This study evaluates the ability of deep learning to improve the knowledge about structural and vascular retinal changes in diabetic patients undergoing artificial pancreas device, using optical coherence tomography angiography.
hybrid artificial pancreas systems (CSII) are able to adjust the type 1 diabetic patient's glycemic levels with insulin doses appropriate to the patient's blood glucose. The optical coherence tomography angiography represents a novel and noninvasive diagnostic technique that allows a detailed and quantitative analysis of retinal and choriocapillary vascular features. The study evaluates the changes in optical coherence tomography angiography features in diabetic patients undergoing artificial pancreas device, elaborating these data with artificial intelligence.
Study Type
OBSERVATIONAL
Enrollment
11
artificial device that adjust the patient's glycemic levels with insulin doses appropriate to the patient's blood glucose
University of Naples "Federico II"
Naples, Italy
The measurements of retinal and choriocapillary vessel density in type 1 diabetic patients undergoing artificial pancreas device
The parameters analyzed by optical coherence tomography angiography were: retinal and choriocapillary vessel density matched with clinical parameters resulted from the artificial pancreas device
Time frame: up to 3months
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