Continuous Glucose Monitoring Metrics Predict All-cause Mortality in Diabetes, A Real-world Long-term Study

Objective: Investigate the association between continuous glucose monitoring (CGM)-derived glucose metrics and all-cause mortality in patients with type 1 or type 2 diabetes (T2D).Research Design and Methods: We analyzed data from 2,752 adults (≥21 years) with diabetes (65% T2D) from the Veterans Affairs Healthcare System who received Dexcom CGM between 2015 and 2020. All participants had ≥10 days of CGM data over landmark periods (14 days, 3 months, and 6 months) merged with electronic health records. All-cause mortality was assessed over five years from CGM initiation. Cox models evaluated associations between mortality and CGM metrics: mean glucose (MG, mg/dL), time-in-range (TIR, %), time-above-range (TAR, %), coefficient of variation (CV), and glycemic risk index (GRI, %).Results: Mean age at CGM initiation was 64 years and median CGM use was nearly 3 years. There were 407 deaths. In separate multivariable Cox models (adjusting for mortality-related variables) higher MG, TAR, CV, and GRI, and lower TIR during the 6-month landmark were associated with 5-year mortality (hazard ratios: MG 1.18, TAR 1.20, GRI 1.23, CV 1.18, and TIR 0.83, all p ≤ 0.01). Associations remained significant after adjusting for landmark HbA1c. Results were similar with shorter CGM landmark observation windows. The association between CV and mortality was independent of other CGM metrics and appeared strongest in those with lower HbA1c levels.Conclusions: 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.