Global Prevalence of Diabetic Retinopathy and Projection of Burden through 2045: Systematic Review and Meta-analysis

Analysis of independent risk factors for progression of different degrees of diabetic retinopathy as well as non-diabetic retinopathy among type 2 diabetic patients

Purpose

To study the independent risk factors for development of different degrees of diabetic retinopathy (DR) as well as non-DR (NDR) among type 2 diabetic patients.

Methods

This cross-sectional study included 218 patients with type 2 diabetes between January 2022 and June 2022. All the patients were divided into two groups: the DR group and the NDR group. The DR group was subdivided into the mild, moderate and severe non-proliferative DR (NPDR) group and the proliferative DR (PDR) group. Data recorded for all patients included age, gender, duration of diabetes, blood pressure, glycated hemoglobin (HbA1c), fasting blood glucose (FBG), blood lipids, best corrected visual acuity (BCVA), intraocular pressure (IOP), axial length (AL), anterior chamber depth (ACD), and renal function. Logistic regression methods were used to analyze the risk factors for DR.

Results

The prevalence of DR in type 2 diabetes was 28.44%. The duration of diabetes, age, mean arterial pressure (MAP), HbA1c, FBG, urinary albumin/creatinine ratio (UACR), BCVA, AL, and ACD were significantly different between the DR and the NDR groups (p < 0.05). Multivariate logistic regression analysis identified age, FBG, UACR, and AL as the independent risk factors for DR (OR = 0.843, 2.376, 1.049, 0.005; p = 0.034, 0.014, 0.016, p < 0.001).

Conclusion

Young age, short AL, higher levels of FBG and UACR were the independent risk factors for the progression of DR in type 2 diabetes.

Category weighted network and relation weighted label for diabetic retinopathy screening

Diabetic retinopathy (DR) is the primary cause of blindness in adults. Incorporating machine learning into DR grading can improve the accuracy of medical diagnosis. However, problems, such as severe data imbalance, persists. Existing studies on DR grading ignore the correlation between its labels. In this study, a category weighted network (CWN) was proposed to achieve data balance at the model level. In the CWN, a reference for weight settings is provided by calculating the category gradient norm and reducing the experimental overhead. We proposed to use relation weighted labels instead of the one-hot label to investigate the distance relationship between labels. Experiments revealed that the proposed CWN achieved excellent performance on various DR datasets. Furthermore, relation weighted labels exhibit broad applicability and can improve other methods using one-hot labels. The proposed method achieved kappa scores of 0.9431 and 0.9226 and accuracy of 90.94% and 86.12% on DDR and APTOS datasets, respectively.

Ophthalmic Solution of Smart Supramolecular Peptides to Capture Semaphorin 4D against Diabetic Retinopathy

Diabetic retinopathy (DR) is the leading cause of vision loss in working age population. Intravitreal injection of anti-VEGF antibody is widely used in clinical practice. However, about 27% of patients show poor response to anti-VEGF therapy and about 50% of these patients continue to have macular thickening. Frequent intravitreal injections of antibody may increase the chance of endophthalmitis and cause visual loss or even blindness once happened. Therefore, there is a greatly urgent need for novel noninvasive target to treat DR clinically. Here, the formulation of a smart supramolecular peptide (SSP) eye drop for DR treatment that is effective via specifically identifying and capturing soluble semaphorin 4D (sSema4D), a strongly pro-angiogenesis and exudates factor, is reported. The SSP nanostructures encapsulate sSema4D so that all biological effects mediated by three receptors of sSema4D are inhibited, thereby significantly alleviating pathological retinal angiogenesis and exudates in DR. Moreover, it is found that combination of SSPs eye drop and anti-VEGF injection shows better therapeutic effect over anti-VEGF treatment alone. Overall, SSP eye drop provide an alternative and effective method for noninvasive treatment for DR.

Neuroprotective effects of açaí (Euterpe oleracea Mart.) against diabetic retinopathy

Introduction: Diabetes mellitus describes a metabolic disorder of multiple etiologies, characterized by chronic hyperglycemia, which induces a series of molecular events capable of leading to microvascular damage, affecting the blood vessels of the retina, causing diabetic retinopathy. Studies indicate that oxidative stress plays a central role in complications involving diabetes. Açaí (Euterpe oleracea) has attracted much attention given its antioxidant capacity and potential associated health benefits in preventing oxidative stress, one of the causes of diabetic retinopathy. The objective of this work was to evaluate the possible protective effect of açaí (E. oleracea) on the retinal function of mice with induced diabetes, based on full field electroretinogram (ffERG). Methods: We opted for mouse models with induced diabetes by administration of a 2% alloxan aqueous solution and treatment with feed enriched with açaí pulp. The animals were divided into 4 groups: CTR (received commercial ration), DM (received commercial ration), DM + açaí (E. oleracea-enriched ration) and CTR + açaí (E. oleracea-enriched ration). The ffERG was recorded three times, 30, 45 and 60 days after diabetes induction, under scotopic and photopic conditions to access rod, mixed and cone responses, in addition to monitoring the weight and blood glucose of the animals during the study period. Statistical analysis was performed using the two-way ANOVA test with Tukey's post-test. Results: Our work obtained satisfactory results with the ffERG responses in diabetic animals treated with açaí, where it was observed that there was no significant decrease in the b wave ffERG amplitude of this group over time when compared to the results of the Diabetic group not treated with açaí, which showed a significant reduction of this ffERG component. Discussion: The results of the present study show, for the first time, that treatment with an açaí-enriched diet is effective against the decrease in the amplitude of visual electrophysiological responses in animals with induced diabetes, which opens a new horizon for the prevention of retinal damage in diabetic individuals from treatment with açaí base. However, it is worth mentioning that our findings consist of a preliminary study and further researches and clinical trials are needed to examine açaí potential as an alternative therapy for diabetic retinopathy.

Meta-analysis of Serum Vitamin B12 Levels and Diabetic Retinopathy in Type 2 Diabetes

BACKGROUND

Previous studies have shown an association between low serum vitamin B12 levels and the risk of diabetic retinopathy (DR) in type 2 diabetes, but the conclusions from various studies were inconsistent. Therefore, we collected relevant data from various databases to perform a meta-analysis and address the inconsistencies in these studies.

METHODS

We searched PubMed, Embase, Cochrane Library, CNKI, Wanfang and CQVIP for eligible studies published up to April 10, 2022, and performed a meta-analysis using Stata software to assess the association between serum vitamin B12 levels and DR.

RESULTS

A total of 15 studies were included in this meta-analysis. Statistical analysis showed that serum vitamin B12 levels were significantly reduced in patients with type 2 diabetic retinopathy ,WMD 95% CI = -68.91 (-76.76, -61.06) (p <0.00001, I² = 88.30%). In subgroup analyses by ethnicity, an association between low serum vitamin B12 levels and DR risk was found in East Asian, South Asian and mixed populations, but not in Caucasian populations.

CONCLUSIONS

This meta-analysis analyzed vitamin B12 in patients with type 2 diabetic retinopathy and emphasized the importance of monitoring serum vitamin B12 levels in patients with type 2 diabetic retinopathy, but this meta-analysis still has deficiencies and limitations, and more clinical studies are needed to confirm this conclusion in the future.

Diabetic Macular Edema and Diode Subthreshold Micropulse Laser: A Randomized Double-Masked Noninferiority Clinical Trial

PURPOSE

To determine clinical effectiveness, safety, and cost-effectiveness of subthreshold micropulse laser (SML), compared with standard laser (SL), for diabetic macular edema (DME) with central retinal thickness (CRT) < 400 μm.

DESIGN

Pragmatic, multicenter, allocation-concealed, double-masked, randomized, noninferiority trial.

PARTICIPANTS

Adults with center-involved DME < 400 μm and best-corrected visual acuity (BCVA) of > 24 Early Treatment Diabetic Retinopathy Study (ETDRS) letters in one/both eyes.

METHODS

Randomization 1:1 to 577 nm SML or SL treatment. Retreatments were allowed. Rescue with intravitreal anti-vascular endothelial growth factor therapies or steroids was permitted if 10 or more ETDRS letter loss occurred, CRT increased > 400 μm, or both.

MAIN OUTCOME MEASURES

Primary outcome was mean change in BCVA in the study eye at 24 months (noninferiority margin 5 ETDRS letters). Secondary outcomes were mean change from baseline to month 24 in binocular BCVA; CRT and mean deviation of Humphrey 10-2 visual field in the study eye; percentage meeting driving standards; EuroQoL EQ-5D-5L, 25-item National Eye Institute Visual Function Questionnaire (NEI-VFQ-25), and Vision and Quality of Life Index (VisQoL) scores; cost per quality-adjusted life-years (QALYs) gained; adverse effects; and number of laser and rescue treatments.

RESULTS

The study recruited fully (n = 266); 87% of SML-treated and 86% of SL-treated patients had primary outcome data. Mean ± standard deviation BCVA change from baseline to month 24 was -2.43 ± 8.20 letters and -0.45 ± 6.72 letters in the SML and SL groups, respectively. Subthreshold micropulse laser therapy was deemed not only noninferior but also equivalent to SL therapy because the 95% confidence interval (CI; -3.9 to -0.04 letters) lay wholly within both upper and lower margins of the permitted maximum difference (5 ETDRS letters). No statistically significant difference was found in binocular BCVA (0.32 ETDRS letters; 95% CI, -0.99 to 1.64 ETDRS letters; P = 0.63); CRT (-0.64 μm; 95% CI, -14.25 to 12.98 μm; P = 0.93); mean deviation of the visual field (0.39 decibels (dB); 95% CI, -0.23 to 1.02 dB; P = 0.21); meeting driving standards (percentage point difference, 1.6%; 95% CI, -25.3% to 28.5%; P = 0.91); adverse effects (risk ratio, 0.28; 95% CI, 0.06-1.34; P = 0.11); rescue treatments (percentage point difference, -2.8%; 95% CI, -13.1% to 7.5%; P = 0.59); or EQ-5D, NEI-VFQ-25, or VisQoL scores. Number of laser treatments was higher in the SML group (0.48; 95% CI, 0.18-0.79; P = 0.002). Base-case analysis indicated no differences in costs or QALYs.

