Glucose Regulation Beyond HbA1c in Type 2 Diabetes Treated With Insulin: Real-World Evidence From the DIALECT-2 Cohort

OBJECTIVE To investigate glucose variations associated with glycated hemoglobin (HbA(1c)) in insulin-treated patients with type 2 diabetes. RESEARCH DESIGN AND METHODS Patients included in Diabetes and Lifestyle Cohort Twente (DIALECT)-2 (n = 79) were grouped into three HbA(1c) categories: low, intermediate, and high (<= 53, 54-62, and >= 63 mmol/mol or <= 7, 7.1-7.8, and >= 7.9%, respectively). Blood glucose time in range (TIR), time below range (TBR), time above range (TAR), glucose variability parameters, day and night duration, and frequency of TBR and TAR episodes were determined by continuous glucose monitoring (CGM) using the FreeStyle Libre sensor and compared between HbA(1c) categories. RESULTS CGM was performed for a median (interquartile range) of 10 (7-12) days/patient. TIR was not different for low and intermediate HbA(1c) categories (76.8% [68.3-88.2] vs. 76.0% [72.5.0-80.1]), whereas in the low category, TBR was higher and TAR lower (7.7% [2.4-19.1] vs. 0.7% [0.3-6.1] and 8.2% [5.7-17.6] vs. 20.4% [11.6-27.0], respectively; P < 0.05). Patients in the highest HbA(1c) category had lower TIR (52.7% [40.9-67.3]) and higher TAR (44.1% [27.8-57.0]) than the other HbA(1c) categories (P < 0.05), but did not have less TBR during the night. All patients had more (0.06 +/- 0.06/h vs. 0.03 +/- 0.03/h; P = 0.002) and longer (88.0 [45.0-195.5] vs. 53.4 [34.4-82.8] minutes; P < 0.001) TBR episodes during the night than during the day. CONCLUSIONS In this study, a high HbA(1c) did not reduce the occurrence of nocturnal hypoglycemia, and low HbA(1c) was not associated with the highest TIR. Optimal personalization of glycemic control requires the use of newer tools, including CGM-derived parameters.

Automated summary

In insulin-treated patients with type 2 diabetes, high HbA(1c) did not decrease the occurrence of nocturnal hypoglycemia, and low HbA(1c) was not associated with the highest time in range (TIR). Optimal personalization of glycemic control requires the use of newer tools, including CGM-derived parameters.