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Background: Glucose data from intermittently scanned continuous glucose monitoring (isCGM) is a combination of scanned and imported glucose values. The present knowledge of glycemic metrics originate mostly from glucose data from real-time CGM sampled every five minutes with a lack of information derived from isCGM. Methods: Glucose data obtained with isCGM and hemoglobin A1c (HbA1c) were obtained from 169 patients with type 1 diabetes. Sixty-one patients had two observations with an interval of more than three months. Results: The best regression line of HbA1c against mean glucose was observed from 60 days prior to HbA1c measurement as compared to 14, 30, and 90 days. The difference between HbA1c and estimated HbA1c (=glucose management indicator [GMI]) first observed correlated with the second observation (R2 0.61, P < .001). Time in range (TIR, glucose between 3.9 and 10 mmol/L) was significantly related to GMI (R2 0.87, P < .001). A TIR of 70% corresponded to a GMI of 6.8% (95% confidence interval, 6.3-7.4). The fraction of patients with the optimal combination of TIR >70% and time below range (TBR) 4% was four times higher for those with high glycemic variability (coefficient of variation [CV] >36%) than for those with lower CV. Conclusion: The individual difference between HbA1c and GMI was reproducible. High glycemic variability was related to increased TBR. A combination of TIR and TBR is suggested as a new composite quality indicator.

Background: The relation between the frequency of intermittently scanned continuous glucose monitoring (isCGM) and diurnal variation of time in range (TIR) and time below range (TBR) is unknown. Method: A total of 163 persons with type 1 diabetes who used isCGM had glucose data for 60 days downloaded. Mean TIR and median TBR were calculated for 15-minute periods and presented for daytime and nighttime. The values for tertiles of scanning frequency were compared. Results: The 1st tertile ( n = 53) of the population scanned 13 per 24 hours. TIR (%, mean ± (SD)) increased significantly from the 1st to the 3rd scan tertile both during the day (43.8 ± 14.8, 52.0 ± 12.3, 62.1 ± 12.8) and the night (44.5 ± 17.3, 52.3 ± 18.5, 64.0 ± 13.9; P < .0001). In contrast, TBR (median, (IQR)) was not significantly associated with scan tertiles during daytime (3.5% (1.1-7.8), 4.4% (1.8-6.1), 3.5% (2.1-6.1); P = .85) or nighttime (3.8% (1.4-13.7), 5.0% (1.6-9.6), 5.7% (3.6-10.9); P = .24). In a multiple regression model, a 50% increase in 24-hour scanning frequency was associated with a 7.8 percentage point increase in TIR (95% CI, 5.6-10.0). Conclusions: Increased scanning frequency was associated with a higher TIR both during daytime and nighttime with no change in TBR.