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Temporal Glycemic Patterns in Type 1 and Type 2 Diabetes: Insights From Extended Continuous Glucose Monitoring.
Tomoki Okuno1,2, Lucas Sort3, Bowen Zhang1
1Department of Biostatistics, University of California, Los Angeles, Los Angeles, CA, USA.
Journal of Diabetes Science and Technology
|May 25, 2025
Summary
Real-world continuous glucose monitoring (CGM) reveals daily and seasonal glucose variations in diabetes. Higher CGM use correlates with better glycemic control, highlighting the need for tailored management strategies.
Area of Science:
- Endocrinology
- Metabolic Diseases
- Diabetes Management
Background:
- Optimal glycemic control in diabetes remains challenging.
- Real-world continuous glucose monitoring (CGM) data reveals underrecognized glycemic fluctuations.
- Understanding glucose trajectories is crucial for effective diabetes care.
Purpose of the Study:
- Characterize glucose trajectories in Type 1 and Type 2 diabetes patients.
- Examine the impact of baseline glycemic control on glucose patterns.
- Investigate how CGM usage frequency and regional differences influence glycemic trajectories.
Main Methods:
- Linked Dexcom CGM data (2015-2020) with electronic health records.
- Analyzed data from 892 Type 1 and 1716 Type 2 diabetes patients.
- Focused on the first three years of CGM use, analyzing over 2.1 million glucose readings.
Main Results:
- Both cohorts showed a gradual increase in mean daily glucose over time.
- Higher CGM usage frequency was linked to lower glucose levels or attenuated increases.
- Identified weekly patterns (highest glucose on Sundays, lowest on Wednesdays) and seasonal variations (deterioration Oct-Feb, rebound Apr-Aug).
Conclusions:
- Recognizing day-of-week and seasonal glycemic variations is vital for diabetes management.
- Tailoring interventions to real-world fluctuations can improve patient engagement.
- Optimizing glycemic control through personalized strategies may lead to better health outcomes.
Keywords:
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