CONCLUSIONS

Subthreshold micropulse laser therapy was equivalent to SL therapy, requiring slightly higher laser treatments.

Deep semi-supervised multiple instance learning with self-correction for DME classification from OCT images

Supervised deep learning has achieved prominent success in various diabetic macular edema (DME) recognition tasks from optical coherence tomography (OCT) volumetric images. A common problematic issue that frequently occurs in this field is the shortage of labeled data due to the expensive fine-grained annotations, which increases substantial difficulty in accurate analysis by supervised learning. The morphological changes in the retina caused by DME might be distributed sparsely in B-scan images of the OCT volume, and OCT data is often coarsely labeled at the volume level. Hence, the DME identification task can be formulated as a multiple instance classification problem that could be addressed by multiple instance learning (MIL) techniques. Nevertheless, none of previous studies utilize unlabeled data simultaneously to promote the classification accuracy, which is particularly significant for a high quality of analysis at the minimum annotation cost. To this end, we present a novel deep semi-supervised multiple instance learning framework to explore the feasibility of leveraging a small amount of coarsely labeled data and a large amount of unlabeled data to tackle this problem. Specifically, we come up with several modules to further improve the performance according to the availability and granularity of their labels. To warm up the training, we propagate the bag labels to the corresponding instances as the supervision of training, and propose a self-correction strategy to handle the label noise in the positive bags. This strategy is based on confidence-based pseudo-labeling with consistency regularization. The model uses its prediction to generate the pseudo-label for each weakly augmented input only if it is highly confident about the prediction, which is subsequently used to supervise the same input in a strongly augmented version. This learning scheme is also applicable to unlabeled data. To enhance the discrimination capability of the model, we introduce the Student-Teacher architecture and impose consistency constraints between two models. For demonstration, the proposed approach was evaluated on two large-scale DME OCT image datasets. Extensive results indicate that the proposed method improves DME classification with the incorporation of unlabeled data and outperforms competing MIL methods significantly, which confirm the feasibility of deep semi-supervised multiple instance learning at a low annotation cost.

Diabetic Retinopathy – Diagnostics and Treatment Guidelines

Diabetic retinopathy is one of the most common complications of diabetes mellitus and represents a serious health, social and economic problem. With the expected increase in the number of patients with diabetes, it is becoming the leading cause of severe vision loss in the working-age population.  The presented guidelines summarize the current knowledge about this disease in order to standardize and update the procedures for the diagnosis, classification and treatment of diabetic retinopathy.

A Nomogram for Predicting Vision-Threatening Diabetic Retinopathy Among Mild Diabetic Retinopathy Patients: A Case-Control and Prospective Study of Type 2 Diabetes

AIM

This study aims to develop a nomogram for predicting vision-threatening diabetic retinopathy (VTDR) in type 2 diabetes mellitus (T2DM) with mild non-proliferative diabetic retinopathy (NPDR) patients.

MATERIALS AND METHODS

In case-control analysis, 440 patients with mild NPDR or VTDR were enrolled to identify predictors and develop a nomogram. In the prospective cohort, 120 T2DM patients with mild NPDR were enrolled for external validation. Sensitivity, specificity, and area under the receiver operating characteristic (AUC) were calculated to evaluate the predictive performance of the nomogram.

RESULTS

In case-control analysis, 2-h C-peptide (OR = 0.85, 95% CI: 0.75 to 0.95, p = 0.006), sural nerve conduction impaired (SNCI) (mildly: OR = 2.18, 95% CI: 1.10 to 4.33, p = 0.026; moderately/severely: 3.66, 95% CI: 1.74 to 7.70, p < 0.001) and UACR (microalbuminuria: OR = 2.37, 95% CI: 1.25 to 4.48, p = 0.008; macroalbuminuria: 4.02, 95% CI: 1.61 to 10.06, p = 0.003) were identified as independent predictors. The concordance index of the prediction nomogram was 0.76 in the training set. In the test set, sensitivity, specificity, and AUC were 84.8%, 60.6%, and 0.73, respectively. In the prospective cohort, median follow-up period was 42 months, and 15 patients (12.5%) developed VTDR. Sensitivity, specificity, and AUC of prediction were 66.7%, 89.5%, and 0.75, respectively.

CONCLUSION

Introducing 2-h C-peptide, UACR, and SNCI, the nomogram demonstrated a good discriminatory power for predicting risk of VTDR in mild NPDR individuals.

Prevalence of diabetic retinopathy in patients with newly diagnosed type 2 diabetes: A systematic review and meta-analysis

AIMS

Type 2 diabetes mellitus (T2DM) can remain undiagnosed for many years, during which micro- and macro-vascular complications may develop. This study aimed to assess the worldwide prevalence of diabetic retinopathy (DR) in patients with newly diagnosed T2DM.

MATERIALS AND METHODS

We systematically searched electronic databases for relevant studies published from inception to 01 January 2022. Selected studies reported the prevalence of DR among patients with newly diagnosed T2DM, specifying the case definition used. Random-effects meta-analysis was used to derive the pooled prevalence. Subgroup and meta-regression analyses were used to investigate variations in the prevalence estimates in terms of available variables.

RESULTS

Data from 77 studies including 99,847 patients with newly diagnosed T2DM were included from 26 countries. The pooled prevalence of DR among patients with newly diagnosed T2DM was 13.1% (95% CI, 11.1%-15.1%; I²  = 97.0%). DR was higher in clinic-based samples compared with community-based samples (15.0%, 95% CI = 12.4%-17.8% vs. 11.5%, 95% CI = 8.9%-14.5%; p = 0.05; I²  = 97.0%) and was higher in countries in the WHO African 19.2% (95% CI, 14.6%-24.3%; I²  = 76.0%), South-East Asia 15.4% (95% CI, 10.0%-21.6%; I²  = 79.1%), and European 15.0% (95% CI, 11.2%-19.2%; I²  = 82.0%) regions. A higher proportion of female patients was significantly associated with a lower prevalence of DR in patients with newly diagnosed T2DM. We observed that the prevalence of DR in patients with newly diagnosed T2DM has remained unchanged over time.

CONCLUSIONS

Globally, DR is a prevalent complication among patients with newly diagnosed T2DM indicating the importance of establishing effective strategies to promote regular screening for the early diagnosis of T2DM alongside routine ophthalmic assessment at the time of T2DM diagnosis to reduce the burden of vision-threatening retinopathy.

Traumatic brain injury: Mechanisms, manifestations, and visual sequelae

Traumatic brain injury (TBI) results when external physical forces impact the head with sufficient intensity to cause damage to the brain. TBI can be mild, moderate, or severe and may have long-term consequences including visual difficulties, cognitive deficits, headache, pain, sleep disturbances, and post-traumatic epilepsy. Disruption of the normal functioning of the brain leads to a cascade of effects with molecular and anatomical changes, persistent neuronal hyperexcitation, neuroinflammation, and neuronal loss. Destructive processes that occur at the cellular and molecular level lead to inflammation, oxidative stress, calcium dysregulation, and apoptosis. Vascular damage, ischemia and loss of blood brain barrier integrity contribute to destruction of brain tissue. This review focuses on the cellular damage incited during TBI and the frequently life-altering lasting effects of this destruction on vision, cognition, balance, and sleep. The wide range of visual complaints associated with TBI are addressed and repair processes where there is potential for intervention and neuronal preservation are highlighted.

Proximity Extension Assay (PEA) Platform to Detect Vitreous Biomarkers of Diabetic Retinopathy

Diabetic retinopathy (DR) is one of the leading causes of blindness, affecting more than 100 million people worldwide. Currently, DR prognosis and management are based mainly on biomarkers identified by direct retinal fundus observation or by imaging devices. The use of molecular biology to discover biomarkers of DR has great potential to impact the standard of care, and the vitreous humor can serve as an indirect source for those molecular biomarkers because it is rich in proteins secreted by the retina. Proximity extension assay (PEA) is a technology that combines antibody-based immunoassays with DNA-coupled methodology to obtain information on the abundance of multiple proteins while using minimal sample volume, with high specificity and sensitivity. Matched antibodies labelled with a complementary sequence of oligonucleotides are used to simultaneously bind a target protein in solution, and when in proximity, the complementary sequences on each antibody hybridize, serving as template for DNA polymerase-dependent extension and the generation of a unique double-stranded DNA "barcode." PEA works well with vitreous matrix and has great potential to support the identification of novel predictive and prognostic biomarkers of DR.

