Complications Of Diabetic Retinopathy Research Articles

Continuous Glucose Data Construction and Risk Assessment Application of Diabetic Retinopathy Complications for Patients with Type 2 Diabetes Mellitus

Managing diabetes mellitus (DM) includes achieving acceptable blood glucose levels and minimizing the risk of complications from DM. The appropriate glucose sensing method is continuous glucose monitoring (CGM). Effective evaluation metrics that reflect glucose fluctuations can be realized. However, compared with self-monitoring of blood glucose (SMBG), CGM data are not easy to obtain. Therefore, this article studies a fusion model to achieve this objective, including Gaussian process regression (GPR) and long short-term memory (LSTM). Compared with the three commonly used LSTM, GPR, and support vector machine, the proposed model can construct accurate results. By using the constructed CGM data, the conventional metrics, such as the mean amplitude of glycemic excursion (MAGE), mean blood glucose (MBG), standard deviation (SD), and time in range (TIR), are calculated. These metrics and other variables are input into statistical methods to realize diabetic retinopathy risk assessment. In this way, the relationship between the glycemic variability of the constructed CGM data by the mathematical model and DR could be achieved. The utilized statistical methods include single-factor analysis and binary multivariate logistic regression analysis. Results show that fasting blood glucose, disease course, history of hypertension, MAGE and TIR are independent risk factors for DR.

What are the effects of anti-vascular endothelial growth factors (anti-VEGF) on people undergoing vitrectomy for complications of proliferative diabetic retinopathy?

What are the effects of anti-vascular endothelial growth factors (anti-VEGF) on people undergoing vitrectomy for complications of proliferative diabetic retinopathy?

Prevalence and Correlation between HbA1c Control and Duration of Diabetes with Blindness in the Eastern Part of Libya: Double Centers Study

A prospective cross-sectional study of diabetic patients registered at the Eye department of Tobruk Medical Center in Tobruk-Libya between (01.06.2023 to 29.02.2024). At the same time data was collected in the eye department in Alwahda Derna Teaching Hospital, Data was collected using the same administered questionnaire. Grading of DR was done by slit-lamp examination and Fundoscopy by an ophthalmologist. Descriptive analysis included percentage mean, median, and p - value by using SPSS 25. There were 185 diabetic patients, ages ranging between 30 and 90 years, with a mean of 58, the majority (97.6%) were of Libyan nationality. There were 86 males and 99 females. Patients with a duration of diabetes ranging between 11 and 15 years were at almost a five-fold risk of developing DR compared to those with a duration of < 10 years. Most of advanced complicated diabetic retinopathy cases had diabetes for more than fifteen years, and no advanced disease in the cases with a duration of less than 10 years. The patients with poor controlled blood sugar and HbA1c > 9 throughout the disease were at almost five-folded risk of developing DR compared to those with moderate controlled diabetes cases were HbA1c between (7.5 - 9), patients with poor control of diabetes HbA1c> 9 was 25-folded risk of developing PRP than cases with good control HbA1c < 7.5. The majority of advanced diabetic retinopathy cases were correlated with non-controlled diabetes mellitus HbA1c > 9, where no advanced complication was recorded in well-controlled cases.

Impact of glucagon-like peptide-1 receptor agonists on diabetic retinopathy: A meta-analysis of clinical studies emphasising retinal changes as a primary outcome.

