Effects of a structured self-monitoring of blood glucose method on patient self-management behavior and metabolic outcomes in type 2 diabetes mellitus

Background

The purpose of this study was to evaluate the effect of structured self-monitoring of blood glucose (SMBG) on patient self-management behavior and metabolic outcomes in patients with type 2 diabetes mellitus (T2DM).

Methods

From January to June 2009, 30 patients with basic diabetes education were followed for a period of 90 days. To provide assessment of glycemic control and frequency of dysglycemia, patients, underwent 3 consecutive days of seven-point SMBG during each month for 3 consecutive months, using the ACCU-CHEK 360° View tool. Glucose profiles of the first and third month were used for comparison.

Results

Hemoglobin A1c (HbA1c) improved significantly during the 90-day period in all patients [confidence interval (CI) 95%, 0.32–1.64%, p < .05] and those with poor metabolic control (group B; CI 95%, 0.86–2.64%, p < .05). Mean blood glucose (MBG) values decreased significantly in group B (CI 95%, 0.56–24.78 mg/dl, p < .05) and all cases (CI 95%, 1.61–19.73 mg/dl, p < .05). Meanwhile, there was an average decrease of 15.7 mg/dl in fasting blood sugar (FBS) levels in the whole subjects. Mean postprandial blood glucose levels (MPP) decreased by 19.3 and 11.3 mg/dl in group B and in all cases, respectively. However, there were no significant changes in HbA1c, MBG, FBS, and MPP in people with good metabolic control.

Conclusion

A structured SMBG program improves HbA1c, FBS, MPP, and MBG in people with poorly controlled diabetes. This improvement shows the importance of patient self-management behavior on metabolic outcomes in T2DM.     

The relationship between the frequency of self‐monitoring of blood glucose and glycemic control in patients with type 1 diabetes mellitus on continuous subcutaneous insulin infusion or on multiple daily injections

Aims/Introduction

We investigated the relationship between the frequency of self-monitoring of blood glucose (SMBG) and glycemic control in type 1 diabetes mellitus patients on continuous subcutaneous insulin infusion (CSII) or on multiple daily injections (MDI) using data management software.

Materials and Methods

We recruited 148 adult type 1 diabetes mellitus patients (CSII n = 42, MDI n = 106) and downloaded their SMBG records to the MEQNET™ SMBG Viewer software (Arkray Inc., Kyoto, Japan). The association between the SMBG frequency and the patients'' hemoglobin A1c (HbA1c) levels was analyzed using the χ²-test and linear regression analysis was carried out to clarify their relationship.

Results

The odds ratio of achieving a target HbA1c level of <8% (63.9 mmol/mol) was significantly higher in subjects with SMBG frequencies of ≥3.5 times/day compared with those with SMBG frequencies of <3.5 times/day in the CSII group (odds ratio 7.00, 95% confidence interval 1.72–28.54), but not in the MDI group (odds ratio 1.35, 95% CI 0.62–2.93). A significant correlation between SMBG frequency and the HbA1c level was detected in the CSII group (HbA1c [%] = –0.24 × SMBG frequency [times/day] + 8.60 [HbA1c {mmol/L} = –2.61 × SMBG frequency {times/day} + 70.5], [r = –0.384, P = 0.012]), but not in the MDI group.

Conclusions

A SMBG frequency of <3.5 times per day appeared to be a risk factor for poor glycemic control (HbA1c ≥8%) in type 1 diabetes mellitus patients on CSII.     

Association between sitagliptin adherence and self-monitoring of blood glucose

Background:

We evaluated the association between self-monitoring of blood glucose (SMBG) use and sitagliptin or sitagliptin/metformin (SSMT) adherence. SSMT was chosen as these medications have little risk of hypoglycemia and are believed to not require SMBG data for titration.

Methods

This was an observational study using data extracted from a large United States insurance claims database (i3 InVision™ Data Mart, Ingenix, Inc.). Data were extracted on noninsulin-using patients initiating SSMT for each 12-month period pre- and post-SSMT initiation. Logistic regression was used to assess the relationship between SMBG use and the likelihood of being medication adherent (defined as a medication possession ratio of ≥75%) while controlling for covariates.