Anomalies in neurovascular coupling during early diabetes: A review

Diabetic retinopathy is the most feared complication for those with diabetes. Although visible vascular pathology traditionally defines the management of this condition, it is now recognised that a range of cellular changes occur in the retina from an early stage of diabetes. One of the most significant functional changes that occurs in those with diabetes is a loss of vasoregulation in response to changes in neural activity. There are several retinal cell types that are critical for mediating so-called neurovascular coupling, including Müller cells, microglia and pericytes. Although there is a great deal of evidence that suggests that Müller cells are integral to regulating the vasculature, they only modulate part of the vascular tree, highlighting the complexity of vasoregulation within the retina. Recent studies suggest that retinal immune cells, microglia, play an important role in mediating vasoconstriction. Importantly, retinal microglia contact both the vasculature and neural synapses and induce vasoconstriction in response to neurally expressed chemokines such as fractalkine. This microglial-dependent regulation occurs via the vasomediator angiotensinogen. Diabetes alters the way microglia regulate the retinal vasculature, by increasing angiotensinogen expression, causing capillary vasoconstriction and contributing to a loss of vascular reactivity to physiological signals. This article summarises recent studies showing changes in vascular regulation during diabetes, the potential mechanisms by which this occurs and the significance of these early changes to the progression of diabetic retinopathy.

Optimizing treatment for diabetic macular edema during cataract surgery

Diabetic macular edema (DME) causes visual impairment in diabetic retinopathy (DR). Diabetes mellitus is a global epidemic and diabetic individuals are at risk of developing DR. Approximately 1 in 10 diabetic patients suffers from DME, which is the commonest cause of vision-threatening DR at primary-care screening. Furthermore, diabetes predisposes to a higher frequency and a younger onset of cataract, which further threatens vision in DME patients. Although cataract extraction is an effective cure, vision may still deteriorate following cataract surgery due to DME progression or recurrence, of which the risks are significantly higher than for patients without concurrent or previous history of DME at the time of operation. The management of pre-existing DME with visually significant cataract is a clinical conundrum. Deferring cataract surgery until DME is adequately treated is not ideal because of prolonged visual impairment and maturation of cataract jeopardizing surgical safety and monitoring of DR. On the other hand, the progression or recurrence of DME following prompt cataract surgery is a profound disappointment for patients and ophthalmic surgeons who had high expectations for postoperative visual improvement. Prescription of perioperative anti-inflammatory eye drops is effective in lowering the risk of new-onset DME after cataract surgery. However, management of concurrent DME at the time of cataract surgery is much more challenging because DME is unlikely to resolve spontaneously even with the aid of anti-inflammatory non-steroidal or steroid eye drops. A number of clinical trials using intravitreal injection of corticosteroids and anti-vascular endothelial growth factor (anti-VEGF) as first-line therapy have demonstrated safety and efficacy to treat DME. These drugs have also been administered perioperatively for the prevention of DME worsening in patients undergoing cataract surgery. This article reviews the scientific evidence to guide ophthalmologists on the efficacy and safety of various therapies for managing patients with DME who are particularly vulnerable to cataract surgery-induced inflammation, which disintegrates the blood-retinal barrier and egression of fluid in macular edema.

Protective effects of Scoparia dulcis L. extract on high glucose-induced injury in human retinal pigment epithelial cells

Diabetic retinopathy (DR) is a major cause of vision loss in diabetic patients. Hyperglycemia-induced oxidative stress and the accumulation of inflammatory factors result in blood-retinal barrier dysfunction and the pathogenesis of DR. Scoparia dulcis L. extract (SDE), a traditional Chinese medicine, has been recently recognized for its various pharmacological effects, including anti-diabetic, anti-hyperlipidemia, anti-inflammatory, and anti-oxidative activities. However, there is no relevant research on the protective effect of SDE in DR. In this study, we treated high glucose (50 mM) in human retinal epithelial cells (ARPE-19) with different concentrations of SDE and analyzed cell viability, apoptosis, and ROS production. Moreover, we analyzed the expression of Akt, Nrf2, catalase, and HO-1, which showed that SDE dose-dependently reduced ROS production and attenuated ARPE-19 cell apoptosis in a high-glucose environment. Briefly, we demonstrated that SDE exhibited an anti-oxidative and anti-inflammatory ability in protecting retinal cells from high-glucose (HG) treatment. Moreover, we also investigated the involvement of the Akt/Nrf2/HO-1 pathway in SDE-mediated protective effects. The results suggest SDE as a nutritional supplement that could benefit patients with DR.

Citation trends in ophthalmology articles and keywords in mainland China, Hong Kong, and Taiwan since 2013 using temporal bar graphs (TBGs): Bibliometric analysis

BACKGROUND

We selected authors from mainland China, Hong Kong, and Taiwan (CHT) to examine citation trends on articles and keywords. The existence of suitable temporal bar graphs (TBGs) for displaying citation trends is unknown. It is necessary to enhance the traditional TBGs to provide readers with more information about the citation trend. The purpose of this study was to propose an advanced TBG that can be applied to understand the most worth-reading articles by ophthalmology authors in the CHT.

METHODS

Using the search engine of the Web of Science core collection, we conducted bibliometric analyses to examine the article citation trends of ophthalmology authors in CHT since 2013. A total of 6695 metadata was collected from articles and review articles. Using radar plots, the Y-index, and the combining the Y-index with the CJAL scores (CJAL) scores, we could determine the dominance of publications by year, region, institute, journal, department, and author. A choropleth map, a dot plot, and a 4-quadrant radar plot were used to visualize the results. A TBG was designed and provided for readers to display citation trends on articles and keywords.

RESULTS

We found that the majority of publications were published in 2017 (2275), Shanghai city (935), Sun Yat-Sen University (China) (689), the international journal Ophthalmology (1399), the Department of Ophthalmology (3035), and the author Peizeng Yang (Chongqing) (65); the highest CAJL scores were also from Guangdong (2767.22), Sun Yat-Sen University (China) (2147.35), and the Ophthalmology Department (7130.96); the author Peizeng Yang (Chongqing) (170.16) had the highest CAJL; and the enhanced TBG features maximum counts and recent growth trends that are not included in traditional TBGs.

CONCLUSION

Using the Y-index and the CJAL score compared with research achievements of ophthalmology authors in CHT, a 4-quadrant radar plot was provided. The enhanced TBGs and the CJAL scores are recommended for future bibliographical studies.

Subthreshold Micropulse Laser for Diabetic Macular Edema: A Review

Diabetic macular edema (DME) is one of the main causes of visual impairment in patients of working age. DME occurs in 4% of patients at all stages of diabetic retinopathy. Using a subthreshold micropulse laser is an alternative or adjuvant treatment of DME. Micropulse technology demonstrates a high safety profile by selectively targeting the retinal pigment epithelium. There are no standardized protocols for micropulse treatment, however, a 577 nm laser application over the entire macula using a 200 μm retinal spot, 200 ms pulse duration, 400 mW power, and 5% duty cycle is a cost-effective, noninvasive, and safe therapy in mild and moderate macular edemas with retinal thickness below 400 μm. Micropulse lasers, as an addition to the current gold-standard treatment for DME, i.e., anti-vascular endothelial growth factor (anti-VEGF), stabilize the anatomic and functional retinal parameters 3 months after the procedure and reduce the number of required injections per year. This paper discusses the published literature on the safety and application of subthreshold micropulse lasers in DME and compares them with intravitreal anti-VEGF or steroid therapies and conventional grid laser photocoagulation. Only English peer-reviewed articles reporting research within the years 2010-2022 were included.

Novel Black Seed Polysaccharide Extract-g-Poly (Acrylate) pH-Responsive Hydrogel Nanocomposites for Safe Oral Insulin Delivery: Development, In Vitro, In Vivo and Toxicological Evaluation

Oral delivery of insulin has always been a challenging task due to harsh gut environment involving variable pH and peptidase actions. Currently, no Food and Drug Administration (FDA) approved oral insulin formulation is commercially available, only intravenous (IV) or subcutaneous (SC) routes. Therefore, it is really cumbersome for diabetic patients to go through invasive approaches for insulin delivery on daily basis. In the present study, a novel pH-responsive hydrogel nanocomposite (NC) system was developed and optimized for safe oral delivery of insulin. Black seed polysaccharide extract-based hydrogel (BA hydrogel) was formulated by free radical polymerization and loaded with insulin. Blank BA hydrogel was also incorporated with insulin-loaded montmorillonite nanoclay (Ins-Mmt) to form an Ins-Mmt-BA hydrogel NC and compared with the insulin-loaded hydrogel. Swelling, sol-gel analysis and in vitro release studies proved that Ins-Mmt-BA6 hydrogel NC has the best formulation, with 96.17% maximum insulin released in 24 h. Kinetic modeling applied on insulin release data showed the Korsemeyer-Peppas model (R2 = 0.9637) as the best fit model with a super case II transport mechanism for insulin transport (n > 0.89). Energy Dispersive X-ray (EDX) Spectroscopy, Fourier Transformed Infrared (FTIR) spectroscopy and Powdered X-ray diffraction (PXRD) analysis results also confirmed successful development of a hydrogel NC with no significant denaturation of insulin. Toxicity results confirmed the safety profile and biocompatibility of the developed NC. In vivo studies showed a maximum decrease in blood glucose levels of 52.61% and percentage relative bioavailability (% RBA) of 26.3% for an Ins-Mmt-BA hydrogel NC as compared to BA hydrogels and insulin administered through the SC route.

Aldosterone as a Possible Contributor to Eye Diseases

Aldosterone, an effector molecule of the renin-angiotensin-aldosterone system (RAAS), has been receiving more attention in the field of ophthalmology because of its possible role in the pathogenesis of various eye diseases or abnormalities; it may even become a target for their treatment. Primary aldosteronism, a typical model of a systemic aldosterone excess, may cause vision loss due to various ocular diseases, such as retinal vein occlusion, central serous chorioretinopathy, and, possibly glaucoma. RAAS components are present in various parts and types of cells present in the eye. Investigations of the local RAAS in various animal models of diabetic macular edema, retinal vein occlusion, retinopathy of prematurity, central serous chorioretinopathy, and glaucoma have found evidence that aldosterone or mineralocorticoid receptors may exacerbate the pathology of these disorders. Further studies are needed to elucidate whether the modulation of aldosterone or mineralocorticoid receptors is an effective treatment for preventing vision loss in patients with eye diseases.

