pre-treatment and post-treatment clinical and macular optical coherence tomography (OCT) were assessed by retina specialists, who annotated pre-treatment images for five prognostic features. Patients were also classified based on their response to treatment in their post-treatment OCT into either good responder, defined as a reduction of thickness by >25% or 50 µm by 3 months, or poor responder. A novel modified U-net DL model for image segmentation, and another DL EfficientNet-B3 model for response classification were developed and implemented for predicting response to anti-VEGF injections among patients with DME. Finally, the classification DL model was compared with different levels of ophthalmology residents and specialists regarding response classification accuracy. The segmentation deep learning model resulted in segmentation accuracy of 95.9%, with a specificity of 98.9%, and a sensitivity of 87.9%. The classification accuracy of classifying patients’ images into good and poor responders reached 75%. Upon comparing the model’s performance with practicing ophthalmology residents, ophthalmologists and retina specialists, the model’s accuracy is comparable to ophthalmologist’s accuracy. The developed DL models can segment and predict response to anti-VEGF treatment among DME patients with comparable accuracy to general ophthalmologists. Further training on a larger dataset is nonetheless needed to yield more accurate response predictions.

Long-Term Oral Administration of Salidroside Alleviates Diabetic Retinopathy in db/db Mice

Diabetic retinopathy (DR), a microvascular complication of diabetes mellitus, is the leading cause of vision loss in the working-age population worldwide. Unfortunately, current clinical treatments cannot completely prevent the occurrence and development of DR. Salidroside (Sal) is a medicinal supplement that has antioxidative and cytoprotective properties. This study aimed to investigate the therapeutic effect of Sal on DR. Briefly, Sal treatment was applied to wide-type mice and db/db mice (a widely used diabetic mice) at 25 mg/kg by oral gavage once daily from 8 weeks to 20 weeks. Mice's bodyweight, blood glucose, total cholesterol, triglyceride, high density lipoprotein and low density lipoprotein were recorded and analyzed. Retinal trypsin digestion and evans blue dye assay were used to detect retinal microvessel changes and function. Retinal glutathione and malondialdehyde content measurements were applied to assess retinal oxidative stress. Full-length transcriptome analysis was performed to explore the underlying mechanisms of Sal protection. Our results found that Sal treatment could successfully relieve blood glucose and blood lipid abnormalities, and reduce retinal oxidative stress level in diabetic mice. Also, Sal treatment repaired the abnormal transcriptome caused by diabetes, alleviated the microvascular lesion of the fundus in diabetic mice, and protected retinal normal barrier function. This study enriches the indications of Sal in the treatment of diabetic diseases, providing practical research ideas for the comprehensive preventions and treatments of DR.

Regional analysis of diabetic retinopathy and co-existing social and demographic factors in the overall population of Poland

INTRODUCTION

The aim of our study was to analyse the regional differences in diabetic retinopathy (DR) prevalence and its co-existing social and demographic factors in the overall population of Poland in the year 2017.

MATERIAL AND METHODS

Data from all levels of healthcare services at public and private institutions recorded in the National Health Fund database were evaluated. International Classification of Diseases codes were used to identify patients with type 1 and type 2 diabetes mellitus (DM) and with DR. Moran's I statistics and Spatial Autoregressive (SAR) model allowed us to understand the distribution of DR prevalence and its possible association with environmental and demographic exposures.

RESULTS

In total, 310,815 individuals with diabetic retinopathy (DR) were diagnosed in the year 2017 in Poland. Of them, 174,384 (56.11%) were women, 221,144 (71.15%) lived in urban areas, and 40,231 (12.94%) and 270,584 (87.06%) had type 1 and type 2 DM, respectively. The analysis of the SAR model showed that the significant factors for the occurrence of DR in particular counties were a higher level of average income and a higher number of ophthalmologic consultations per 10,000 adults.

CONCLUSIONS

The analyses of social, demographic, and systemic factors co-existing with DR revealed that level of income and access to ophthalmologic and diabetic services are crucial in DR prevalence in Poland.

Relationship Between Acylcarnitine and the Risk of Retinopathy in Type 2 Diabetes Mellitus

OBJECTIVE

Diabetic retinopathy is a common complication of type 2 diabetes mellitus (T2DM). Due to the limited effectiveness of current prevention and treatment methods, new biomarkers are urgently needed for the prevention and diagnosis of DR. This study aimed to explore the relationships between plasma acylcarnitine with DR in T2DM.

METHODS

From May 2015 to August 2016, data of 1032 T2DM patients were extracted from tertiary hospitals. Potential non-linear associations were tested by binary logistic regression models, and ORs and 95% CIs of the research variables were obtained. Correlation heat map was used to analyze the correlation between variables. The change of predictive ability was judged by the area under the receiver operating characteristic curve.

RESULTS

Of the 1032 patients with T2DM, 162 suffered from DR. After adjusting for several confounding variables, C2 (OR:0.55, 95%CI:0.39-0.76), C14DC (OR:0.64, 95%CI:0.49-0.84), C16 (OR:0.64, 95%CI:0.49-0.84), C18:1OH (OR:0.51, 95%CI:0.36-0.71) and C18:1 (OR:0.60, 95%CI:0.44-0.83) were negatively correlated with DR. The area under the curve increased from 0.794 (95% CI 0.745 to 0.842) to 0.840 (95% CI 0.797 to 0.833) when C2, C14DC, C18:1OH and C18:1 added to the traditional risk factor model.

