The Predictive Utility of Circulating PCSK9 Levels on Diabetic Retinopathy Stage.

PURPOSE: To investigate the value of proprotein-converting subtilisin kexin type 9 (PCSK9) levels in type 2 diabetes mellitus (T2D) patients with different stages of diabetic retinopathy (DR) and to compare these findings with a healthy control group without diabetes mellitus (DM). METHODS: A total of 135 patients, 100 of whom were patients with T2D and 35 of whom were in the health control group, were included in this prospective study. T2D patients were divided into three groups: the first group included 34 people with T2D without DR, the second group had 32 people with non-proliferative DR (NPDR), and the third group had 34 people with proliferative DR (PDR). Serum PCSK9 levels were analyzed and compared between the groups. RESULTS: Forty-nine percent of the participants were female, and the mean age was 64 ± 9.1 years, with no statistically significant results between the four groups in terms of age and sex. The mean serum PCSK9 value was significantly different (p = 0.01) when all groups were evaluated, and statistically significant change was observed with the progression of DR. When serum PCSK9 levels were evaluated in all T2D patients (groups 1, 2, and 3), a medium-level correlation was observed with low-density lipoprotein (p < 0.05). CONCLUSION: Serum PCSK9 values differed significantly in diabetic patients compared to the control group. One should be clinically cautious about the usefulness of circulating PCSK9 concentrations as an indicator of the risk of diabetic retinopathy.

Diabetes management in the era of artificial intelligence.

Artificial intelligence is growing quickly, and its application in the global diabetes pandemic has the potential to completely change the way this chronic illness is identified and treated. Machine learning methods have been used to construct algorithms supporting predictive models for the risk of getting diabetes or its complications. Social media and Internet forums also increase patient participation in diabetes care. Diabetes resource usage optimisation has benefited from technological improvements. As a lifestyle therapy intervention, digital therapies have made a name for themselves in the treatment of diabetes. Artificial intelligence will cause a paradigm shift in diabetes care, moving away from current methods and toward the creation of focused, data-driven precision treatment.

Transforming the future of ophthalmology: artificial intelligence and robotics' breakthrough role in surgical and medical retina advances: a mini review.

Over the past decade, artificial intelligence (AI) and its subfields, deep learning and machine learning, have become integral parts of ophthalmology, particularly in the field of ophthalmic imaging. A diverse array of algorithms has emerged to facilitate the automated diagnosis of numerous medical and surgical retinal conditions. The development of these algorithms necessitates extensive training using large datasets of retinal images. This approach has demonstrated a promising impact, especially in increasing accuracy of diagnosis for unspecialized clinicians for various diseases and in the area of telemedicine, where access to ophthalmological care is restricted. In parallel, robotic technology has made significant inroads into the medical field, including ophthalmology. The vast majority of research in the field of robotic surgery has been focused on anterior segment and vitreoretinal surgery. These systems offer potential improvements in accuracy and address issues such as hand tremors. However, widespread adoption faces hurdles, including the substantial costs associated with these systems and the steep learning curve for surgeons. These challenges currently constrain the broader implementation of robotic surgical systems in ophthalmology. This mini review discusses the current research and challenges, underscoring the limited yet growing implementation of AI and robotic systems in the field of retinal conditions.

Mendelian randomization study and mediation analysis about the relation of inflammatory bowel disease and diabetic retinopathy: the further exploration of gut-retina axis.

