Time in range, time in tight range and average glucose relationships are modulated by glycemic variability: identification of a glucose distribution model connecting glycemic parameters using real-world data.

Background Time in range (TIR), time in tight range (TITR) and average glucose (AG) are used to adjust glycemic therapies in diabetes. However, TIR/TITR and AG can show a disconnect, which may create management difficulties. We aimed to understand the factors influencing the relationships between these glycemic markers. Materials and methods Real-world glucose data were collected from self-identified diabetes individuals using flash continuous glucose monitoring (CGM). The effects of glycemic variability (GV), assessed as glucose coefficient of variation (CV), on the relationship between AG and TIR/TITR was investigated together with the best-fit glucose distribution model that addresses these relationships. Results Glucose readings were collected from 29,164 users (16,367 T1D, 11,061 T2D, and 1,736 others, 38,259 readings/subject). Comparing low and high CV tertiles, TIR at average glucose of 150 mg/dL varied from 80±5.6% to 62±6.8%, respectively (p<0.001), while TITR at average glucose of 130 mg/dL varied from 65±7.5% to 49±7.0%, respectively (p<0.001). In contrast, higher CV was associated with increased TIR and TITR at AG levels outside the upper limit of these ranges. Gamma distribution was superior to five other models fitting the glucose distribution and explained the observed trends, values, and non-linear interplay among CGM-derived glycemic metrics. Conclusions GV can significantly influence the relationship between AG and TIR with opposing effects according to AG levels, with the gamma model accurately predicting interactions among the different glycemic metrics. These data can potentially help the clinical management of individuals with diabetes, particularly when a mismatch between AG and TIR is apparent.