Cardiovascular Disease and Diabetes: A New Challenge in the Treatment and Management
Abstract
Cardiovascular diseases (CVDs) represent one of the leading causes of morbidity and mortality in patients with diabetes. However, a correct and effective glycaemic control obtained by pharmacologic interventions, such as the use the novel glucose-lowering agents, demonstrated efficacy in reducing the risk of both cardiovascular events and mortality. The latest classes of glucose-lowering drugs introduced in the clinical practice are DPP4 inhibitors (sitagliptin, saxagliptin, vildagliptin, linagliptin, and alogliptin), GLP-1 receptor agonists (semaglutide, liraglutide, albiglutide, dulaglutide, exenatide, and lixenatide), and SGLT-2 inhibitors (empaglifozin, canaglifozin, and dapaglifozin). Multiple lines of evidence show that all these new drugs associated with the treatment of diabetic disease have the same effectiveness as the traditional antidiabetic drugs, and excellent cardiovascular safety, highlighting their potential in significantly reducing major cardiovascular events and mortality. The aim of our review is to summarise the clinical efficacy of these recently introduced drugs to optimise treatment strategies, especially in the early phase of diabetic disease.
Read the paper
Related studies
- The Role of AMPK Activation for Cardioprotection in Doxorubicin-Induced Cardiotoxicity
- Hypoglycemic medicines in the treatment of Alzheimer’s disease: Pathophysiological links between AD and glucose metabolism
- Isorhamnetin Reduces Glucose Level, Inflammation, and Oxidative Stress in High-Fat Diet/Streptozotocin Diabetic Mice Model
- Modulating Sirtuin Biology and Nicotinamide Adenine Diphosphate Metabolism in Cardiovascular Disease—From Bench to Bedside
- Characterization of the SGLT2 Interaction Network and Its Regulation by SGLT2 Inhibitors: A Bioinformatic Analysis
- Early Treatment with Empagliflozin and GABA Improves β-Cell Mass and Glucose Tolerance in Streptozotocin-Treated Mice
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.