Diabetic kidney disease (DKD) is the leading cause of kidney failure and is associated with substantial risk of cardiovascular disease, morbidity, and mortality. Traditionally, DKD prevention and management have focused on addressing hyperglycemia, hypertension, obesity, and renin-angiotensin system activation as important risk factors for disease. Over the last decade, sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists have been shown to meaningfully reduce risk of diabetes-related kidney and cardiovascular complications. Additional agents demonstrating benefit in DKD such as non-steroidal mineralocorticoid receptor antagonists and endothelin A receptor antagonists are further contributing to the growing arsenal of DKD therapies. With the availability of greater therapeutic options comes the opportunity to individually optimize DKD prevention and management. Novel applications of transcriptomic, proteomic, and metabolomic/lipidomic technologies, as well as use of artificial intelligence and reinforced learning methods through consortia such as the Kidney Precision Medicine Project and focused studies in established cohorts hold tremendous promise for advancing our understanding and treatment of DKD. Specifically, enhanced understanding of the molecular mechanisms underlying DKD pathophysiology may allow for the identification of new mechanism-based DKD subtypes and the development and implementation of targeted therapies. Implementation of personalized care approaches has the potential to revolutionize DKD care.
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http://dx.doi.org/10.1016/j.jdiacomp.2022.108357 | DOI Listing |
World J Diabetes
January 2025
Department of Endocrinology, Wuhu Second People's Hospital, Wuhu 241000, Anhui Province, China.
Background: The progression of diabetic kidney disease (DKD) affects the patient's kidney glomeruli and tubules, whose normal functioning is essential for maintaining normal calcium (Ca) and phosphorus (P) metabolism in the body. The risk of developing osteoporosis (OP) in patients with DKD increases with the aggravation of the disease, including a higher risk of fractures, which not only affects the quality of life of patients but also increases the risk of death.
Aim: To analyze the risk factors for the development of OP in patients with DKD and their correlation with Ca-P metabolic indices, fibroblast growth factor 23 (FGF23), and Klotho.
Cureus
December 2024
Nephrology, Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute, Mumbai, IND.
Research conducted in India has shown that there is a high prevalence of non-diabetic kidney disease (NDKD) among Indian patients. Sodium-glucose co-transporter 2 inhibitors (SGLT2i) are emerging as potential treatments for preventing the progression of chronic kidney disease to advanced stages, regardless of their anti-diabetic effects. Dapagliflozin, which has been approved by the Central Drugs Standard Control Organization, is the SGLT2i drug class approved for use in both DKD and NDKD patients.
View Article and Find Full Text PDFNarra J
December 2024
Doctoral Program of Public Health, Faculty of Public Health, Universitas Diponegoro, Semarang, Indonesia.
To the best of our knowledge, bibliometric analysis has not been performed for studies related to diabetic kidney disease (DKD) and hemodialysis using healthcare big data. Herein, the aim of this bibliometric analysis was to identify emerging research trends in DKD and hemodialysis within healthcare insurance databases by exploring authors, co-author networks, and countries to discover new potential research areas. A bibliometric study was conducted, utilizing data obtained from the Scopus database.
View Article and Find Full Text PDFDiabetes Obes Metab
January 2025
Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, Shenyang, China.
Background: Diabetic kidney disease (DKD) makes up nearly half of all chronic kidney disease cases and is a major cause of mortality for people with diabetes. However, the study of the association of longitudinal Chinese visceral adiposity index (CVAI) with DKD is still missing.
Methods: This prospective cohort study included 7874 diabetes patients from the Kailuan study.
Background: Diabetic kidney disease (DKD) is one of the typical complications of type 2 diabetes (T2D), with approximately 10 % of DKD patients experiencing a Rapid decline (RD) in kidney function. RD leads to an increased risk of poor outcomes such as the need for dialysis. Albuminuria is a known kidney damage biomarker for DKD, yet RD cases do not always show changes in albuminuria, and the exact mechanism of RD remains unclear.
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