CONCLUSION

There was a negative correlation between C2, C14DC, C16, C18:1OH, and C18:1 and the risk of retinopathy in patients with T2DM. C2, C14DC, C18:1OH, and C18:1 may be new predictors and diagnostic markers of DR.

Down-expression of the NLRP3 inflammasome delays the progression of diabetic retinopathy

The investigation aimed to evaluate the effects of Mcc950, an inhibitor of the NLRP3 inflammasome, on diabetic retinopathy (DR) mice. The general physiological condition of each group of mice was recorded. Retinal blood vessels were stained for observation of the density of blood vessels, and retinas were used for further morphological examination and fluorescent staining after the intravitreal injection of Mcc950. Mcc950 partially reversed hyperglycemia-induced vascular damage and had reduced histological changes compared to DR mice. IL-1β production in mice retinas in the diabetic model (DM) group increased, but pretreatment with Mcc950 significantly reversed these changes. Additionally, Mcc950 engineered reduced FITC dextran extravasation and vascular leakage. Therefore, it played an apparent protective role in DR and could be a new treatment strategy for DR.

Achievement of treatment targets predicts progression of vascular complications in type 1 diabetes

BACKGROUND AND AIM

To study the association between achievement of guideline-defined treatment targets on HbA1c, low-density lipoproteins (LDL-C), and blood pressure with the progression of diabetic complications in patients with type 1 diabetes (T1D).

METHODS

The study included 355 patients at baseline and 114 patients with follow-up data after 3-5 years. Outcome variables were the progression of diabetic kidney disease, retinopathy, or cardiovascular disease (CVD). We used logistic regression and other machine learning algorithms (MLA) to model the association of achievement of treatment targets and probability of progression of complications.

RESULTS

Achievement of the target blood pressure was associated with 96% lower odds of a new CVD event (0.04 (95% CI 0.00, 0.53), p = 0.016), and 72% lower odds of progression of any complication (0.28 (95% CI 0.09, 0.89), p = 0.027. Achievement of HbA1c target was associated with lower odds of composite complication progression by 82% (0.18 (95% CI 0.04, 0.88), p = 0.034.) None of the patients who achieved HbA1c target progressed in CVD. MLA demonstrated good accuracy for the prediction of progression of CVD (AUC 0.824), and lower accuracy for other complications.

CONCLUSION

The achievement of blood pressure and HbA1c treatment targets is associated with lower odds of vascular complication of T1D in a real life study.

Review on diabetic retinopathy with deep learning methods

Purpose: The purpose of our review paper is to examine many existing works of literature presenting the different methods utilized for diabetic retinopathy (DR) recognition employing deep learning (DL) and machine learning (ML) techniques, and also to address the difficulties faced in various datasets used by DR. Approach: DR is a progressive illness and may become a reason for vision loss. Early identification of DR lesions is, therefore, helpful and prevents damage to the retina. However, it is a complex job in view of the fact that it is symptomless earlier, and also ophthalmologists have been needed in traditional approaches. Recently, automated identification of DR-based studies has been stated based on image processing, ML, and DL. We analyze the recent literature and provide a comparative study that also includes the limitations of the literature and future work directions. Results: A relative analysis among the databases used, performance metrics employed, and ML and DL techniques adopted recently in DR detection based on various DR features is presented. Conclusion: Our review paper discusses the methods employed in DR detection along with the technical and clinical challenges that are encountered, which is missing in existing reviews, as well as future scopes to assist researchers in the field of retinal imaging.

Barriers in establishing systematic diabetic retinopathy screening through telemedicine in low- and middle-income countries

Vision-threatening diabetic retinopathy (VTDR) is one of the leading causes of impaired vision in the working-age population. Early identification, timely diagnosis, and prompt treatment of VTDR have to be tackled simultaneously to reduce the rate of blindness due to this condition. Considerable emphasis has been placed globally on establishing diabetic retinopathy screening (DRS) programs to enable early identification and referral of VTDR for treatment. However, there is an urgent need to shift from the common practice of opportunistic screening to a systematic DRS pathway to ensure that individuals with diabetes are screened at regular intervals and treated appropriately. While systematic DRS programs have been successfully established in countries such as the United Kingdom (UK), it continues to be a challenge to initiate and sustain such programs in low- and middle-income countries (LMIC), home to approximately 80% of people with diabetes. Telemedicine is widely recognized as an ideal DRS screening program. Although it has resulted in an upsurge of opportunistic screening, systematic recall of screened patients remains a challenge. In addition, the link between referred patients from the telemedicine programs to treatment centers is often not established or has failed to deliver; so, there is minimal impact of these telemedicine programs on VTDR blindness at present. This review covers the various barriers of establishing and sustaining systematic telemedicine DRS programs, especially in resource-constrained settings, and the challenges in aligning telemedicine to VTDR treatment pathways to ensure patients with VTDR are treated promptly and effectively.

Selfie fundus imaging for diabetic retinopathy screening

Background

Regular screening for retinopathy and timely intervention reduces blindness from diabetes by 90%. Screening is currently dependent on the interpretation of images captured by trained technicians. Inherent barriers of accessibility and affordability with this approach impede widespread success of retinopathy screening programs. Herein, we report our observations on the potential of a novel approach, Selfie Fundus Imaging (SFI), to enhance diabetic retinopathy screening.