To determine if glucagon-like peptide-1 receptor agonists (GLP-1RA) are associated with the development and progression of diabetic retinopathy (DR). A systematic search was conducted on PubMed, Cochrane Library, and Embase from inception to February 2024 to identify clinical studies reporting the development of and changes in DR as the primary outcome in patients with type 2 diabetes taking GLP-1RA, insulin, or oral antidiabetic medication (OAD). Two researchers independently completed the search and referred to a third as necessary. Data for meta-analysis was pooled using a random-effects model. Analysis of seven studies representing 242 537 patients showed a significantly decreased risk of incidence of DR between GLP-1RA and insulin use (RR = 0.66, 95% CI (0.48, 0.91), p = 0.01). There was no difference in the risk of DR complications (e.g., vitreous haemorrhage, retinal detachment, or requiring treatment with intravitreal injections, lasers, vitrectomy). Between GLP-1RA and OAD use, there was no difference in the risk of incidence of DR, while there was a significantly increased risk of DR complications (RR = 1.39, 95% CI (1.07, 1.80), p = 0.01). Our findings indicate no elevated risk of incidence of DR linked to GLP-1RA compared to insulin. In fact, GLP-1RA may offer potential advantages over insulin regarding the overall incidence of DR. The increased risk of DR requiring treatment and associated complications in the GLP-1RA group compared to OAD may be due to the transient progression of DR associated with a rapid decrease in HbA1c - a phenomenon not specific to GLP-1RA and warrants further investigation.

Efficacy and Safety of Fluocinolone Acetonide Implant in Diabetic Macular Edema: Practical Guidelines from Reference Center.

Diabetic macular edema (DME) is a common complication of diabetic retinopathy. Treatment with intravitreal injections is effective in most cases but is associated with a high therapeutic burden for patients. This implies the need for long-term treatments, such as the fluocinolone acetonide (FAc) implant. A review of basic science, pharmacology, and clinical data was conducted to provide a state-of-the-art view of the FAc implant in 2024. Although generally well tolerated, the FAc implant has been associated with ocular hypertension and cataract, and caution should be advised to the patients in this regard. By synthesizing information across these domains, a comprehensive evaluation can be attained, facilitating informed decision-making regarding the use of the FAc implant in the management of DME. The main objective of this review is to provide clinicians with guidelines on how to introduce and use the FAc implant in a patient with DME.

SURGICAL OUTCOMES IN CONCURRENT SICKLE CELL AND DIABETIC RETINOPATHY.

To report the clinical features and outcomes in eyes that underwent vitreoretinal surgery for complications of concurrent sickle cell retinopathy and diabetic retinopathy. Retrospective, consecutive case series of all eyes that underwent vitreoretinal surgery for complications secondary to concurrent sickle cell retinopathy and diabetic retinopathy between January 01, 2014, and December 31, 2021. The study included 20 eyes of 14 patients. Indications for surgery included tractional retinal detachment in 12 eyes (60%), combined tractional retinal detachment/rhegmatogenous retinal detachment in 6 eyes (30%), and vitreous hemorrhage in 2 eyes (10%). Pars plana vitrectomy was performed in all eyes. One eye received a scleral buckle at the same time as pars plana vitrectomy. There was no change in mean best-corrected visual acuity at the last follow-up examination (1.5 [20/678]) when compared with mean preoperative best-corrected visual acuity (1.6 [20/762], P = 0.83). Preoperative best-corrected visual acuity correlated with postoperative best-corrected visual acuity at the last follow-up examination in eyes with retinal detachment (r = 0.49, P = 0.04). Single operation anatomic success was achieved in 11 of 17 eyes (65%) with retinal detachment. Functional and anatomic outcomes after surgery in eyes with concurrent sickle cell retinopathy and diabetic retinopathy are relatively poor.

Anterior Chamber Flare as a Non-Invasive Assessment of Intraocular Immune Status and Ocular Complications in Proliferative Diabetic Retinopathy.