Acylcarnitines in Ophthalmology: Promising Emerging Biomarkers

Several common ocular diseases are leading causes of irreversible visual impairment. Over the last decade, various mainly untargeted metabolic studies have been performed to show that metabolic dysfunction plays an important role in the pathogenesis of ocular diseases. A number of metabolites in plasma/serum, aqueous or vitreous humor, or in tears have been found to differ between patients and controls; among them are L-carnitine and acylcarnitines, which are essential for mitochondrial fatty acid oxidation. The metabolic profile of carnitines regarding a variety of diseases has attracted researchers' interest. In this review, we present and discuss recent advances that have been made in the identification of carnitines as potential metabolic biomarkers in common ocular diseases, such as age-related macular degeneration, diabetic retinopathy, retinopathy of prematurity, central retinal vein occlusion, primary open-angle glaucoma, rhegmatogenous retinal detachment, and dry eye syndrome.

Classification of diabetic retinopathy: Past, present and future

Diabetic retinopathy (DR) is a leading cause of visual impairment and blindness worldwide. Since DR was first recognized as an important complication of diabetes, there have been many attempts to accurately classify the severity and stages of disease. These historical classification systems evolved as understanding of disease pathophysiology improved, methods of imaging and assessing DR changed, and effective treatments were developed. Current DR classification systems are effective, and have been the basis of major research trials and clinical management guidelines for decades. However, with further new developments such as recognition of diabetic retinal neurodegeneration, new imaging platforms such as optical coherence tomography and ultra wide-field retinal imaging, artificial intelligence and new treatments, our current classification systems have significant limitations that need to be addressed. In this paper, we provide a historical review of different classification systems for DR, and discuss the limitations of our current classification systems in the context of new developments. We also review the implications of new developments in the field, to see how they might feature in a future, updated classification.

Keeping an eye on the diabetic foot: The connection between diabetic eye disease and wound healing in the lower extremity

Diabetic eye disease is strongly associated with the development of diabetic foot ulcers (DFUs). DFUs are a common and significant complication of diabetes mellitus (DM) that arise from a combination of micro- and macrovascular compromise. Hyperglycemia and associated metabolic dysfunction in DM lead to impaired wound healing, immune dysregulation, peripheral vascular disease, and diabetic neuropathy that predisposes the lower extremities to repetitive injury and progressive tissue damage that may ultimately necessitate amputation. Diabetic retinopathy (DR) is caused by cumulative damage to the retinal mic-rovasculature from hyperglycemia and other diabetes-associated factors. The severity of DR is closely associated with the development of DFUs and the need for lower extremity revascularization procedures and/or amputation. Like the lower extremity, the eye may also suffer end-organ damage from macrovascular compromise in the form of cranial neuropathies that impair its motility, cause optic neuropathy, or result in partial or complete blindness. Additionally, poor perfusion of the eye can cause ischemic retinopathy leading to the development of proliferative diabetic retinopathy or neovascular glaucoma, both serious, vision-threatening conditions. Finally, diabetic corneal ulcers and DFUs share many aspects of impaired wound healing resulting from neurovascular, sensory, and immunologic compromise. Notably, alterations in serum biomarkers, such as hemoglobin A1c, ceruloplasmin, creatinine, low-density lipoprotein, and high-density lipoprotein, are associated with both DR and DFUs. Monitoring these parameters can aid in prognosticating long-term outcomes and shed light on shared pathogenic mechanisms that lead to end-organ damage. The frequent co-occurrence of diabetic eye and foot problems mandate that patients affected by either condition undergo reciprocal comprehensive eye and foot evaluations in addition to optimizing diabetes management.

Integrated Metabolomics and Transcriptomics Reveal Metabolic Patterns in Retina of STZ-Induced Diabetic Retinopathy Mouse Model

Diabetic retinopathy (DR), as the leading cause of vision loss in the working-age population, exhibits unique metabolite profiles in human plasma and vitreous. However, those in retina are not fully understood. Here, we utilized liquid and gas chromatography-tandem mass spectrometry technology to explore metabolite characteristics of streptozotocin (STZ)-induced diabetic mice retina. A total of 145 metabolites differed significantly in diabetic retinas compared with controls. These metabolites are mainly enriched in the Warburg effect, and valine, leucine and isoleucine degradation pathways. To further identify underlying regulators, RNA sequencing was performed to integrate metabolic enzyme alterations with metabolomics in STZ-induced diabetic retina. Retinol metabolism and tryptophan metabolism are the shared pathways enriched by metabolome and transcriptome. Additionally, transcriptomic analysis identified 71 differentially expressed enzyme-related genes including Hk2, Slc7a5, Aldh1a3 and Tph integrated with altered metabolic pathways. In addition, single nucleotide polymorphisms within 6 out of 71 genes are associated with increased diabetes risk. This study lays the foundation for mechanism research and the therapeutic target development of DR.

Associations between diabetic retinopathy, mortality, disease, and mental health: an umbrella review of observational meta-analyses

BACKGROUND

Diabetic retinopathy is a complication of diabetes affecting the eyes and can lead to blindless if left untreated. Several significant risk factors have been reported for DR, of which several can be classified as some form of disease. Furthermore, several systematic reviews have reported associations between several types of mortality and DR. Numerous meta-analyses have pooled the data on these factors, however, a systematic evaluation of these meta-analytic relationships is lacking. In this study, therefore, we performed an umbrella review of systematic reviews of meta-analyses for mortality, diseases and DR, grading the credibility of evidence.

METHODS

A comprehensive database search for observational meta-analyses was conducted from inception until 29/04/2022 against pre-published inclusion criteria. For each meta-analytic outcome, a random-effects meta-analysis was re-conducted, stratifying by study design (and type of DR where possible) of included studies. Several statistical variables, including publication bias, heterogeneity, excess significance bias, and prediction intervals were used to grade the credibility of significant evidence from I to IV, using the recommendations from the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria.

RESULTS

Of the 1,834 initial results, 11 systematic reviews with meta-analyses were included covering 16 independent outcomes (total participants = 299,655; median participants per outcome: 7,266; median individual studies per outcome = 5). Overall, 10/16 outcomes (62.5%) yielded significant results, most of which were graded as 'highly suggestive' (Grade II) evidence. DR was associated with all-cause and cardio-vascular mortality, obstructive sleep apnoea, depression eating disorders, and several forms of cognitive impairment.

CONCLUSIONS

Results show highly suggestive evidence for associations between health outcomes and/or conditions and DR. Public health professionals and practitioners should note these findings when developing and/or reviewing public health polices.

Exploration of the mechanisms underlying the beneficial effect of Luo Tong formula on retinal function in diabetic rats via the "gut microbiota-inflammation-retina" axis

BACKGROUND

Diabetic retinopathy (DR) is a common microvascular complication of diabetes. Luo Tong formula (LTF), a classical traditional Chinese medicine (TCM) prescription, consists of four plants that have been widely and effectively used to treat DR. Previous work in our laboratory has confirmed that LTF can effectively ameliorate DR. However, the potential mechanism underlying the therapeutic effect of LTF on DR has not been fully elucidated. To explore the potential mechanism of action through which LTF prevents and alleviates DR from an inflammation and gut microbiota perspective.

MATERIALS AND METHODS

Metabolite profiling of LTF was performed using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). Type 1 diabetes was induced in male Sprague Dawley (SD) rats via tail vein injection of 45 mg/kg streptozotocin. Next, 100 SD rats were randomly divided into four groups, normal control; diabetic control; diabetic + insulin + calcium dobesilate; and diabetic + insulin + LTF. After 12 weeks of treatment, glucose metabolism, fundus oculi, blood-retinal barrier permeability, retinal thickness, microvascular damage, as well as cell junction expression in retinas were measured and the changes observed in different groups were compared. Finally, the alteration in gut microbiota and inflammatory cytokine expression in serum and tissues were monitored, and their correlation was analyzed.

RESULTS

A total of 1024 valid peaks were obtained for LTF using GC-MS. The HbA1c and fasting blood glucose (FBG) levels in the LTF group were slightly decreased. LTF exerted protective effects on fundus oculi and the retina structure to different degrees. LTF attenuated systemic and local retinal inflammation by significantly decreasing the levels of seven pro-inflammatory cytokines, including ICAM-1, IL-6, IL-8, MCP-1, VCAM-1, VEGF, and IL-1β. LTF restored the intestinal microbiota of diabetic rats to levels that were similar to those of normal rats. Further analysis revealed that Enterobacteriales, Prevotellaceae, Enterobacteriaceae, Bacteroides, and Klebsiella were significantly and positively correlated with the inflammatory factors in DR after LTF treatment.

CONCLUSIONS

Our results revealed the mechanisms underlying the preventive effects of LTF on DR development and progression. LTF inhibited pathological changes in retinal histopathology, cell composition, and cell junction proteins while effectively ameliorating systemic and local retinal inflammation via regulating pivotal gut microbiota.