Methods

The study was undertaken over a two-month period during COVID 19 lockdown. 60 diabetic patients participated in the study. Retinal images were captured using three different approaches, handheld smartphone-based photographs captured by patients themselves after a short video-assisted training session (SFI group), and smartphone-based photographs captured by a trained technician and photographs taken on desktop conventional digital fundus camera (Gold standard). Sensitivity and kappa statistics was determined for retinopathy and macular oedema grading.

Findings

Mean age of the study participants was 52.4 years ± 9.8 years and 78% were men. Of 120 images captured using SFI, 90% were centred-gradable, 8% were decentred-gradable and 2% were ungradable. 82% patients captured the image within a minute (majority by 31–45 s). The sensitivity of SFI to detect diabetic retinopathy was 88.39%. Agreement between SFI grading and standard fundus photograph grading was 85.86% with substantial kappa (0.77). For the detection of diabetic macular oedema, the agreement between SFI images and standard images was 93.67, with almost perfect kappa (0.91).

Conclusion

Fundus images were captured by patients using SFI without major difficulty and were comparable to images taken by trained specialist. With greater penetrance, advances, and availability of mobile photographic technology, we believe that SFI would positively impact the success of diabetic retinopathy screening programs by breaking the barriers of availability, accessibility, and affordability. SFI could ensure continuation of screening schedules for diabetic retinopathy, even in the face a highly contagious pandemic.

Fenofibrate increases circulating haematopoietic stem cells in people with diabetic retinopathy: a randomised, placebo-controlled trial

AIM/HYPOTHESIS

In two large RCTs, fenofibrate reduced the progression of diabetic retinopathy. We investigated whether fenofibrate increases circulating haematopoietic stem/progenitor cells (HSPCs), which have vascular properties and have been shown to protect from retinopathy.

METHODS

We conducted a 12 week parallel-group RCT comparing fenofibrate vs placebo. Patients with diabetic retinopathy and without other conditions that would affect HSPCs were enrolled at a tertiary diabetes outpatient clinic and randomised to receive fenofibrate or placebo based on a computer-generated sequence. Patients and study staff assessing the outcomes were blinded to group assignment. The primary endpoint was the change in the levels of circulating HSPCs, defined by expression of the stem cell markers CD34 and/or CD133. Secondary endpoints were the changes in endothelial progenitor cells, lipids, soluble mediators and gene expression. We used historical data on the association between HSPCs and retinopathy outcomes to estimate the effect of fenofibrate on retinopathy progression.

RESULTS

Forty-two participants with diabetic retinopathy were randomised and 41 completed treatment and were analysed (20 in the placebo group and 21 in the fenofibrate group). Mean age was 57.4 years, diabetes duration was 18.2 years and baseline HbA_1c was 60 mmol/mol (7.6%). When compared with placebo, fenofibrate significantly increased levels of HSPCs expressing CD34 and/or CD133. CD34⁺ HSPCs non-significantly declined in the placebo group (mean ± SD -44.2 ± 31.6 cells/10⁶) and significantly increased in the fenofibrate group (53.8 ± 31.1 cells/10⁶). The placebo-subtracted increase in CD34⁺ HSPCs from baseline was 30% (99.3 ± 43.3 cells/10⁶; p = 0.027) which, projected onto the relationship between HSPC levels and retinopathy outcomes, yielded an OR of retinopathy progression of 0.67 for fenofibrate vs placebo. Endothelial differentiation of CD34⁺ cells, estimated by the %KDR (kinase insert domain receptor) expression, was significantly reduced by fenofibrate. Fenofibrate decreased serum triacylglycerols, but the change in triacylglycerols was unrelated to the change in HSPCs. No effect was observed for endothelial progenitor cells, cytokines/chemokines (stromal-cell derived factor-1, vascular endothelial growth factor, monocyte chemoattractant protein-1) and gene expression in peripheral blood mononuclear cells.

CONCLUSIONS/INTERPRETATION

Fenofibrate increased HSPC levels in participants with diabetic retinopathy and this mechanism may explain why fenofibrate reduced retinopathy progression in previous studies.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01927315.

Dapagliflozin increases retinal thickness in type 2 diabetic patients as compared with glibenclamide: A randomized controlled trial

AIM

In patients with type 2 diabetes mellitus (T2DM) a progressive thinning in the central retinal thickness (CRT) is mainly related to neuroretinal degeneration and occurs before the decline in visual acuity or capillary density. We investigated the change in CRT by optical coherence tomography (OCT) in T2DM patients after 12 weeks of treatment with dapagliflozin or glibenclamide.

METHODS

Ninety-seven patients (57 ± 7 years) with T2DM and clinical or subclinical atherosclerosis were randomized 1:1 to dapagliflozin (10 mg/day) or glibenclamide (5 mg/day) on top of metformin XR 1.5 g/day. OCT was obtained in all patients enrolled in the study, both at the time of randomization and at the end of the study.

RESULTS

Baseline and post-treatment values of fasting glucose and glycated hemoglobin were equivalent in the two arms. There was no difference in change in diabetic retinopathy status after therapy. The center subfield thickness changed by +2(6)μm in the dapagliflozin group and by -1(7) μm in the glibenclamide group (P = 0.001).

CONCLUSION

A short-term treatment with dapagliflozin may increase CRT as compared with equivalent glycemic control with glibenclamide.

