View clinical trials related to Diabetic Retinopathy.
Filter by:Phase 2 randomized, active-controlled, double-masked, dose-ranging trial in adults with Diabetic Macular Edema (DME).
All OCTA data and biochemical indexes of diabetic patients were acquired. A prediction model of diabetic retinopathy was built, and the random forest method was used to identify sensitive indicators.
We plan to explore the usability of Generative AI-Chatbot for Diabetic Patient
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.
Evolucare OphtAI is a medical device offering automated, artificial intelligence powered, screening capabilities for Diabetic Retinopathy, Diabetic Macular Edema, Glaucoma, ARM and AMD, whose performances will by tested through the OphtAI-EVAL.
The goal of this observational study is to analyse and compare Diabetic Retinopathy severity level using 30º ETDRS 7-fields and Wide-field Imaging techniques using Clarus 500 (Carl Zeiss Meditech Inc., Dublin, USA) and Optos (Optos, Dunfermline, UK) in diabetic patients with mild to moderate diabetic retinopathy. The main questions it aims to answer are: 1. To compare the Clarus 500TM wide-field imaging technique with the ETDRS 7-fields method in the assessment of DR severity level using the ETDRS DRSS.2. To compare the two wide-field imaging techniques (Clarus 500TM vs OptosTM) in the assessment of DR severity level using the ETDRS DRSS.3. To evaluate the peripheral area imaged by the wide-field Clarus 500TM and OptosTM to characterize DR lesions distribution (predominantly observed within or outside the ETDRS 7-fields) and severity (according to the ETDRS standard photos).4. To determine the relevance and frequency of DR PPL, located outside the ETDRS 7-fields area, and to explore PPL occurrence in different DR severity levels. Participants will undergo a non-invasive ophthalmological examination, which includes BCVA, 7-fields CFP and UWF FP to assess ETDRS DRSS level.
The increasing prevalence of diabetes mellitus represents a major health problem, especially since around 40% of diabetic patients develop diabetic retinopathy, which severely impairs vision and can lead to blindness. This development could be prevented by annual check-ups and timely referral for treatment. However, there are major differences in the quality of examinations and bottlenecks in examination appointments. A solution to the problem could be the use of artificial intelligence (AI), especially deep learning. Initial studies have shown that deep learning algorithms can be used successfully to detect diabetic retinopathy. However, it remains to be clarified whether the use of AI can achieve a sufficiently high level of accuracy in the detection of retinopathies. Therefore, in the present study, the positive predictive value (PPV), the negative predictive value (NPV), the sensitivity (SEN) and the specificity (SPEZ) of the AI algorithm 'MONA-DR-Model' in the detection of diabetic retinopathy should be measured. In addition, it is to be examined how well the classification into mild and severe retinopathy corresponds and how well this new examination method is accepted by the patients.
This is an unmasking randomized clinical trial. the main purpose of this study is to analyze whether posvitrectomy proactive use of conbercept can reduce the rate of postoperative complication in PDR patients.
Diabetic retinopathy (DR) is the main cause of blindness among working-age adults in the world. Proliferative diabetic retinopathy (PDR) is the severe stage of DR, which is characterized by neovascularization of the retina. Vitreous hemorrhage and traction retinal detachment caused by PDR often require vitrectomy. The purpose of vitrectomy is to remove vitreous hemorrhage, peel off the preretinal proliferative membrane and help restore the retina. With the deepening of people's understanding of diabetes and the development and application of various hypoglycemic drugs, the life expectancy of patients with diabetes continues to prolong. Therefore, the goal of vitrectomy in patients with DR is not only to prevent blindness, but also to maintain good vision for a long time. The purpose of this study is to analyze the risk factors related to the occurrence of long-term low vision postoperatively and establish a risk prediction model, which can help patients adjust their psychological expectations reasonably and promote communication between doctors and patients.
The primary goal of the project is to create a normative database from data collected from a healthy pediatric population. A secondary aim is to compare normative data with data from pediatric patients with pre-existing type 1 diabetes mellitus.