Proliferative diabetic retinopathy (PDR) is a vision-threatening complication of diabetes mellitus (DM). Anterior chamber (AC) flare and intraocular cytokines are potent biomarkers reflecting the intraocular immune status in PDR. This study aimed to elucidate the complex interrelationship between AC flare and intraocular cytokines in PDR eyes. A retrospective observational study was conducted on 19 PDR eyes of 19 patients with type 2 DM, and on 19 eyes of 19 patients with idiopathic macular hole or epiretinal membrane as controls. AC flare was measured before pars plana vitrectomy (PPV). Aqueous humor (AH) and vitreous fluid (VF) samples were collected at the time of PPV, and the quantities of 27 cytokines in both intraocular fluids were analyzed. In the PDR and control groups, Spearman's rank correlation analysis revealed a positive correlation between AC flare and IL-8 level in both AH and VF. Additionally, IL-8 levels in AH correlated positively with IL-8 levels in VF. In the PDR group, receiver operating characteristic curve analysis identified IL-8 level in AH as a significant predictor for both diabetic macular edema (DME) and vitreous hemorrhage (VH) complications. The cut-off values of IL-8 were established at ≥26.6 pg/mL for DME and ≥7.96 pg/mL for VH. Given the positive correlation between AC flare and AH IL-8 level, the present findings suggest that AC flare value may potentially be a non-invasive biomarker for predicting DME.

Diabetic Retinopathy Using Deep Learning

Untreated diabetic retinopathy, a complication of uncontrolled diabetes, may lead to total blindness if not addressed promptly. Consequently, in order to avoid the serious complications of diabetic retinopathy, it is crucial to diagnose the condition early and treat it medically. Patients go through a lot of pain and suffering as ophthalmologists manually identify diabetic retinopathy. With the use of an automated method, diabetic retinopathy may be detected more rapidly, allowing for easier follow-up therapy to prevent more eye damage. This paper presents a machine learning strategy for feature extraction including exudates, hemorrhages, and micro aneurysms. The strategy involves a hybrid classifier that integrates support vector machine, k closest neighbour, random forest, logistic regression, and multilayer perceptron networks. To further assist in DR stage image recognition, for instance to detect blood vessels, future research may center on applying object identification techniques based on convolutional neural networks (CNNs).

Vitrectomy for cases of diabetic retinopathy.

Microvascular complications of diabetic retinopathy (DR) may require surgical intervention in the form of vitrectomy. Since its inception, diabetic vitrectomy has evolved with introduction of better instruments, newer techniques, and smaller port sizes. Common indications for diabetic vitrectomy include nonresolving vitreous hemorrhage, tractional retinal detachment, epiretinal membrane, progression of fibrovascular membranes despite laser therapy, recalcitrant diabetic macular edema, and neovascular glaucoma. Preoperative systemic stabilization is essential prior to planning surgery. Surgical techniques commonly used in diabetic vitrectomy are segmentation, delamination, and rarely en-bloc dissection. Modification in surgical techniques such as chandelier-assisted bimanual dissection and pharmacological adjuvants improve surgical outcomes in these patients. Prognosis in these patients could be improved with early intervention. Studies evaluating the outcome of vitrectomy in patients with early proliferative DR are required to understand the appropriate time of intervention in patients. Treatment aimed at arresting the progression of DR and gene therapy are avenues that need further evaluation. The following review will focus on covering the epidemiology of DR, indications of vitrectomy, preoperative considerations, surgical procedures of diabetic vitrectomy, methods of membrane dissection, pharmacological adjuvants to vitrectomy, outcomes of diabetic vitrectomy, and future directions of diabetic vitrectomy.

Identification of key biomarkers for early warning of diabetic retinopathy using BP neural network algorithm and hierarchical clustering analysis

