Stages Of Diabetic Retinopathy Research Articles

Systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio in patients with type 2 diabetes at different stages of diabetic retinopathy

AIM: To investigate systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) levels in patients with type 2 diabetes at different stages of diabetic retinopathy (DR). METHODS: This retrospective study included 141 patients with type 2 diabetes mellitus (DM): 45 without diabetic retinopathy (NDR), 47 with non-proliferative diabetic retinopathy (NPDR), and 49 with proliferative diabetic retinopathy (PDR). Complete blood counts were obtained, and NLR, PLR, and SII were calculated. The study analysed the ability of inflammatory markers to predict DR using receiver operating characteristic (ROC) curves. The relationships between DR stages and SII, PLR, and NLP were assessed using multivariate logistic regression. RESULTS: The average NLR, PLR, and SII were higher in the PDR group than in the NPDR group (P=0.011, 0.043, 0.009, respectively); higher in the NPDR group than in the NDR group (P<0.001 for all); and higher in the PDR group than in the NDR group (P<0.001 for all). In the ROC curve analysis, the NLR, PLR, and SII were significant predictors of DR (P<0.001 for all). The highest area under the curve (AUC) was for the PLR (0.929 for PLR, 0.925 for SII, and 0.821 for NLR). Multivariate regression analysis indicated that NLR, PLR, and SII were statistically significantly positive and independent predictors for the DR stages in patients with DM [odds ratio (OR)=1.122, 95% confidence interval (CI): 0.200–2.043, P<0.05; OR=0.038, 95%CI: 0.018–0.058, P<0.05; OR=0.007, 95%CI: 0.001–0.01, P<0.05, respectively). CONCLUSION: The NLR, PLR, and SII may be used as predictors of DR.

Associations of quantitative contrast sensitivity with vascular metrics on widefield swept-source OCT angiography across stages of diabetic retinopathy

PurposeTo investigate structure–function associations between contrast sensitivity (CS) and widefield swept-source optical coherence tomography angiography (WF SS-OCTA) vascular metrics across stages of non-proliferative (NPDR) and proliferative diabetic retinopathy (PDR), without...

Diabetic Retinopathy Stage Detection Using CNN and Inception V3

The project explores the deployment of Convolutional Neural Networks (CNN) and the Inception V3 model for the automated detection and classification of diabetic retinopathy stages using fundus images. Recognizing diabetic retinopathy as a leading cause of blindness among the working-age population globally, this research aims to streamline the diagnostic process, traditionally reliant on the manual examination by ophthalmologists. Through the utilization of the DRIVE and STARE datasets, the project benchmarks the performance of CNN and Inception V3 models in accurately categorizing the severity of diabetic retinopathy into five distinct stages. The comparison between these models is grounded on parameters such as accuracy, loss, and predicted value, with findings indicating Inception V3's superiority in both performance metrics and diagnostic precision. This advancement could significantly contribute to early and more accessible detection of diabetic retinopathy, thereby mitigating progression towards blindness. Furthermore, the project underscores the potential of deep learning algorithms in enhancing diagnostic methodologies for retinal diseases, paving the way for future explorations in the field of medical imaging and artificial intelligence.

MiR-9-3 hypermethylation is associated with stages of diabetic retinopathy

MiR-9-3 hypermethylation is associated with stages of diabetic retinopathy

The Superficial and Deep Vascular Complexes are Damaged to Different Extents in Advanced Stages of Diabetic Retinopathy

The Superficial and Deep Vascular Complexes are Damaged to Different Extents in Advanced Stages of Diabetic Retinopathy

The Effect of Diabetic Retinopathy and Blood Glucose Regulation on Corneal Biomechanical Parameters.