Vision impairment and differential access to eye health services in Aotearoa New Zealand: protocol for a scoping review

INTRODUCTION

In Aotearoa New Zealand, Māori and Pacific people experience worse health outcomes compared with other New Zealanders. No population-based eye health survey has been conducted, and eye health services do not generate routine monitoring reports, so the extent of eye health inequality is unknown. This information is required to plan equitable eye health services. Here we outline the protocol for a scoping review to report the nature and extent of the evidence reporting vision impairment, and the use of eye health services by ethnicity in New Zealand.

METHODS AND ANALYSIS

An information specialist will conduct searches on MEDLINE and Embase, with no limit on publication dates or language. We will search the grey literature via websites of relevant government and service provider agencies. Reference lists of included articles will be screened. Observational studies will be included if they report the prevalence of vision impairment, or any of the main causes (cataract, uncorrected refractive error, macular degeneration, glaucoma or diabetic retinopathy) or report the use of eye health services in New Zealand among people of any age. Two authors will independently review titles, abstracts and full-text articles, and complete data extraction. Overall findings will be summarised using descriptive statistics and thematic analysis, with an emphasis on disaggregation by ethnicity where this information is available.

ETHICS AND DISSEMINATION

Ethical approval has not been sought as our review will only include published and publicly accessible data. We will publish the review in an open access peer-reviewed journal. We anticipate the findings will be useful to organisations and providers in New Zealand responsible to plan and deliver eye care services, as well as stakeholders in other countries with differential access to eye care.

REGISTRATION DETAILS

The protocol has been registered with Open Science Framework (https://osf.io/yw7xb).

Hu-Zhang-Qing-Mai-Yin Inhibits Proliferation of Human Retinal Capillary Endothelial Cells Exposed to High Glucose

Background: Diabetic retinopathy (DR) is one of the serious complications of diabetes and an important cause of blindness. Despite much research on the pathogenesis of DR, there is still a lack of safe and effective treatment methods. Hu-zhang-qing-mai-yin (HZQMY), a Chinese medicine formula, has been clinically used in the safe and effective treatment of DR for many years. However, the systematic pharmacological research is lacking. The aim of this study was to evaluate the anti-DR effects of HZQMY and explore the possible mechanism involved. Methods: The constituents of HZQMY were analyzed by LC-MS/MS. DR model was established by high glucose simulation on human retinal capillary endothelial cells (HRCECs) in vitro. The cell viability, cell proliferation, cell apoptosis, and tube formation were assessed. Subsequently the related mechanisms were analyzed by assays for JC-1 mitochondrial membrane potential (MMP), intracellular ROS, ATP, western blot and proteomics. Results: 27 main chemical components contained in HZQMY were identified. HZQMY significantly inhibited the viability and proliferation of HRCECs exposed to high glucose, and promoted the apoptosis. In addition, HZQMY also boosted the release of ROS and suppressed tube formation of HRCECs under high glucose exposure. Meanwhile, HRCECs treated with high glucose released more ROS than normal cells, which could be markedly inhibited by HZQMY in a dose-dependent manner. Additionally, western blot assay indicated that HZQMY increased the expression of proteins related to the P38 signaling pathway and inhibited nuclear factor kappa-B (NF-κB) pathway. Proteomic analysis predicted that HSPA4, MAPK3, ENO1, EEF2 and ERPS may be the candidate targets of HZQMY in HRCECs. Conclusions: HZQMY inhibited the proliferation and promoted the Mitochondria related apoptosis of HRCECs exposed to high glucose possibly through regulating P38 and NF-κB signaling pathway.

Neurovascular Unit: A New Target for Treating Early Stages of Diabetic Retinopathy

The concept of diabetic retinopathy as a microvascular disease has evolved and is now considered a more complex diabetic complication in which neurovascular unit impairment plays an essential role and, therefore, can be considered as a main therapeutic target in the early stages of the disease. However, neurodegeneration is not always the apparent primary event in the natural story of diabetic retinopathy, and a phenotyping characterization is recommendable to identify those patients in whom neuroprotective treatment might be of benefit. In recent years, a myriad of treatments based on neuroprotection have been tested in experimental models, but more interestingly, there are drugs with a dual activity (neuroprotective and vasculotropic). In this review, the recent evidence concerning the therapeutic approaches targeting neurovascular unit impairment will be presented, along with a critical review of the scientific gaps and problems which remain to be overcome before our knowledge can be transferred to clinical practice.

Subclinical Hypothyroidism in Patients with Diabetic Retinopathy: Role of Vascular Endothelial Growth Factor

BACKGROUND

Considering the vital role of vascular endothelial growth factor (VEGF) in the development of diabetic retinopathy (DR) in one hand and the frequent association between subclinical hypothyroidism (SCH) and DR on the other hand.

OBJECTIVE

The present study was proposed to explore the possible role of VEGF in the relation between SCH and DR, thus we investigated the relation between SCH and VEGF levels in patients with DR.

METHODS

Two hundred patients with DR were recruited in this study [100 patients with proliferative diabetic retinopathy (PDR) and 100 patients with non-proliferative diabetic retinopathy (NPDR)]. Patients with DR were divided into 2 groups according to thyroid function: patients with SCH or those with euthyroidism. Patients were subjected to careful history taking, and underwent clinical and ophthalmological examination. Fasting blood glucose, glycosylated hemoglobin, fasting insulin, homeostasis model assessment of insulin resistance (HOMA-IR), TSH, FT4, FT3, VEGF and thyroid volume were assessed Results: Among all the studied patients, 21.5% (43/200) had SCH. DR patients with SCH had higher age, diabetes duration, HbA1c, HOMA-IR and VEGF than those with euthyroidism. The frequency of PDR in patients with SCH was 72.1% (31/43) and 43.9% (69/157) in those with euthyroidism, whereas the frequency of NPDR in patients with SCH was 27.9 (12/43) and 56.1% (88/157) in those with euthyroidism (P < 0.003). In multivariate analysis, PDR, HOMA-IR and VEGF levels were the significant predictor variables of SCH.

