Artificial Intelligence-Based Screening System for Diabetic Retinopathy in Primary Care.

Background: This study aimed to test an artificial intelligence-based reading system (AIRS) capable of reading retinographies of type 2 diabetic (T2DM) patients and a predictive algorithm (DRPA) that predicts the risk of each patient with T2DM of developing diabetic retinopathy (DR).

Methods: We tested the ability of the AIRS to read and classify 15,297 retinal photographs from our database of diabetics and 1200 retinal images taken with Messidor-2 into the different DR categories. We tested the DRPA in a sample of 40,129 T2DM patients.

Evaluation of Postoperative Pain When Adding a Tibial Nerve Block to the Femoral Nerve Block for Total Knee Arthroplasty.

: The aim of this study was to compare the postoperative analgesic efficacy when a tibial nerve block was added to the femoral nerve block for total knee arthroplasty (TKA). : A total of 60 patients were randomly assigned to the experimental group (EG) or the control group (CG) in a 1:1 ratio. The thirty patients who formed the CG underwent an ultrasound-guided femoral nerve block together with neuraxial anaesthesia and the administration of opioids and NSAIDs through an intravenous elastomeric pump for the management of the postoperative pain; the other thirty, who formed the EG, underwent neuraxial anaesthesia together with femoral and tibial nerve blocks.

Distribution of Microaneurysms and Hemorrhages in Accordance with the Grading of Diabetic Retinopathy in Type Diabetes Patients.

(1) Underlying Diabetic Retinopathy (DR) is the primary cause of poor vision in young adults. There are automatic image reading systems that can aid screening for DR. (2) Methods: Using our automatic reading system we have counted the number of microaneurysms and hemorrhages in the four quadrants of the ETDRS grid and evaluated the differences between them according to the type of DR.

Referable Diabetic Retinopathy Prediction Algorithm Applied to a Population of 120,389 Type 2 Diabetics over 11 Years Follow-Up.

(1) Background: Although DR screening is effective, one of its most significant problems is a lack of attendance. The aim of the present study was to demonstrate the effectiveness of our algorithm in predicting the development of any type of DR and referable DR. (2) Methods: A retrospective study with an 11-year follow-up of a population of 120,389 T2DM patients was undertaken.