Diabetic retinopathy is one of the most common microangiopathy in diabetes, essentially caused by abnormal blood glucose metabolism resulting from insufficient insulin secretion or reduced insulin activity. Epidemiological survey results show that about one third of diabetes patients have signs of diabetic retinopathy, and another third may suffer from serious retinopathy that threatens vision. However, the pathogenesis of diabetic retinopathy is still unclear, and there is no systematic method to detect the onset of the disease and effectively predict its occurrence. In this study, we used medical detection data from diabetic retinopathy patients to determine key biomarkers that induce disease onset through back propagation neural network algorithm and hierarchical clustering analysis, ultimately obtaining early warning signals of the disease. The key markers that induce diabetic retinopathy have been detected, which can also be used to explore the induction mechanism of disease occurrence and deliver strong warning signal before disease occurrence. We found that multiple clinical indicators that form key markers, such as glycated hemoglobin, serum uric acid, alanine aminotransferase are closely related to the occurrence of the disease. They respectively induced disease from the aspects of the individual lipid metabolism, cell oxidation reduction, bone metabolism and bone resorption and cell function of blood coagulation. The key markers that induce diabetic retinopathy complications do not act independently, but form a complete module to coordinate and work together before the onset of the disease, and transmit a strong warning signal. The key markers detected by this algorithm are more sensitive and effective in the early warning of disease. Hence, a new method related to key markers is proposed for the study of diabetic microvascular lesions. In clinical prediction and diagnosis, doctors can use key markers to give early warning of individual diseases and make early intervention.

Advancements in the Treatment of Diabetic Macular Edema: Current Strategies and Future Directions

This narrative review examines current and emerging treatment strategies for diabetic macular edema (DME), a complication of diabetic retinopathy characterised by fluid accumulation in the macula, which can lead to vision impairment. The incidence of DME is particularly high in patients with long-standing diabetes and advanced retinopathy. The current treatment options for DME include anti-vascular endothelial growth factor (anti-VEGF) agents, corticosteroids, and laser therapies. Anti-VEGF agents, including bevacizumab, ranibizumab, aflibercept, and the more recently developed brolucizumab and faricimab, have been demonstrated to reduce macular thickness and improve visual acuity. Brolucizumab offers the advantage of fewer injections due to its longer duration of action, although it carries a higher risk of ocular inflammation compared to other anti-VEGF agents. The dual inhibition of the VEGF and angiopoietin-2 (Ang-2) pathways by faricimab may enhance vascular stability and reduce inflammation, potentially improving patient outcomes. Steroid therapies, including dexamethasone, fluocinolone acetonide, and triamcinolone acetonide, represent an alternative for patients who do not respond adequately to anti-VEGF treatment. Laser therapies, including focal, navigated, and subthreshold laser treatments, remain a crucial component in the management of DME, with the ability to seal leaking vessels and reduce fluid accumulation. In order to achieve the best outcomes for patients, it is essential to continue to advance these treatment modalities and adopt a personalised, multifaceted approach.

Burden of Disease Study of Patients with Diabetic Macular Oedema in Spain.

Diabetic macular oedema (DMO) is a complication of diabetic retinopathy that can result in vision loss. The disease can impact different spheres of a patient's life, including physical and psychological health, work, and activities of daily living, entailing an important use of healthcare and non-healthcare resources. This study aimed to estimate the socio-economic burden of DMO in Spain. The burden of DMO was estimated from a societal perspective, per patient, year of treatment since diagnosis, and type of treatment. Four categories were considered: direct healthcare costs (DHC), direct non-healthcare costs (DNHC), labour productivity losses (LPL), and intangible costs (IC) associated with loss of quality of life. Average annual costs were calculated by multiplying the resources used per patient by their corresponding unit price (or financial proxy). For a more accurate estimation, differences in resource use between treatments (intravitreal anti-vascular endothelial growth factor injections of ranibizumab or aflibercept, and intravitreal dexamethasone implants) and year since diagnosis (first, second, and third year or beyond) were considered and presented separately. The reference year for costs was 2021. The average annual costs of DMO in the first year of treatment after diagnosis was estimated at €18,774, €17,512, and €16,188 per patient treated with ranibizumab, aflibercept, and dexamethasone, respectively. This burden would be reduced to €15,783, €15,701, and €12,233 in the second year, and to €15,119, €15,043, and €12,790 in the third year, respectively. Diagnosis of DMO entails an additional one-off cost of €485. DHC accounted for the greatest proportion of total annual costs per patient, independent of the year, with LPL also making an important contribution to total costs. The socio-economic impact of DMO on patients, the healthcare system, and society at large is substantial. The constant increase in its prevalence accentuates the need for planning and implementation of healthcare strategies to prevent vision loss and reduce the socio-economic burden of the disease.

