View clinical trials related to Diabetic Retinopathy.
Filter by: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.
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
The present study aims to support previous research on the effects of antioxidant therapy on the outcome of diabetic retinopathy and local oxidative stress values. The researchers intend to evaluate 56 patients with proliferative diabetic retinopathy undergoing the vitrectomy procedure, who will be assigned to a placebo group or combination antioxidant therapy. Each group will receive the intervention for 2 months. This intervention consists of taking one tablet (placebo or antioxidant therapy) orally, once a day. At the beginning of the study, only blood samples will be collected to evaluate the state of oxidative and metabolic stress at a systemic level. After 2 months of intervention, blood samples will be taken again on the day of the intervention, adding the samples of aqueous and vitreous humor obtained during the vitrectomy. The results obtained between both groups and the different analysis matrices will be compared.
PURPOSE: To evaluate the efficacy of switching from bevacizumab to ranibizumab (Lucentis; Genentech, South San Francisco, CA) or aflibercept (Eylea; Regeneron, Tarrytown, NY) in eyes with diabetic macular edema (DME) nonresponders to bevacizumab (Avastin; Genentech, South San Francisco, CA). METHODS: Single-center retrospective comparative study of patients with DME unresponsive to intravitreal bevacizumab that were switched to ranibizumab or aflibercept. Best-corrected visual acuity and central foveal thickness will be analysed prior to and 3 months after the switch. OCT biomarkers will also analyzed. A p value of 0.05 or less will be considered to be statistically significant. HYPOTHESIS: Patients will improve anatomically and functionally after switch.
To compare the efficacy and comfort of two FDA approved pre-injection antiseptics when used for intravitreal injections.
This study determined the clinical impact and causes of loss to follow-up (LTFU) from the patients' perspective in individuals with proliferative diabetic retinopathy (PDR) who received panretinal photocoagulation (PRP) and/or intravitreal injections (IVIs) of anti-vascular endothelial growth factor (VEGF). This prospective cohort study included 467 patients with PDR who received PRP and/or IVIs of anti-VEGF between May 2013 and June 2018. LTFU was defined as missing any follow-up visit for any interval exceeding 6 months, provided that patients eventually resumed care. Main outcome measures include rates and causes of LTFU.
Citicoline (cytidine-5'-diphosphocholine) is an essential precursor in the synthesis of phosphatidylcholine, a component of cell membranes. Several experimental in vitro and in vivo studies have suggested that citicoline plays a neuroprotective role. A recent clinical study has shown that treatment with topical citicoline induces, after 60 days of therapy, a significant improvement in the ganglion cell function .In addition topical citicoline has been demonstrated in vivo a neuroprotective effect in preventing diabetic retinopathy . The Investigators want to evaluate if citicoline may reduce the progression of retinal damage in patients with mild diabetic retinopathy.
To evaluate the safety and performance of an innovative artificial intelligence based Computer-Aided Diagnosis(CAD) system for diabetic retinography, Retinal images of patients with diabetes mellitus or diabetic retinopathy(DR) were collected retrospectively. All images were graded by a retinal specialists expert panel and the CAD device using the International Clinical Diabetic Retinopathy severity scale criteria. Investigator responsible for DR grading by CAD system is blinded to the DR grading results from the expert panel. Finally, DR grading results of the CAD system and experts were compared using sensitivity and specificity.
This was a multicentre, randomised, double-blind controlled study that compared the efficacy and safety of V. vinifera extract, calcium dobesilate (CD), and placebo in subjects with DME. Patients made 6 clinic visits, namely the screening visit; baseline visit (T0); and follow-up visits at 3 (T3), 6 (T6), 9 (T9), and 12 (T12) months.