CONCLUSIONS

Increased VEGF levels may be implicated in the relationship between SCH and DR.

Retinal vascular geometry detection as a biomarker in diabetes mellitus

OBJECTIVE

To compare the vessel geometry characteristics of color fundus photographs in normal control and diabetes mellitus (DM) patients and to find potential biomarkers for early diabetic retinopathy (DR) based on a neural network vessel segmentation system and automated vascular geometry parameter analysis software.

METHODS

A total of 102 consecutive patients with type 2 DM (T2DM) and 132 healthy controls were recruited. All participants underwent general ophthalmic examinations, and retinal fundus photographs were taken with a digital fundus camera without mydriasis. Color fundus photographs were input into a dense-block generative adversarial network (D-GAN)-assisted retinal vascular segmentation system (http://www.gdcerc.cn:8081/#/login) to obtain binary images. These images were then analyzed by customized software (ocular microvascular analysis system V2.9.1) for automatic processing of vessel geometry parameters, including the monofractal dimension (D_box), multifractal dimension (D₀), vessel area ratio (R), max vessel diameter (d_max), average vessel diameter (d_ave), arc-chord ratio (A/C), and tortuosity (τ_n). Geometric differences between the healthy subjects and DM patients were analyzed. Then, regression analysis and receiver operating characteristic (ROC) curve analysis were performed to evaluate the diagnostic efficiency of the vascular geometry parameters.

RESULTS

No significant differences were observed between the baseline characteristics of each group. DM patients had lower D_box and D₀ values (1.330 ± 0.041; 1.347 ± 0.038) than healthy subjects (1.343 ± 0.048, p < 0.05; 1.362 ± 0.042, p < 0.05) and showed increasing values of d_max, d_ave, A/C, and τ_n compared with normal controls, although only the differences in d_ave and τ_n between the groups were statistically significant. In the regression analysis, d_ave and τ_n showed a good correlation with diabetes (d_ave, OR 1.765, 95% CI 1.319-2.362, p < 0.001; τ_n, OR 9.323, 95% CI 1.492-58.262, p < 0.05).

CONCLUSIONS

We demonstrated the relationship between retinal vascular geometry and the process in DM patients, showing that D_box, D₀, d_ave, and τ_n may be indicators of morphological changes in retinal vessels in DM patients and can be early biomarkers of DR.

A Systematic Review of Carotenoids in the Management of Diabetic Retinopathy

Diabetic retinopathy, which was primarily regarded as a microvascular disease, is the leading cause of irreversible blindness worldwide. With obesity at epidemic proportions, diabetes-related ocular problems are exponentially increasing in the developed world. Oxidative stress due to hyperglycemic states and its associated inflammation is one of the pathological mechanisms which leads to depletion of endogenous antioxidants in retina in a diabetic patient. This contributes to a cascade of events that finally leads to retinal neurodegeneration and irreversible vision loss. The xanthophylls lutein and zeaxanthin are known to promote retinal health, improve visual function in retinal diseases such as age-related macular degeneration that has oxidative damage central in its etiopathogenesis. Thus, it can be hypothesized that dietary supplements with xanthophylls that are potent antioxidants may regenerate the compromised antioxidant capacity as a consequence of the diabetic state, therefore ultimately promoting retinal health and visual improvement. We performed a comprehensive literature review of the National Library of Medicine and Web of Science databases, resulting in 341 publications meeting search criteria, of which, 18 were found eligible for inclusion in this review. Lutein and zeaxanthin demonstrated significant protection against capillary cell degeneration and hyperglycemia-induced changes in retinal vasculature. Observational studies indicate that depletion of xanthophyll carotenoids in the macula may represent a novel feature of DR, specifically in patients with type 2 or poorly managed type 1 diabetes. Meanwhile, early interventional trials with dietary carotenoid supplementation show promise in improving their levels in serum and macular pigments concomitant with benefits in visual performance. These findings provide a strong molecular basis and a line of evidence that suggests carotenoid vitamin therapy may offer enhanced neuroprotective effects with therapeutic potential to function as an adjunct nutraceutical strategy for management of diabetic retinopathy.

Maturation and Protection Effect of Retinal Tissue-Derived Bioink for 3D Cell Printing Technology

Retinal degeneration is a leading cause of incurable vision loss and blindness. The increasing incidence of retinal degeneration has triggered research into the development of in vitro retinal models for drug development and retinal alternatives for transplantation. However, the complex retinal structure and the retinal microenvironment pose serious challenges. Although 3D cell printing technology has been widely used in tissue engineering, including in vitro model development and regeneration medicine, currently available bioinks are insufficient to recapitulate the complex extracellular matrix environment of the retina. Therefore, in this study, we developed a retinal decellularized extracellular matrix (RdECM) from the porcine retina and evaluated its characteristics. The RdECM conserved the ECM components from the native retina without cellular components. Then, we mixed the RdECM with collagen to form a bioink and confirmed its suitability for 3D cell printing. We further studied the effect of the RdECM bioink on the differentiation of Muller cells. The retinal protective effect of the RdECM bioink was confirmed through a retinal degeneration animal model. Thus, we believe that the RdECM bioink is a promising candidate for retinal tissue engineering.