Background: The concept of the gut-retinal axis proposed by previous scholars primarily focused on the relationship between intestinal microbiota and retinal diseases, and few further expanded the relationship between intestinal diseases and retinal diseases. To further substantiate the concept of the gut-retinal axis, we analyzed inflammatory bowel disease (IBD) and diabetic retinopathy (DR) using Mendelian randomization (MR), and use mediation analysis to further explore the potential substances that influence this causal relationship. Methods: The genome-wide association study's (GWAS) summary statistics for genetic variations were utilized in a Mendelian randomization (MR) investigation. GWAS data on IBD (including ulcerative colitis (UC), Crohn's disease (CD), and IBD) for non-Finnish Europeans (NFE) were sourced from published articles. In contrast, data on DR (including DR and diabetic maculopathy (DMP)) were obtained from FinnGen R9. The causal relationship has been investigated using inverse variance weighted (IVW), MR-Egger, and weighted median and sensitivity analysis was applied to verify the stability of the results. In addition, we applied mediation analysis to investigate whether circulating inflammatory proteins and plasma lipids played a mediating role, and calculated its effect ratio. Results: The causal relationship between IBD and DR was discovered by employing the inverse variance weighted (IVW) method and weighted median method. In forward MR, UC was significantly associated with lower risk of DR (IVW: OR=0.874; 95%CI= 0.835-0.916; P value= 1.28E-08) (Weighted median: OR=0.893; 95%CI= 0.837-0.954; P value= 7.40E-04). In reverse MR, it was shown that DR (IVW: OR=0.870; 95%CI= 0.828-0.914; P value= 2.79E-08)(Weighted median: OR=0.857; 95%CI= 0.801-0.916; P value= 6.40E-06) and DMP (IVW: OR=0.900; 95%CI= 0.865-0.937; P value= 3.34E-07)(Weighted median: OR=0.882; 95%CI= 0.841-0.924; P value= 1.82E-07) could reduce the risk of CD. What's more, DR is associated with a lower risk of IBD according to genetic prediction (IVW: OR=0.922; 95%CI= 0.873-0.972; P value= 0.002) (Weighted median: OR=0.924; 95%CI= 0.861-0.992; P value= 0.029). Fibroblast growth factor 21 (FGF21), phosphatidylcholine (PC), and triacylglycerol (TG) serve as mediators in these relationships. Conclusions: Our research offers novel insights and sources for investigating the gut-retina axis in the genetic relationship between IBD and DR. We discover four mediators and more about the association between the intestine and retinal disorders and provide more evidence for the gut-retinal axis theory.

Segmentation of retinal microaneurysms in fluorescein fundus angiography images by a novel three-step model.

Introduction: Microaneurysms serve as early signs of diabetic retinopathy, and their accurate detection is critical for effective treatment. Due to their low contrast and similarity to retinal vessels, distinguishing microaneurysms from background noise and retinal vessels in fluorescein fundus angiography (FFA) images poses a significant challenge. Methods: We present a model for automatic detection of microaneurysms. FFA images were pre-processed using Top-hat transformation, Gray-stretching, and Gaussian filter techniques to eliminate noise. The candidate microaneurysms were coarsely segmented using an improved matched filter algorithm. Real microaneurysms were segmented by a morphological strategy. To evaluate the segmentation performance, our proposed model was compared against other models, including Otsu's method, Region Growing, Global Threshold, Matched Filter, Fuzzy c-means, and K-means, using both self-constructed and publicly available datasets. Performance metrics such as accuracy, sensitivity, specificity, positive predictive value, and intersection-over-union were calculated. Results: The proposed model outperforms other models in terms of accuracy, sensitivity, specificity, positive predictive value, and intersection-over-union. The segmentation results obtained with our model closely align with benchmark standard. Our model demonstrates significant advantages for microaneurysm segmentation in FFA images and holds promise for clinical application in the diagnosis of diabetic retinopathy. Conclusion: The proposed model offers a robust and accurate approach to microaneurysm detection, outperforming existing methods and demonstrating potential for clinical application in the effective treatment of diabetic retinopathy.

Case Report: Longitudinal Evaluation and Treatment of a Melanoma-Associated Retinopathy Patient.

Melanoma-associated retinopathy (MAR) is a paraneoplastic syndrome associated with cutaneous metastatic melanoma in which patients develop vision deficits that include reduced night vision, poor contrast sensitivity, and photopsia. MAR is caused by autoantibodies targeting TRPM1, an ion channel found in melanocytes and retinal ON-bipolar cells (ON-BCs). The visual symptoms arise when TRPM1 autoantibodies enter ON-BCs and block the function of TRPM1, thus detection of TRPM1 autoantibodies in patient serum is a key criterion in diagnosing MAR. Electroretinograms are used to measure the impact of TRPM1 autoantibodies on ON-BC function and represent another important diagnostic tool for MAR. To date, MAR case reports have included one or both diagnostic components, but only for a single time point in the course of a patient's disease. Here, we report a case of MAR supported by longitudinal analysis of serum autoantibody detection, visual function, ocular inflammation, vascular integrity, and response to slow-release intraocular corticosteroids. Integrating these data with the patient's oncological and ophthalmological records reveals novel insights regarding MAR pathogenesis, progression, and treatment, which may inform new research and expand our collective understanding of the disease. In brief, we find TRPM1 autoantibodies can disrupt vision even when serum levels are barely detectable by western blot and immunohistochemistry; intraocular dexamethasone treatment alleviates MAR visual symptoms despite high levels of circulating TRPM1 autoantibodies, implicating antibody access to the retina as a key factor in MAR pathogenesis. Elevated inflammatory cytokine levels in the patient's eyes may be responsible for the observed damage to the blood-retinal barrier and subsequent entry of autoantibodies into the retina.