Single-cell RNA sequencing reveals the Müller subtypes and inner blood-retinal barrier regulatory network in early diabetic retinopathy

As the basic pathological changes of diabetic retinopathy (DR), the destruction of the blood-retina barrier (BRB) and vascular leakage have attracted extensive attention. Without timely intervention, BRB damage will eventually lead to serious visual impairment. However, due to the delicate structure and complex function of the BRB, the mechanism underlying damage to the BRB in DR has not been fully clarified. Here, we used single-cell RNA sequencing (RNA-seq) technology to analyze 35,910 cells from the retina of healthy and streptozotocin (STZ)-induced diabetic rats, focusing on the degeneration of the main cells constituting the rat BRB in DR and the new definition of two subpopulations of Müller cells at the cell level, Ctxn3 +Müller and Ctxn3 -Müller cells. We analyzed the characteristics and significant differences between the two groups of Müller cells and emphasized the importance of the Ctxn3 +Müller subgroup in diseases. In endothelial cells, we found possible mechanisms of self-protection and adhesion and recruitment to pericytes. In addition, we constructed a communication network between endothelial cells, pericytes, and Müller subsets and clarified the complex regulatory relationship between cells. In summary, we constructed an atlas of the iBRB in the early stage of DR and elucidate the degeneration of its constituent cells and Müller cells and the regulatory relationship between them, providing a series of potential targets for the early treatment of DR.

Proteinuria in early referral to spectral domain optical coherence tomography for macular edema detection in type 2 diabetes individuals: results from the Brazilian diabetes study

BACKGROUND

Measurement of retinal thickness by optical coherence tomography (OCT) shows higher diagnostic accuracy for diabetic macular edema (DME) than fundus photography alone. The expanding gap between the rising number of type 2 diabetes (T2D) individuals and the availability of OCT devices demands a targeted selection of individuals at higher risk of DME who would benefit the most from early referral. We sought to appraise if proteinuria should be considered in a targeted referral of T2D individuals to OCT examination.

METHODS

This study was a cross-sectional analysis of 576 consecutive patients enrolled in the Brazilian Diabetes Study between June/2016 and December/2021 who underwent OCT exam and urinalysis to assess ME and proteinuria status, respectively. Differences in the prevalence of DME between proteinuria groups and across a range of diabetic retinopathy (DR) stages were evaluated.

RESULTS

Among 1134 eyes included in this analysis, the prevalence of proteinuria was 22% and 18.2% of eyes had DME. Proteinuria was related to an increased prevalence of DME (13.2% vs 38.7% for control vs proteinuria, respectively; p < .001), with an OR of 4.08 [95% confidence interval (CI): 2.50-6.64, p < .001), after adjustment for covariates. Proteinuria was independently related to DME also among eyes with non-apparent DR [OR: 2.82; 95%CI: 1.34-5.93; p = .003] and non-proliferative DR (OR of 5.94, 95%CI 2.13-16.62, p < .001). Fundus photography spotted only half of the DME cases detected by OCT.

CONCLUSION

In T2D individuals, early referral to OCT examination should be pursued for all individuals with concurrent proteinuria.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04949152.

Digital innovations for retinal care in diabetic retinopathy

AIM

The purpose of this review is to examine the applications of novel digital technology domains for the screening and management of patients with diabetic retinopathy (DR).

METHODS

A PubMed engine search was performed, using the terms "Telemedicine", "Digital health", "Telehealth", "Telescreening", "Artificial intelligence", "Deep learning", "Smartphone", "Triage", "Screening", "Home-based", "Monitoring", "Ophthalmology", "Diabetes", "Diabetic Retinopathy", "Retinal imaging". Full-text English language studies from January 1, 2010, to February 1, 2022, and reference lists were considered for the conceptual framework of this review.

RESULTS

Diabetes mellitus and its eye complications, including DR, are particularly well suited to digital technologies, providing an ideal model for telehealth initiatives and real-world applications. The current development in the adoption of telemedicine, artificial intelligence and remote monitoring as an alternative to or in addition to traditional forms of care will be discussed.

CONCLUSIONS

Advances in digital health have created an ecosystem ripe for telemedicine in the field of DR to thrive. Stakeholders and policymakers should adopt a participatory approach to ensure sustained implementation of these technologies after the COVID-19 pandemic. This article belongs to the Topical Collection "Diabetic Eye Disease", managed by Giuseppe Querques.

Prevalence of diabetic retinopathy in India stratified by known and undiagnosed diabetes, urban-rural locations, and socioeconomic indices: results from the SMART India population-based cross-sectional screening study

BACKGROUND

National and subnational estimates of the prevalence of diabetic retinopathy and vision-threatening diabetic retinopathy (VTDR) are needed to inform the stepwise implementation of systematic retinal screening for people with diabetes in India to decrease the rate of blindness. We aimed to assess these national and subnational estimates and to stratify the prevalence of diabetic retinopathy and VTDR on the basis of people with known versus undiagnosed diabetes, urban versus rural residence, and epidemiological transition level (ETL) and Socio-demographic Index (SDI) categories of states.

METHODS

We did a multicentre cross-sectional screening study for diabetic retinopathy using a complex cluster sampling design in people aged 40 years or older in ten Indian states and one union territory between Dec 20, 2018, and March 20, 2020. We did non-mydriatic retinal screening and assessed risk factor burden for people with diabetes. We estimated nationally weighted prevalence of diabetic retinopathy and VTDR for individuals with known and undiagnosed diabetes by urban versus rural residence, and by state categorisation by ETL and SDI. We also assessed adjusted risk factors.

FINDINGS

From 42 146 participants screened, 7910 (18·8%) were identified to have diabetes. Of these, 6133 (77·5%; 4350 with known diabetes and 1783 with undiagnosed diabetes) had gradable retinal images. 3411 (56%) participants were women and 2722 (44%) were men, and the median age was 56 years (IQR 49-65). The estimated national prevalence was 12·5% (95% CI 11·0-14·2) for diabetic retinopathy and 4·0% (3·4-4·8) for VTDR, with no significant differences between urban and rural residence for diabetic retinopathy. Compared with individuals with undiagnosed diabetes, we observed a higher prevalence of diabetic retinopathy (15·5% [13·4-17·8] vs 8·0% [6·3-10·1]) and VTDR (5·3% [4·5-6·3] vs 2·4% [1·6-3·6]) in individuals with known diabetes. The prevalence was significantly lower in low ETL-SDI states compared with high and middle ETL-SDI states for diabetic retinopathy (by 7·0%, 1·9-12·2, p=0·024) and VTDR (by 4·8%, 3·0-6·6, p<0·0001). Hyperglycaemia was the strongest modifiable risk factor.

INTERPRETATION

We estimate that, in absolute numbers, approximately 3 million people aged 40 years or older have VTDR in India, with a higher prevalence in those with known diabetes residing in high and middle ETI-SDI states.

FUNDING

UKRI Global Challenge Research Fund.

Diabetic Retinopathy Telemedicine Outcomes With Artificial Intelligence-Based Image Analysis, Reflex Dilation, and Image Overread

PURPOSE

To examine real-world telemedicine outcomes of diabetic retinopathy (DR) screening with artificial intelligence (AI)-based image analysis, reflex dilation, and secondary image overread in a primary care setting.

DESIGN

Validity and reliability analysis.

METHODS

Single institution review of 1052 consecutive adult patients who received diabetic retinopathy photoscreening in the primary care setting over an 18-month period. Nonmydriatic fundus photographs were acquired and analyzed by the IDx-DR AI-based system. When nonmydriatic images were ungradable, reflex dilation (1% tropicamide) and mydriatic photography were performed for repeat AI-based analysis. Manual overread was performed on all images. Patient demographics, clinical characteristics, and screening outcomes were recorded.

RESULTS

A total of 965 of 1052 patients (91.7%) had AI-gradable fundus photographs: 580 had gradable nonmydriatic imaging (55.1%) and 440 of 472 patients with ungradable nonmydriatic photographs had reflex dilation (93.2%). One hundred thirty-eight of 965 patients (14.3%) were AI-graded as "positive" (greater than mild NPDR) and 827 of 965 were "negative" (85.7%), with 100% sensitivity (95% CI 90.8-100%), 89.2% specificity (95% CI 87.0-91.1%), 27.5% positive predictive value (95% CI 24.0-31.4%), and 100% negative predictive value (95% CI 99.6-100%) compared with manual overread assessment of greater than mild NPDR requiring further evaluation with a comprehensive dilated examination. Image gradeability was inversely related to patient age: 93.5% gradable (61.9% nonmydriatic) for patients aged <70 years vs 85.3% (31.0% nonmydriatic) for patients aged 70+ years (P < .001).

CONCLUSION

Incorporation of AI-based image analysis into real-world primary care diabetic retinopathy screening yielded no false negative results and offered excellent image gradeability within a protocol combining nonmydriatic fundus photography and pharmacologic dilation, as needed. Image gradeability was lower with increasing patient age.

Optical coherence tomography angiography metrics in different stages of diabetic macular edema

Background

To investigate the optical coherence tomography angiography (OCTA) characteristics of diabetic macular edema (DME) at different stages.

Methods

This study was a cross-sectional study. Patients diagnosed with DME were recruited. DME was classified into early, advanced, and severe DME. The vessel density (VD) in the superficial vascular plexus (SVP), deep vascular plexus (DVP) and foveal avascular zone (FAZ) parameters, including FAZ area, FAZ perimeter, acircularity index and foveal VD in a 300-μm-wide region around the FAZ (FD-300), were calculated by the AngioVue software. A multivariate generalized estimating equation was used to evaluate the associations between visual acuity and OCTA metrics.

Results

Ninety-two eyes from 74 patients with DME were included in this study. Compared to early (P = 0.006) and advanced DME (P = 0.003), the acircularity index was higher in severe DME. Both whole and parafoveal VD in the DVP decreased in eyes with severe DME compared to early DME (P = 0.018, P = 0.005, respectively) and advanced DME (P = 0.035, P = 0.012, respectively). In the multivariate generalized estimating equation, DME severity, FAZ area and foveal thickness were positively associated with worse visual acuity (P = 0.001, P = 0.007 and P = 0.001, respectively).