The aim of this study was to evaluate the effects of different stages of diabetic retinopathy (DR) and metabolic control of blood glucose levels on corneal biomechanical parameters. Diabetic patients were categorized into three groups: no DR group, nonproliferative DR (NPDR) group, and proliferative DR (PDR) group. Of the 141 eyes examined, 40 belonged to the control group, 34 to no DR group, 34 to NPDR group, and 33 to PDR group. Using an Ocular Response Analyzer to measure corneal hysteresis (CH), corneal resistance factor (CRF), Goldmann-correlated intraocular pressure (IOPg), and corneal-compensated IOP (IOPcc). IOP was assessed using a Tono-Pen, while central corneal thickness (CCT) was determined using an ultrasonic pachymeter. HbA1c levels were also recorded. We conducted comparisons among these groups across biomechanical parameters and IOP (tonopen), and CCT, while also investigating the impact of HbA1c levels on these parameters. Among any groups show a statistically significant difference in CCT, IOP (tonopen), CH, CRF, IOPg, and IOPcc. In diabetic patients, CRF, CTT, and IOPg values were significantly higher in those with HbA1c levels ≥ 7 mg/dl than in those with HbA1c levels < 7 mg/dl (p = 0.009, p = 0.013, p = 0.038), respectively, while there was no statistically significant difference in IOPcc, CH, and IOP (tonopen). Linear regression analysis showed that CH was positively associated with CCT (p < 0.001) and negatively associated with IOPcc (p < 0.001), while CRF was positively associated with CCT (p < 0.001), HbA1c (p < 0.05), and negatively associated with diagnosis of DR (p < 0.05). This study underscores the influence of metabolic control, as reflected by HbA1c levels, on corneal biomechanical parameters in diabetic patients, emphasizing the importance of monitoring and managing glycemic control in this population.

Changes in the level of some tryptophan metabolites in the blood of patients with type 2 diabetes mellitus complicated by diabetic retinopathy

Aim: To study the content of tryptophan and the intermediate metabolites of kynurenine and serotonin pathways of its metabolism in the blood plasma of patients with type 2 diabetes mellitus (DM) and non-proliferative diabetic retinopathy as candidates for markers of the early stage of the pathological process.Material and Methods. Three groups of people were analyzed: the first group of 10 patients with type 2 diabetes mellitus and without diabetic retinopathy; the second group of 10 people with type 2 diabetes mellitus and non-proliferative stage of diabetic retinopathy; and the control group of 10 healthy people. The features of the first group were a decrease of macula’s photosensitivity in the fundus and a slight increase in the central thickness of the retina. Patients with diabetic retinopathy tended to have a moderate number of microaneurysms and microhemorrhages, moderately presented intraretinal microvascular anomalies in one quadrant, vein dilatation, clearness of the central retinal vein and its branches. In the macular zone there was an edema with hard exudates in the center and lateral to the fovea centralis. All participants of the study gave blood on an empty stomach in the morning, and after that in we measured the content of tryptophan (TRP), kynurenins ((kynurenine (KYN), 3-hydroxykynurenine (3-HKYN), kynurenic acid (KYNA)) and the level of L-5-hydroxytyrptophan (5HTrp) in blood plasma by HPLC method with fluorimetric and spectrophotometric detection.Results. The groups of people with type 2 diabetes mellitus showed the increasing of TRP level in blood relatively to healthy individuals: by 15.1% (p = 0.032) and 17.9% (p = 0.030) in the first and second groups, respectively. As for the patients of the first group, the content of their KYN was increased by 57.7% (p = 0.012) and KYNA by 33.6% (p = 0.012) relatively to the control and the concentration of 3-НKYN decreased by 18.1% (p = 0.020) relatively to healthy people. As for the patients in the second group, the changes in their level of kynurenines had the same direction, but were more visible. Thus, the concentration of KYN exceeded the same parameters of healthy individuals by 84.5% (p = 0.001) and the parameters of the first group by 18.0% (p = 0.049); the KYNA level increased by 56.6% (p = 0.001) relatively to the control and by 17.3% (p = 0.049) from that of the first group. There was a decrease in the content of 3-HKYN amounted to 18.6% of the control (p = 0.038) and an increase in the concentration of 5HTrp – 193,9% (p &lt; 0.001).

