Quality Improvement Success Stories are published by the American Diabetes Association in collaboration with the American College of Physicians and the National Diabetes Education Program. This series is intended to highlight best practices and strategies from programs and clinics that have successfully improved the quality of care for people with diabetes or related conditions. Each article in the series is reviewed and follows a standard format developed by the editors of . The following article describes efforts at a large midwestern pediatric health system to improve planning for patients' transition from pediatric to adult diabetes care settings.
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http://dx.doi.org/10.2337/cd23-0018 | 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 PDFInt Urol Nephrol
January 2025
Nephrology, Dialysis and Kidney Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Introduction: Kidney transplantation is the preferred treatment for end-stage kidney disease (ESKD), enhancing survival and quality of life. However, kidney transplant recipients (KTRs) are at high risk for bone disorders, particularly low bone turnover disease, which increases fracture risk. Teriparatide, an anabolic agent, may provide a beneficial treatment option for these patients.
View Article and Find Full Text PDFNat Methods
January 2025
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
A key challenge of the modern genomics era is developing empirical data-driven representations of gene function. Here we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-wide genotype-phenotype maps comprising CRISPR-Cas9-based knockouts of >20,000 genes in >30 million cells. Our optical pooled cell profiling platform (PERISCOPE) combines a destainable high-dimensional phenotyping panel (based on Cell Painting) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Pharmacy, University of Miyazaki Hospital, 5200 Kihara, Kiyotake-cho, Miyazaki, 889-1692, Japan.
Intra-patient variability in immunosuppressive blood drug concentrations is a potential biomarker in managing organ transplant patients. However, the association between the time in therapeutic range of tacrolimus blood concentrations and its efficacy in preventing graft-versus-host disease remains unknown. In this study, we analyzed the relationship between the time in therapeutic range of tacrolimus blood concentrations and its efficacy in acute graft-versus-host disease prophylaxis in patients undergoing allogeneic hematopoietic stem cell transplantation.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Endocrinology and Metabolism, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.
With the rapid advancement of proteomics, numerous scholars have investigated the intricate relationships between plasma proteins and various diseases. Therefore, this study aims to elucidate the relationship between BDH1 and type 2 diabetes using Mendelian randomization (MR) and to identify novel targets for the prevention and treatment of type 2 diabetes through proteomics. This study primarily employed the Mendelian Randomization (MR) method, leveraging genetic data from numerous large-scale, publicly accessible genome-wide association studies (GWAS).
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