Background/objectives: To determine long-term outcomes of patients referred with proliferative diabetic retinopathy (PDR) from diabetic eye screening programmes (DESP) to tertiary care centres in the United Kingdom (UK).
Methods: Retrospective multicentre study of patients referred from two DESPs in the UK over a 36-month period (2007-9) and followed-up for 10 years. Critical outcomes included severe vision loss (SVL) and the need for vitrectomy. Other outcomes assessed included moderate vision loss (MVL), and patient survival time. Univariate and multiple variable Cox proportional hazards regressions were used to analyse survival outcomes.
Results: 212 eyes of 150 patients were referred with a diagnosis of PDR. 109 eyes of 72 patients were confirmed to have active PDR and included in the study. 61% of patients had low-risk PDR, while 39% exhibited high-risk features in at least one eye. Eight (7.3%) eyes developed SVL and 16 (14.7%) MVL during follow up. Vitrectomy was required in 24% (95% CI: 15 to 31%) of all PDR eyes and was most commonly performed for vitreous haemorrhage (65%). The 10-year survival in all PDR patients was 76% (95% CI: 63 to 85%) with the mean time to death for all deceased patients being 5.4 ± 3.6 years. On multivariable analysis, only age was found to have a significant association with the survival of patients with PDR.
Conclusions: During the 10 year follow up SVL was uncommon, but MVL occurred in almost one-fifth of the eyes. Approximately 1 in 4 eyes required vitrectomy, highlighting its significance in patient management.
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http://dx.doi.org/10.1038/s41433-024-03078-1 | DOI Listing |
J Imaging Inform Med
January 2025
College of Engineering, Department of Computer Engineering, Koç University, Rumelifeneri Yolu, 34450, Sarıyer, Istanbul, Turkey.
This study explores a transfer learning approach with vision transformers (ViTs) and convolutional neural networks (CNNs) for classifying retinal diseases, specifically diabetic retinopathy, glaucoma, and cataracts, from ophthalmoscopy images. Using a balanced subset of 4217 images and ophthalmology-specific pretrained ViT backbones, this method demonstrates significant improvements in classification accuracy, offering potential for broader applications in medical imaging. Glaucoma, diabetic retinopathy, and cataracts are common eye diseases that can cause vision loss if not treated.
View Article and Find Full Text PDFPak J Med Sci
January 2025
Juan Chen, Department of Ophthalmology, Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China.
Objective: To design a deep learning-based model for early screening of diabetic retinopathy, predict the condition, and provide interpretable justifications.
Methods: The experiment's model structure is designed based on the Vision Transformer architecture which was initiated in March 2023 and the first version was produced in July 2023 at Affiliated Hospital of Hangzhou Normal University. We use the publicly available EyePACS dataset as input to train the model.
Pak J Med Sci
January 2025
Syed Khurram Shehzad, Department of Medicine, Lahore Medical and Dental College, Lahore, Pakistan.
Objectives: To determine the frequency of undiagnosed hypertension among the diabetic patients with micro vascular complications.
Method: This is a descriptive case series conducted at Department of Medicine, Ghurki Trust Teaching Hospital, in this six month stud which enrolled 213 patients between 18-60 years from March 28, 2021 to September 28, 2021, having diabetes with microvascular complications. These patients were not previously diagnosed as hypertensives.
Purpose: To develop an algorithm using routine clinical laboratory measurements to identify people at risk for systematic underestimation of glycated hemoglobin (HbA1c) due to p.Val68Met glucose-6-phosphate dehydrogenase (G6PD) deficiency.
Methods: We analyzed 122,307 participants of self-identified Black race across four large cohorts with blood glucose, HbA1c, and red cell distribution width measurements from a single blood draw.
Int J Nanomedicine
January 2025
Department of Drug Sciences, University of Pavia, Pavia, 27100, Italy.
Purpose: The main purpose of the study was the formulation development of nanogels (NHs) composed of chondroitin sulfate (CS) and low molecular weight chitosan (lCH), loaded with a naringenin-β-cyclodextrin complex (NAR/β-CD), as a potential treatment for early-stage diabetic retinopathy.
Methods: Different formulations of NHs were prepared by varying polymer concentration, lCH ratio, and pH and, then, characterized for particle size, zeta potential, particle concentration (particles/mL) and morphology. Cytotoxicity and internalization were assessed in vitro using Human Umbilical Vein Endothelial Cells (HUVEC).
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