Results

This analysis included 7,306 patients (57.6% male; mean age 54.2 years). Mean pre-SSMT hemoglobin A1c (HbA1c) was 8.0%. In the post-SSMT initiation period, 58% of patients were adherent with SSMT. Older age, male gender, prior use of oral diabetes medication, and lower HbA1c were associated with improved SSMT adherence. SMBG use was associated with improved adherence [odds ratio (OR) ranged from 1.198 to 1.338; p < .05] compared with patients with no SMBG use pre- or post-SSMT initiation. For patients who began SMBG after starting SSMT, greater SMBG use was associated with better adherence (OR 1.449 for higher vs 1.246 for lower strip use; p < .05).

Conclusions

This study demonstrated that SMBG is associated with improved SSMT adherence. This relationship is strengthened with greater SMBG use.     

Parameters Affecting Postprandial Blood Glucose: Effects of Blood Glucose Measurement Errors

Background

The Diabetes Error Test Model (DETM) has been developed to characterize the clinical relevance of the large and varying margins of error of parameters affecting postprandial blood glucose (BG) levels, which increase the risk for hypo- or hyperglycemia.

Methods

The DETM is based on a treatment concept aimed at normoglycemia after meals. The model includes as parameters (a) preprandial BG measurement by patient self-monitoring (SMBG), (b) patient estimate of carbohydrate amounts (CARB-P) in food, (c) effect of CARB-P on maximum BG increase, (d) effect of insulin on maximum BG decrease, and (e) insulin dosage. Covering the relevant range of preprandial BG (30–330 mg/dl), the DETM simulates the maximum effect of these parameters and their margins of error on postprandial BG values.

Results

According to the DETM, a SMBG error of +20% results in normoglycemia (BG range: 60–160 mg/dl) as the postprandial outcome if preprandial BG values are in the range of 30–130 or 260–330 mg/dl, but can unexpectedly result in hypoglycemia if preprandial BG values are between 131 and 259 mg/dl. If the SMBG error of +20% is combined, e.g., with an error of CARB-P estimate in the food of +20%, hypoglycemia as the postprandial outcome is worsened. If one combines the effects of errors of more than two parameters, even with errors that are so small that they have no clinically relevant dysglycemic effect on postprandial BG per se (e.g., ±6%), this can result in postprandial hypo- or hyperglycemic values.

Conclusion

The DETM simulates the effects of errors of parameters affecting postprandial BG within the clinically relevant BG range. The DETM offers the opportunity to evaluate the clinical relevance of these errors and their contribution to the increased risk of meal-related excessive glucose excursions during intensified insulin therapy.     

Are late-night eating habits and sleep duration associated with glycemic control in adult type 1 diabetes patients treated with insulin pumps?

Aims/Introduction

Little is known about the impact of sleep duration and late-night snacking on glycemic control in patients with type 1 diabetes using insulin pumps. The aim of the present study was to examine whether late-night eating habits and short sleep duration are associated with glycemic control in continuous subcutaneous insulin infusion-treated type 1 diabetic patients.

Materials and Methods

We included 148 consecutive adult type 1 diabetic subjects using an insulin pump (100 women and 48 men). Participants completed a questionnaire regarding sleep duration (classified as short if ≤6 h) and late-night snacking. Other sources of information included medical records and data from blood glucose meters. Glycemic control was assessed by glycated hemoglobin (HbA1c) levels and mean self-monitoring of blood glucose (SMBG) readings.

Results

The mean age of patients was 26 years, mean type 1 diabetes duration was 13.4 years and mean HbA1c level was 7.2%. In a univariate regression analysis, sleep duration was a predictor of both HbA1c (β = 0.51, P = 0.01) and SMBG levels (β = 11.4, P = 0.02). Additionally, an association was found between frequent late-night snacking and higher SMBG readings (often snacking β = 18.1, P = 0.05), but not with increased HbA1c levels. In the multivariate linear regression, independent predictors for HbA1c and SMBG were sleep duration and patient age. In a univariate logistic regression, sleep duration and frequency of late-night snacking were not predictors of whether HbA1c target levels were achieved.

