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.

Diabetes Data Management System to Improve Glycemic Control in People With Type 1 Diabetes: Prospective Cohort Study.

BACKGROUND: Smartphone and Web technology can improve the health care process, especially in chronic diseases. OBJECTIVE: The aim of this study was to investigate whether the use of blood glucose (BG) data management system, which enables connection to smartphones, the Web, the cloud, and downloading, can improve glycemic control in subjects with type 1 diabetes mellitus (T1DM). METHODS: This study was a prospective, single-arm, cohort feasibility study with 6 months of duration. T1DM subjects enrolled had experience in self-monitoring blood glucose, but were download data naïve. Fasting BG and glycated hemoglobin (HbA1c) were collected at the enrollment and at follow-up. Subjects were divided into Downloader (DL) and No-downloader (NDL). RESULTS: A total of 63 subjects were analyzed, of which 30 were classified as DL and 33 as NDL. At the end of the study, DL had significantly lower HbA1c, mean daily glucose, standard deviation, percentage of BG values above target, and pre- and postprandial (lunch and dinner) values compared with NDL (all P<.05). The percentage of BG values within treatment target was significantly higher in DL compared with NDL (47% [SD 9] vs 37% [SD 13]; P=.001). CONCLUSIONS: The findings suggest that, in T1DM, downloading of BG from data management system, which enables connection to smartphones, the Web, and the cloud, might be a valuable contributor to improved glycemic control.

Use of an insulin bolus advisor facilitates earlier and more frequent changes in insulin therapy parameters in suboptimally controlled patients with diabetes treated with multiple daily insulin injection therapy: results of the ABACUS trial.

BACKGROUND: We assessed the impact of using an automated bolus advisor integrated into a blood glucose meter on the timing and frequency of adjusting insulin therapy parameter settings and whether the availability of this technology would increase blood glucose test strip utilization in diabetes patients treated with multiple daily insulin injection (MDI) therapy. SUBJECTS AND METHODS: The Automated Bolus Advisor Control and Usability Study (ABACUS) trial, a 26-week, prospective, randomized, controlled, multinational study that enrolled 218 type 1 and type 2 diabetes patients, demonstrated that use of an automated insulin bolus advisor helps improve glycemic control in suboptimally controlled, MDI-treated patients. Patient data were assessed to determine when and how often changes in insulin parameter settings occurred during the study. Patient meters were downloaded to determine blood glucose monitoring frequency. RESULTS: One hundred ninety-three patients completed the study: 93 control arm (CNL) and 100 intervention (experimental) arm (EXP). Significantly more EXP (47.5%) than CNL (30.7%) patients received one or more changes in their insulin sensitivity factor (ISF) settings during the study (P=0.0191). Changes in ISF settings occurred earlier and more frequently in EXP than CNL patients throughout the study. A similar trend was seen in changes in insulin-to-carbohydrate ratios. There were no differences in daily self-monitoring of blood glucose frequency [mean (SD)] between CNL and EXP patients: 4.7 (1.5) versus 4.6 (1.3) (P=0.4085). CONCLUSIONS: Use of an automated bolus advisor was associated with earlier, more frequent changes in key insulin parameters, which may have contributed to subsequent improvements in glycemic control but without increased glucose test strip utilization.

Use of an insulin bolus advisor improves glycemic control in multiple daily insulin injection (MDI) therapy patients with suboptimal glycemic control: first results from the ABACUS trial.

OBJECTIVE: Use of automated bolus advisors is associated with improved glycemic control in patients treated with insulin pump therapy. We conducted a study to assess the impact of using an insulin bolus advisor embedded in a blood glucose (BG) meter on glycemic control and treatment satisfaction in patients treated with multiple daily insulin injection (MDI) therapy. The study goal was to achieve >0.5% A1C reduction in most patients. RESEARCH DESIGN AND METHODS: This was a 26-week, prospective, randomized, controlled, multinational study that enrolled 218 MDI-treated patients with poorly controlled diabetes (202 with type 1 diabetes, 16 with type 2 diabetes) who were 18 years of age or older. Participants had mean baseline A1C of 8.9% (SD, 1.2 [74 mmol/mol]), mean age of 42.4 years (SD, 14.0), mean BMI of 26.5 kg/m(2) (SD, 4.2), and mean diabetes duration of 17.7 years (SD, 11.1). Control group (CNL) patients used a standard BG meter and manual bolus calculation; intervention group (EXP) patients used the Accu-Chek Aviva Expert meter with an integrated bolus advisor to calculate insulin dosages. Glucose data were downloaded and used for therapy parameter adjustments in both groups. RESULTS: A total of 193 patients (CNL, n = 93; EXP, n = 100) completed the study. Significantly more EXP than CNL patients achieved >0.5% A1C reduction (56.0% vs. 34.4%; P < 0.01). Improvement in treatment satisfaction (Diabetes Treatment Satisfaction Questionnaire scale) was significantly greater in EXP patients (11.4 [SD, 6.0] vs. 9.0 [SD, 6.3]; P < 0.01). Percentage of BG values <50 mg/dL was <2% in both groups during the study. CONCLUSIONS: Use of an automated bolus advisor resulted in improved glycemic control and treatment satisfaction without increasing severe hypoglycemia.