The m6A-ncRNAs axis in diabetes complications: novel mechanism and therapeutic potential.

Diabetes, a multifaceted metabolic disorder, poses a significant global health burden with its increasing prevalence and associated complications, such as diabetic nephropathy, diabetic retinopathy, diabetic cardiomyopathy, and diabetic angiopathy. Recent studies have highlighted the intricate interplay between N6-methyladenosine (m6A) and non-coding RNAs (ncRNAs) in key pathways implicated in these diabetes complications, like cell apoptosis, oxidative stress, and inflammation. Thus, understanding the mechanistic insights into how m6A dysregulation impacts the expression and function of ncRNAs opens new avenues for therapeutic interventions targeting the m6A-ncRNAs axis in diabetes complications. This review explores the regulatory roles of m6A modifications and ncRNAs, and stresses the role of the m6A-ncRNA axis in diabetes complications, providing a therapeutic potential for these diseases.

Mechanistic and therapeutic perspectives of non-coding RNA-modulated apoptotic signaling in diabetic retinopathy.

Diabetic retinopathy (DR), a significant and vision-endangering complication associated with diabetes mellitus, constitutes a substantial portion of acquired instances of preventable blindness. The progression of DR appears to prominently feature the loss of retinal cells, encompassing neural retinal cells, pericytes, and endothelial cells. Therefore, mitigating the apoptosis of retinal cells in DR could potentially enhance the therapeutic approach for managing the condition by suppressing retinal vascular leakage. Recent advancements have highlighted the crucial regulatory roles played by non-coding RNAs (ncRNAs) in diverse biological processes. Recent advancements have highlighted that non-coding RNAs (ncRNAs), including microRNAs (miRNAs), circular RNAs (circRNAs), and long non-coding RNAs (lncRNAs), act as central regulators in a wide array of biogenesis and biological functions, exerting control over gene expression associated with histogenesis and cellular differentiation within ocular tissues. Abnormal expression and activity of ncRNAs has been linked to the regulation of diverse cellular functions such as apoptosis, and proliferation. This implies a potential involvement of ncRNAs in the development of DR. Notably, ncRNAs and apoptosis exhibit reciprocal regulatory interactions, jointly influencing the destiny of retinal cells. Consequently, a thorough investigation into the complex relationship between apoptosis and ncRNAs is crucial for developing effective therapeutic and preventative strategies for DR. This review provides a fundamental comprehension of the apoptotic signaling pathways associated with DR. It then delves into the mutual relationship between apoptosis and ncRNAs in the context of DR pathogenesis. This study advances our understanding of the pathophysiology of DR and paves the way for the development of novel therapeutic strategies.

Unveiling the Potential: A Comprehensive Review of Artificial Intelligence Applications in Ophthalmology and Future Prospects.

Artificial intelligence (AI) has emerged as a transformative force in healthcare, particularly in the field of ophthalmology. This comprehensive review examines the current applications of AI in ophthalmology, highlighting its significant contributions to diagnostic accuracy, treatment efficacy, and patient care. AI technologies, such as deep learning algorithms, have demonstrated exceptional performance in the early detection and diagnosis of various eye conditions, including diabetic retinopathy (DR), age-related macular degeneration (AMD), and glaucoma. Additionally, AI has enhanced the analysis of ophthalmic imaging techniques like optical coherence tomography (OCT) and fundus photography, facilitating more precise disease monitoring and management. The review also explores AI's role in surgical assistance, predictive analytics, and personalized treatment plans, showcasing its potential to revolutionize clinical practice and improve patient outcomes. Despite these advancements, challenges such as data privacy, regulatory hurdles, and ethical considerations remain. The review underscores the need for continued research and collaboration among clinicians, researchers, technology developers, and policymakers to address these challenges and fully harness the potential of AI in improving eye health worldwide. By integrating AI with teleophthalmology and developing AI-driven wearable devices, the future of ophthalmic care promises enhanced accessibility, efficiency, and efficacy, ultimately reducing the global burden of visual impairment and blindness.