Conclusions

Short sleep duration, but not late-night snacking, seems to be associated with poorer glycemic control in type 1 diabetic patients treated with continuous subcutaneous insulin infusion.     

Association of Self-Monitoring of Blood Glucose Use on Glycated Hemoglobin and Weight in Newly Diagnosed,Insulin-Na?ve Adult Patients with Type 2 Diabetes

Background

Clinical trials have shown that self-monitoring of blood glucose (SMBG) combined with patient education and medication titration can lead to improved glycated hemoglobin (HbA1c) and reduced weight in recently diagnosed non-insulin-treated type 2 diabetes mellitus (T2DM) patients. This retrospective matched cohort study assessed the association of SMBG with achieving long-term clinical outcomes in these patients in a real-world clinical setting.

Methods

Using electronic medical records (2008–2011), we selected a population of adult patients recently diagnosed with T2DM not receiving insulin who were SMBG users and a population of non-SMBG controls with similar demographic and clinical characteristics using propensity score matching. The main study outcomes compared between the two groups were time to achieve (1) HbA1c <7% for patients with baseline HbA1c ≥7% and (2) a ≥5% reduction in weight from baseline.

Results

Of the 589 patients identified in each group, 113 in each group had a baseline HbA1c ≥7% (mean, 8.2%). The SMBG users were more likely to achieve an HbA1c <7% (12 months: 58.4% versus 38.9%, p = .0037; 36 months: 84.0% versus 70.0%, p = .0013) and to do so faster (median, 6.5 versus 20.5 months; log-rank p = . 0016). Self-monitoring of blood glucose was associated with faster weight reduction (median time to achieve a ≥5% reduction, 23.5 versus 35.9 months for SMBG and non-SMBG, respectively; log-rank p = .0005).

Conclusions

In newly diagnosed T2DM insulin-naïve patients, SMBG users had an improved rate of achieving long-term glycemic control and weight loss in a real-world clinical setting.     

Pancreatic polypeptide administration enhances insulin sensitivity and reduces the insulin requirement of patients on insulin pump therapy

Introduction

The effects of pancreatic polypeptide (PP) infusion were examined in patients on insulin pump therapy to determine whether PP administration can reduce insulin requirements in patients with type 1 diabetes mellitus (T1DM) or type 3c diabetes mellitus (T3cDM; pancreatogenic).

Methods

Ten subjects with long-standing T1DM (n = 7) or T3cDM (n = 3) on insulin pump treatment received a 72 h subcutaneous infusion of 2 pmol/kg/min bovine PP or saline by portable infusion pump in a single-blinded, randomized, crossover design.

Results

Pancreatic polypeptide infusion raised plasma PP levels to 450–700 pmol/liter. Daily insulin infusion requirements (I) fell from 48 ± 6.9 to 40 ± 7.5 U on day 2 (p < .05) and from 46 ± 7.7 to 37 ± 6.6 U on day 3 (p < .05) of PP infusion compared with saline. Corrected for average blood glucose concentration (G), I/G fell in 10/10 subjects during the second 24 h period and in 7/10 subjects during the third 24 h period; sensitivity to insulin, calculated as 1/(I/G), increased 45% ± 12% on day 2 (p < .01) and 34% ± 14% on day 3 (p < .05) of PP infusion. Pancreatic polypeptide responses to a test meal were compared with the change in insulin infusion requirements in 5 subjects; the reduction in insulin requirements seen during PP infusion correlated with the degree of baseline PP deficiency (p < .002).

Conclusions

A concurrent subcutaneous infusion of PP enhances insulin sensitivity and reduces insulin requirements in patients with long-standing T1DM and T3cDM on insulin pump therapy. The benefit of PP infusion correlated with the degree of PP deficiency.     

