Diabetic Retinopathy Clinical Trial
Official title:
Intelligent Evaluation of Diabetic Retinopathy
Brief Summary: The main objective of EviRed project is to develop and validate a system assisting the ophthalmologist by improving prediction of evolution, and decision making during diabetic retinopathy (DR) follow-up. It will replace the current classification of diabetic retinopathy (DR) which provides an insufficient prediction precision. It will use modern available fundus imaging devices and artificial intelligence (AI) to properly integrate the amount of data they provide with other medical data of the patient. A cohort of 5000 diabetic patients will be recruited and followed for an average of 2 years in order to collect data to train and validate the new prediction system.
A cohort of 5,000 diabetic patients with different stages of DR will be recruited and followed for an average of 2 years. Each year, general data as well as ophthalmological data will be collected. Retinal images and videos of both eyes will be acquired using different imaging modalities including ultrawidefield photography, OCT and OCT angiography. The EviRed cohort will be split in two groups: one group of 1,000 patients (validation cohort) will be randomly selected during the inclusion period by unbalanced draw to be representative of the general diabetic population. Their data will be used for the validation of the algorithms. The data of the remaining 4,000 patients (training cohort) will be used to train the algorithms. The main objective will be the validation of the prognostic tool and evaluate how accurately the algorithm can predict progression to severe retinopathy in the following year. Secondary objectives will be to evaluate how accurately the algorithm can assess DR severity and individual components of DR complications as well as to compare prediction by algorithm to that made by ophthalmologists based on the current DR classification ;
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