Single-Cell RNA Sequencing Reveals Transcriptional Signatures and Cell-Cell Communication in Diabetic Retinopathy.

BACKGROUND: Diabetic retinopathy (DR) is a major cause of vision loss in workingage individuals worldwide. Cell-to-cell communication between retinal cells and retinal pigment epithelial cells (RPEs) in DR is still unclear, so this study aimed to generate a single-cell atlas and identify receptor‒ligand communication between retinal cells and RPEs. METHODS: A mouse single-cell RNA sequencing (scRNA-seq) dataset was retrieved from the GEO database (GSE178121) and was further analyzed with the R package Seurat. Cell cluster annotation was performed to further analyze cell‒cell communication. The differentially expressed genes (DEGs) in RPEs were explored through pathway enrichment analysis and the protein‒ protein interaction (PPI) network. Core genes in the PPI were verified by quantitative PCR in ARPE-19 cells. RESULTS: We observed an increased proportion of RPEs in STZ mice. Although some overall intercellular communication pathways did not differ significantly in the STZ and control groups, RPEs relayed significantly more signals in the STZ group. In addition, THBS1, ITGB1, COL9A3, ITGB8, VTN, TIMP2, and FBN1 were found to be the core DEGs of the PPI network in RPEs. qPCR results showed that the expression of ITGB1, COL9A3, ITGB8, VTN, TIMP2, and FBN1 was higher and consistent with scRNA-seq results in ARPE-19 cells under hyperglycemic conditions. CONCLUSION: Our study, for the first time, investigated how signals that RPEs relay to and from other cells underly the progression of DR based on scRNA-seq. These signaling pathways and hub genes may provide new insights into DR mechanisms and therapeutic targets.

Plasma metabolomics identifies key metabolites and improves prediction of diabetic retinopathy: development and validation across multi-national cohorts.

PURPOSE: To identify longitudinal metabolomic fingerprints of diabetic retinopathy (DR) and evaluate their utility in predicting DR development and progression. DESIGN: Multicenter, multi-ethnic cohort study. PARTICIPANTS: This study included 17,675 participants with baseline pre-diabetes/diabetes, in accordance with the 2021 American Diabetes Association guideline, and free of baseline DR from the UK Biobank (UKB); and an additional 638 diabetic participants from the Guangzhou Diabetic Eye Study (GDES) for external validation. METHODS: Longitudinal DR metabolomic fingerprints were identified through nuclear magnetic resonance assay in UKB participants. The predictive value of these fingerprints for predicting DR development were assessed in a fully withheld test set. External validation and extrapolation analyses of DR progression and microvascular damage were conducted in the GDES cohort. Model assessments included the C-statistic, net classification improvement (NRI), integrated discrimination improvement (IDI), calibration, and clinical utility in both cohorts. MAIN OUTCOME MEASURES: DR development, progression, and retinal microvascular damage. RESULTS: Of 168 metabolites, 118 were identified as candidate metabolomic fingerprints for future DR development. These fingerprints significantly improved the predictability for DR development beyond traditional indicators (C-statistic: 0.802, 95% CI, 0.760-0.843 vs. 0.751, 95% CI, 0.706-0.796; P = 5.56×10-4). Glucose, lactate, and citrate were among the fingerprints validated in the GDES cohort. Using these parsimonious and replicable fingerprints yielded similar improvements for predicting DR development (C-statistic: 0.807, 95% CI, 0.711-0.903 vs. 0.617, 95% CI, 0.494, 0.740; P = 1.68×10-4) and progression (C-statistic: 0.797, 95% CI, 0.712-0.882 vs. 0.665, 95% CI, 0.545-0.784; P = 0.003) in the external cohort. Improvements in NRIs, IDIs, and clinical utility were also evident in both cohorts (all P <0.05). In addition, lactate and citrate were associated to microvascular damage across macular and optic disc regions (all P <0.05). CONCLUSIONS: Metabolomic profiling has proven effective in identifying robust fingerprints for predicting future DR development and progression, providing novel insights into the early and advanced stages of DR pathophysiology.

