Continuous Glucose Monitoring Metrics Predict All-Cause Mortality in Diabetes: A Real-world Long-term Study.

Area of Science:

• Endocrinology
• Diabetes Management
• Clinical Research

Background:

• Continuous glucose monitoring (CGM) provides detailed glycemic insights.
• Traditional metrics like HbA1c may not fully capture mortality risk in diabetes.

Purpose of the Study:

• To investigate the association between CGM-derived glucose metrics and all-cause mortality in adults with type 1 or type 2 diabetes.
• To determine if CGM metrics offer superior risk prediction compared to HbA1c.

Main Methods:

• Analysis of 2,752 adult diabetes patients from the Veterans Affairs Healthcare System with Dexcom CGM data (2015-2020).
• Evaluation of CGM metrics (mean glucose, time in range, time above range, coefficient of variation, glycemic risk index) against 5-year all-cause mortality using Cox models.
• Data merged with electronic health records, with landmark periods of 14 days, 3 months, and 6 months.

Main Results:

• Higher mean glucose, time above range, coefficient of variation, and glycemic risk index, along with lower time in range during the 6-month landmark period, were significantly associated with 5-year mortality.
• These associations remained significant even after adjusting for HbA1c.
• The association between coefficient of variation and mortality was independent of other CGM metrics and stronger in individuals with lower HbA1c.

Conclusions:

• CGM-derived metrics are significantly associated with all-cause mortality in patients with diabetes.
• CGM metrics may provide a more comprehensive assessment of long-term mortality risk than HbA1c alone, capturing risks from glucose variability and excursions.