Prevalence and associated factors of proliferative diabetic retinopathy among adult diabetic patients in Northwest Ethiopia, 2023: A cross-sectional multicenter study.

Proliferative diabetic retinopathy is one of the advanced complications of diabetic retinopathy. If left untreated, almost all eyes could lose a significant portion of their vision within four months. There is limited evidence regarding the magnitude of proliferative diabetic retinopathy and associated factors in the study setting and also in Ethiopia. To determine the magnitude and associated factors of proliferative diabetic retinopathy among adult diabetic patients attending Specialized Comprehensive Hospital-Diabetic Care Clinics in Northwest Ethiopia, 2023. A multicenter, hospital-based, cross-sectional study was conducted on 1219 adult diabetic patients selected by systematic random sampling technique. Data were collected through an in-person interview and physical examination. The Statistical Package for Social Science Version 20 was used to analyze the data. Logistic regression methods were used to test the association between predisposing factors and proliferative diabetic retinopathy. The adjusted odds ratio with a 95% confidence interval was used to determine the strength of association. The prevalence of proliferative diabetic retinopathy was 3.1% (95% CI: 2.10%-4.10%). Hypertension (AOR = 4.35 (95% CI: 1.87-10.12)), peripheral neuropathy (AOR = 3.87 (95% CI: 1.57-9.54)), nephropathy (AOR = 2.58 (95% CI: 1.13-5.87)), ≥10 years duration of diabetes mellitus (AOR = 5.30 (95% CI: 2.32-12.14)), insulin use (AOR = 3.07 (95% CI: 1.08-8.68)), and poor adherence to diabetes mellitus medications (AOR = 3.77 (95% CI: 1.64-8.64)) were confirmed to have statistically significant association with proliferative diabetic retinopathy. The prevalence of proliferative diabetic retinopathy among adult diabetic patients in the diabetes clinic was higher than the global study. Hypertension, peripheral neuropathy, nephropathy, ≥10 year's duration of diabetic mellitus, insulin use and poor adherence to diabetes mellitus medications were among the factors significantly associated with proliferative diabetic retinopathy.

Comparative Effectiveness of Glucagon-Like Peptide-1 Receptor Agonists, Sodium-Glucose Cotransporter 2 Inhibitors, Dipeptidyl Peptidase-4 Inhibitors, and Sulfonylureas for Sight-Threatening Diabetic Retinopathy

