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
Authors' conclusion
The gamma model accurately predicts interactions between CGM-derived glycemic metrics and reveals that glycemic variability can significantly influence the relationship between AG and TIR with opposing effects according to AG levels.
Study context
- Population
- Self-identified T1D and T2D individuals using flash CGM (16,367 T1D, 11,061 T2D, 1736 others); 38,259 glucose readings/individual
- Participants
- 29,164 flash continuous glucose monitoring (FCGM) users
- Exposure
- Low vs high glucose coefficient of variation (CV) tertiles
- Outcome
- Effect of glycemic variability (glucose CV) on the relationship between AG and TIR/TITR, and best-fit glucose distribution model
Methodological detailsreal-world data
- Real-world data
Main finding
As reported in the abstract
TIR at AG of 150 mg/dL
P < 0.001
Observational data: associations, not effects.
Further findings
| Outcome | Low CV tertile | High CV tertile | P value |
|---|---|---|---|
| TITR at AG of 130 mg/dL | 65% ± 7.5% | 49% ± 7.0% | P < 0.001 |
Time in range (TIR) and time in tight range (TITR) at average glucose (AG) above the upper limit of these ranges
- Higher CV associated with increased TIR and TITR at AG levels outside the upper limit of these ranges
Glucose distribution model
- Gamma distribution superior to six other models at explaining AG and TIR/TITR interactions; nonlinear interplay between these metrics
Original publication
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. Diabetes Technol Ther. Published 26 February 2024. doi:10.
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