Impact of Blood Glucose Self-Monitoring Errors on Glucose Variability, Risk for Hypoglycemia, and Average Glucose Control in Type 1 Diabetes: An In Silico Study

Background

Clinical trials assessing the impact of errors in self-monitoring of blood glucose (SMBG) on the quality of glycemic control in diabetes are inherently difficult to execute. Consequently, the objectives of this study were to employ realistic computer simulation based on a validated model of the human metabolic system and to provide potentially valuable information about the relationships among SMBG errors, risk for hypoglycemia, glucose variability, and long-term glycemic control.

Methods

Sixteen thousand computer simulation trials were conducted using 100 simulated adults with type 1 diabetes. Each simulated subject was used in four simulation experiments aiming to assess the impact of SMBG errors on detection of hypoglycemia (experiment 1), risk for hypoglycemia (experiment 2), glucose variability (experiment 3), and long-term average glucose control, i.e., estimated hemoglobin A1c (HbA1c)(experiment 4). Each experiment was repeated 10 times at each of four increasing levels of SMBG errors: 5, 10, 15, and 20% deviation from the true blood glucose value.

Results

When the permitted SMBG error increased from 0 to 5–10% to 15–20%-the current level allowed by International Organization for Standardization 15197–(1) the probability for missing blood glucose readings of 60 mg/dl increased from 0 to 0–1% to 3.5–10%; (2) the incidence of hypoglycemia, defined as reference blood glucose ≤70 mg/dl, changed from 0 to 0–0% to 0.1–5.5%; (3) glucose variability increased as well, as indicated by control variability grid analysis; and (4) the incidence of hypoglycemia increased from 15.0 to 15.2–18.8% to 22–25.6%. When compensating for this increase, glycemic control deteriorated with HbA1c increasing gradually from 7.00 to 7.01–7.12% to 7.26–7.40%.

Conclusions

A number of parameters of glycemic control deteriorated substantially with the increase of permitted SMBG errors, as revealed by a series of computer simulations (e.g., in silico) experiments. A threshold effect apparent between 10 and 15% permitted SMBG error for most parameters, except for HbA1c, which appeared to be increasing relatively linearly with increasing SMBG error above 10%.     

Reduction of postprandial glycemic excursions in patients with type 1 diabetes: a novel human insulin formulation versus a rapid-acting insulin analog and regular human insulin

Background:

Evaluation of postprandial glycemic excursions in patients with type 1 diabetes with three prandial insulins: VIAject™ (Linjeta™), an ultra-fast insulin (UFI); insulin lispro (LIS); and regular human insulin (RHI).

Methods:

After stabilization of preprandial glycemia, 18 patients received a subcutaneous injection with an individualized insulin dose prior to a meal.

Results:

Injection of UFI resulted in a more rapid insulin absorption than with either LIS or RHI (time to half-maximal insulin levels: 13.1 ± 5.2 vs 25.4 ± 7.6 and 38.4 ± 19.5 min; p = .001 vs LIS and p < .001 vs RHI, LIS vs. RHI p < .001). Maximal postprandial glycemia was lower with UFI (0–180 min; 157 ± 30 mg/dl; p = .002 vs RHI) and LIS (170 ± 42 mg/dl; p = .668 vs RHI) than after RHI (191 ± 46 mg/dl; RHI vs LIS p = .008). The difference between maximum and minimum glycemia was smaller with UFI (70 ± 17 mg/dl) than with either RHI (91 ± 33 mg/dl; p = .007 vs UFI) or LIS (89 ± 18 mg/dl; p = .011 vs UFI). Also, the area under the blood glucose profile was lower with UFI than with RHI (0–180 min; 21.8 ± 5.8 vs 28.4 ± 7.6 g·min/dl; p < .001).

Conclusions:

The rapid absorption of UFI results in a reduction of postprandial glycemic excursions.     

Interindividual and intraindividual variations in postprandial glycemia peak time complicate precise recommendations for self-monitoring of glucose in persons with type 1 diabetes mellitus

Background

In glycemic control, postprandial glycemia may be important to monitor and optimize as it reveals glycemic control quality, and postprandial hyperglycemia partly predicts late diabetic complications. Self-monitoring of blood glucose (SMBG) may be an appropriate technology to use, but recommendations on measurement time are crucial.