To investigate whether the choice of glucose-lowering agent for type 2 diabetes (T2D) impacts a patient's risk of developing sight-threatening diabetic retinopathy complications. Retrospective observational database study emulating an idealized target trial. Adult (≥21 years) enrollees in United States commercial, Medicare Advantage, and Medicare fee-for-service plans from January 1, 2014, to December 31, 2021, with T2D and moderate cardiovascular disease (CVD) risk who had no baseline history of advanced diabetic retinal complications, initiating treatment with glucagon-like peptide-1 receptor agonists (GLP-1 RA), sodium-glucose cotransporter 2 inhibitors (SGLT2i), dipeptidyl peptidase-4 inhibitors (DPP-4i), and sulfonylureas. We used inverse propensity scoring weights in time-to-event Cox proportional hazards models. Treatment for either diabetic macular edema or proliferative diabetic retinopathy. The final study population included 371 698 patients, of whom 42 265 initiated GLP-1 RA, 53 476 initiated SGLT2i, 78 444 initiated DPP-4i, and 197 513 initiated sulfonylurea agents. The probability of treatment for sight-threatening retinopathy within 2 and 5 years was 0.3% and 0.7% for patients initiating SGLT2i (median follow-up 830 [interquartile range (IQR), 343-1401] days), 0.4% and 1.0% for GLP-1 RA (669 [IQR, 256-1167] days), 0.4% and 0.9% for DPP-4i (1263 [IQR, 688-1938] days), and 0.5% and 1.2% for sulfonylurea (1223 [IQR, 662-1879] days). Sodium-glucose cotransporter 2 inhibitors use was associated with a lower risk of treatment for sight-threatening retinopathy compared with all other medication classes, including GLP-1 RA (hazard ratio [HR], 0.73; 95% confidence interval [CI], 0.55-0.97), DPP-4i (HR, 0.79; 95% CI, 0.64-0.97), and sulfonylurea (HR, 0.61; 95% CI, 0.50-0.74). Glucagon-like peptide-1 receptor agonists use was associated with a similar risk of sight-threatening retinopathy as DPP-4i (HR, 1.07; 95% CI, 0.85-1.35) and sulfonylurea (HR, 0.83; 95% CI, 0.67-1.03). Sodium-glucose cotransporter 2 inhibitors use was associated with a lower risk of sight-threatening diabetic retinopathy among adults with T2D and moderate CVD risk compared with other glucose-lowering therapies. Glucagon-like peptide-1 receptor agonists do not confer increased retinal risk, relative to DPP-4i and sulfonylurea medications. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Short Term Effect of Pre-Operative Anti-VEGF on Angiogenic and Fibrotic Profile of Fibrovascular Membranes of Proliferative Diabetic Retinopathy.

Adjuvant, pre-operative intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections have been used to reduce peri-operative bleeding in eyes undergoing pars-plana vitrectomy for complications of proliferative diabetic retinopathy (PDR). To address the concern over their potential off-target effects of progressive fibrous contraction, we sought to dissect the transcriptional changes in the surgically extracted fibrovascular membranes (FVMs). We analyzed surgically extracted FVMs from 10 eyes: 4 eyes pretreated with intravitreal bevacizumab (IVB) and 6 untreated eyes. FVMs were digested into single cells, mRNA was extracted from endothelial cell-enriched (microbead selection with CD31) and non-endothelial cell compartments, followed by RT-qPCR quantification. We then compared the relative expression of genes involved in angiogenesis, endothelial cell integrity, and myofibroblastic processes between treated and untreated FVMs. Endothelial cells from IVB pretreated FVMs showed significant reduction of VEGFA, VEGF receptors (FLT1 and KDR), and angiopoietin 2 expression as well as increased vascular endothelial cadherin and endothelin, suggesting reduced angiogenesis and enhanced vascular integrity. The non-endothelial cell fraction showed decreased expression of VEGFA and fibronectin, without significant difference in the expression of other profibrotic factors. Our findings confirm that adjuvant pre-operative IVB decreased fibronectin and increase endothelin-1 expression without affecting other profibrotic gene expression, uncovering an important interaction between IVB and endothelin-1 that deserves further study.

Интраоперационная периферическая эндолазеркоагуляция сетчатки в профилактике неоваскулярной глаукомы