Diabetic Retinopathy Screening and Registration in Europe-Narrative Review

Diabetic retinopathy (DR) is a leading cause of preventable vision impairment and blindness in the European Region. Despite the fact that almost all European countries have some kind of prophylactic eye examination for people with diabetes, the examinations are not properly arranged and are not organized according to the principles of screening in medicine. In 2021, the current COVID-19 pandemic moved telemedicine to the forefront healthcare services. Due to that, a lot more patients could benefit from comfortable and faster access to ophthalmology specialist care. This study aimed to conduct a narrative literature review on current DR screening programs and registries in the European Union for the last 20 years. With the implementation of telemedicine in daily medical practice, performing screening programs became much more attainable. Remote assessment of retinal pictures simultaneously saves countries time, money, and other resources.

Reduced Levels of Drp1 Protect against Development of Retinal Vascular Lesions in Diabetic Retinopathy

High glucose (HG)-induced Drp1 overexpression contributes to mitochondrial dysfunction and promotes apoptosis in retinal endothelial cells. However, it is unknown whether inhibiting Drp1 overexpression protects against the development of retinal vascular cell loss in diabetes. To investigate whether reduced Drp1 level is protective against diabetes-induced retinal vascular lesions, four groups of mice: wild type (WT) control mice, streptozotocin (STZ)-induced diabetic mice, Drp1^+/− mice, and STZ-induced diabetic Drp1^+/− mice were examined after 16 weeks of diabetes. Western Blot analysis indicated a significant increase in Drp1 expression in the diabetic retinas compared to those of WT mice; retinas of diabetic Drp1^+/− mice showed reduced Drp1 level compared to those of diabetic mice. A significant increase in the number of acellular capillaries (AC) and pericyte loss (PL) was observed in the retinas of diabetic mice compared to those of the WT control mice. Importantly, a significant decrease in the number of AC and PL was observed in retinas of diabetic Drp1^+/− mice compared to those of diabetic mice concomitant with increased expression of pro-apoptotic genes, Bax, cleaved PARP, and increased cleaved caspase-3 activity. Preventing diabetes-induced Drp1 overexpression may have protective effects against the development of vascular lesions, characteristic of diabetic retinopathy.

Vamos E, Molina G, Sivaprasad S. Associations between attainment of incentivized primary care indicators and incident sight-threatening diabetic retinopathy in England: A population-based historical cohort study

AIM

To examine the impact of attainment of primary care diabetes clinical indicators on progression to sight-threatening diabetic retinopathy (STDR) among those with mild non-proliferative diabetic retinopathy (NPDR).

MATERIALS AND METHODS

An historical cohort study of 18,978 adults (43.63% female) diagnosed with type 2 diabetes before 1 April 2010 and mild NPDR before 1 April 2011 was conducted. The data were obtained from the UK Clinical Practice Research Datalink during 2010-2017, provided by 330 primary care practices in England. Exposures included attainment of the Quality and Outcomes Framework HbA1c (≤59 mmol/mol [≤7.5%]), blood pressure (≤140/80 mmHg) and cholesterol (≤5 mmol/L) indicators in the financial year 2010-2011, as well as the number of National Diabetes Audit processes completed in 2010-2011. The outcome was time to incident STDR. Nearest neighbour propensity score matching was undertaken, and univariable and multivariable Cox proportional hazards models were then fitted using the matched samples. Concordance statistics were calculated for each model.

RESULTS

A total of 1037 (5.5%) STDR diagnoses were observed over a mean follow-up of 3.6 (SD 2.0) years. HbA1c, blood pressure and cholesterol indicator attainment were associated with lower rates of STDR (adjusted hazard ratios [95% CI] 0.64 [0.55-0.74; p < .001], 0.83 [0.72-0.94; p = .005] and 0.80 [0.66-0.96; p = .015], respectively).

CONCLUSIONS

Our findings provide support for meeting appropriate indicators for the management of type 2 diabetes in primary care to bring a range of benefits, including improved health outcomes-such as a reduction in the risk of STDR-for people with type 2 diabetes.

Opa1 Deficiency Promotes Development of Retinal Vascular Lesions in Diabetic Retinopathy

This study investigates whether reduced optic atrophy 1 (Opa1) level promotes apoptosis and retinal vascular lesions associated with diabetic retinopathy (DR). Four groups of mice: wild type (WT) control mice, streptozotocin (STZ)-induced diabetic mice, Opa1^+/- mice, and diabetic Opa1^+/- mice were used in this study. 16 weeks after diabetes onset, retinas were assessed for Opa1 and Bax levels by Western blot analysis, and retinal networks were examined for acellular capillaries (AC) and pericyte loss (PL). Apoptotic cells were detected in retinal capillaries using TUNEL assay, and caspase-3 activity was assessed using fluorometric analysis. Opa1 expression was significantly downregulated in retinas of diabetic and Opa1^+/- mice compared with those of WT mice. Inducing diabetes further decreased Opa1 expression in retinas of Opa1^+/- mice. Increased cytochrome c release concomitant with increased level of pro-apoptotic Bax and elevated caspase-3 activity were observed in retinas of diabetic and Opa1^+/- mice; the number of TUNEL-positive cells and AC/PL was also significantly increased. An additional decrease in the Opa1 level in retinas of diabetic Opa1^+/- mice exacerbated the development of apoptotic cells and AC/PL compared with those of diabetic mice. Diabetes-induced Opa1 downregulation contributes, at least in part, to the development of retinal vascular lesions characteristic of DR.

