Okuno Tomoki, Sort Lucas, Zhang Bowen, Zhou Kerry, Kitchen Matthew, Li Victor, Miller Donald R, Norman Gregory J, Reaven Peter, Zhou Jin J
Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, USA.
Phoenix VA Health Care System, Phoenix, AZ, USA.
J Diabetes Sci Technol. 2025 May 24:19322968251341264. doi: 10.1177/19322968251341264.
Achieving optimal glycemic control for persons with diabetes remains difficult. Real-world continuous glucose monitoring (CGM) data can illuminate previously underrecognized glycemic fluctuations. We aimed to characterize glucose trajectories in individuals with Type 1 and Type 2 diabetes, and to examine how baseline glycemic control, CGM usage frequency, and regional differences shape these patterns.
We linked Dexcom CGM data (2015-2020) with Veterans Health Administration electronic health records, identifying 892 Type 1 and 1716 Type 2 diabetes patients. Analyses focused on the first three years of CGM use, encompassing over 2.1 million glucose readings. We explored temporal trends in average daily glucose and time-in-range values.
Both Type 1 and Type 2 cohorts exhibited a gradual rise in mean daily glucose over time, although higher CGM usage frequency was associated with lower overall glucose or attenuated increases. Notable weekly patterns emerged: Sundays consistently showed the highest glucose values, whereas Wednesdays tended to have the lowest. Seasonally, glycemic control deteriorated from October to February and rebounded from April to August, with more pronounced fluctuations in the Northeast compared to the Southwest U.S.
Our findings underscore the importance of recognizing day-of-week and seasonal glycemic variations in diabetes management. Tailoring interventions to account for these real-world fluctuations may enhance patient engagement, optimize glycemic control, and ultimately improve health outcomes.
实现糖尿病患者的最佳血糖控制仍然困难。现实世界中的连续血糖监测(CGM)数据可以揭示以前未被充分认识的血糖波动情况。我们旨在描述1型和2型糖尿病患者的血糖轨迹,并研究基线血糖控制、CGM使用频率和地区差异如何塑造这些模式。
我们将德康CGM数据(2015 - 2020年)与退伍军人健康管理局的电子健康记录相链接,识别出892名1型糖尿病患者和1716名2型糖尿病患者。分析集中在CGM使用的前三年,涵盖超过210万次血糖读数。我们探讨了平均每日血糖和血糖在目标范围内时间值的时间趋势。
1型和2型队列的平均每日血糖均随时间逐渐上升,尽管更高的CGM使用频率与更低的总体血糖或减弱血糖上升幅度相关。出现了显著的每周模式:周日的血糖值始终最高,而周三往往最低。在季节方面,血糖控制从10月到2月恶化,从4月到8月反弹,与美国西南部相比,东北部地区血糖波动更为明显。
我们的研究结果强调了在糖尿病管理中认识到每周日期和季节血糖变化的重要性。针对这些现实世界中的波动调整干预措施可能会提高患者的参与度,优化血糖控制,并最终改善健康结果。