What does this research mean for the field?

Continuous Glucose Monitoring (CGM) metrics, particularly mean glucose, time in range, and time above range, predict clinically meaningful eGFR decline independently of HbA1c in adults with type 1 and type 2 diabetes. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This research aims to assess whether continuous glucose monitoring (CGM) metrics can enhance prediction of renal failure risk in adults with diabetes.

June 7, 2026

1902-P: Continuous Glucose Monitoring Metrics Predict ≥40% EGFR Decline among Adults with Type 1 and Type 2 Diabetes

Key Points

This research aims to assess whether continuous glucose monitoring (CGM) metrics can enhance prediction of renal failure risk in adults with diabetes.
Analyzed CGM metrics from 2,500 U.S. Veterans with type 1 and type 2 diabetes over a 6-month period after initiating Dexcom CGM.
Derived mean glucose, time in range, time above range, coefficient of variation, glycemic risk index, and mean lab HbA1c for each participant.
Used Cox models to evaluate the association between CGM metrics and time to ≥40% eGFR decline over a mean follow-up of 3.6 years.
Out of 2,308 patients, 120 experienced a ≥40% decline in eGFR during the study period.
Higher mean glucose, time above range, and glycemic risk index were linked to increased risk of eGFR decline (all p≤0.02).
The impact of LM HbA1c was less pronounced, indicating CGM metrics provide additional risk stratification beyond HbA1c.

Abstract

Introduction and Objective: To determine whether CGM metrics improve the prediction of those at high risk for renal failure (ESRD). Methods: CGM metrics from 2,500 U.S. Veterans with type 1 and type 2 diabetes initiating Dexcom CGM (2015-2022) were linked to patients’ health records. In a 6-month landmark (LM) period after first CGM upload (index date), we derived mean glucose (MG), time in range (TIR), time above range (TAR), coefficient of variation (CV), glycemic risk index (GRI), and mean lab HbA1c (LM HbA1c). The primary outcome was time to ≥40% eGFR decline (persisting 45 days) over 5 years after the index date. Exclusions included ESRD, missing eGFR at baseline (within 1 year pre-index date), 10 CGM wear days, or an outcome occurring within the LM. Cox models adjusted for baseline risk factors and then additionally for LM HbA1c. Results: In 2,308 patients (mean age 61 years; baseline eGFR 76.5 mL/min/1.73 m²), 120 events occurred over a mean follow-up of 3.6 years. Higher MG, TAR, GRI, and lower TIR were associated with higher risk (all p≤0.02) (Figure). LM HbA1c showed weaker associations. Adding LM HbA1c made little difference to the estimates. Findings were similar with a 90-day persistence definition. Associations were not evident at 14 days but were evident by 3 months and were similar at 6 months. Conclusion: CGM metrics, especially MG, TIR, and TAR, predict clinically meaningful eGFR decline beyond and independent of HbA1c, supporting CGM-based renal risk stratification. Disclosure T. Okuno: None. S. Macwan: None. G. Norman: Employee; Current; Dexcom, Inc. Stock/Shareholder; Current; Dexcom, Inc. D.R. Miller: None. P. Reaven: Research Support; Current; Dexcom, Inc., Lilly Global Health Partnership. J. Zhou: None. Funding National Institutes of Health (R01 DK142026)National Science Foundation (DMS 2054253 and IIS 2205441)

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1902-P: Continuous Glucose Monitoring Metrics Predict ≥40% EGFR Decline among Adults with Type 1 and Type 2 Diabetes

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