Hsa_circ_0004776 regulates the retina neovascularization in progression of diabetic retinopathy via hsa-miR-382-5p/BDNF axis.

The aim of this work was to identify the regulatory function of hsa_circ_0004776 in the progression of diabetic retinopathy (DR). The direct interactions between hsa_circ_0004776 and hsa-miR-382-5p and between hsa-miR-382-5p and BDNF, were confirmed via dual-luciferase reporter assays. Quantitative Real-Time PCR analysis indicated that hsa_circ_0004776 was highly expressed in aqueous humour samples of DR patients and human retinal microvascular epithelial cells (hRECs) under a high-glucose environment, whereas hsa-miR-382-5p showed the opposite trend. Overexpressed hsa_circ_0004776 significantly enhanced DNA synthesis, proliferation, migration, and tube formation in hRECs in hyperglycaemia, while hsa-miR-382-5p mimics reversed these changes. Additionally, in a streptozotocin-induced Sprague-Dawley rat model of DR, vitreous microinjection of rno-miR-382-5p agomir reversed the pathologic features in the progression of DR, including retinal vascular leakage, capillary decellularization, loss of pericytes, fibrosis, and gliosis. Our results indicated that under hyperglycaemic conditions, hsa_circ_0004776 influences the progression of DR via hsa-miR-382-5p and thus represents a potential therapeutic target.

Evaluation of peripheral blood inflammatory biomarkers in sickle cell disease with and without retinopathy.

BACKGROUND: The aim of this study was to evaluate the clinical significance of blood-cell associated inflammation markers in patients with sickle cell disease (SCD) and sickle cell retinopathy (SCR). METHODS: Neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR), systemic immune inflammation index (SIII), systemic inflammation response index (SIRI), systemic inflammation modulation index (SIMI) and aggregate systemic inflammation index (AISI) were calculated. This study included 45 healthy controls (Group 1) and 100 SCD (Group 2). Patients in Group 2 were then divided into two groups: without SCR (Group 3) and with SCR (Group 4), and patients with SCR (Group 4) were further divided into two groups: non-proliferative sickle cell retinopathy (NPSCR) (Group 5) and proliferative sickle cell retinopathy (PSCR) (Group 6). RESULTS: The mean values for NLR, PLR, SIII, SIRI, AISI, and SIMI were significantly higher in Group 2 compared to Group 1 (p = 0.011 for NLR, p = 0.004 for SIII, and p < 0.001 for others). Furthermore, AISI and SIMI parameters demonstrated statistically significant discriminatory power to distinguish Group 5 from Group 6 (p = 0.0016 and p = 0.0006, respectively). CONCLUSION: Given the critical role of inflammatory mechanisms in the pathogenesis of SCD and its related complications, the assessment of blood-cell-associated inflammatory markers may present a pragmatic and advantageous approach to the clinical oversight and therapeutic intervention of SCD.

Risk evaluation for diabetic retinopathy in Chinese renal-biopsied type 2 diabetes mellitus patients.

AIM: To investigate diabetic retinopathy (DR) prevalence in Chinese renal-biopsied type 2 diabetes mellitus (T2DM) patients with kidney dysfunction, and to further evaluate its relationship with diabetic nephropathy (DN) incidence and the risk factors for DR development in this population. METHODS: A total of 84 renal-biopsied T2DM patients were included. Fundus and imaging examinations were employed for DR diagnosis. Demographic information and clinical measures along with renal histopathology were analyzed for comparisons between the DR and non-DR groups. Risk factors on DR development were analyzed with multiple logistic regression. RESULTS: DR prevalence was 50% in total. The incidences of DN, non-diabetic renal disease (NDRD) and mixed-type pathology were 47.6%, 19.0% and 33.3% in the DR group respectively, while 11.9%, 83.3% and 4.8% in the non-DR group. Systolic blood pressure, ratio of urinary albumin to creatine ratio, urinary albumin, 24-hours urinary protein, the incidence and severity of DN histopathology were found statistically increased in the DR group. Multiple logistic regression analysis showed histopathological DN incidence significantly increased the risk of DR development [odds ratio (OR)=21.664, 95% confidential interval (CI) 5.588 to 83.991, P<0.001 for DN, and OR=45.475, 95%CI 6.949 to 297.611, P<0.001 for mixed-type, respectively, in reference to NDRD)], wherein DN severity positively correlated. CONCLUSION: Renal histopathological evidence indicates DN incidence and severity increases the risk of DR development in Chinese T2DM patients inexperienced of regular fundus examinations.