Risk of Blindness Among Patients With Diabetes and Newly Diagnosed Diabetic Retinopathy

OBJECTIVE

To evaluate the association between initial diabetic retinopathy (DR) severity/risk of blindness in patients with newly diagnosed DR/good vision in the U.S.

RESEARCH DESIGN AND METHODS

This retrospective cohort study evaluated adult patients with good vision (20/40 or better) and newly diagnosed DR between 1 January 2013 and 31 December 2017 (index date) in the American Academy of Ophthalmology's Intelligent Research in Sight (IRIS) Registry. The primary exposure of interest was DR severity at index: mild nonproliferative DR (NPDR), moderate NPDR, severe NPDR, and proliferative DR (PDR). The main outcome measure was development of sustained blindness (SB), defined as study eyes with Snellen visual acuity readings of 20/200 or worse at two separate visits ≥3 months apart that did not improve beyond 20/100.

RESULTS

Among 53,535 eligible eyes (mean follow-up 662.5 days), 678 (1.3%) eyes developed SB. Eyes with PDR at index represented 10.5% (5,629 of 53,535) of the analysis population but made up 26.5% (180 of 678) of eyes that developed SB. Kaplan-Meier analysis revealed that eyes with moderate NPDR, severe NPDR, and PDR at index were 2.6, 3.6, and 4.0 times more likely, respectively, to develop SB after 2 years of DR diagnosis versus eyes with mild DR at index. In a Cox proportional hazards model adjusted for index characteristics/development of ocular conditions during follow-up, eyes with PDR had an increased risk of developing SB versus eyes with mild NPDR at index (hazard ratio 2.26 [95% CI 2.09-2.45]).

CONCLUSIONS

In this longitudinal ophthalmologic registry population involving eyes with good vision, more advanced DR at first diagnosis was a significant risk factor for developing SB.

Application of Deep Learning for Diagnosing, Classifying, and Treating Age-Related Macular Degeneration

Age-related macular degeneration (AMD) affects nearly 200 million people and is the third leading cause of irreversible vision loss worldwide. Deep learning, a branch of artificial intelligence that can learn image recognition based on pre-existing datasets, creates an opportunity for more accurate and efficient diagnosis, classification, and treatment of AMD on both individual and population levels. Current algorithms based on fundus photography and optical coherence tomography imaging have already achieved diagnostic accuracy levels comparable to human graders. This accuracy can be further increased when deep learning algorithms are simultaneously applied to multiple diagnostic imaging modalities. Combined with advances in telemedicine and imaging technology, deep learning can enable large populations of patients to be screened than would otherwise be possible and allow ophthalmologists to focus on seeing those patients who are in need of treatment, thus reducing the number of patients with significant visual impairment from AMD.

Predicting Keratoconus Progression and Need for Corneal Crosslinking Using Deep Learning

We aimed to predict keratoconus progression and the need for corneal crosslinking (CXL) using deep learning (DL). Two hundred and seventy-four corneal tomography images taken by Pentacam HR^® (Oculus, Wetzlar, Germany) of 158 keratoconus patients were examined. All patients were examined two times or more, and divided into two groups; the progression group and the non-progression group. An axial map of the frontal corneal plane, a pachymetry map, and a combination of these two maps at the initial examination were assessed according to the patients’ age. Training with a convolutional neural network on these learning data objects was conducted. Ninety eyes showed progression and 184 eyes showed no progression. The axial map, the pachymetry map, and their combination combined with patients’ age showed mean AUC values of 0.783, 0.784, and 0.814 (95% confidence interval (0.721–0.845) (0.722–0.846), and (0.755–0.872), respectively), with sensitivities of 87.8%, 77.8%, and 77.8% ((79.2–93.7), (67.8–85.9), and (67.8–85.9)) and specificities of 59.8%, 65.8%, and 69.6% ((52.3–66.9), (58.4–72.6), and (62.4–76.1)), respectively. Using the proposed DL neural network model, keratoconus progression can be predicted on corneal tomography maps combined with patients’ age.

A Novel Tree Shrew Model of Diabetic Retinopathy

Existing animal models with rod-dominant retinas have shown that hyperglycemia injures neurons, but it is not yet clearly understood how blue cone photoreceptors and retinal ganglion cells (RGCs) deteriorate in patients because of compromised insulin tolerance. In contrast, northern tree shrews (Tupaia Belangeri), one of the closest living relatives of primates, have a cone-dominant retina with short wave sensitivity (SWS) and long wave sensitivity (LWS) cones. Therefore, we injected animals with a single streptozotocin dose (175 mg/kg i.p.) to investigate whether sustained hyperglycemia models the features of human diabetic retinopathy (DR). We used the photopic electroretinogram (ERG) to measure the amplitudes of A and B waves and the photopic negative responses (PhNR) to evaluate cone and RGC function. Retinal flat mounts were prepared for immunohistochemical analysis to count the numbers of neurons with antibodies against cone opsins and RGC specific BRN3a proteins. The levels of the proteins TRIB3, ISR-1, and p-AKT/p-mTOR were measured with western blot. The results demonstrated that tree shrews manifested sustained hyperglycemia leading to a slight but significant loss of SWS cones (12%) and RGCs (20%) 16 weeks after streptozotocin injection. The loss of BRN3a-positive RGCs was also reflected by a 30% decline in BRN3a protein expression. These were accompanied by reduced ERG amplitudes and PhNRs. Importantly, the diabetic retinas demonstrated increased expression of TRIB3 and level of p-AKT/p-mTOR axis but reduced level of IRS-1 protein. Therefore, a new non-primate model of DR with SWS cone and RGC dysfunction lays the foundation to better understand retinal pathophysiology at the molecular level and opens an avenue for improving the research on the treatment of human eye diseases.