Deep Learning Approach for Diabetic Retinopathy Detection

One of the main causes of diabetic vision loss in the active population is diabetic retinopathy, which is more commonly abbreviated as DR. This condition is caused by changes in the vessels that line the retina. One of the most serious entanglements of diabetes, diabetic retinopathy can bring about long-lasting visual impairment whenever left untreated. One of the basic troubles is early distinguishing proof, which is fundamental for treatment accomplishment. One critical ensnarement is Diabetic Retinopathy. Diabetic retinopathy is an eye infirmity caused because of delayed diabetes. On the off chance that unacknowledged or incapable treatment can prompt irreversible vision misfortune. This illness can be recognized by examining variety fundus photos of the human retina. Our work evaluates in profound learning field which is utilized for the discovery and class isolation of diabetic retinopathy into parallel or multiclass and examine them in view of various measurement estimates like accuracy, review, precision. The characterization of diabetic retinopathy includes various advances like pre-handling of picture; include extraction, dimensionality decrease and order of exudates, woolen spot, hemorrhages and microaneurysm. The mechanized methods for Diabetic Retinopathy affirmation are versatile for cost and time decline and are more able over manual examination. Significant Learning technique performs PC upheld clinical end. This paper is an undertaking toward finding a modified response for Diabetic Retinopathy affliction in early phase unfortunately; the particular unmistakable evidence of the diabetic retinopathy stage is broadly fascinating and requires ace human interpretation of fundus pictures. Improvement of the revelation step is fundamental and can help an enormous number of people. Convolutional cerebrum associations (CNN) have been really applied in various adjoining subjects, and for examination of diabetic retinopathy itself. With the right treatment, numerous issues brought about by DR can be kept away from. Since the diabetic retinopathy progresses through a couple of stages, it is really trying for diabetic retinopathy acknowledgment and exploring of such pictures is a drawn-out manual connection. In this work, we are searching for a technique that consequently isolates a picture into different phases of diabetic retinopathy. This errand uses convolutional mind association (CNNs) power for DR area and usages an unreservedly open dataset of Aptos competition open on Kaggle for setting up these models. Each of the 3663 high-quality fundus images in the dataset was approximately 4000 * 2000. The calculation can order the given picture into various DR phases toward the end. In this undertaking we are using Convolutional Cerebrum Association computation. Execution and accuracy of the applied computations is discussed and examined.

Classification Features of Severe Stages of Proliferative Diabetic Retinopathy (Clinical Cases)

Purpose: analysis of clinical cases illustrating the classification features of severe stages of proliferative diabetic retinopathy (PDR).Patient and methods. Three clinical cases of PDR are presented, in which ophthalmoscopic signs (according to the classification of the Early Treatment Diabetic Retinopathy Study, 1991) corresponded to severe PDR (high risk 1, high risk 2) and advanced PDR. The ophthalmological status was assessed using standard methods based on measuring the best corrected distance visual acuity, performing ultrasound (Opticon 2000, Italy), photographic recording of the condition of the fundus (Carl Zeiss Visucam 500, Germany) and optical coherence tomography of the macular region (on an RTVue-100 tomograph, OptoVue, USA).Results and conclusion. The presented clinical examples will provide the ophthalmologist with a more complete understanding of the clinical picture of pathological changes in the retina in diabetes mellitus, which will ultimately increase the level of diagnosis and tactics of surgical intervention both during the initial (preoperative) examination and after vitrectomy.

CENTRAL AND PERIPHERAL INVOLVEMENT OF THE RETINA IN THE INITIAL STAGES OF DIABETIC RETINOPATHY.

To determine the degree of central microvascular closure using optical coherence tomography angiography in eyes of patients with type 2 diabetes with visible lesions only in the central retina or only in the periphery. Cross-sectional study. All 127 eyes underwent ultra-widefield fundus photography 200° examinations with OPTOS California (Optos, Dunfermline, United Kingdom) and Cirrus Angioplex optical coherence tomography angiography 3 × 3 mm acquisitions (ZEISS, Dublin, CA). Twenty-five eyes showed visible lesions only in the central retina, 57 only in the peripheral retina, and 45 presented visible lesions in entire retina. The group with visible lesions only in the periphery showed definite closure in the superficial capillary plexus in 49% of the eyes, whereas the group with visible lesions only in the central seven-early treatment diabetic retinopathy study fields area showed a definite closure in 64%. Central capillary closure is already present in the initial stages of diabetic retinopathy even when lesions are only visible in the peripheral retina. Capillary closure in the superficial capillary plexus is three times more frequent than in the deep capillary plexus, demonstrating earlier closure of the superficial capillary plexus. Eyes with visible lesions only in the periphery show a milder form of retinopathy.

