Objective: To assess the relationship between vitamin D status and diabetic retinopathy.
Methods: A clinic-based, cross-sectional study was conducted at Emory University, Atlanta, Georgia. Overall, 221 patients were classified into 5 groups based on diabetes status and retinopathy findings: no diabetes or ocular disease (n = 47), no diabetes with ocular disease (n = 51), diabetes with no background diabetic retinopathy (n = 41), nonproliferative diabetic retinopathy (n = 40), and proliferative diabetic retinopathy (PDR) (n = 42). Patients with type 1 diabetes and those taking >1,000 IU of vitamin D daily were excluded from the analyses. Study subjects underwent dilated funduscopic examination and were tested for hemoglobin A1c, serum creatinine, and 25-hydroxyvitamin D [25(OH)D] levels between December 2009 and March 2010.
Results: Among the study groups, there was no statistically significant difference in age, race, sex, or multivitamin use. Patients with diabetes had lower 25(OH)D levels than did those without diabetes (22.9 ng/mL versus 30.3 ng/mL, respectively; P<.001). The mean 25(OH)D levels, stratified by group, were as follows: no diabetes or ocular disease = 31.9 ng/mL; no diabetes with ocular disease = 28.8 ng/mL; no background diabetic retinopathy = 24.3 ng/mL; nonproliferative diabetic retinopathy = 23.6 ng/mL; and PDR = 21.1 ng/mL. Univariate analysis of the 25(OH)D levels demonstrated statistically significant differences on the basis of study groups, race, body mass index, multivitamin use, hemoglobin A1c, serum creatinine level, and estimated glomerular filtration rate. In a multivariate linear regression model with all potential confounders, only multivitamin use remained significant (P<.001).
Conclusion: This study suggests that patients with diabetes, especially those with PDR, have lower 25(OH)D levels than those without diabetes.
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http://dx.doi.org/10.4158/EP11147.OR | 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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