Changes in A1C levels are significantly associated with changes in levels of the cardiovascular risk biomarker hs-CRP: results from the SteP study.

OBJECTIVE: The effect of therapeutic strategies on cardiovascular (CV) disease can be evaluated by monitoring changes in CV risk biomarkers. This study investigated the effect of a structured self-monitoring of blood glucose (SMBG) protocol and the resulting improvements in glycemic control on changes in high-sensitivity C-reactive protein (hs-CRP) in insulin-naïve patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: The Structured Testing Program (STeP) study was a prospective, cluster-randomized, multicenter trial in which 483 poorly controlled, insulin-naïve patients with type 2 diabetes were randomized to active control (ACG) or structured testing (STG) that included quarterly structured SMBG. Changes in A1C, hs-CRP, and glycemic variability (STG subjects only) were measured at baseline and quarterly. RESULTS: Reductions in geometric mean hs-CRP values were significantly greater in the STG group at months 3 (P = 0.005), 6 (P = 0.0003), and 12 (P = 0.04) than in the ACG group. STG patients at high CV risk (>3 mg/L) showed significantly greater reductions in hs-CRP levels than ACG patients at high CV risk: -3.64 mg/dL (95% CI -4.21 to -3.06) versus -2.18 mg/dL (-2.93 to -1.43), respectively (P = 0.002). There was a strong correlation between reductions in hs-CRP and A1C in both groups: standardized coefficient (ß) was 0.25 for the entire cohort (P < 0.0001), 0.31 for STG (P < 0.0001), and 0.16 for ACG (P = 0.02). CONCLUSIONS: Reductions in hs-CRP level are associated with reductions in A1C but not reductions in lipids or glycemic variability. Comprehensive structured SMBG-based interventions that lower A1C may translate into improvements in CV risk, as evidenced by levels of the biomarker hs-CRP.

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.

Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes: results from the Structured Testing Program study.

OBJECTIVE: To assess the effectiveness of structured blood glucose testing in poorly controlled, noninsulin-treated type 2 diabetes. RESEARCH DESIGN AND METHODS: This 12-month, prospective, cluster-randomized, multicenter study recruited 483 poorly controlled (A1C ≥ 7.5%), insulin-naïve type 2 diabetic subjects from 34 primary care practices in the U.S. Practices were randomized to an active control group (ACG) with enhanced usual care or a structured testing group (STG) with enhanced usual care and at least quarterly use of structured self-monitoring of blood glucose (SMBG). STG patients and physicians were trained to use a paper tool to collect/interpret 7-point glucose profiles over 3 consecutive days. The primary end point was A1C level measured at 12 months. RESULTS: The 12-month intent-to-treat analysis (ACG, n = 227; STG, n = 256) showed significantly greater reductions in mean (SE) A1C in the STG compared with the ACG: -1.2% (0.09) vs. -0.9% (0.10); Δ = -0.3%; P = 0.04. Per protocol analysis (ACG, n = 161; STG, n = 130) showed even greater mean (SE) A1C reductions in the STG compared with the ACG: -1.3% (0.11) vs. -0.8% (0.11); Δ = -0.5%; P < 0.003. Significantly more STG patients received a treatment change recommendation at the month 1 visit compared with ACG patients, regardless of the patient's initial baseline A1C level: 179 (75.5%) vs. 61 (28.0%); <0.0001. Both STG and ACG patients displayed significant (P < 0.0001) improvements in general well-being (GWB). CONCLUSIONS: Appropriate use of structured SMBG significantly improves glycemic control and facilitates more timely/aggressive treatment changes in noninsulin-treated type 2 diabetes without decreasing GWB.

