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March 29, 2026Diabetes Obesity and Metabolism3 citationsOpen Access

Glycemic Variability Bridges Time in Range and Time in Tight Range: A Unified Equation for Both Type 1 and Type 2 Diabetes Based on Large‐Scale Continuous Glucose Monitoring Data

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YYYu YaoUniversity of Science and Technology of ChinaZHZhigang HuShenzhen Institute of Information TechnologyYMYifei MoShenzhen Institute of Information Technology

Key Points

  • The aim is to establish a unified model for understanding the relationship between time in range and time in tight range for diabetes management.
  • Utilized large-scale continuous glucose monitoring (CGM) data
  • Analyzed data from individuals with type 1 and type 2 diabetes
  • Developed an exponential model for the time in range and time in tight range relationship
  • Introduced a new model to quantify the TIR-TITR relationship
  • Provided insights that may aid in personalizing diabetes treatment goals
  • Demonstrated the relevance of glycemic variability in diabetes management

Abstract

This study established the exponential model for TIR-TITR relationship in individuals with T1D and T2D, using a real-world CGM dataset. The model may provide new insights into the setting of individualized treatment goals.

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Cite This Study

Yao et al. (2026) studied this question.

synapsesocial.com/papers/69c8c2a4de0f0f753b39d001https://doi.org/10.1111/dom.70702
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Is It Time to Move Beyond TIR to TITR? Real-World Data from Over 20,000 Users of Continuous Glucose Monitoring in Patients with Type 1 and Type 2 Diabetes2024 · 73 citations
  2. 23 Time in range and time in tighter range in type 1 diabetes2024
  3. 3Clinical Implications and Applicability of Time in Tight Range2026
  4. 48 How can we correlate time in range and complications?2024
  5. 5Clinical Significance of Time-Based Glycemic Metrics in Continuous Glucose Monitoring2026