Human umbilical cord mesenchymal stem cells derived-exosomes on VEGF-A in hypoxic-induced mice retinal astrocytes and mice model of retinopathy of prematurity.

AIM: To observe the effect of human umbilical cord mesenchymal stem cells (hUCMSCs) secretions on the relevant factors in mouse retinal astrocytes, and to investigate the effect of hUCMSCs on the expression of vascular endothelial growth factor-A (VEGF-A) and to observe the therapeutic effect on the mouse model of retinopathy of prematurity (ROP). METHODS: Cultured hUCMSCs and extracted exosomes from them and then retinal astrocytes were divided into control group and hypoxia group. MTT assay, flow cytometry, reverse transcription-polymerase chain reaction (RT-PCR) and Western blot were used to detect related indicators. Possible mechanisms by which hUCMSCs exosomes affect VEGF-A expression in hypoxia-induced mouse retinal astrocytes were explored. At last, the efficacy of exosomes of UCMSCs in a mouse ROP model was explored. Graphpad6 was used to comprehensively process data information. RESULTS: The secretion was successfully extracted from the culture supernatant of hUCMSCs by gradient ultracentrifugation. Reactive oxygen species (ROS) and hypoxia inducible factor-1α (HIF-1α) of mice retinal astrocytes under different hypoxia time and the expression level of VEGF-A protein and VEGF-A mRNA increased, and the ROP cell model was established after 6h of hypoxia. The secretions of medium and high concentrations of hUCMSCs can reduce ROS and HIF-1α, the expression levels of VEGF-A protein and VEGF-A mRNA are statistically significant and concentration dependent. Compared with the ROP cell model group, the expression of phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signal pathway related factors in the hUCMSCs exocrine group is significantly decreased. The intravitreal injection of the secretions of medium and high concentrations of hUCMSCs can reduce VEGF-A and HIF-1α in ROP model tissues. HE staining shows that the number of retinal neovascularization in ROP mice decreases with the increase of the dose of hUCMSCs secretion. CONCLUSION: In a hypoxia induced mouse retinal astrocyte model, hUCMSCs exosomes are found to effectively reduce the expression of HIF-1α and VEGF-A, which are positively correlated with the concentration of hUCMSCs exosomes. HUCMSCs exosomes can effectively reduce the number of retinal neovascularization and the expression of HIF-1α and VEGF-A proteins in ROP mice, and are positively correlated with drug dosage. Besides, they can reduce the related factors on the PI3K/AKT/mTOR signaling pathway.

Diabetic retinopathy identification based on multi-source-free domain adaptation.

AIM: To address the challenges of data labeling difficulties, data privacy, and necessary large amount of labeled data for deep learning methods in diabetic retinopathy (DR) identification, the aim of this study is to develop a source-free domain adaptation (SFDA) method for efficient and effective DR identification from unlabeled data. METHODS: A multi-SFDA method was proposed for DR identification. This method integrates multiple source models, which are trained from the same source domain, to generate synthetic pseudo labels for the unlabeled target domain. Besides, a softmax-consistence minimization term is utilized to minimize the intra-class distances between the source and target domains and maximize the inter-class distances. Validation is performed using three color fundus photograph datasets (APTOS2019, DDR, and EyePACS). RESULTS: The proposed model was evaluated and provided promising results with respectively 0.8917 and 0.9795 F1-scores on referable and normal/abnormal DR identification tasks. It demonstrated effective DR identification through minimizing intra-class distances and maximizing inter-class distances between source and target domains. CONCLUSION: The multi-SFDA method provides an effective approach to overcome the challenges in DR identification. The method not only addresses difficulties in data labeling and privacy issues, but also reduces the need for large amounts of labeled data required by deep learning methods, making it a practical tool for early detection and preservation of vision in diabetic patients.

Frequency of Restless Legs Syndrome in Pakistani Patients With Type 2 Diabetes Mellitus.

