Impact of Fast-Acting Insulin Aspart on Glycemic Control in Patients with Type 1 Diabetes Using Intermittent-Scanning Continuous Glucose Monitoring Within a Real-World Setting: The GoBolus Study.

Background: The GoBolus study investigated the real-world effectiveness of faster aspart in patients with type 1 diabetes (T1D) using intermittent-scanning continuous glucose monitoring (iscCGM) systems. Methods: This 24-week, multicenter, single-arm, noninterventional study investigated adults with T1D (HbA1c, 7.5%-9.5%) receiving multiple daily injections (MDI) of insulin and using iscCGM within local healthcare settings for ≥6 months before switching to faster aspart at study start (week 0; baseline). Primary endpoint was HbA1c change from baseline to week 24. Exploratory endpoint was change in iscCGM metrics from baseline to week 24. Results: Overall, 243 patients were included (55.6% male), with mean age/diabetes duration, 49.9/18.8 years; mean HbA1c, 8.1%. By week 24, HbA1c had decreased by 0.19% (-2.1 mmol/mol, P < 0.0001) with no mean change in insulin doses or basal/bolus insulin ratios. For patients with sufficient available iscCGM data (n = 92): "time in range" (TIR; 3.9-10.0 mmol/L) increased from 46.9% to 50.1% (P = 0.01), corresponding to an increase of 46.1 min/day; time in hyperglycemia decreased from 49.1% to 46.1% (>10.0 mmol/L, P = 0.026) and 20.4% to 17.9% (>13.9 mmol/L, P = 0.013), corresponding to 43.5 (P = 0.024) and 35.6 (P = 0.015) fewer minutes per day on average spent in these ranges, respectively; no change for time in hypoglycemia (<3.9 and <3.0 mmol/L). Mean interstitial and postprandial glucose improved from 10.4 to 10.1 mmol/L (P = 0.035) and 11.9 to 11.0 mmol/L (P = 0.002), respectively. Conclusion: Real-world switching to faster aspart in adults with T1D on MDI improved HbA1c, increased TIR, and decreased time in hyperglycemia without affecting time in hypoglycemia. The GoBolus study: NCT03450863.

Results that matter: structured vs. unstructured self-monitoring of blood glucose in type 2 diabetes.

Self-monitoring of blood glucose (SMBG) is one component of diabetes management. SMBG presents information about current glycemic status and provides the ability to obtain immediate feedback regarding the impact of behavioral and pharmacological interventions on glucose levels. However, SMBG is useful only when the glucose information is understood correctly, data are accurately interpreted, and results prompt appropriate therapeutic actions. The International Diabetes Federation (IDF) recently published guidelines for SMBG use in non-insulin treated people with diabetes, recommending that SMBG should be used only when patients and/or their clinicians possess the ability and willingness to incorporate SMBG monitoring and therapy adjustment into their diabetes care plan. If SMBG is used, the IDF also recommends that structured SMBG be performed utilizing defined regimens to meet individual needs. Structured SMBG can be performed as daily glucose profiles that are representative of daily glucose excursions. Measuring preprandial/postprandial blood glucose (bG) levels on consecutive or alternating days ("testing in pairs") also provides impactful glucose information for daily diabetes management. This article reviews recent studies that appropriately utilized structured SMBG as an integral component of comprehensive diabetes management and discusses how their findings support the IDF recommendations. Our goal is to help clinicians make more informed decisions about the value and utility of SMBG in diabetes management.

Use of an automated decision support tool optimizes clinicians' ability to interpret and appropriately respond to structured self-monitoring of blood glucose data.

OBJECTIVE: We evaluated the impact of an automated decision support tool (DST) on clinicians' ability to identify glycemic abnormalities in structured self-monitoring of blood glucose (SMBG) data and then make appropriate therapeutic changes based on the glycemic patterns observed. RESEARCH DESIGN AND METHODS: In this prospective, randomized, controlled, multicenter study, 288 clinicians (39.6% family practice physicians, 37.9% general internal medicine physicians, and 22.6% nurse practitioners) were randomized to structured SMBG alone (STG; n = 72); structured SMBG with DST (DST; n = 72); structured SMBG with an educational DVD (DVD; n = 72); and structured SMBG with DST and the educational DVD (DST+DVD; n = 72). Clinicians analyzed 30 patient cases (type 2 diabetes), identified the primary abnormality, and selected the most appropriate therapy. RESULTS: A total of 222 clinicians completed all 30 patient cases with no major protocol deviations. Significantly more DST, DVD, and DST+DVD clinicians correctly identified the glycemic abnormality and selected the most appropriate therapeutic option compared with STG clinicians: 49, 51, and 55%, respectively, vs. 33% (all P < 0.0001) with no significant differences among DST, DVD, and DST+DVD clinicians. CONCLUSIONS: Use of structured SMBG, combined with the DST, the educational DVD, or both, enhances clinicians' ability to correctly identify significant glycemic patterns and make appropriate therapeutic decisions to address those patterns. Structured testing interventions using either the educational DVD or the DST are equally effective in improving data interpretation and utilization. The DST provides a viable alternative when comprehensive education is not feasible, and it may be integrated into medical practices with minimal training.

A structured self-monitoring of blood glucose approach in type 2 diabetes encourages more frequent, intensive, and effective physician interventions: results from the STeP study.

BACKGROUND: We evaluated how a structured patient/physician self-monitoring of blood glucose (SMBG) intervention influenced the timing, frequency, and effectiveness of primary care physicians' treatment changes with type 2 diabetes mellitus (T2DM) patients over 12 months. METHODS: The Structured Testing Program (STeP) study was a cluster-randomized, multicenter trial with 483 poorly controlled, insulin-naive T2DM subjects. Primary care practices were randomized to the Active Control Group (ACG) or the Structured Testing Group (STG), the latter of which included quarterly review of structured SMBG results. STG patients used a paper tool that graphs seven-point glucose profiles over 3 consecutive days; physicians received a treatment algorithm based on SMBG patterns. Impact of structured SMBG on physician treatment modification recommendations (TMRs) and glycemic outcomes was examined. RESULTS: More STG than ACG patients received a TMR at each study visit (P < 0.0001). Of patients who received at least one TMR, STG patients demonstrated a greater reduction in glycated hemoglobin A1c (HbA1c) than ACG patients (-1.2% vs. -0.8%, P < 0.03). Patients with a baseline HbA1c ≥8.5% who received a TMR at the Month 1 visit experienced greater reductions in HbA1c (P = 0.002) than patients without an initial TMR. More STG than ACG patients were started on incretins (P < 0.01) and on thiazolidinediones (P = 0.004). The number of visits with a TMR was unrelated to HbA1c change over time. CONCLUSIONS: Patient-provided SMBG data contribute to glycemic improvement when blood glucose patterns are easy to detect, and well-trained physicians take timely action. Collaborative use of structured SMBG data leads to earlier, more frequent, and more effective TMRs for poorly controlled, non-insulin-treated T2DM subjects.