Method

We retrospectively analyzed interindividual and intraindividual variations in postprandial glycemic peak time. Continuous glucose monitoring (CGM) and carbohydrate intake were collected in 22 patients with type 1 diabetes mellitus. Meals were identified from carbohydrate intake data. For each meal, peak time was identified as time from meal to CGM zenith within 40–150 min after meal start. Interindividual (one-way Anova) and intraindividual (intraclass correlation coefficient) variation was calculated.

Results

Nineteen patients were included with sufficient meal data quality. Mean peak time was 87 ± 29 min. Mean peak time differed significantly between patients (p = 0.02). Intraclass correlation coefficient was 0.29.

Conclusions

Significant interindividual and intraindividual variations exist in postprandial glycemia peak time, thus hindering simple and general advice regarding postprandial SMBG for detection of maximum values.     

Combined Insulin Pump Therapy with Real-Time Continuous Glucose Monitoring Significantly Improves Glycemic Control Compared to Multiple Daily Injection Therapy in Pump Na?ve Patients with Type 1 Diabetes; Single Center Pilot Study Experience

Objectives

This study assessed the safety and clinical effectiveness of the training protocol for initiating insulin pump therapy with real-time continuous glucose monitoring (MiniMed Paradigm REAL-Time System) in a stepwise approach on pump naive subjects with type 1 diabetes compared to a control group who remained on multiple daily injection (MDI) therapy.

Methods

This was a 15-week treat-to-target pilot study of 16 adult subjects (n = 50% male, age 45.9 ± 16 years) with type 1 diabetes (duration of diabetes 21.9 ± 11 years) on MDI therapy with hemoglobin A1c levels at or above 7.5% at baseline. Subjects were randomized to either the study arm (using a combined insulin pump and real-time continuous glucose monitoring system) or the control arm [which continued on MDI therapy with self-monitored blood glucose (SMBG) only]. All subjects dosed insulin according to results of SMBG by finger stick and uploaded data into the CareLink data management software.

Results

Significant improvements in glycemic control were observed from baseline in both study groups—study arm: pre-A1c 9.45 ± 0.55 and post-A1c 7.4 ± 0.66 (p = 0.00037); control arm: pre-A1c 8.58 ± 1.30 and post-A1c 7.5 ±1.01 (p = 0.04). Both arms had no incidence of severe hypoglycemia.

Conclusion

In this pilot study, the Paradigm REAL-Time System was initiated safely and effectively in type 1 diabetes patients who were pump naïve using a stepwise educational protocol.     

The Benefits of Continuous Glucose Monitoring and a Glucose Monitoring Schedule in Individuals with Type 1 Diabetes during Recreational Diving

Background

Our objective is to evaluate the Medtronic CGMS^® continuous glucose monitoring system and plasma glucose (PG) measurement performed in a monitoring schedule as tools to identify individuals with type 1 diabetes at risk when diving.

Methods

We studied 24 adults, 12 type 1 diabetes subjects and 12 controls, during 5 recreational scuba dives performed on 3 consecutive days. The CGMS was used by all participants on all the days and all the dives. Comparisons were made between PG performed in a monitoring schedule during the days of diving, self-monitored blood glucose (SMBG) performed 2 weeks prior to diving, and the CGMS during the study.

Results

One hundred seventeen dives were performed. Hypoglycemia (<70 mg/dl) was found in six individuals and on nine occasions. However, no symptoms of hypoglycemia were present during or immediately postdiving. In one case, repetitive hypoglycemia prediving gave rise to a decision not to dive. None of the dives were aborted. The number of hypoglycemic episodes, 10 min prediving or immediately postdiving, were related to the duration of diabetes, r = 0.83 and p =0.01, and the percentage of SMBG values below target (<72 mg/dl), r = 0.65 and p =0.02. Moreover, the number of hypoglycemic episodes was also related to the total duration below low limit (<70 mg/dl), measured by the CGMS, r =0.74 and p =0.006.