Microaneurysms and Exudates Detection in Retinal Images using Deep Neural Network

One frequent diabetes consequence that affects the eyes is diabetic retinopathy(DR). The most frequent reasonfor blindness in working-age adults in the world is diabetic retinopathy. One in three diabetics has diabetic retinopathy to some extent. DR affects nearly all persons having type 1 diabetes and more than 60% of people having type 2 diabetes to some extent after 20 years of diabetes. In the US, approximately 4.2 million persons, 40 and older have diabetic retinopathy. In the United States, 12% of all new occurrences of blindness are caused by diabetic retinopathy.A 95% reduction in the risk of blindness is possible with a diabetic retinopathy early detection and treatment. The retina's appearance, the presence or absence of Microaneurysm and Exudates, and the degree of participation are all taken into account in the grading process. It has been demonstrated that deep neural networks (DNNs) work well for automatically grading diabetic retinopathy. The features like Microaneurysm and Exudates that are diagnostic of various stages of diabetic retinopathy are taught to these DNNs utilizing vast datasets of retinal pictures and accompanying grading information.It has been demonstrated that deep neural networks (DNNs) are efficient in automatically detecting diabetic retinopathy from retinal pictures. Sensitivity, specificity, precision, accuracy, and Kappa value are used to measure how well DNNs work in detecting diabetic retinopathy; these values are 95.74%, 92.31%, 96.77%, 94.74%, and 0.87, respectively.

New Approaches to Surgical Treatment of Patients with Advanced Stage of Proliferative Diabetic Retinopathy

Purpose. Development and evaluation of the clinical effectiveness and safety of a vitrectomy (VE) technique for patients with advanced stage proliferative diabetic retinopathy (ASPDR).Materials and methods. We observed 132 patients (mean age 62.8 ± 2.4 years) with the following criteria for inclusion in the study, corresponding to the classification criteria of ASPDR: it is impossible to estimate the area of neovascularization; the fundus of the eye is partially ophthalmoscoped or not ophthalmoscoped in the posterior pole; preretinal or vitreal hemorrhage in the posterior pole with an area of more than 4 optic discs; retinoschisis in the macular zone. All patients were divided into the following two groups, equal in age, gender and visual status of the “healthy” eye: the main group (MG, 69 patients, 69 eyes), who underwent VE was performed according to the developed method and a control group (CG, 63 patients, 63 eyes), in which VE was performed according to the traditional method.Results. The incidence of intraoperative complications in patients in the MG (5.8 %) was 8.1 % (p &lt; 0.05) lower than in the CG (13.9 %). The incidence of postoperative complications in patients from the MG (5.5 ± 0.5 %) was 4.2 % (p &lt; 0.01) lower than in the CG (9.7 ± 1.0 %). The increase in best-corrected visual acuity after surgery in patients from the MG was significantly (by 0.13 rel. units, p &lt; 0.001) higher than in the CG. The value of the average decrease in the developed qualitative criteria for the condition of the fundus in patients in the MG (1.6 ± 0.1) was 23.1 % (p &lt; 0.05), higher than in the CG (1.3 ± 0.1).Conclusion. Surgical treatment of patients with ASPDR using the developed technique provides (compared to the traditional approach) a higher level of safety and clinical effectiveness. The main advantage of the developed technique is an integrated approach to surgical intervention, including the improvement of ophthalmological “techniques” (use of one-stage combined surgery, endolaser coagulation technology, etc.) and drug support (administration of ranibizumab at a dose of 0.05 mg 3–5 days before surgery) and the choice of intravenous sedation as the optimal anesthetic aid.

Redox Regulation of Immunometabolism in Microglia Underpinning Diabetic Retinopathy.

