Prediction of the risk to develop diabetes-related late complications by means of the glucose pentagon model: analysis of data from the Juvenile Diabetes Research Foundation continuous glucose monitoring study

Background

By taking parameters into account that describe the variability of continuously monitored glucose and long-term metabolic control [hemoglobin A1c (HbA1c)], the glucose pentagon model (GPM) allows characterization of the glucose profile of individual patients with diabetes in a graphical format. A glycemic risk parameter (GRP) derived from this model might allow a better prognosis of the risk to develop diabetes-related complications than the HbA1c.

Methods

To evaluate this hypothesis, we analyzed a subset of data from the Juvenile Diabetes Research Foundation continuous glucose monitoring (CGM) study. The values of the different parameters that are integrated in the GPM were extracted automatically from CGM profiles registered before and after 6 months by means of the Medtronic CGM system in 108 patients.

Results

In these patients, the significant reduction in HbA1c from 7.4% to 7.0% was accompanied by a reduction in glycemia from 164 to 156 mg/dl, standard deviation from 61 to 57 mg/dl, area under the curve >160 mg/dl 29.2 to 23.1, and time per day >160 mg/dl 634 to 576 min. This led to a subsequent reduction in GRP from 3.3 to 2.7; this decrease by 18.2% was significantly larger than that in HbA1c by 8.6% (p < .001). Changes in individual GPMs/GRPs support this observation. They also show the impact of high glycemic variability on GPM/GRP.

Conclusions

Our analysis of data of a study with a considerable sample size and study duration showed that the GPM is not only helpful for rapid assessment of individual glycemic profiles and how therapeutic interventions influence these, but also appears to provide a better prognosis of the risk to develop late complications than the HbA1c per se. However, it is also clear that a true validation of such a model requires performance of a long-term study in a large number of patients with diabetes.     

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.     

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.     

Determinants of the accuracy of continuous glucose monitoring in non-critically ill patients with heart failure or severe hyperglycemia

Background

The accuracy of continuous glucose monitoring (CGM) in non-critically ill hospitalized patients with heart failure or severe hyperglycemia (SH) is unknown.

Methods

Hospitalized patients with congestive heart failure (CHF) exacerbation (receiving IV or subcutaneous insulin) or SH requiring insulin infusion were compared to outpatients referred for retrospective CGM.

Results

Forty-three patients with CHF, 15 patients with SH, and 88 outpatients yielded 470, 164, and 2150 meter–sensor pairs, respectively. Admission glucose differed (188 versus 509 mg/dl in CHF and SH, p < .001) but not the first sensor glucose (p = .35). In continuous glucose error grid analysis, 67–78% of pairs during hypoglycemia were in zones A+B (p = .63), compared with 98–100% in euglycemia (p < .001) and 98%, 92%, and 99% (p = .001) during hyperglycemia for the CHF, SH, and outpatient groups, respectively. Mean absolute relative difference (MARD) was lower in the CHF versus the SH group in glucose strata above 100 mg/dl, but there was no difference between the CHF and outpatient groups. Linear regression models showed that CHF versus outpatient, SH versus CHF, and coefficient of variation were significant predictors of higher MARD. Among subjects with CHF, MARD was not associated with brain natriuretic peptide or change in plasma volume, but it was significantly higher in subjects randomized to IV insulin (p = .04).

Conclusions

The results suggest that SH and glycemic variability are more important determinants of CGM accuracy than known CHF status alone in hospitalized patients.     

Changes in Diabetes Distress Related to Participation in an Internet-Based Diabetes Care Management Program and Glycemic Control

Background

This article investigated how changes in diabetes distress relate to receiving care management through an Internet-based care management (IBCM) program for diabetes and level of participation in this program. Further, it examined the relationship between diabetes distress and changes in glycemic control.

Methods

We enrolled patients of the Veterans Affairs Boston Healthcare System with diabetes who had hemoglobin A1c (HbA1c) levels of ≥9.0%. Subjects were randomized to usual care (n = 52) or IBCM (n = 52) for 1 year. We measured diabetes distress at baseline and quarterly thereafter using the Problem Areas in Diabetes (PAID) questionnaire. Glycemic control was determined by baseline and quarterly HbA1c. For subjects randomized to IBCM, we measured participation by observing frequency and consistency of their usage of the IBCM patient portal over 12 months. Linear mixed models were used to analyze THE data.