Clinical performance of three bolus calculators in subjects with type 1 diabetes mellitus: a head-to-head-to-head comparison.

BACKGROUND: Insulin pump systems now provide automated bolus calculators (ABCs) that electronically calculate insulin boluses to address carbohydrate intake and out-of-range blood glucose (bG) levels. We compared the efficacy of three ABCs (Accu-Chek(®) Combo [Roche Insulin Delivery Systems (IDS), Inc., Fishers, IN, a member of the Roche Group], Animas(®) 2020 [Animas Corp., West Chester, PA, a Johnson and Johnson company], and MiniMed Paradigm Bolus Wizard(®) [Medtronic MiniMed, Northridge, CA]) to safely reduce postprandial hyperglycemia in type 1 diabetes mellitus (T1DM). METHODS: T1DM subjects (n = 24) were recruited at a single center for a prospective, triple crossover study. ABCs with the programmed target range (80-140 mg/dL) were used in random order. Postprandial hyperglycemia was induced by reducing the calculated bolus by 25%. Two hours after test meals, the ABCs were allowed to determine whether a correction bolus was needed. Differences between 6-h bG values after test meals that achieved 2-h postprandial hyperglycemia and the mean of the target range (110 mg/dL) were determined. RESULTS: The mean difference between 6-h bG levels following test meals and the 110 mg/dL bG target with the MiniMed device (47.4 ± 31.8 mg/dL) was significantly higher than the Animas (17.3 ± 30.9 mg/dL) and Roche IDS (18.8 ± 33.8 mg/dL) devices (P = 0.0022 and P = 0.0049, respectively). The number of meals with 2-h postprandial hyperglycemia and bG levels at 2 h was similar. Roche IDS and Animas devices recommended correction boluses significantly (P = 0.0001 and P = 0.0002, respectively) more frequently than the MiniMed device. ABC use was not associated with severe hypoglycemia. There was no significant difference in the rate of mild hypoglycemia (bG <60 mg/dL not requiring assistance) among the three groups (Roche IDS and Animas, n = 2; MiniMed, n = 0). CONCLUSIONS: In this study, the Roche IDS and Animas devices were more efficacious in controlling postprandial hyperglycemia than the MiniMed device. This may be due, in part, to differences in ABC setup protocols and algorithms. Use of ABCs can assist in controlling postprandial glycemia without significant hypoglycemia.

The value of episodic, intensive blood glucose monitoring in non-insulin treated persons with Type 2 Diabetes: design of the Structured Testing Program (STeP) study, a cluster-randomised, clinical trial [NCT00674986].

BACKGROUND: The value and utility of self-monitoring of blood glucose (SMBG) in non-insulin treated T2DM has yet to be clearly determined. Findings from studies in this population have been inconsistent, due mainly to design differences and limitations, including the prescribed frequency and timing of SMBG, role of the patient and physician in responding to SMBG results, inclusion criteria that may contribute to untoward floor effects, subject compliance, and cross-arm contamination. We have designed an SMBG intervention study that attempts to address these issues. METHODS/DESIGN: The Structured Testing Program (STeP) study is a 12-month, cluster-randomised, multi-centre clinical trial to evaluate whether poorly controlled (HbA1c >or= 7.5%), non-insulin treated T2DM patients will benefit from a comprehensive, integrated physician/patient intervention using structured SMBG in US primary care practices. Thirty-four practices will be recruited and randomly assigned to an active control group (ACG) that receives enhanced usual care or to an enhanced usual care group plus structured SMBG (STG). A total of 504 patients will be enrolled; eligible patients at each site will be randomly selected using a defined protocol. Anticipated attrition of 20% will yield a sample size of at least 204 per arm, which will provide a 90% power to detect a difference of at least 0.5% in change from baseline in HbA1c values, assuming a common standard deviation of 1.5%. Differences in timing and degree of treatment intensification, cost effectiveness, and changes in patient self-management behaviours, mood, and quality of life (QOL) over time will also be assessed. Analysis of change in HbA1c and other dependent variables over time will be performed using both intent-to-treat and per protocol analyses. Trial results will be available in 2010. DISCUSSION: The intervention and trial design builds upon previous research by emphasizing appropriate and collaborative use of SMBG by both patients and physicians. Utilization of per protocol and intent-to-treat analyses facilitates a comprehensive assessment of the intervention. Use of practice site cluster-randomisation reduces the potential for intervention contamination, and inclusion criteria (HbA1c >or= 7.5%) reduces the possibility of floor effects. Inclusion of multiple dependent variables allows us to assess the broader impact of the intervention, including changes in patient and physician attitudes and behaviours. TRIAL REGISTRATION: Current Controlled Trials NCT00674986.