Diabetic retinopathy (DR) is the leading cause of visual impairment and blindness among the working-age population. Microglia, resident immune cells in the retina, are recognized as crucial drivers in the DR process. Microglia activation is a tightly regulated immunometabolic process. In the early stages of DR, the M1 phenotype commonly shifts from oxidative phosphorylation to aerobic glycolysis for energy production. Emerging evidence suggests that microglia in DR not only engage specific metabolic pathways but also rearrange their oxidation-reduction (redox) system. This redox adaptation supports metabolic reprogramming and offers potential therapeutic strategies using antioxidants. Here, we provide an overview of recent insights into the involvement of reactive oxygen species and the distinct roles played by key cellular antioxidant pathways, including the NADPH oxidase 2 system, which promotes glycolysis via enhanced glucose transporter 4 translocation to the cell membrane through the AKT/mTOR pathway, as well as the involvement of the thioredoxin and nuclear factor E2-related factor 2 antioxidant systems, which maintain microglia in an anti-inflammatory state. Therefore, we highlight the potential for targeting the modulation of microglial redox metabolism to offer new concepts for DR treatment.

Quality of life of patients with an advanced stage of proliferative diabetic retinopathy after application of various vitrectomy technologies

Purpose: A comparative assessment of quality of life (QL) after the use of various vitrectomy (VE) technologies in patients with an advanced stage of proliferative diabetic retinopathy (ASPDR).Material and methods. We examined 132 patients aged 42 to 76 (average age 62.8 ± 2.4 years) who met the classification criteria of ASPDR: impossibility to estimate the area of neovascularization; the fundus of the eye in the posterior pole cannot be seen or can only partialy be seen using an ophthalmoscope; evidence of preretinal or vitreal hemorrhage in the posterior pole with an area of more than 4 optic discs and retinoschisis in the macular zone. All patients were divided into two groups, comparable in age, gender and visual status of the “healthy” eye: the main group (69 eyes), in which VE was performed according to the technique developed by the authors, and the control (63 eyes), in which the traditional VE technique was used. QL was assessed before surgery and 3 months after it using the VFQ-25 and QL-20 questionnaires.Results. QL was found to be higher when the new surgery technique was used: the data of VFA-25 showed a 12.9% increase (p &lt; 0.05) and QL-20 showed a 29.2% increase (p &lt; 0.01), which points to a higher clinical effectiveness of the newly developed surgical treatment technique than that of the traditional technique.Conclusion. The results obtained are related to the ophthalmological features of the developed surgical treatment of ASPDR: combined (phacoemulsification of cataracts + IOL + vitrectomy) one-stage intervention, lack of drainage of subretinal fluid, etc.), medication support (preliminary intravitreal administration of an angiogenesis inhibitor) and anesthesia (intervention under local anesthesia with intravenous sedation). The differences are most effectively identified using the special QL-20 questionnaire.

Automated analysis of retinal microcirculation in type 1 diabetes mellitus

BACKGROUND: The paper is dedicated to the assessment of the retinal microvasculature in patients with type 1 diabetes mellitus (DM) with various features of the clinical course and different stages of diabetic retinopathy (DR). Automatic analysis of optical coherence tomogram angiograms (OCT-A) was carried out with specially developed software that provides the ability to estimate quantitative vascular parameters.AIM: The purpose of the study was to assess diagnostic accuracy of clinical parameters and imaging biomarkers in type 1 diabetes using a new algorithm for OCT-A analysis.MATERIALS AND METHODS: The study involved 186 people (365 eyes) with type 1 diabetes. The analysis of the OCT-A parameters was performed with a specially developed software. The range of studied parameters included: foveal avascular zone (FAZ), vessel area density (VAD), skeletonized vessel density (VSD), vessel diameter index (VDI), vascular curvature index (VCI) at the level of superficial (SCP) and deep (DCP) retinal capillary plexuses in the macular region. A correlation between the involvement of OCT-A biomarkers and age, degree of DM, increased glycated hemoglobin (HbA1c) level, stage of DR, and maximally corrected visual acuity (BCVA) was analysed.RESULTS: A significant dependence of all quantitative OCT-A parameters on the age of and duration of diabetes (p&lt;0.05) was revealed. An increase in FAZ SCP (K=0.788, p=0) and DCP (K=0.764, p=0.03); decrease in VAD SCP (K=-0.476, p=0) and DCP (K=-0.485, p=0); VSD SCP (K=0.692, p=0) and DCP (K=0.713, p=0); an increase in VDI SCP (K=0.698, p=0) and DCP (K=787, p&lt;0.01), as well as an increase in the VCI SCP (K=0.735, p=0) and DCP (K=0.694, p p=0). An inverse relationship was found between HbA1c level and VAD SCP (K=-0.636, p=0) and DCP (K=-0.619, p=0.05) were identified as well as a direct relationship with VDI DCP (K=0.717, p&lt;0.05). The influence of the HbA1c level on other parameters was not confirmed (p&gt;0.05). The presence of correlation between BCVA and FAZ DCP (K=-0.728, p=0), as well as VSD DCP (K=-0.754, p=0) was proved.CONCLUSION: As a result of a comprehensive analysis of clinical data and imaging biomarkers, a number of patterns that have diagnostic value in diabetic retinopathy were identified.