Conclusion

Safe dives are possible to achieve by well-informed, well-controlled individuals with type 1 diabetes. Using downloaded SMBG, CGMS, and repetitive PG in a monitoring schedule, it is possible to identify those subjects who are suitable for diving.     

Self-Monitoring of Blood Glucose in Type 1 Diabetes Patients with Insufficient Metabolic Control: Focused Self-Monitoring of Blood Glucose Intervention Can Lower Glycated Hemoglobin A1C

Objective

Little attention has been given and few studies have been published focusing on how to optimize self-monitoring of blood glucose (SMBG) use to monitor daily therapy for persons with type 1 diabetes mellitus. This study was designed to evaluate the effect on glycated hemoglobin (A1C) of a structured intervention focused on SMBG in type 1 diabetes patients with insufficient metabolic control (A1C ≥ 8%) using a randomized clinical trial design.

Method

One hundred fifty-nine outpatients with type 1 diabetes on multiple injection therapy with insulin and A1C ≥8% were recruited and randomized to one group receiving a focused, structured 9-month SMBG intervention (n = 59) and another group receiving regular care based on guidelines (n = 64).

Results

Glycated hemoglobin values (mean % ± standard deviation) at study start was similar: 8.65 ± 0.10 in the intervention group and 8.61 ± 0.09 in the control group. The two groups were comparable (age, gender, body mass index, complication rate, and treatment modality) at study start and had mean diabetes duration and SMBG experience of 19 and 20 years, respectively. At study end, there was decrease in A1C in the intervention group (p < .05), and the A1C was 0.6% lower compared with the control group (p < .05). No increase in the number of minor or major hypoglycemia episodes was observed in the intervention group during the study period.

Conclusions

A simple, structured, focused SMBG intervention improved metabolic control in patients with longstanding diabetes type 1 and A1C ≥ 8%. The intervention was based on general recommendations, realistic in format, and can be applied in a regular outpatient setting.     

Gastric Electrical Stimulation with the TANTALUS? System in Obese Type 2 Diabetes Patients: Effect on Weight and Glycemic Control

Background

The TANTALUS^® System is an investigational device that consists of an implantable pulse generator connected to gastric electrodes. The system is designed to automatically detect when eating starts and only then deliver sessions of gastric electrical stimulation (GES) with electrical pulses that are synchronized to the intrinsic antral slow waves. We report the effect of this type of GES on weight loss and glucose control in overweight/obese subjects with type 2 diabetes mellitus (T2DM). This study was conducted under a Food and Drug Administration/Institutional Review Board-approved investigational device exemption.

Method

Fourteen obese T2DM subjects on oral antidiabetes medication were enrolled and implanted laparoscopically with the TANTALUS System (body mass index 39 ± 1 kg/m², hemoglobin A1c [HbA1c] 8.5 ± 0.2%).Gastric electrical stimulation was initiated four weeks after implantation. Weight, HbA1c, fasting blood glucose, blood pressure, and lipid levels were assessed during the study period.

Results

Eleven subjects reached the 6-month treatment period endpoint. Gastric electrical stimulation was well tolerated by all subjects. In those patients completing 6 months of therapy, HbA1c was reduced significantly from 8.5 ± 0.7% to 7.6 ± 1%, p < .01. Weight was also significantly reduced from 107.7 ± 21.1 to 102.4 ± 20.5 kg, p < .01. The improvement in glucose control did not correlate with weight loss (R² = 0.05, p = .44). A significant improvement was noted in blood pressure, triglycerides, and cholesterol (low-density lipoprotein only).

Conclusions

Short-term therapy with the TANTALUS System improves glucose control, induces weight loss, and improves blood pressure and lipids in obese T2DM subjects on oral antidiabetes therapy.     

Display of Glucose Distributions by Date, Time of Day, and Day of Week: New and Improved Methods

Objective

There is a need for improved methods for display of glucose distributions to facilitate comparisons by date, time of day, day of the week, and other variables for data obtained using self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM).