Changes in basal insulin infusion rates with subcutaneous insulin infusion: time until a change in metabolic effect is induced in patients with type 1 diabetes.

OBJECTIVE Evaluation of the time required until a change in the basal insulin infusion rate with an insulin pump induces subsequent changes in the metabolic effect. RESEARCH DESIGN AND METHODS In this euglycemic glucose clamp study, 10 male subjects with type 1 diabetes received three different subcutaneous insulin infusion rates (0.5, 1.0, and 2.0 units/h; for 4 h each) of insulin lispro (IL) with insulin pumps. RESULTS An increase in insulinemia occurred within 15-30 min after changing the infusion rate. While the serum IL levels reached a steady state at the end of the infusion period, the glucose infusion rates did not always reach steady-state levels with the higher infusion rates. However, an increase in the glucose consumption occurred within 30-60 min after switching the infusion rate. CONCLUSIONS Several hours are required until a new steady state in the metabolic effect is achieved after a significant change in basal insulin infusion.

Comparison of basal insulin added to oral agents versus twice-daily premixed insulin as initial insulin therapy for type 2 diabetes.

OBJECTIVE: To compare the efficacy and safety of adding once-daily basal insulin versus switching to twice-daily premixed insulin in type 2 diabetic patients insufficiently controlled by oral antidiabetic agents (OADs). RESEARCH DESIGN AND METHODS: In a 24-week, multinational, multicenter, open, parallel group clinical trial, 371 insulin-naive patients with poor glycemic control (fasting blood glucose [FBG] >/=120 mg/dl, HbA(1c) 7.5-10.5%) on OADs (sulfonylurea plus metformin) were randomized to once-daily morning insulin glargine plus glimepiride and metformin (glargine plus OAD) or to 30% regular/70% human NPH insulin (70/30) twice daily without OADs. Insulin dosage was titrated to target FBG

Glimepiride combined with morning insulin glargine, bedtime neutral protamine hagedorn insulin, or bedtime insulin glargine in patients with type 2 diabetes. A randomized, controlled trial.

BACKGROUND: Patients with type 2 diabetes are often treated with oral antidiabetic agents plus a basal insulin. OBJECTIVE: To investigate the efficacy and safety of glimepiride combined with either morning or bedtime insulin glargine or bedtime neutral protamine Hagedorn (NPH) insulin in patients with type 2 diabetes. DESIGN: Open-label, randomized, controlled trial. SETTING: 111 centers in 13 European countries. PATIENTS: 695 patients with type 2 diabetes who were previously treated with oral antidiabetic agents. INTERVENTION: Randomization to treatment with morning insulin glargine, bedtime NPH insulin, or bedtime insulin glargine for 24 weeks in addition to 3 mg of glimepiride. The insulin dose was titrated by using a predefined regimen to achieve fasting blood glucose levels of 5.56 mmol/L or lower (< or =100 mg/dL). MEASUREMENTS: Hemoglobin A(1c) values, blood glucose levels, insulin dose, and body weight. RESULTS: Hemoglobin A(1c) levels improved by -1.24% (two-sided 90% CI, -1.10% to -1.38%) with morning insulin glargine, by -0.96% (CI, -0.81% to -1.10%) with bedtime insulin glargine, and by -0.84% (CI, -0.69% to -0.98%) with bedtime NPH insulin. Hemoglobin A(1c) improvement was more pronounced with morning insulin glargine than with NPH insulin (0.40% [CI, 0.23% to 0.58%]; P = 0.001) or bedtime insulin glargine (0.28% [CI, 0.11% to 0.46%]; P = 0.008). Baseline to end-point fasting blood glucose levels improved similarly in all three groups. Nocturnal hypoglycemia was less frequent with morning (39 of 236 patients [17%]) and bedtime insulin glargine (52 of 227 patients [23%]) than with bedtime NPH insulin (89 of 232 patients [38%]) (P < 0.001). CONCLUSION: The risk for nocturnal hypoglycemia was lower with glimepiride in combination with morning and bedtime insulin glargine than with glimepiride in combination with bedtime NPH insulin in patients with type 2 diabetes. Morning insulin glargine provided better glycemic control than did bedtime insulin glargine or bedtime NPH insulin.