View clinical trials related to Diabetic Retinopathy.
Filter by:The investigators are conducting a 5-year prospective, cluster-randomized controlled trial, funded by the Centers for Disease Control (CDC), which provides vision screenings to underserved, vulnerable New York City residents living in affordable housing buildings in Harlem and Washington Heights.
The study's main purpose is to asses the safety, tolerability, and effect of oral administration of RG7774 on the severity of diabetic retinopathy (DR) in participants with moderately severe to severe non-proliferative diabetic retinopathy (NPDR) and good vision.
The greatest harm of diabetes is various acute and chronic complications, especially diabetic retinopathy(DR), leading to extremely high rates of disability and blindness. Early screening, early diagnosis, and early treatment are the keys to maintaining vision in patients with DR. However, compared with the high prevalence of diabetes in China, the DR screening ability is relatively inadequate. To change this situation, deep learning(DL), a form of artificial intelligence (AI), might be a potential effective method to solve this dilemma.
Diabetes mellitus is a major and growing problem worldwide with many known micro and macrovascular complications. According to International Diabetes Federation, there were 285 million adults diagnosed with diabetes in 2010 and expected to increase to 439 million adult in 2030. It is a leading cause of chronic kidney disease (CKD) followed by hypertension, glomerulonephritis, and cystic kidney disease. Renal impairment patients metabolize and excrete drugs differently from patients with normal renal function and hence only limited number of oral hypoglycemic agent (OHA) available for them. One of the choices is sodium glucose co-transporter-2 inhibitor (SGLT2i) which is now widely used. Apart from its nephroprotective advantage, it also has additional benefit on cardiovascular and renal function based on EMPA-REG OUTCOME trial. One of the examples of SGLT2i is Empagliflozin (JARDIANCE) tablet, which has FDA U.S. Approval in 2014. It acts by reduces renal reabsorption of filtered glucose and lowers the renal threshold for glucose, thus increases urinary glucose excretion. It can cause osmotic diuresis, which may lead to intravascular volume contraction. Apart from its additional cardiovascular and nephroprotective effect, SGLT2 inhibitor might have additional protective effect to the eye. Nowadays, optical coherence tomography angiography (OCT-A) has emerged as one of a non-invasive methods to study the microvasculature of the retina and choroid. Many studies had discussed regarding-pre clinical changes present on OCT-A in patients without clinical diabetic retinopathy. These pre-clinical changes includes capillary dropout, microaneurysm, neovascularization, venous beading and enlargement of fovea avascular zone. However, there are minimal data and publications on different type of diabetic CKD with OCT-A parameters in diabetic patients. The purpose of this study is to determine the effect of short term SGLT2 inhibition on OCT-A parameters (fovea avascular zone (FAZ) size, vessel density and perfusion density) in diabetic CKD.
This is an open label dose-escalation study to evaluate the safety and treatment benefits of MS-553 in treatment-naive diabetic retinopathy patients with central involved macular edema. Fifteen subjects with diabetic macular edema will be enrolled into each of three dose cohorts and will receive oral administration of MS-553 for 8 weeks.
This study is to evaluate the clinical performance of VeriSee DR for DR screening from color fundus photography images in patients with diabetes mellitus. The sensitivity and specificity of VeriSee DR's automated image analysis for screening the diabetes retinopathy will be determined.
This Stage II randomized, controlled, longitudinal trial seeks to assess the acceptability, feasibility, and effects of a driving decision aid use among geriatric patients and providers. This multi-site trial will (1) test the driving decision aid (DDA) in improving decision making and quality (knowledge, decision conflict, values concordance and behavior intent); and (2) determine its effects on specific subpopulations of older drivers (stratified for cognitive function, decisional capacity, and attitudinally readiness for a mobility transition). The overarching hypotheses are that the DDA will help older adults make high-quality decisions, which will mitigate the negative psychosocial impacts of driving reduction, and that optimal DDA use will target certain populations and settings.
The investigator study evaluate the effect of different lipid lowering agents on the progression of diabetic retinopathy and other reduction of cardiovascular risk of diabetic patients
Background: Diabetic retinopathy (DR) is one of the most important causes of blindness worldwide, especially in developed countries. In diabetic patients, periodic examination of the back of the eye using a nonmydriatic camera has been widely demonstrated to be an effective system to control and prevent the onset of DR. Convolutional neural networks have been used to detect DR, achieving very high sensitivities and specificities. Hypothesis It is possible to develop algorithms based on artificial intelligence that can demonstrate equal or superior performance and that constitute an alternative to the current screening of RD and other ophthalmic pathologies in diabetic patients. Objectives: - Development of an artificial intelligence system for the detection of signs of retinal pathology and other ophthalmic pathologies in diabetic patients. - Scientific validation of the system to be used as a screening system in primary care. Methods: This project will consist of carrying out two studies simultaneously: 1. Development of an algorithm with artificial intelligence to detect signs of DR, other pathologies of the central retina and glaucoma in patients with diabetes. 2. Carrying out a prospective study that will make it possible to compare the diagnostic capacity of the algorithms with that of the family medicine specialists who read the background images. The reference will be double-blind reading by ophthalmologists who specialize in retina. Cession of the images began at the end of 2018. The development of the AI algorithm is calculated to last about 3 to 4 months. Inclusion of patients in the cohort will start in early 2019 and is expected to last 3 to 4 months. Preliminary results are expected to be published by the end of 2019. The study will allow the development of an algorithm based on AI that can demonstrate an equal or superior performance, and that constitutes a complement or an alternative, to the current screening of DR in diabetic patients
To increase the clinical experience of using the rtx1 camera in various retinal disorders and to follow the evolution of structural alterations during retinal diseases using adaptive optics imaging with the rtx1 camera