View clinical trials related to Diabetic Retinopathy.
Filter by:The purpose of this study is to evaluate the combined effects of diabetes self-management education (DSME) and nutritional supplementation on visual function and retinopathy incidence & progression in patients with type 1 diabetes, type 2 diabetes and pre-diabetes.
To evaluate the differences in retinal function as measured by ERG in diabetics with and without retinopathy 2) the ability of the Chromatic Electroretinogram (chERG) to detect changes in global retinal function following treatment with Carotenoid Vitamins supplement in patients with diabetic retinopathy (DR). 3) the ability of the Full Field flicker (ffERG) to detect changes in global retinal function following treatment with Carotenoid Vitamins supplement in patients with diabetic retinopathy (DR). 4) Changes in retinal function as observed by OCT-Angiography, following treatment with Carotenoid Vitamins supplement in patients with diabetic retinopathy (DR).
It is estimated that there are about 600 million diabetes mellitus (DM) patients all over the world until 2040，and almost 50% of whom have some degree of diabetic retinopathy (DR) at any given time. About 5% to 10% diabetic retinopathy would develop vision-threatening complications, including proliferative diabetic retinopathy (PDR), capillary non-perfusion, or macular edema. Data from the DRS suggest that given long enough duration of diabetes, approximately 60% of patients with DR will develop PDR, and without intervention, 75% nonproliferative diabetic retinopathy (NPDR) will development PDR within 1 year follow up, 45% will develop high-risk PDR, nearly half of PDR will experience profound visual loss. panretinal photocoagulation (PRP) only reduced 50% risk of sever visual loss and about 25% of the sNPDR patients who finished PRP need Pars-plana vitrectomy (PPV) in a 5 year follow up. Vitreous have been proven to play an important role in the development of NPDR to PDR, which were the collection of vascular endothelial growth factor (VEGF) factors and the major component of proliferative lesion in the later stage of PDR. Micro-invasive Pars-plana vitrectomy has been shown as a safe and effective method in the treatment of PDR, through removing the pathological vitreous, proliferative membrane and also the VEGF factors. However, whether or not Micro-invasive Pars-plana vitrectomy will be more effective than PRP to control the progression of NDPR remained unknown.
To identify biomarkers of common eye diseases based on single-cell sequencing technologies using PBMC samples. These diseases include uveitis, diabetic retinopathy, age-related macular degeneration and polypoid choroidal vasculopathy. Our study may provide new insight into the underlying mechanisms, and reveal novel predictors and intervention targets for the diagnosis, prognosis and treatment of these diseases.
The objective of this study is to test the hypothesis that following the use of intravitreal dexamethasone implant for the treatment of DME, there will be an observable increase in the capillary density plexus as denoted by the quantitative assessment of the superficial capillary plexus on OCTA, as well as a decrease in size of the foveal avascular zone (FAZ).
Diabetic retinopathy (DR) is the leading cause of impaired visual function and blindness in adults. The fundus photographs were examined to detect DR. The DR severity was graded non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR) according to the International Clinical Diabetic Retinopathy and Diabetic Macular Edema Disease Severity Scales. The pathogenesis of DR is complex and not fully understood, and platelet aggregation, microvascular damage, microvascular enlargement, leakage, hemorrhage, or obstruction, resulting in retinal hypoxia and retinal neovascularization. Traditional Chinese medicine (TCM) diagnostic tools are non-invasive and convenient. This study apply TCM diagnostic tools for clinical diseases, providing objective diagnostic data for evaluation to assess the association of blood stasis and DR. Furtherly we would evaluate the sensitivity and specificity of TCM diagnostic tools. This study is a prospective cross-sectional study. We enroll participants form the department of Chinese medicine, China Medical University Hospital. In total, 100 participants , composed of 50 of type 2 diabetes and 50 of diabetic retinopathy, whom previously had a retinal examination. We apply tongue diagnosis system, pulse wave analysis, body constitution questionnaires, and nailfold capillaroscopy to assess the differences of TCM diagnosis in DR. This study aims to identify the clinical symptoms of DR with TCM diagnostic tools and investigate the pattern difference and treatment for DR. Furtherly, we could design a clinical trial with improving blood circulation to treat or prevent DR, and improve the health status and quality of life in patients with type 2 diabetes.
Retinopathy may be associated with diastolic dysfunction and/or coronary flow reserve in the heart, and albuminuria in diabetic patients. The objective of this study is to examine the cross-sectional relationships of retinopathy with indices of left ventricular diastolic function, coronary flow reserve and urinary albumin excretion, among diabetic patients.
The object of this study is to investigate the damage to the retinal nerve fiber layer (RNFL) and ganglion cell complex layer (GCL+) in diabetic patients without retinal microangioma as detected by fundus fluorescein angiography (FFA) and to determine the kind of nerve damage more likely to indicate early injury.
Recently, artificial intelligence algorithm has made great progress in the prediction of diabetic retinopathy based on fundus images，showing very high sensitivity and specificity. However，the real-world diagnosis effectiveness of deep learning model is still unclear. This study is designed to evaluate the clinical efficacy of such an algorithm in detecting referable diabetic retinopathy.
This study is to build an multi-modal artificial intelligence ophthalmological imaging diagnostic system covering multi-level medical institutions. We are going to evaluate this system in an evidence-based medicine view, taking diabetic retinopathy as an example. And clinical diagnostic criteria will be made based on this multi-modal artificial intelligence imaging diagnostic system. The study is designed as a cross-sectional study involving 1,000 normal individuals, 1,000 diabetes patients without ocular complications, and 1,000 with diabetic ocular complications. Statistical analysis of the diagnostic sensitivity and specificity of the artificial intelligence system will be made, and ROC curve wil be draw.