Neovascular glaucoma (NVG) is a severe long-term complication of proliferative diabetic retinopathy (PDR), including that developing in patients after vitreoretinal surgical treatment. Methods of influence aimed at breaking the cascade of biochemical processes leading to neovascularization, thereby preventing the development of NVG, are pathogenetically justified. The use of retinal laser photocoagulation (RLP) of ischemic zones and intravitreal angiogenesis inhibitors (AI) are effective. The problem of choosing a method and developing a strategy for preventing NVG is relevant. Purpose. To comparatively evaluate the effectiveness of peripheral intraoperative endolaser RLP in the prevention of NVG. Material and methods. The study included 182 patients (182 eyes) who received vitreoretinal surgical treatment for PDR complications. At baseline, all patients did not have NVG or other forms of glaucoma. Patients were divided into comparable groups depending on the type of intraoperative intervention. All patients underwent standard three-port 25 Ga vitrectomy with membrane peeling. Patients in 2nd group underwent panretinal endolaser RLP in the area from the arcades to retianl equator. Patients in 3rd group underwent peripheral endolaser RLP in the area from the retinal equator to ora serrata in combination with intravitreal injection of AI. In 1st group, endolaser RLP and AI were not used. Results. At a follow-up period of 1 month after treatment, no statistically significant differences in the incidence of rubeosis iridis were observed, and there were no cases of NVG development. At a follow-up period of 12 months after treatment in 3rd group, the development of rubeosis iridis was noted in one case and the absence of cases of NVG. In 2nd group, rubeosis iridis was detected in five patients, and NVG was detected in four patients. In 1st group, rubeosis iridis was detected in seven patients, and NVG was detected in ten patients, which is statistically significantly higher than in the other groups of the study. Conclusion. It has been established that the use of peripheral endolaser RLP in combination with intravitreal injection of AI is the most effective method for the prevention of postoperative neovascular complications in the anterior segment of the eye. Further study of the method on a representative sample of patients and in a longer postoperative period is promising. Keywords: vitreoretinal surgery, proliferative diabetic retinopathy, retinal laser photocoagulation, neovascular glaucoma, neoangiogenesis

Novel Antidiabetic Drugs and the Risk of Diabetic Retinopathy: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Background: The aim of this study is to compare the effect of sodium-glucose cotransporter-2 inhibitors (SGLT-2i), glucagon-like peptide-1 receptor agonists (GLP-1RA), and dipeptidyl peptidase-4 inhibitors (DPP-4i) on the risk of diabetic retinopathy (DR) in patients with type 2 diabetes (DM2). Methods: We systematically searched the databases Pubmed, Embase, and Clinicaltrials up to October 2, 2023, for randomized clinical trials (RCTs) of drugs from the GLP-1RA, SGLT-2i, and DPP-4i groups, with at least 24 weeks duration, including adult patients with DM2 and reported ocular complications. A pairwise meta-analysis was performed to calculate the odds ratio (OR) of DR incidents. Results: Our study included 61 RCTs with a total of 188,463 patients and 2773 DR events. Pairwise meta-analysis showed that included drug groups did not differ in the risk of DR events: GLP1-RA vs. placebo (OR 1.08; CI 95% 0.94, 1.23), DPP-4i vs. placebo (OR 1.10; CI 95% 0.84, 1.42), SGLT2i vs. placebo (OR 1.02; CI 95% 0.76, 1.37). Empagliflozin may be associated with a lower risk of DR, but this sub-analysis included only three RCTs (OR 0.38; 95% CI 0.17, 0.88, p = 0.02). Conclusions: Based on currently available knowledge, it is challenging to conclude that the new antidiabetic drugs significantly differ in their effect on DR complications.

Clinical Profile and Ocular Morbidities in Patients with Both Diabetic Retinopathy and Uveitis

