谷歌Chrome浏览器插件
订阅小程序
在清言上使用

Regimen comprising GLP-1 receptor agonist and basal insulin can decrease the effect of food on glycemic variability compared to a pre-mixed insulin regimen

EUROPEAN JOURNAL OF MEDICAL RESEARCH(2022)

引用 3|浏览3
暂无评分
摘要
Background Increasing evidence suggests that glucagon-like peptide 1 (GLP-1) receptor agonists (RA) can stabilize glycemic variability (GV) and interfere with eating behavior. This study compared the impact of insulin, GLP-1 RA, and dietary components on GV using professional continuous glucose monitoring (CGM). Methods Patients with type 2 diabetes underwent CGM before and after switching from a twice-daily pre-mixed insulin treatment regimen to a GLP-1 RA (liraglutide) plus basal insulin regimen. The dietary components were recorded and analyzed by a certified dietitian. The interactions between the medical regimen, GV indices, and nutrient components were analyzed. Results Sixteen patients with type 2 diabetes were enrolled in this study. No significant differences in the diet components and total calorie intake between the two regimens were found. Under the pre-mixed insulin regimen, for increase in carbohydrate intake ratio, mean amplitude of glucose excursion (MAGE) and standard deviation (SD) increased; in contrast, under the new regimen, for increase in fat intake ratio, MAGE and SD decreased, while when the protein intake ratio increased, the coefficient of variation (CV) decreased. The impact of the food intake ratio on GV indices disappeared under the GLP-1 RA regimen. After switching to the GLP-1 RA regimen, the median MAGE, SD, and CV values decreased significantly. However, the significant difference in GV between the two regimens decreased during the daytime. Conclusion A GLP-1 RA plus basal insulin regimen can stabilize GV better than a regimen of twice-daily pre-mixed insulin, especially in the daytime, and can diminish the effect of food components on GV.
更多
查看译文
关键词
Continuous glucose monitoring,Glucose variability,Pre-mixed insulin,GLP-1 receptor agonist,Diet
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要