The Influence of GLP1 on Body Weight and Glycemic Management in Patients with Diabetes-A Scientometric Investigation...

Diabetes medications can affect weight and cardiovascular health. Some medications can aid in weight management, while others may lead to weight gain. Patients must be monitored and receive appropriate care to manage weight and prevent cardiovascular complications. Despite advancements in diabetes treatments that can influence weight and cardiovascular outcomes, ongoing research is necessary in this intricate field. Long-term effects, individual variations, and combination therapies are still subjects of uncertainty and ongoing investigation. The major objective of the research is to evaluate the impact of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) on body weight in diabetic patients through a scientometric assessment. Methodology: Research data were gathered from the Web of Science Core Collection (WoSCC) database by searching for the keywords "Body Weight", dulaglutide, and semaglutide, identifying 60 relevant articles in the field. While there are advantages in managing diseases in which the cardiovascular system is implicated, there are also clinical considerations for personalized medicine and shared decision-making. The scientometric analysis of the articles revealed important insights into how dulaglutide and semaglutide impact weight management and their potential benefits for managing cardiovascular diseases in individuals with diabetes. Conclusions: Semaglutide shows superior outcomes compared to other commercially available GLP-1RAs, particularly in improving blood sugar control, lowering body weight, and addressing other cardio-metabolic risk factors in individuals with type 2 diabetes (T2DM). The findings suggest that GLP-1 RAs have the potential to provide cardiovascular protection by influencing various physiological factors such as blood pressure, pulse rate, glycated hemoglobin (HbA1c) levels, and the urinary albumin-to-creatinine ratio (RAC). The development and validation of the 4GI model provides a sophisticated tool for evaluating the complex interactions involved in diabetes treatments, offering insights into the mechanisms of action of various medications.