Assessing Diabetic Retinopathy Staging With AI: A Comparative Analysis Between Pseudocolor and LED Imaging.

To compare the diagnostic performance of artificial intelligence (AI)-based diabetic retinopathy (DR) staging system across pseudocolor, simulated white light (SWL), and light-emitting diode (LED) camera imaging modalities. A cross-sectional investigation involved patients with diabetes undergoing imaging with an iCare DRSplus confocal LED camera and an Optos confocal, ultra-widefield pseudocolor camera, with and without SWL. Macula-centered and optic nerve-centered 45 × 45-degree photographs were processed using EyeArt v2.1. Human graders established the ground truth (GT) for DR severity on dilated fundus exams. Sensitivity and weighted Cohen's weighted kappa (wκ) were calculated. An ordinal generalized linear mixed model identified factors influencing accurate DR staging. The study included 362 eyes from 189 patients. The LED camera excelled in identifying sight-threatening DR stages (sensitivity=0.83, specificity=0.95 for proliferative DR) and had the highest agreement with the GT (wκ=0.71). The addition of SWL to pseudocolor imaging resulted in decreased performance (sensitivity=0.33, specificity=0.98 for proliferative DR; wκ=0.55). Peripheral lesions reduced the likelihood of being staged in the same or higher DR category by 80% (P<0.001). Pseudocolor and LED cameras, although proficient, demonstrated non-interchangeable performance, with the LED camera exhibiting superior accuracy in identifying advanced DR stages. These findings underscore the importance of implementing AI systems trained for ultra-widefield imaging, considering the impact of peripheral lesions on correct DR staging. This study underscores the need for artificial intelligence-based systems specifically trained for ultra-widefield imaging in diabetic retinopathy assessment.

Proliferative diabetic retinopathy in severe stages: modern approaches to diagnosis and treatment (systematic review)

Diabetic retinopathy (DR) is a leading complication in patients with diabetes mellitus (DM). Because of the increase in the clinical effectiveness of treatment for diabetes, the life expectancy of patients has increased, which accordingly increases the risk of severe forms of DR (proliferative DR), which is one of the main causes of blindness and low vision in the working-age population. In the literature, the overall prevalence of DR and proliferative DR is up to 34.6% and 12.0%, respectively, whereas 25% of cases of vision loss associated with DR are caused by complications of proliferative DR. Colour fundus photography and optical coherence tomography are the most informative clinical diagnostic methods for DR. In severe stages of proliferative DR, the information content of the presented indicators can be significantly reduced because of insufficient visualisation of the patient’s fundus. Thus, the literature proposes qualitative criteria (specific and single indicators) based on an expert assessment of the condition of the fundus by an ophthalmic surgeon. The described approach has a fairly high diagnostic efficiency. Along with this, it appears relevant to study the ‘quality of life’ of a patient with symptoms of proliferative DR caused by the occurrence of characteristic manifestations of psychological distress (psychological and anxiety disorders and depression). In surgical terms, functional results notably improved after vitrectomy for proliferative DR in 49–83% of cases. Moreover, the proposed methods for conducting vitrectomy for patients with advanced stages of proliferative DR do not fully consider ophthalmological and somatic features, which requires the consideration of the surgical treatment of this contingent as a separate area of vitrectomy for improving ophthalmological ‘techniques’, drug support and choice of anaesthesia.