Conclusion

Compared to early and advanced DME, severe DME showed increased irregularity in the FAZ and more extensive vessel damage in the DVP. Greater severity level of DME, larger FAZ area, and increased foveal thickness could be risk factors for poor visual acuity.

Trial registration The protocol was published in the Chinese Clinical Trial Registry (ChiCTR2000033082).

Diosgenin protects retinal pigment epithelial cells from inflammatory damage and oxidative stress induced by high glucose by activating AMPK/Nrf2/HO-1 pathway

INTRODUCTION

Diosgenin is a natural steroidal compound with reported antidiabetic and many other protective properties. This study aimed to explore the protective effect of diosgenin on high-glucose (HG)-induced retinal pigment epithelial cells.

METHODS

HG-induced ARPE-19 cells were considered as a cell model of diabetic retinopathy (DR). The viability and apoptosis of ARPE-19 cells induced by HG treated with either diosgenin or Compound C (CC; dorsomorphin) were detected by Cell Counting Kit-8 assay and flow cytometric analysis. The expression of apoptosis-related proteins, inflammation-related proteins, and AMPK/Nrf2/HO-1 pathway-related proteins was detected by western blotting. The levels of inflammatory cytokines and detection of oxidative stress indexes were performed using the appropriate assay kits. The messenger RNA expression of inflammatory cytokines was detected by real-time quantitative polymerase chain reaction.

RESULTS

There was no obvious effect of diosgenin on the viability of ARPE-19 cells and the viability of ARPE-19 cells was significantly reduced after HG induction. However, diosgenin increased the viability, inhibited the apoptosis, and reduced the inflammatory response and oxidative stress of ARPE-19 cells induced by HG. In addition, diosgenin could activate the AMPK/Nrf2/HO-1 pathway. CC, an AMPK inhibitor, could reverse the above changes caused by diosgenin treatment in ARPE-19 cells induced by HG.

CONCLUSIONS

Diosgenin could protect ARPE-19 cells from inflammatory damage and oxidative stress induced by HG, by activating the AMPK/Nrf2/HO-1 pathway.

Digital solution for detection of undiagnosed diabetes using machine learning-based retinal image analysis

INTRODUCTION

Undiagnosed diabetes is a global health issue. Previous studies have estimated that about 24.1%-75.1% of all diabetes cases are undiagnosed, leading to more diabetic complications and inducing huge healthcare costs. Many current methods for diabetes diagnosis rely on metabolic indices and are subject to considerable variability. In contrast, a digital approach based on retinal image represents a stable marker of overall glycemic status.

RESEARCH DESIGN AND METHODS

Our study involves 2221 subjects for developing a classification model, with 945 subjects with diabetes and 1276 controls. The training data included 70% and the testing data 30% of the subjects. All subjects had their retinal images taken using a non-mydriatic fundus camera. Two separate data sets were used for external validation. The Hong Kong testing data contain 734 controls without diabetes and 660 subjects with diabetes, and the UK testing data have 1682 subjects with diabetes.

RESULTS

The 10-fold cross-validation using the support vector machine approach has a sensitivity of 92% and a specificity of 96.2%. The separate testing data from Hong Kong provided a sensitivity of 99.5% and a specificity of 91.1%. For the UK testing data, the sensitivity is 98.0%. The accuracy of the Caucasian retinal images is comparable with that of the Asian data. It implies that the digital method can be applied globally. Those with diabetes complications in both Hong Kong and UK data have a higher probability of risk of diabetes compared with diabetes subjects without complications.

CONCLUSIONS

A digital machine learning-based method to estimate the risk of diabetes based on retinal images has been developed and validated using both Asian and Caucasian data. Retinal image analysis is a fast, convenient, and non-invasive technique for community health applications. In addition, it is an ideal solution for undiagnosed diabetes prescreening.

Optical coherence tomography image based eye disease detection using deep convolutional neural network

Over the past few decades, health care industries and medical practitioners faced a lot of obstacles to diagnosing medical-related problems due to inadequate technology and availability of equipment. In the present era, computer science technologies such as IoT, Cloud Computing, Artificial Intelligence and its allied techniques, etc. play a crucial role in the identification of medical diseases, especially in the domain of Ophthalmology. Despite this, ophthalmologists have to perform the various disease diagnosis task manually which is time-consuming and the chances of error are also very high because some of the abnormalities of eye diseases possess the same symptoms. Furthermore, multiple autonomous systems also exist to categorize the diseases but their prediction rate does not accomplish state-of-art accuracy. In the proposed approach by implementing the concept of Attention, Transfer Learning with the Deep Convolution Neural Network, the model accomplished an accuracy of 97.79% and 95.6% on the training and testing data respectively. This autonomous model efficiently classifies the various oscular disorders namely Choroidal Neovascularization, Diabetic Macular Edema, Drusen from the Optical Coherence Tomography images. It may provide a realistic solution to the healthcare sector to bring down the ophthalmologist burden in the screening of Diabetic Retinopathy.

Identification of Potential Molecular Targets and Active Ingredients of Mingmu Dihuang Pill for the Treatment of Diabetic Retinopathy Based on Network Pharmacology

Objective. Mingmu Dihuang Pill (MMDHP) is a traditional Chinese formula that has shown remarkable improvements of dry eyes, tearing, and blurry vision; however, the mechanisms underlying MMDHP treatment for diabetic retinopathy have not been fully understood. This study is aimed at identifying the molecular targets and active ingredients of MMDHP for the treatment of diabetic retinopathy based on network pharmacology. Methods. All active ingredients of MMDHP were retrieved from TCMSP and BATMAN-TCM databases, and the targets of active ingredients of MMDHP were predicted on the SwissTargetPrediction website. Diabetic retinopathy-related target sets were retrieved from GeneCards and OMIM databases, and the intersecting targets between targets of active ingredients of MMDHP and potential therapeutic targets of diabetic retinopathy were collected to generate the traditional Chinese medicine-ingredient-target-diabetic retinopathy network and to create the protein-protein interaction network. In addition, GO terms and KEGG pathway enrichment analyses were performed to identify the potential pathways, and molecular docking was employed to verify the binding of active ingredients of MMDHP to key targets of diabetic retinopathy. Results. Network pharmacology predicted 183 active ingredients and 904 targets from MMDHP, and 203 targets were intersected with the therapeutic targets of diabetic retinopathy. The top 10 hub targets included PIK3RA, TP53, SRC, JUN, HRAS, AKT1, VEGFA, EGFR, ESR1, and PI3KCA. GO terms and KEGG pathway enrichment analyses identified AGE-RAGE, PI3K-AKT, and Rap1 signaling pathways as major pathways involved in MMDHP treatment for diabetic retinopathy. Molecular docking confirmed a good binding affinity of active ingredients of MMDHP, including luteolin, acacetin, naringenin, and alisol B, with AKT1, SRC, and VEGFA as the three key targets of diabetic retinopathy. Conclusion. MMDHP may be effective for the treatment of diabetic retinopathy through active ingredients luteolin, acacetin, naringenin, and alisol B via AKT1, SRC, and VEGFA in AGE-RAGE, PI3K-AKT, and Rap1 signaling pathways.

Characterization of NLRP3 Inflammasome Activation in the Onset of Diabetic Retinopathy

The aim of this study was to characterize the role of nucleotide-binding oligomerization domain- (NOD-) like receptor (NLR) protein 3 (NLRP3) inflammasome activation in the onset of diabetic retinopathy (DR) using retina and vitreous from donors without diabetes mellitus (CTL), with diabetes mellitus alone (DM), and with DR. Retinal expression of glial fibrillary acidic protein (GFAP) and ionized calcium-binding adapter molecule 1 (Iba-1), the key markers of retinal inflammation, connexin43 (Cx43) which is involved in upstream inflammasome regulation, as well as NLRP3 and cleaved caspase-1, the main markers of inflammasome activation, were evaluated using immunohistochemistry and Western blotting. Vitreous interleukin (IL)-1β and IL-18, biomarkers of the activated inflammasome, were measured using a Luminex multiplex assay. Results showed a significant increase in the number and size of Iba-1⁺ cells and NLRP3 expression in DM, while a significant increase in GFAP, Cx43, cleaved caspase-1 and vitreous IL-18, as well as a further increase in Iba-1 and NLRP3 was found in DR. This suggests that the inflammasome is already primed in DM before its activation in DR. Furthermore, IL-18 may act as the major effector of inflammasome activation in DR while nuclear translocation of cleaved caspase-1 may play a role in gene transcription contributing to DR onset.

Selective Activation of the Wnt-Signaling Pathway as a Novel Therapy for the Treatment of Diabetic Retinopathy and Other Retinal Vascular Diseases

Retinal ischemia, often associated with various disorders such as diabetic retinopathy (DR), retinal vein occlusion, glaucoma, optic neuropathies, stroke, and other retinopathies, is a major cause of visual impairment and blindness worldwide. As proper blood supply to the retina is critical to maintain its high metabolic demand, any impediment to blood flow can lead to a decrease in oxygen supply, resulting in retinal ischemia. In the pathogenesis of DR, including diabetic macular edema (DME), elevated blood glucose leads to blood-retina barrier (BRB) disruptions, vascular leakage, and capillary occlusion and dropouts, causing insufficient delivery of oxygen to the retina, and ultimately resulting in visual impairment. Other potential causes of DR include neuronal dysfunction in the absence of vascular defect, genetic, and environmental factors. The exact disease progression remains unclear and varies from patient to patient. Vascular leakage leading to edema clearly links to visual impairment and remains an important target for therapy. Despite recent advances in the treatment of DME and DR with anti-VEGFs, effective therapies with new mechanisms of action to address current treatment limitations regarding vessel regeneration and reperfusion of ischemic retinal areas are still needed. The Wnt signaling pathway plays a critical role in proper vascular development and maintenance in the retina, and thus provides a novel therapeutic approach for the treatment of diabetic and other retinopathies. In this review, we summarize the potential of this pathway to address treatment gaps with current therapies, its promise as a novel and potentially disease modifying therapy for patients with DR and opportunities in other retinal vascular diseases.