Method

Stacked bar charts are utilized for multiple ranges of glucose values, e.g., very low, low, borderline low, target range, borderline high, high, and very high. Glucose ranges for these categories can be defined by the user, e.g., <40, 40–70, 71–80, 81–140, 141–180, 181–250, and 251–400 mg/dl. Glucose distributions can be displayed by time of day, in relation to meals, by date, or by day of week. The graphic display can be generated using general purpose spreadsheet software such as Microsoft Excel or with special purpose software.

Result

Stacked bar charts are extremely compact and effective. They facilitate comparison of multiple days, multiple time segments within a day, preprandial and postprandial glucose levels, days of the week, treatment periods, patients, and groups of patients. They are superior to use of pie charts in terms of compactness and in their ability to facilitate comparisons using multiple criteria and multiple subsets of the data. One can identify episodes of hypoglycemia and hyperglycemia and can display standard errors of estimates of percentages. Interpretation of these graphs is readily learned and requires minimal training.

Conclusion

Use of stacked bar charts is generally superior to use of pie charts for display of glucose distributions and can potentially facilitate the analysis and interpretation of SMBG and CGM data.     

Translation of personalized decision support into routine diabetes care

Objective

The aim of this study was to evaluate the impact of personalized decision support (PDS) on metabolic control in people with diabetes and cardiovascular disease.

Research Design and Methods

The German health insurance fund BKK TAUNUS offers to its insured people with diabetes and cardiovascular disease the possibility to participate in the Diabetiva^® program, which includes PDS. Personalized decision support is generated by the expert system KADIS^® using self-control data and continuous glucose monitoring (CGM) as its data source. The physician of the participating person receives the PDS once a year, decides about use or nonuse, and reports his/her decision in a questionnaire. Metabolic control of participants treated by use or nonuse of PDS for one year and receiving CGM twice was analyzed in a retrospective observational study. The primary outcome was hemoglobin A1c (HbA1c); secondary outcomes were mean sensor glucose (MSG), glucose variability, and hypoglycemia.

Results

A total of 323 subjects received CGM twice, 289 had complete data sets, 97% (280/289) were type 2 diabetes patients, and 74% (214/289) were treated using PDS, resulting in a decrease in HbA1c [7.10 ± 1.06 to 6.73 ± 0.82%; p < .01; change in HbA1c_{t0–t12 months} -0.37 (95% confidence interval -0.46 to -0.28)] and MSG (7.7 ± 1.6 versus 7.4 ± 1.2 mmol/liter; p = .003) within one year. Glucose variability was also reduced, as indicated by lower high blood glucose index (p = .001), Glycemic Risk Assessment Diabetes Equation (p = .009), and time of hyper-glycemia (p = .003). Low blood glucose index and time spent in hypoglycemia were not affected. In contrast, nonuse of PDS (75/289) resulted in increased HbA1c (p < .001). Diabetiva outcome was strongly related to baseline HbA1c (HbA1c_t0; p < .01) and use of PDS (p < .01). Acceptance of PDS was dependent on HbA1c_t0 (p = .049).

Conclusions

Personalized decision support has potential to improve metabolic outcome in routine diabetes care.     

In type 2 diabetes patients, insulin glargine is associated with lower postprandial release of intact proinsulin compared with sulfonylurea treatment

Objective

Our objective was to investigate how postprandial processing of intact proinsulin is influenced by different pharmacological strategies in type 2 diabetes mellitus (T2DM).

Materials/Methods

This exploratory, nonrandomized, cross-sectional study recruited T2DM patients and healthy subjects. Upon recruitment, eligible T2DM patients had been treated for ≥6 months with insulin glargine (GLA) plus metformin (MET), sulfonylureas (SU) plus MET, or dipeptidyl-peptidase-4 inhibitors (DPP-4-I) plus MET. Blood samples were drawn from study participants after an 8 h fast and at regular intervals for up to 5 h after consumption of a standardized meal. Study endpoints included postprandial intact proinsulin and insulin levels and the insulin/proinsulin ratio.

Results

As expected, postprandial secretion of proinsulin was greater in all T2DM treatment groups than in healthy subjects (p < .01 for all comparisons). Postprandial release of proinsulin was significantly greater in T2DM patients treated with SU plus MET than in those treated with GLA plus MET (p = .003). Treatment with DPP-4-I plus MET was associated with reduced proinsulin secretion versus SU plus MET and an increased insulin/proinsulin ratio versus the other T2DM groups.

