Different Times for Different Metrics: Predicting 90 Days of Intermittently Scanned Continuous Glucose Monitoring Data in Subjects With Type 1 Diabetes on Multiple Daily Injection Therapy. Findings From a Multicentric Real-World Study.
Alessandro Csermely, Nicolò D Borella, Anna Turazzini, Martina Pilati, Sara S Sheiban, Riccardo C Bonadonna, Roberto Trevisan, Maddalena Trombetta, Giuseppe Lepore
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引用次数: 0
Abstract
Aims: According to the 2023 International Consensus, glucose metrics derived from two-week-long continuous glucose monitoring (CGM) can be extrapolated up to 90 days before. However, no studies have focused on adults with type 1 diabetes (T1D) on multiple daily injections (MDIs) and with second-generation intermittently scanned CGM (isCGM) sensors in a real-world setting.
Methods: This real-world, retrospective study included 539 90-day isCGM data from 367 adults with T1D on MDI therapy. For each sensor metric, the coefficients of determination (R2) were computed for sampling periods from 2 to 12 weeks versus the whole 90-day interval. Correlations were considered strong for R2 ≥0.88.
Results: The two-week sampling period displayed strong correlations for time in range (TIR, 70-180 mg/dl; R2 = 0.89) and above range (TAR, >180 mg/dl; R2 = 0.88). The four-week sampling period showed additional strong correlations for time in tight range (TITR, 70-140 mg/dl; R2 = 0.92), for the coefficient of variation (CV; R2 = 0.88), and for the glycemia risk index (GRI; R2 = 0.92). The six-week sampling period displayed an additional strong correlation for time below range (TBR, <70 mg/dl; R2 = 0.90). After stratification by clinical variables, lower R2 values were found for older age quartiles (>40 years), higher CV (>36%), lower sensor use (≤94%), and higher HbA1c (>7.5%).
Conclusion: In patients with T1D on MDI, two- to six-week intervals of isCGM use can provide clinically useful estimates of TIR, TAR, TITR, TBR, CV, and GRI, which can be extrapolated to longer (up to 90 days) time intervals. Longer intervals might be needed in case of older age, higher glucose variability, lower sensor use, and higher HbA1c.
期刊介绍:
The Journal of Diabetes Science and Technology (JDST) is a bi-monthly, peer-reviewed scientific journal published by the Diabetes Technology Society. JDST covers scientific and clinical aspects of diabetes technology including glucose monitoring, insulin and metabolic peptide delivery, the artificial pancreas, digital health, precision medicine, social media, cybersecurity, software for modeling, physiologic monitoring, technology for managing obesity, and diagnostic tests of glycation. The journal also covers the development and use of mobile applications and wireless communication, as well as bioengineered tools such as MEMS, new biomaterials, and nanotechnology to develop new sensors. Articles in JDST cover both basic research and clinical applications of technologies being developed to help people with diabetes.