Continuous Glucose Monitoring Metrics Predict All-Cause Mortality in Diabetes: A Real-world Long-term Study
Authors' conclusion
CGM-derived metrics were associated with all-cause mortality in patients with diabetes and may better capture long-term risk associated with glucose fluctuations and periods of hypo- and hyperglycemia than HbA1c.
Study context
- Population
- Adults (≥21 years) with diabetes (65% T2D) in the Veterans Affairs Healthcare System who received Dexcom continuous glucose monitoring (CGM) 2015–2020, with ≥10 days of CGM data over landmark periods; mean age 64 years407 deaths
- Participants
- 2,752 adults
- Exposure
- Association of CGM-derived metrics with all-cause mortality
- Outcome
- All-cause mortality
- Follow-up
- 5 years from CGM initiation
Methodological detailsreal-world, landmark analysis, multivariable Cox models
- Real-world
- Landmark analysis
- Multivariable Cox models
Main finding
As reported in the abstract
5-year all-cause mortality by CGM metrics during 6-month landmark (separate multivariable Cox models) · 5 years
- HR, mean glucose (MG)
- 1.18
- HR, time above range (TAR)
- 1.20
- HR, glycemic risk index (GRI)
- 1.23
- HR, coefficient of variation (CV)
- 1.18
- HR, time in range (TIR)
- 0.83
Observational data: associations, not effects.
Further findings
Adjustment for landmark HbA1c
- Associations remained significant after adjusting for landmark (LM) HbA1c
Shorter CGM landmark windows
- Results similar with shorter CGM LM observation windows
CV and mortality
- Association independent of other CGM metrics; appeared strongest in those with lower HbA1c
Original publication
Continuous Glucose Monitoring Metrics Predict All-Cause Mortality in Diabetes: A Real-world Long-term Study. Diabetes Care. Published 6 August 2025. doi:10.
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