Genetic regulation of THBS1 methylation in diabetic retinopathy

Background

Diabetic retinopathy (DR) is a common and serious microvascular complication of diabetes mellitus (DM), but its pathological mechanism, especially the formation mechanism of new blood vessels remains unclear. Thrombospondin-1 (THBS1) is a potent endogenous inhibitor of angiogenesis and it was found over expressed in DR in our previous study. Our study aimed to determine whether overexpression of THBS1 is associated with its promoter methylation level, and whether methylation of THBS1 is regulated by genetic variants in DR.

Methods

Patients diagnosed with DR and DM patients without retinal problems were included in the case-control study. DNA methylation detection of THBS1 by bisulfite sequencing and genotyping of specific SNPs by MassARRAY analysis were performed in the patients recruited from 2019-2020. Real time quantitative PCR was performed to obtain mRNA expression of THBS1 in the patients recruited from August to October 2022. The differentially methylated CpG loci of THBS1 were identified by logistic regression, and associations between 13 SNPs and methylation levels of CpG loci were tested by methylation quantitative trait loci (meQTLs) analysis. Mediation analysis was applied to determine whether CpG loci were intermediate factors between meQTLs and DR.

Results

150 patients diagnosed with DR and 150 DM patients without retinal complications were enrolled in the first recruitment, seven DR patients and seven DM patients were enrolled in the second recruitment. The patients with DR showed promoter hypomethylation of THBS1 (P value = 0.002), and six out of thirty-nine CpG sites within two CpG islands (CGIs) showed hypomethylation(P value < 0.05). THBS1 mRNA expression in peripheral blood was significantly higher in DR patients than in DM patients. Five out of thirteen cis-meQTLs were identified to be associated with CpG sites: rs13329154, rs34973764 and rs5812091 were associated with cis-meQTLs of CpG-4 (P value=0.0145, 0.0095, 0.0158), rs11070177 and rs1847663 were associated with cis-meQTLs of CpG-2 and CpG-3 respectively (P value=0.0201, 0.0275). CpG-4 methylation significantly mediated the effect of the polymorphism rs34973764 on DR (B=0.0535, Boot 95%CI: 0.004~0.1336).

Conclusion

THBS1 overexpression is related to THBS1 hypomethylation in patients with DR. DNA methylation may be genetically controlled in DR.

Deep-Learning-Aided Diagnosis of Diabetic Retinopathy, Age-Related Macular Degeneration, and Glaucoma Based on Structural and Angiographic OCT

Purpose

Timely diagnosis of eye diseases is paramount to obtaining the best treatment outcomes. OCT and OCT angiography (OCTA) have several advantages that lend themselves to early detection of ocular pathology; furthermore, the techniques produce large, feature-rich data volumes. However, the full clinical potential of both OCT and OCTA is stymied when complex data acquired using the techniques must be manually processed. Here, we propose an automated diagnostic framework based on structural OCT and OCTA data volumes that could substantially support the clinical application of these technologies.

Design

Cross sectional study.

Participants

Five hundred twenty-six OCT and OCTA volumes were scanned from the eyes of 91 healthy participants, 161 patients with diabetic retinopathy (DR), 95 patients with age-related macular degeneration (AMD), and 108 patients with glaucoma.

Methods

The diagnosis framework was constructed based on semisequential 3-dimensional (3D) convolutional neural networks. The trained framework classifies combined structural OCT and OCTA scans as normal, DR, AMD, or glaucoma. Fivefold cross-validation was performed, with 60% of the data reserved for training, 20% for validation, and 20% for testing. The training, validation, and test data sets were independent, with no shared patients. For scans diagnosed as DR, AMD, or glaucoma, 3D class activation maps were generated to highlight subregions that were considered important by the framework for automated diagnosis.

Main Outcome Measures

The area under the curve (AUC) of the receiver operating characteristic curve and quadratic-weighted kappa were used to quantify the diagnostic performance of the framework.

Results

For the diagnosis of DR, the framework achieved an AUC of 0.95 ± 0.01. For the diagnosis of AMD, the framework achieved an AUC of 0.98 ± 0.01. For the diagnosis of glaucoma, the framework achieved an AUC of 0.91 ± 0.02.

Conclusions

Deep learning frameworks can provide reliable, sensitive, interpretable, and fully automated diagnosis of eye diseases.

Financial Disclosures

Proprietary or commercial disclosure may be found after the references.

Association of Long Noncoding RNA HOTAIR Polymorphism and the Clinical Manifestations of Diabetic Retinopathy

The aim of the current study is to evaluate the possible correlation between the single-nucleotide polymorphisms (SNP) of HOX transcript antisense intergenic RNA (HOTAIR) and the clinical characteristics of diabetic retinopathy (DR). Four loci of HOTAIR SNPs, including rs920778 (T/C), rs12427129 (C/T), rs4759314 (A/G), and rs1899663 (G/T), were genotyped via the TaqMan allelic discrimination for 276 DR individuals and 452 non-DR patients. The distribution frequency of HOTAIR SNP rs12427129 CT [adjusted odds ratio (AOR): 1.571, 95% CI: 1.025-2.408, p = 0.038], HOTAIR SNP rs12427129 CT+TT (AOR: 1.611, 95% CI: 1.061-2.446, p = 0.025), and HOTAIR SNP rs1899663 TT (AOR: 2.443, 95% CI: 1.066-5.595, p = 0.035) were significantly higher in the DR group. Moreover, the proliferative diabetic retinopathy (PDR) subgroup revealed a significantly higher distribution of HOTAIR SNP rs12427129 CT+TT (AOR: 2.016, 95% CI: 1.096-3.710, p = 0.024) and HOTAIR SNP rs1899663 TT (AOR: 4.693, 95% CI: 1.765-12.479, p = 0.002), and the distribution frequencies of HOTAIR SNP rs12427129 CT (AOR: 3.722, 95% CI: 1.555-8.909, p = 0.003), HOTAIR SNP rs12427129 CT+TT (AOR: 4.070, 95% CI: 1.725-9.600, p = 0.001), and HOTAIR SNP rs1899663 TT (AOR: 11.131, 95% CI: 1.521-81.490, p = 0.018) were significantly higher in the female PDR subgroup. Regarding the clinical characters, the DR patients with HOTAIR SNP rs1899663 GT+TT revealed a significantly shorter duration of diabetes compared to the DR patients with HOTAIR SNP rs1899663 GG (10.54 ± 8.19 versus 12.79 ± 7.73, p = 0.024). In conclusion, HOTAIR SNP rs12427129 and rs1899663 are strongly correlated to the presence of DR, especially for a female with PDR.

Prevalence of diabetic retinopathy in the Eastern Mediterranean Region: a systematic review and meta-analysis

Objectives

Individual studies in the Eastern Mediterranean Region (EMR) have shown the high prevalence of diabetic retinopathy. We conducted a meta-analysis to yield an estimate of the prevalence of diabetic (type 1 and 2) retinopathy in the EMR. Additionally, we explored its potential modulators.

Methods

Two-step screening of relevant articles published from 1 January 2000 to 13 December 2019 was carried out. An estimation of summary proportions, subgroup analysis, meta-regression, and publication bias assessment were performed.

Results

One hundred nine articles were included in the meta-analysis, involving 280,566 patients. The prevalence of diabetic retinopathy was 31% (95% confidence interval [CI] = 28, 33). The highest and lowest diabetic retinopathy prevalence rates were observed in low human development index (HDI) countries (63.6; 95% CI = 52.4, 74.0) and very high HDI countries 22.6 (95% CI = 20.5, 24.7), respectively.

Conclusions

The prevalence of diabetic retinopathy is high in the EMR. Our results provide important information for diverse healthcare surveillance systems in the EMR to implement the modifiable risk factors, diabetes screening to decrease undiagnosed diabetes, early detection of retinopathy, and proper diabetes care to decrease untreated diabetes.

Stress response protein REDD1 promotes diabetes-induced retinal inflammation by sustaining canonical NF-κB signaling

Inflammation contributes to the progression of retinal pathology caused by diabetes. Here, we investigated a role for the stress response protein regulated in development and DNA damage response 1 (REDD1) in the development of retinal inflammation. Increased REDD1 expression was observed in the retina of mice after 16-weeks of streptozotocin (STZ)-induced diabetes, and REDD1 was essential for diabetes-induced pro-inflammatory cytokine expression. In human retinal MIO-M1 Müller cell cultures, REDD1 deletion prevented increased pro-inflammatory cytokine expression in response to hyperglycemic conditions. REDD1 deletion promoted nuclear factor erythroid-2-related factor 2 (Nrf2) hyperactivation; however, Nrf2 was not required for reduced inflammatory cytokine expression in REDD1-deficient cells. Rather, REDD1 enhanced inflammatory cytokine expression by promoting activation of nuclear transcription factor κB (NF-κB). In WT cells exposed to tumor necrosis factor α (TNFα), inflammatory cytokine expression was increased in coordination with activating transcription factor 4 (ATF4)-dependent REDD1 expression and sustained activation of NF-κB. In both Müller cell cultures exposed to TNFα and in the retina of STZ-diabetic mice, REDD1 deletion promoted inhibitor of κB (IκB) expression and reduced NF-κB DNA-binding activity. We found that REDD1 acted upstream of IκB by enhancing both K63-ubiquitination and auto-phosphorylation of IκB kinase complex. In contrast with STZ-diabetic REDD1^+/+ mice, IκB kinase complex autophosphorylation and macrophage infiltration were not observed in the retina of STZ-diabetic REDD1^-/- mice. The findings provide new insight into how diabetes promotes retinal inflammation and support a model wherein REDD1 sustains activation of canonical NF-κB signaling.