A Systematic Literature Review on Diabetic Retinopathy Stage Diagnosis Using Deep Learning Approach

Diabetic retinopathy is a medical condition that occurs due to diabetic mellitus causing blindness in the later stages. As the name says it is caused for people with the diabetes of type 1 and type 2 for a period of 20 years or more. However, early diagnosis and proper treatment at the initial stages could reduce aggressive forms of threatening retinopathy by up to 90%. According to the 2019 census from the ninth edition of the IDF Diabetes Atlas, India is put in the second slot right up to 2045 with people who are aged between 20-79 years. In 2019, India had 77 diabetic patients. In the recent survey of 2022 by the Union Health Ministry of India, almost 17% of the Indian population has diabetic retinopathy of which 3.6% is sight threatening. Specific to the rural population, 10.4% had diabetes of which 10.3% were diabetic retinopathy affected. From the WHO survey, it is estimated that by 2030, diabetics with retinopathy will increase by 50%. Without proper treatment, the individual is more likely to lose his vision. So, to prevent it, early detection of diabetic retinopathy and its stage is necessary. Key Words: Diabetic retinopathy, fundus, proliferative and non-proliferative, deep learning.

Epiretinal Macrophage-like Cells on Optical Coherence Tomography: Potential Inflammatory Imaging Biomarker of Severity in Diabetic Retinopathy.

To investigate the clinical value of epiretinal macrophage-like cells (eMLC) in different stages of diabetic retinopathy (DR), including diabetic macular edema (DME). One hundred and seventy-six eyes of 176 patients, including 31 diabetes eyes without retinopathy (NDR), 24 with mild non-proliferative DR (NPDR), 37 with moderate NPDR, 32 with severe NPDR, and 52 with proliferative DR (PDR), were compared to 30 healthy controls. The optic nerve head and macular region were examined using en face optical coherence tomography (OCT) and OCT angiography. A previously described technique was employed to measure the eMLCs on the inner limiting membrane. The optic nerve head (ONH) and macular eMLC densities increased with worsening DR stage and were higher in moderate, severe NPDR and PDR, especially in eyes with DME (all adjusted p<0.01). The ONH and macular eMLC densities in the DME groups were higher than those in their corresponding non-DME groups at the same DR stage (all p<0.05). The average macular thickness was correlated with macular eMLC density (standardized β=0.661, p<0.001) in patients with diabetes. The proportion of eyes with larger and plumper eMLCs increased with worsening DR and was higher in moderate, severe NPDR, PDR and eyes with DME (p=0.018, p<0.001, p<0.001 and p<0.001 respectively). Increased density along with morphological changes of eMLCs are observed beginning with moderate NPDR, and correlate with the progression of DR, including DME.

Association of eGFR with stages of diabetic retinopathy and age-related macular degeneration in Indian population.

To investigate the influence of glomerular filtration rate in renal disease decline and its association with diabetic retinopathy (DR) and age-related macular degeneration (ARMD) in patients in South India. A population-based cross-sectional study was conducted including participants with DR and ARMD recruited from urban and rural populations. The data collection included medical history, anthropometric measurements, and ophthalmic work-up. The estimated glomerular filtration rate (eGFR) was calculated using the equation of chronic kidney disease-epidemiology collaboration (CKD-EPI). The grading of AMD was done by a single experienced (more than 5 years) vitreoretinal surgeon as per the International ARM Epidemiological Study Group and it was staged based on grading in the worsened eye. A decline in eGFR was observed as the severity of DR increased (P < 0.001). Baseline characteristics such as age (P < 0.001), duration of diabetes (P < 0.001), gender (P < 0.001), creatinine (P < 0.001), albumin to creatinine ratio (ACR; P < 0.001), albuminuria (P = 0.023), blood urea (P < 0.001), and high-density lipoprotein (HDL; P = 0.003) were found to be statistically significant. The risk for developing DR with CKD was found to be 5 times higher in male patients compared to female patients. Age and high blood urea level, diastolic blood pressure, mild and moderate DR were the risk factors associated with CKD. A decline in eGFR was observed as the severity of ARMD increased (P < 0.001). The risk factors associated with CKD were age, gender, smoking, alcohol consumed, presence of hypertension, duration of diabetes, systolic and diastolic blood pressure, history of diabetes, body mass index (BMI), serum triglycerides, and serum HDL cholesterol. Reduced eGFR values were associated with an increase in the severity of DR and ARMD.