Active clinical trials for "Retinal Diseases"

This randomized clinical trial will compare retinal outcomes with low-dose intravitreous bevacizumab (0.063 mg) versus laser photocoagulation as treatment for infants with type 1 retinopathy of prematurity (ROP). The study also will assess neurodevelopment, refractive error, visual acuity, and peripheral visual fields.

The purpose of this study is to assess the impact of using autonomous artificial intelligence (AI) system for identification of diabetic retinopathy (DR) and diabetic macular edema on productivity of retina specialists in Bangladesh. Globally, the number of people with diabetes mellitus is increasing. Diabetic retinopathy is a chronic, progressive complication of diabetes mellitus that affects the microvasculature of the retina, which if left untreated can potentially result in vision loss. Early detection and treatment of diabetic retinopathy can prevent potential blindness. Study Aim: To assess the impact of using autonomous artificial intelligence (AI) system for detection of diabetic retinopathy (DR) and diabetic macular edema on physician productivity in Bangladesh. Main study question: Will ophthalmologists with clinic days randomized to use autonomous AI DR detection for all persons with diabetes (diagnosed or un-diagnosed) visiting their clinic system have a greater number of examined patients with diabetes (by either AI or clinical exam), and a greater complexity of examined patients on a recognized grading scale, per physician working hour than those randomized not to have autonomous AI screening for their diabetes population? The investigators anticipate that this study will demonstrate an increase in physician productivity, supporting efficiency for both physicians and patients, while also addressing increased access for DR screening; ultimately, preventing vision loss amongst diabetic patients. The study has the potential to contribute to the evidence base on the benefits of AI for physicians and patients. Additionally, the study has the potential to demonstrate the benefits (and/or challenges) of implementing AI in resource-constrained settings, such as Bangladesh.

Studying normal subjects to create unique normal database for multifocal electroretinogram (mf-ERG) in specific population.

This is a 24-week, multicenter, open-label, single-arm, observational, post approval commitment study, which is designed to collect effectiveness, safety and other clinical information of intravitreal ranibizumab 0.2 mg for the treatment of Retinopathy of Prematurity (ROP) participants in a real world clinical setting in mainland China.

The objective of this study is to apply an artificial intelligence algorithm to diagnose multi-retinal diseases in real-world settings. The effectiveness and accuracy of this algorithm are evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and area under curve.

Optical coherence tomography (OCT )provides high resolution information regarding the anatomic structure of the tissues of the eye in a cross-sectional and 3 dimensional view. Much of this information is not able to be visualized by a clinician. Utilizing this information during surgery will allow for the ophthalmic surgeons to better understand how surgical procedures impact the anatomic structure of the eye. In this study an OCT device that has been built into the microscope (rather than mounted on the side or held in the surgeon's hand) and will be utilized to take images at various milestones during surgery to assess feasibility and potential utility of this technology. Since it is built into the microscope, there are potential significant advantages over a separate system including increased efficiency, improved working distance, and the ability to visualize tissue-instrument interactions.

CD160 represents a new angiogenic factor as its specific engagement by an agonist monoclonal antibody directed against human CD160 reduced angiogenesis of endothelial cells with a distinct mechanism from current angiogenic therapies that target the VEGF/VEGF-R pathway. A soluble form of CD160, sCD160, has been found to be highly expressed in the vitreous and the sera of patients with severe diabetic retinopathies, and can now be dosed with help of an ELISA test. The investigators aim to evaluate the association between ischaemic retinopathies (patients with or without) and sCD160 concentrations in the vitreous, the aqueous humour and the serum.

The duration of diabetes is directly related to eye complications. Diabetic retinopathy affects 80 percent of those who have had diabetes for 20 years or more. At least 90% of new cases can be reduced with proper treatment and monitoring of the eyes. The longer a person has diabetes, the more likely it is to develop diabetic retinopathy. Each year in the United States, diabetic retinopathy accounts for 12% of all new cases of blindness. It is also the leading cause of blindness in people between the ages of 20 and 64. The most important complication of diabetes leading to vision loss is diabetic retinopathy. Depending on this, macular edema, bleeding into the retina and vitreous,neovascular glaucoma can cause blindness. Diabetic retinopathy (DR) is a leading cause of vision-loss globally. Of an estimated 285 million people with diabetes mellitus worldwide, approximately one third have signs of DR and of these, a further one third of DR is vision-threatening DR, including diabetic macular edema (DME). Diabetic retinopathy is a retinal disease that can often be stopped with early diagnosis, but if neglected, it can lead to severe vision loss, including permanent blindness. Diabetes has high morbidity and there are millions of people who should be screened for diabetic retinopathy (DR). Annual eye screening is recommended for all diabetic patients since vision loss can be prevented if DR is diagnosed in its early stages. Currently, the number of clinical personnel trained for DR screening is less than that needed to screen a growing diabetic population. Therefore, the automatic DR screening system will be able to screen more diabetic patients and diagnose them early. EyeCheckup is an automated retinal screening device designed automatically analyze color fundus photographs of diabetic patients to identify patients with referable or vision threatening DR. This study is designed to assess the safety and efficacy of EyeCheckup. The study is a single center study to determine the sensitivity and specificity of EyeCheckup to diabetic retinopathy. EyeCheckup is an automated software device that is designed to analyze ocular fundus digital color photographs taken in frontline primary care settings in order to quickly screen for diabetic retinopathy (DR).

This study aims to compare the accuracy of evaluating diabetic retinopathy using ultra-widefield fundus images versus two-field fundus images. The hypothesis is that screening and grading diabetic retinopathy based on ultra-widefield fundus images may yield higher accuracy compared to the use of two-field fundus images.

Retinopathy of prematurity (ROP) is a disorder of development of the neural retina and its vasculature that can impact vision in vulnerable preterm neonates for a lifetime. This study tests high-speed optical coherence tomography (OCT) technology compared to conventional color photographs at the bedside of very preterm infants in the intensive care nursery, to characterize previously unseen abnormalities that can predict a need for referral for ROP treatment, or poor visual or neurological development later in life, up to pre-school age. Our long-term goal is to help improve preterm infant health and vision via objective bedside imaging and analysis that characterizes early critical indicators of ROP, and poor visual function and neurological development, which will rapidly translate to better early intervention and improved future care.