Lower hydration status increased diabetic retinopathy among middle-aged adults and older adults: Results from NHANES 2005-2008

Background

Diabetic retinopathy (DR) is a common complication of diabetic patients. Retinal physiological function is affected by hydration status. We aimed to explore the association between hydration status and DR.

Methods

National Health and Nutrition Examination Survey (NHANES) 2005-2008 was used to perform this cross-sectional study. Serum osmolality was used to assess hydration status for all participants and calculated osmolality was evaluated for only older people. DR and its severity were evaluated and graded into mild non-proliferative retinopathy, moderate/severe non-proliferative retinopathy, and proliferative diabetic retinopathy by the Early Treatment for Diabetic Retinopathy Study protocol and NHANES Digital Grading Protocol. Fully adjusted multivariable logistic regression models were used by SAS OnDemand for Academics.

Results

Among the 5,220 United States adults aged 40 or older, compared with the lowest osmolality group, participants with the highest quartile of serum osmolarity had higher odds of DR (OR: 1.371, 95% CI: 1.001-1.876). For participants with DR, the adjusted OR (95 % CI) of moderate/severe non-proliferative retinopathy and proliferative diabetic retinopathy in the higher serum osmolarity group was 2.119 (1.200-3.741) and 7.001 (3.175-15.438), respectively. Furthermore, in older people, higher calculated osmolarity was significantly associated with increased occurrence of DR (OR: 2.039, 95% CI: 1.305-3.186).

Conclusions

Adults with lower hydration status had higher risk of DR, moderate/severe non-proliferative retinopathy, and proliferative diabetic retinopathy. Dehydration in older adults, classified by calculated osmolality, is associated with a higher rate of DR. There was consistent trend in the results between the two methods.

Prevalence and Factors Associated with Diabetic Retinopathy among Adult Diabetes Patients in Southeast Ethiopia: A Hospital-Based Cross-Sectional Study

Background

Diabetic retinopathy (DR) is the most prevalent microvascular consequence of diabetes mellitus, and it can result in blindness that is irreversible. Due to delayed diagnosis and limited access to diabetic care, the situation is even worse in developing countries. Scientific evidence on the prevalence of DR and its associated factors among diabetes patients in low-income countries, such as Ethiopia, is limited. This study aimed to determine the prevalence of DR and associated factors among adult diabetes patients in southeast Ethiopia.

Methods

A hospital-based cross-sectional study was conducted among diabetes patients who visited Madda Walabu University Goba Referral Hospital. Fundus and slit-lamp examination were performed for screening of DR. Multivariate binary logistic regression was computed to identify factors associated with DR.

Results

A total of 256 patients (144 men, 56.2%) aged 50.15±15.71 years were included in the study. The prevalence of any DR was 19.9% (95% CI 15.4%-25.3%), mild nonproliferative diabetic retinopathy (NPDR) 10.9% (95% CI 7.6%-15.4%), moderate NPDR 5.9% (95% CI 3.5%-9.5%), severe NPDR 0.9% (95% CI 0.2%-3.9%), and proliferative DR 2.3% (95% CI 1.0%-5.1%). Duration of diabetes ≥10 years (AOR 10.22, 95% CI 1.70-61.44), central obesity (AOR 5.42, 95% CI 1.38-21.19), overweight/obese (AOR 2.65, 95% CI 1.02-6.92), lower high-density lipoprotein (HDL) cholesterol (AOR 5.82, 95% CI 1.86-18.24), moderate triglyceride:HDL cholesterol ratio (AOR 4.13, 95% CI 1.13-15.15), and urban dwelling (AOR 2.84, 95% CI 1.04-7.78) were significantly associated with DR.

Conclusion

One in every five DM patients had DR. Sociodemographic, anthropometric, and blood lipids were independently associated with DR. To reduce the burden of diabetes, strategies that focus on lifestyle modifications targeted at identified modifiable risk factors are essential.

Detection of Diabetic Retinopathy Using Extracted 3D Features from OCT Images

Diabetic retinopathy (DR) is a major health problem that can lead to vision loss if not treated early. In this study, a three-step system for DR detection utilizing optical coherence tomography (OCT) is presented. First, the proposed system segments the retinal layers from the input OCT images. Second, 3D features are extracted from each retinal layer that include the first-order reflectivity and the 3D thickness of the individual OCT layers. Finally, backpropagation neural networks are used to classify OCT images. Experimental studies on 188 cases confirm the advantages of the proposed system over related methods, achieving an accuracy of 96.81%, using the leave-one-subject-out (LOSO) cross-validation. These outcomes show the potential of the suggested method for DR detection using OCT images.

Road Traffic Noise, Obesity, and the Risk of Incident Type 2 Diabetes: A Cohort Study in UK Biobank

Objectives: To assess the association of road traffic noise exposure with Type 2 Diabetes (T2D) risk, and to explore the potential moderation effect of obesity. Methods: A total of 305,969 participants from the UK Biobank Cohort - an open access cohort of 500,000 participants recruited in the United Kingdom (UK) between 2006 and 2010 - were included in the study. A Cox proportional hazard model was fitted to assess the association between road traffic noise exposure and T2D. Results: A total of 19,303 participants were diagnosed with T2D during the 11.9-year median follow-up period. For every 10 dB increase in road traffic noise, there was a 4% increase in T2D risk (HR = 1.04, 95%CI: 1.01, 1.07). Besides, a significant positive interaction was observed between obesity and road traffic noise (P interaction <0.001) for the risk of T2D. The association of road traffic noise with T2D was stronger in overweight and obese participants (HR = 1.04, 95% CI: 1.01-1.08), but not significant among lean ones (HR = 0.96, 95% CI: 0.86-1.07). Conclusion: Our study observed a longitudinal association of road traffic noise exposure with T2D risk, which was stronger among overweight and obese individuals than the lean ones.

Trends in diabetes-related complications in Singapore, 2013-2020: A registry-based study

Background

Diabetes mellitus (DM) is a growing global health problem. In Singapore, the prevalence of Type 2 DM is rising, but comprehensive information about trends in DM-related complications is lacking.

Objectives

We utilized the Singapore Health Services (SingHealth) diabetes registry (SDR) to assess trends in DM micro and macro-vascular complications at the population level, explore factors influencing these trends.

Methods

We studied trends for ten DM-related complications: ischemic heart disease (IHD), acute myocardial infarction (AMI), peripheral arterial disease (PAD) and strokes, diabetic eye complications, nephropathy, neuropathy, diabetic foot, major and minor lower extremity amputation (LEA). The complications were determined through clinical coding in hospital (inpatient and outpatient) and primary care settings within the SingHealth cluster. We described event rates for the complications in 4 age-bands. Joinpoint regression was used to identify significant changes in trends.

Results

Among 222,705 patients studied between 2013 and 2020. 48.6% were female, 70.7% Chinese, 14.7% Malay and 10.6% Indian with a mean (SD) age varying between 64.6 (12.5) years in 2013 and 65.7 (13.2) years in 2020. We observed an increase in event rates in IHD, PAD, stroke, diabetic eye complications nephropathy, and neuropathy. Joinpoints was observed for IHD and PAD between 2016 to 2018, with subsequent plateauing of event rates. Major and minor LEA event rates decreased through the study period.

Conclusion

We found that DM and its complications represent an important challenge for healthcare in Singapore. Improvements in the trends of DM macrovascular complications were observed. However, trends in DM microvascular complications remain a cause for concern.

Tortuosity of branch retinal artery is more associated with the genesis and progress of diabetic retinopathy

OBJECTIVE

The purpose of this study is to investigate the potential of using the tortuosity of branch retinal artery as a more promising indicator for early detection and accurate assessment of diabetic retinopathy (DR).

DESIGN AND METHOD

The diagnoses, consisting of whether DR or not as well as DR severity, were given by ophthalmologists upon the assessment of those fundus images from 495 diabetic patients. Meanwhile, benefiting from those good contrast and high optical resolution fundus images taken by confocal scanning laser ophthalmoscope, the branch arteries, branch veins, main arteries and main veins in retina can be segmented independently, and the tortuosity values of them were further extracted to investigate their potential correlations with DR genesis and progress based on one-way ANOVA test.

RESULTS

For both two comparisons, i.e., between non-DR group and DR group as well as among groups with different DR severity levels, larger tortuosity increments were always observed in retinal arteries and the increments in branch retinal vessels were even larger. Furthermore, it was newly found that branch arterial tortuosity was significantly associated with both DR genesis (p=0.030) and DR progress (p<0.001).

CONCLUSION

Based on this cohort study of 495 diabetic patients without DR and with different DR severity, the branch arterial tortuosity has been found to be more closely associated with DR genesis as well as DR progress. Therefore, the branch arterial tortuosity is expected to be a more direct and specific indicator for early detection of DR as well as accurate assessment of DR severity, which can further guide timely and rational management of DR to prevent from visual impairment or even blindness resulting from DR.