Within-Person and Between-Sensor Variability in Continuous Glucose Monitoring Metrics.

BACKGROUND: The within-person and between-sensor variability of metrics from different interstitial continuous glucose monitoring (CGM) sensors in adults with type 2 diabetes not taking insulin is unclear. METHODS: Secondary analysis of data from 172 participants from the Hyperglycemic Profiles in Obstructive Sleep Apnea randomized clinical trial. Participants simultaneously wore Dexcom G4 and Abbott Libre Pro CGM sensors for up to 2 weeks at baseline and again at the 3-month follow-up visit. RESULTS: At baseline (up to 2 weeks of CGM), mean glucose for both the Abbott and Dexcom sensors was approximately 150 mg/dL (8.3 mmol/L) and time in range (70180 mg/dL [3.910.0 mmol/L]) was just below 80. When comparing the same sensor at 2 different time points (two 2-week periods, 3 months apart), the within-person coefficient of variation (CVw) in mean glucose was 17.4 (Abbott) and 14.2 (Dexcom). CVw for percent time in range: 20.1 (Abbott) and 18.6 (Dexcom). At baseline, the Pearson correlation of mean glucose from the 2 sensors worn simultaneously was r 0.86, root mean squared error (RMSE), 13 mg/dL (0.7 mmol/L); for time in range, r 0.88, RMSE, 8 percentage points. CONCLUSIONS: Substantial variation was observed within sensors over time and across 2 different sensors worn simultaneously on the same individuals. Clinicians should be aware of this variability when using CGM technology to make clinical decisions.ClinicalTrials.gov Identifier: NCT02454153.

Glucose Color Index: Development and Validation of a Novel Measure of the Shape of Glycemic Variability.

BACKGROUND: Standard continuous glucose monitoring (CGM) metrics: mean glucose, standard deviation, coefficient of variation, and time in range, fail to capture the shape of variability in the CGM time series. This information could facilitate improved diabetes management. METHODS: We analyzed CGM data from 141 adults with type 2 diabetes in the Hyperglycemic Profiles in Obstructive Sleep Apnea (HYPNOS) trial. Participants in HYPNOS wore CGM sensors for up to two weeks at two time points, three months apart. We calculated the log-periodogram for each time period, summarizing using disjoint linear models. These summaries were combined into a single value, termed the Glucose Color Index (GCI), using canonical correlation analysis. We compared the between-wear correlation of GCI with those of standard CGM metrics and assessed associations between GCI and diabetes comorbidities in 398 older adults with type 2 diabetes from the Atherosclerosis Risk in Communities (ARIC) study. RESULTS: The GCI achieved a test-retest correlation of R = .75. Adjusting for standard CGM metrics, the GCI test-retest correlation was R = .55. Glucose Color Index was significantly associated (p < .05) with impaired physical functioning, frailty/pre-frailty, cardiovascular disease, chronic kidney disease, and dementia/mild cognitive impairment after adjustment for confounders. CONCLUSION: We developed and validated the GCI, a novel CGM metric that captures the shape of glucose variability using the periodogram signal decomposition. Glucose Color Index was reliable within participants over a three-month period and associated with diabetes comorbidities. The GCI suggests a promising avenue toward the development of CGM metrics which more fully incorporate time series information.

The Associations of Mean Glucose and Time in Range from Continuous Glucose Monitoring with HbA1c in Adults with Type 2 Diabetes.

Associations of mean glucose and time in range (70-180 mg/dL) from continuous glucose monitoring (CGM) with HbA1c in adults with type 2 diabetes are not well characterized. We conducted a secondary analysis of 186 participants from the Hyperglycemic Profiles in Obstructive Sleep Apnea (HYPNOS) trial. Participants simultaneously wore Dexcom G4 and Abbott Libre Pro CGM sensors up to 4 weeks. Mean HbA1c was 7.7% (SD, 1.3). There were strong negative Pearson's correlations of HbA1c with CGM time in range (-0.79, Abbott; -0.81, Dexcom) and strong positive correlations with CGM mean glucose (Dexcom, 0.84; Abbott, 0.82). However, there were large differences in CGM mean glucose (±20 mg/dL) and time in range (±14%) at any given HbA1c value. Mean glucose and HbA1c are strongly correlated in type 2 diabetes patients not taking insulin but discordance is evident at the individual level. Clinicians should expect discordance and use HbA1c and CGM in a complementary manner. ClinicalTrials.gov Identifier: NCT02454153.