Conclusions

Treatment of T2DM with GLA plus MET or DPP-4-I plus MET was associated with a more physiological postprandial secretion pattern of the β cell compared with those treated with SU plus MET.     

Combined Pioglitazone and Metformin Treatment Maintains the Beneficial Effect of Short-Term Insulin Infusion in Patients with Type 2 Diabetes: Results from a Pilot Study

Background

The aim of our study was to examine the efficacy of short-term intravenous insulin intervention followed by oral pioglitazone/metformin therapy to prevent patients from continuous insulin application.

Methods

This prospective, open-label, 4-month pilot study comprised of 14 diabetes patients (5 female, 9 male; age 60 ± 2 years; body mass index 29 ± 3.2 kg/m²; hemoglobin A1c [HbA1c] 7.6 ± 1.1%) with (1) insufficient glycemic control under a dose of metformin ≥1700 mg/day and/or metformin plus additional oral antidiabetes drugs (OADs) and (2) appropriate residual β-cell function. Initially, an inpatient 34 h continuous intravenous insulin infusion was performed, and metformin was given (2x 850 mg/day). Insulin was stopped, and pioglitazone 30 mg/day was added at the second inpatient day. Patients were followed for four months. Efficacy parameters [change of HbA1c, fasting blood glucose [FBG], intact proinsulin, adiponectin, and high-sensitivity C-reactive protein (hsCRP)] were assessed after initial normalization of blood glucose values by intravenous insulin and at the study end point.

Results

During the acute insulin intervention, FBG levels were stabilized in all study subjects. In the following OAD treatment period, five patients showed an improvement of HbA1c > 0.5% [35.7%; seven patients remained stable (50.0%), two patients were nonresponders (14.3%)].Fasting glucose values dropped after insulin infusion (-17.7%; p < .001). This effect was maintained during the consecutive OAD treatment period (glucose +0.3%, not significant (NS); HbA1c -6.0%; p < .05). The initial decrease in fasting intact proinsulin levels was also maintained during the study (end value -41%, p < .05).Improvements in hsCRP values (postinsulin value, -15%, NS; end value -37%; p < .05) and adiponectin values (postinsulin value +15%, NS; end value +128%; p < .001) were demonstrated at end point only after continued glitazone intake.

Conclusions

Our pilot study demonstrated that a beneficial effect of a short-term intravenous insulin application on glycemic control was effectively maintained by pioglitazone/metformin treatment for at least 4 months. In addition, the oral therapy significantly improved cardiovascular risk parameters.     

Mobile phone-based video messages for diabetes self-care support

Background

This study examined whether mobile phone-based, one-way video messages about diabetes self-care improve hemoglobin A1c (A1C) and self-monitoring of blood glucose (SMBG).

Methods

This was a 1-year prospective randomized trial with two groups. The active intervention lasted 6 months. The study enrolled 65 people with A1C >8.0% who were established (>6 months) patients in the endocrinology clinics of the Walter Reed Health Care System. Participants were randomized to receive “usual care” or self-care video messages from their diabetes nurse practitioner. Video messages were sent daily to cell phones of study participants. Hemoglobin A1c and SMBG data were collected at 0, 3, 6, 9, and 12 months.

Results

Participants who received the messages had a larger rate of decline in A1C than people who received usual care (0.2% difference over 12 months, adjusting for covariates; p = .002 and p = .004 for the interaction between time and group and for the quadratic effect of time by group, respectively). Hemoglobin A1c decline was greatest among participants who received video messages and viewed >10 a month (0.6% difference over 12 months, adjusting for covariates; p < .001 for the interaction between time and group and the quadratic effect). Self-monitoring of blood glucose metrics were not related to the intervention.

Conclusions

A one-way intervention using mobile phone-based video messages about diabetes self-care can improve A1C. Engagement with the technology is an important predictor of its success. This intervention is simple to implement and sustain.