OBJECTIVETo determine whether short-time, real-time continuous glucose monitoring (RT-CGM) has long-term salutary glycemic effects in patients with type 2 diabetes who are not on prandial insulin.RESEARCH DESIGN AND METHODSThis was a randomized controlled trial of 100 adults with type 2 diabetes who were not on prandial insulin. This study compared the effects of 12 weeks of intermittent RT-CGM with self-monitoring of blood glucose (SMBG) on glycemic control over a 40-week follow-up period. Subjects received diabetes care from their regular provider without therapeutic intervention from the study team.RESULTSThere was a significant difference in A1C at the end of the 3-month active intervention that was sustained during the follow-up period. The mean, unadjusted A1C decreased by 1.0, 1.2, 0.8, and 0.8% in the RT-CGM group vs. 0.5, 0.5, 0.5, and 0.2% in the SMBG group at 12, 24, 38, and 52 weeks, respectively (P = 0.04). There was a significantly greater decline in A1C over the course of the study for the RT-CGM group than for the SMBG group, after adjusting for covariates (P < 0.0001). The subjects who used RT-CGM per protocol (≥48 days) improved the most (P < 0.0001). The improvement in the RT-CGM group occurred without a greater intensification of medication compared with those in the SMBG group.CONCLUSIONSSubjects with type 2 diabetes not on prandial insulin who used RT-CGM intermittently for 12 weeks significantly improved glycemic control at 12 weeks and sustained the improvement without RT-CGM during the 40-week follow-up period, compared with those who used only SMBG.

Background: Real-time continuous glucose monitoring (RT-CGM) improves hemoglobin A1c (A1C) and hypoglycemia in people with type 1 diabetes mellitus and those with type 2 diabetes mellitus (T2DM) on prandial insulin; however, it has not been tested in people with T2DM not taking prandial insulin. We evaluated the utility of RT-CGM in people with T2DM on a variety of treatment modalities except prandial insulin. Methods: We conducted a prospective, 52-week, two-arm, randomized trial comparing RT-CGM ( n = 50) versus self-monitoring of blood glucose (SMBG) ( n = 50) in people with T2DM not taking prandial insulin. Real-time continuous glucose monitoring was used for four 2-week cycles (2 weeks on/1 week off). All patients were managed by their usual provider. This article reports on changes in A1C 0–12 weeks. Results: Mean (±standard deviation) decline in A1C at 12 weeks was 1.0% (±1.1%) in the RT-CGM group and 0.5% (±0.8%) in the SMBG group ( p = .006). There were no group differences in the net change in number or dosage of hypoglycemic medications. Those who used the RT-CGM for ±48 days (per protocol) reduced their A1C by 1.2% (±1.1%) versus 0.6% (±1.1%) in those who used it <48 days ( p = .003). Multiple regression analyses statistically adjusting for baseline A1C, an indicator for usage, and known confounders confirmed the observed differences between treatment groups were robust ( p = .009). There was no improvement in weight or blood pressure. Conclusions: Real-time continuous glucose monitoring significantly improves A1C compared with SMBG in patients with T2DM not taking prandial insulin. This technology might benefit a wider population of people with diabetes than previously thought.

OBJECTIVETo characterize glucose response patterns of people who wore a real-time continuous glucose monitor (RT-CGM) as an intervention to improve glycemic control. Participants had type 2 diabetes, were not taking prandial insulin, and interpreted the RT-CGM data independently.RESEARCH DESIGN AND METHODSData were from the first 12 weeks of a 52-week, prospective, randomized trial comparing RT-CGM (n = 50) with self-monitoring of blood glucose (n = 50). RT-CGM was used in 8 of the first 12 weeks. A1C was collected at baseline and quarterly. This analysis included 45 participants who wore the RT-CGM ≥4 weeks. Analyses examined the RT-CGM data for common response patterns—a novel approach in this area of research. It then used multilevel models for longitudinal data, regression, and nonparametric methods to compare the patterns of A1C, mean glucose, glycemic variability, and views per day of the RT-CGM device.RESULTSThere were five patterns. For four patterns, mean glucose was lower than expected as of the first RT-CGM cycle of use given participants’ baseline A1C. We named them favorable response but with high and variable glucose (n = 7); tight control (n = 14); worsening glycemia (n = 6); and incremental improvement (n = 11). The fifth was no response (n = 7). A1C, mean glucose, glycemic variability, and views per day differed across patterns at baseline and longitudinally.CONCLUSIONSThe patterns identified suggest that targeting people with higher starting A1Cs, using it short-term (e.g., 2 weeks), and monitoring for worsening glycemia that might be the result of burnout may be the best approach to using RT-CGM in people with type 2 diabetes not taking prandial insulin.