The Indian Health Service Primary Care-Based Teleophthalmology Program for Diabetic Eye Disease Surveillance and Management

Background: Historically, fewer than half of American Indians and Alaska Natives (AI/AN) with diabetes received the annual diabetic retinopathy (DR) examination that is considered the minimum standard of care; this rate is similar to that of the general United States (U.S.) population with diabetes. Solution: The Indian Health Service-Joslin Vision Network (IHS-JVN) Teleophthalmology Program in 2000 to increase compliance with DR standards of care among AI/AN through validated, primary care-based telemedicine. The IHS-JVN provides remote diagnosis of DR severity, with a report including management recommendations that is returned to the patient's primary care provider. The program conforms with the American Telemedicine Association (ATA) Practice Guidelines for Ocular Telehealth-Diabetic Retinopathy. Outcomes: The IHS-JVN has been expanding incrementally since the first patients were recruited in 2000; this expansion coincides with large improvements in the annual DR examination rates reported as part of local, regional, and national regulatory compliance under the Government Performance and Results Act (GPRA). Currently, with 99 clinical implementations in 23 states, IHS-JVN is the largest primary care-based ATA validation category three telemedicine program in the U.S. Summary: This article describes the program's workflow, imaging and reading technologies, diagnostic protocols, reports to providers, training, quality assurance processes, and geographical distribution. In addition to its clinical use, the program has been utilized in research on utilization of diabetic eye care, cost-effectiveness, technology development, and DR epidemiology of the AI/AN population. Potential next steps for this program are discussed.

Modulation of Tmem135 Leads to Retinal Pigmented Epithelium Pathologies in Mice

Purpose

Aging is a critical risk factor for the development of retinal diseases, but how aging perturbs ocular homeostasis and contributes to disease is unknown. We identified transmembrane protein 135 (Tmem135) as a gene important for regulating retinal aging and mitochondrial dynamics in mice. Overexpression of Tmem135 causes mitochondrial fragmentation and pathologies in the hearts of mice. In this study, we examine the eyes of mice overexpressing wild-type Tmem135 (Tmem135 TG) and compare their phenotype to Tmem135 mutant mice.

Methods

Eyes were collected for histology, immunohistochemistry, electron microscopy, quantitative PCR, and Western blot analysis. Before tissue collection, electroretinography (ERG) was performed to assess visual function. Mouse retinal pigmented epithelium (RPE) cultures were established to visualize mitochondria.

Results

Pathologies were observed only in the RPE of Tmem135 TG mice, including degeneration, migratory cells, vacuolization, dysmorphogenesis, cell enlargement, and basal laminar deposit formation despite similar augmented levels of Tmem135 in the eyecup (RPE/choroid/sclera) and neural retina. We observed reduced mitochondria number and size in the Tmem135 TG RPE. ERG amplitudes were decreased in 365-day-old mice overexpressing Tmem135 that correlated with reduced expression of RPE cell markers. In Tmem135 mutant mice, RPE cells are thicker, smaller, and denser than their littermate controls without any signs of degeneration.

Conclusions

Overexpression and mutation of Tmem135 cause contrasting RPE abnormalities in mice that correlate with changes in mitochondrial shape and size (overfragmented in TG vs. overfused in mutant). We conclude proper regulation of mitochondrial homeostasis by TMEM135 is critical for RPE health.

Serum vaspin levels are positively associated with diabetic retinopathy in patients with type 2 diabetes mellitus

Aims/Introduction

Vaspin is linked to obesity and its metabolic abnormalities. However, the role of vaspin serum levels in diabetic retinopathy (DR) is unknown. In the present study, we investigated the association between serum levels of vaspin and both DR and vision‐threatening DR.

Materials and Methods

This was a cross‐sectional single‐center observational study from December 2018 to September 2019. We evaluated circulating serum levels of vaspin in 372 participants with type 2 diabetes. DR was screened through detailed ocular examination. DR patients were also divided two groups: vision‐threatening DR and non‐vision‐threatening DR. The relationship between vaspin and DR was investigated by univariate and multivariate logistic regression analyses, and the results are shown as odds ratios with 95% confidence intervals.

Results

The vaspin serum levels of 372 patients were obtained, with a median value of 1.50 ng/mL (interquartile range 0.94–2.18 ng/mL). The median age of those patients was 53 years (interquartile range 44–62 years), and 44.4% were women. Patients with DR and VDTR had significantly increased vaspin serum levels (P < 0.001 andP < 0.001). A multivariable regression model found that patients with high levels of vaspin were approximately 1.85‐fold (odds ratio for per unit increase 1.85, 95% confidence interval 1.43–2.55; P < 0.001) more likely to experience DR, and 3.76‐fold (odds ratio for per unit increase 3.76, 95% confidence interval 2.05–6.55; P < 0.001) more likely to experience VTDR. The predictive value of vaspin was stronger in women than in men.

Conclusion

Higher vaspin serum levels were associated with an increased risk of DR and VDTR in patients with type 2 diabetes, which showed that vaspin is an important indicator factor for DR.