Objective To determine the frequency of restless legs syndrome (RLS) among Pakistani patients with type 2 diabetes mellitus. Methods This observational cross-sectional study was carried out in the Department of Medicine at Bahawal Victoria Hospital, Quaid-e-Azam Medical College, Bahawalpur, Pakistan, from January 2024 to May 2024. The National Institute of Health (NIH) diagnostic criteria were used to diagnose RLS. Type 2 diabetes mellitus was defined as patients with an HbA1c greater than 7.0%, two random blood glucose readings of ≥200 mg/dL, a previous history of diabetes diagnosis, or those taking anti-hyperglycemic medicines. Patients with a history of leg surgery or amputation, iron deficiency anemia, alcoholism, end-stage kidney disease, chronic liver disease, those on hemodialysis, and pregnant women were excluded from the study. After ethical approval and informed consent were obtained, 255 patients with type 2 diabetes mellitus were included in the study using a non-probability consecutive sampling technique. Demographic information including age, gender, and duration of diabetes was noted, and patients were assessed for diabetes control, peripheral neuropathy, retinopathy, and RLS Patient records were assessed for HbA1c levels and urine examination to diagnose nephropathy. All data were entered into SPSS version 23. A Chi-Square test was applied post-stratification using a p-value of less than 0.05 as significant. Results The mean age was 53.5 ± 12.8 years with 140 (54.9%) females. The mean duration of the disease and mean HbA1c were 6.8 ± 5.4 years and 9.8 ± 2.5%, respectively, with 191 (74.9%) patients having poor control of diabetes. Peripheral neuropathy was seen in 131 (51.4%) patients, retinopathy in 58 (22.7%), and nephropathy in 23 (9.0%). RLS was present in 34 (13.3%) patients with type 2 diabetes mellitus, showing a significant association with diabetes control (p-value = 0.001), peripheral neuropathy (p-value = 0.016), retinopathy (p-value = 0.006), and nephropathy (p-value = 0.011), but not with age (p-value = 0.122), gender (p-value = 0.217), or duration of diabetes (p-value = 0.922). Conclusion RLS was not an uncommon finding in patients with type 2 diabetes mellitus, being more common among those with poor diabetes control and the presence of other complications such as neuropathy, nephropathy, and retinopathy.

Prostanoid signaling in retinal vascular diseases.

The vasculature of the retina is exposed to systemic and local factors that have the capacity to induce several retinal vascular diseases, each of which may lead to vision loss. Prostaglandin signaling has arisen as a potential therapeutic target for several of these diseases due to the diverse manners in which these lipid mediators may affect retinal blood vessel function. Previous reports and clinical practices have investigated cyclooxygenase (COX) inhibition by nonsteroidal anti-inflammatory drugs (NSAIDs) to address retinal diseases with varying degrees of success; however, targeting individual prostanoids or their distinct receptors affords more signaling specificity and poses strong potential for therapeutic development. This review offers a comprehensive view of prostanoid signaling involved in five key retinal vascular diseases: retinopathy of prematurity, diabetic retinopathy, age-related macular degeneration, retinal occlusive diseases, and uveitis. Mechanistic and clinical studies of these lipid mediators provide an outlook for therapeutic development with the potential to reduce vision loss in each of these conditions.

Artificial intelligence in diabetic retinopathy screening: from idea to a medical device in clinical practice.

With the growing significance of artificial intelligence in healthcare, new perspectives are emerging in primary care. Diabetic retinopathy, a microvascular complication of diabetes mellitus, often remains unnoticed until patient is facing complications. Artificial intelligence presents a promising solution that can enhance the accessibility of diabetic retinopathy screening for a broader range of patients. The key challenge lies in successfully integrating the solution into clinical practice, a demanding process with multiple phases to ensure the resulting medical device is effective and safe for patient use. Aireen software uses artificial intelligence to perform diabetic retinopathy screening on retinal images captured by optical fundus cameras. The medical device complies with European Medical Device Regulation 2017/745 and was introduced to the market in 2023. Collaboration between physicians and the development team played a crucial role throughout the entire lifecycle of the medical device. Physicians were engaged in defining the intended use of the medical device, risk analysis, data annotation for training and software validation, as well as throughout a clinical trial. A clinical trial was conducted on 1,274 patients with type 1 and type 2 diabetes mellitus, where Aireen medical device achieved a sensitivity of 94.0% and a specificity of 90.7% compared to the reference evaluation. This clinical trial confirmed the potential of Aireen to enhance the availability of diabetic retinopathy screening and early disease detection.