PurposeTo describe the clinical profile and complications of diabetic retinopathy (DR) and uveitis in patients with co-existing conditions and to derive associations based on site of primary inflammation, stage of DR and complications of each. DesignSingle-center, cross-sectional observational study. Participants66 patients with co-existing diabetic retinopathy and uveitis. MethodsElectronic medical records of 66 such cases were evaluated. The demographic data, diabetic status, clinical characteristics and complications of DR and uveitis on the final follow-up were recorded. Main Outcome MeasuresAssociations between best corrected visual acuity, prevalence of various stages and complications of DR among eyes with and without uveitis. Also, correlation between the intensity and primary sites of inflammation among eyes with proliferative and non-proliferative changes. ResultsOf the 132 eyes, all had DR and 97 eyes had uveitis (35 unilateral and 31 bilateral cases). Mean age of patients was 53.4±8.7 years, duration of diabetes was 10.5±6.9 years and duration of uveitis was 61.3±68.8 months. 54.6% uveitis patients had anterior uveitis, 20.6% had intermediate, 10.3% posterior and 14.4% pan-uveitis. 49.5% eyes had proliferative diabetic retinopathy (PDR) changes. There was a higher proportion PDR cases among anterior (56.6%), posterior (70%), and pan uveitis (64.3%), with difference in anterior uveitis cases approaching statistical significance (p=0.067). Conversely, significant (p<0.001) intermediate uveitis cases had non-proliferative changes (80%). Final BCVA was significantly poorer in the group with uveitis (p=0.045). The proportion of fibrovascular proliferations, tractional detachments and iris neovascularisation among proliferative retinopathy eyes with uveitis (14.6%, 18.8% and 12.5% respectively) was higher than those without uveitis (5.3%, 10.5% and 5.3%). Among uveitis cases, 58.5% eyes developed cataracts, 44.3% had posterior synechiae, 12.3% developed secondary glaucoma, 4.1% had epiretinal membrane, 4.1% had band-shaped keratopathy and 1.0% developed macular neovascularisation. ConclusionsEyes with co-existing DR and uveitis have a higher prevalence of neovascular and uveitis complications along with a risk of poorer visual outcomes. Treatment should aim at limiting the duration and intensity of inflammation. Strict glycaemic control is essential for inflammation control and preventing the progression of DR to more advanced stages.

Controllable editing via diffusion inversion on ultra-widefield fluorescein angiography for the comprehensive analysis of diabetic retinopathy.

By incorporating multiple indicators that facilitate clinical decision making and effective management of diabetic retinopathy (DR), a comprehensive understanding of the progression of the disease can be achieved. However, the diversity of DR complications poses challenges to the automatic analysis of various information within images. This study aims to establish a deep learning system designed to examine various metrics linked to DR in ultra-widefield fluorescein angiography (UWFA) images. We have developed a unified model based on image generation that transforms input images into corresponding disease-free versions. By incorporating an image-level supervised training process, the model significantly reduces the need for extensive manual involvement in clinical applications. Furthermore, compared to other comparative methods, the quality of our generated images is significantly superior.

Clinical Features for Detecting Diabetic Macular Edema using Artificial Intelligence

Background:Vision is a valuable part of life: influencing our perception of the world and of memories. Diabetes, and more specifically, Diabetic Retinopathy (DR) can affect our vision, taking away sight potentially permanently if left untreated. Currently, Diabetic Retinopathy is the leading cause for adult blindness and will continue to rise with increasing prevalence of adult diabetes. Diabetic Macular Edema (DME), a complication of DR, is diagnosed by ophthalmologists using optical coherence tomography (OCT); however, the sheer amount of DME-related imaging creates a time strain on ophthalmologists, creating a demand to further optimize the image reading process. In this study, we hypothesize that increasing the rate and ease of diagnosing DME by introducing artificial intelligence-based methods in primary medical clinics will increase the long-term preservation of ocular health in diabetic patients.&#x0D; Methods:Due to the nature of our retrospective cohort study, consent was not acquired and images were also de-identified. We categorized 676 patient files by HbA1c, non-proliferative diabetic retinopathy (NPDR) severity, and proliferative diabetic retinopathy (PDR). Retinal OCT images were annotated to identify central macular edema, a common feature of DME. Retinal fundus images were also annotated to identify microaneurysms and hemorrhages, two additional features commonly used for detecting either DR or DME.&#x0D; Results:A lesion features dataset was prepared to train our AI model. OCT and fundus imaging features were extracted and combined to train the AI model for DME detection. From annotations of the in-house Macular thickness dataset, it was seen that 167 patients had DME from the total 389 diabetic retinopathy patients.&#x0D; Conclusion:We will continue to prepare more datasets like the macular thickness dataset for our AI. We predict that after our AI receives substantial training with the datasets, the AI will potentially demonstrate some capability of diagnosing DME, supporting its use in medical diagnostics.