Results

PAID scores declined over time for both treatment groups. Among subjects randomized to IBCM, the decline in PAID scores over time was significant for sustained users of the IBCM patient portal but not for nonusers. Moreover, subjects whose usage of the patient portal was sustained throughout the study had lower PAID scores at baseline. With respect to changes in glycemic control, HbA1c reduced individual differences in PAID scores by 44%; a lower baseline HbA1c was associated with lower baseline PAID scores, and over time, the decrease in HbA1c was associated with further decreases in the PAID score.

Conclusions

Participation in IBCM varies by initial diabetes distress, with people with less distress participating more. For people who participate, IBCM further mitigates diabetes distress. There is also a relationship between achievements in glycemic control and subsequent lowering of diabetes distress. Future research should identify how to maximize fit between patient needs and the provisions of IBCM, with the aim of increasing patient engagement in the active management of their health using this care modality. A key to maximizing fit might be first addressing metabolic control aggressively and then using IBCM for sustainment of health.     

No relevant relationship between glucose variability and oxidative stress in well-regulated type 2 diabetes patients

Background

A strong relationship between glycemic variability and oxidative stress in poorly regulated type 2 diabetes (T2DM) on oral medication has been reported. However, this relationship was not seen in type 1 diabetes. The purpose of this study is to reexamine the relation between glycemic variability and oxidative stress in a cohort of T2DM patients on oral medication.

Methods

Twenty-four patients with T2DM on oral glucose lowering treatment underwent 48 hours of continuous glucose monitoring (CGMS^® System Gold^TM, Medtronic MiniMed) and simultaneous collection of two consecutive 24-hour urine samples for determination of 15(S)-8-iso-prostaglandin F_2α (PGF_2α) using high-performance liquid chromatography tandem mass spectrometry. Standard deviation (SD) and mean amplitude of glycemic excursions (MAGE) were calculated as markers of glycemic variability.

Results

Included in the study were 66.7% males with a mean age (range) of 59 (36–76) years and a mean (SD) HbA1c of 6.9% (0.7). Median [interquartile range (IQR)] urinary 15(S)-8-iso-PGF_2α excretion was 176.1 (113.6–235.8) pg/mg creatinine. Median (IQR) SD was 31 (23–40) mg/dl and MAGE 85 (56–106) mg/dl. Spearman correlation did not show a significant relation for SD (ρ = 0.15, p = .49) or MAGE (ρ = 0.23, p = .29) with 15(S)-8-iso-PGF_2α excretion. Multivariate regression analysis adjusted for age, sex, HbA1c, and exercise did not alter this observation.

Conclusions

We did not find a relevant relationship between glucose variability and 15(S)-8-iso-PGF_2α excretions in T2DM patients well-regulated with oral medication that would support an interaction between hyperglycemia and glucose variability with respect to the formation of reactive oxygen species.     

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.     

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.     

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.     

A Single-Center, Open, Comparative Study of the Effect of Using Self-Monitoring of Blood Glucose to Guide Therapy on Preclinical Atherosclerotic Markers in Type 2 Diabetic Subjects

Background

The aim of our study was to determine the effect of treatment based on preprandial and postprandial self-monitoring of blood glucose (SMBG) on the progression of carotid intima-medial thickness (CIMT) in noninsulin-treated type 2 diabetes mellitus (T2DM) subjects.

Methods

In this 18-month prospective trial, we recruited subjects 18–70 years of age, treated with metformin and sulfonylurea, with a standardized hemoglobin A1c (HbA1c) level ≤9.0%. Subjects were randomized to use of fasting/preprandial (FP) SMBG results to adjust evening medication or use of postprandial (PP) SMBG results to adjust morning medication. The primary end point was change in CIMT; change in HbA1c was a secondary end point.

Results

Of the 300 subjects randomized, 280 (140 in each group) completed all biochemical tests and CIMT analysis. Carotid intima-medial thickness was reduced significantly in PP subjects from 0.78 (±0.15) mm to 0.73 (±0.14) mm (p < 0.005), but no significant CIMT reduction was seen in FP subjects. A significant reduction in HbA1c was also seen in the PP group (p < 0.005) but not in the FP group 1 (p = 0.165). Significant improvements in body mass index (p = 0.038), waist circumference (p < 0.001), systolic blood pressure (p = 0.008), and serum cholesterol (p = 0.02) were also seen in PP subjects but not in FP subjects.

Conclusion

Use of postprandial SMBG data to adjust therapy was associated with a significant regression of carotid intima-medial thickening and a reduction in HbA1c in T2DM, whereas no significant improvement in these parameters was seen in subjects who used fasting/preprandial SMBG data for therapy adjustment.     

Plantar fascia thickness is longitudinally associated with retinopathy and renal dysfunction: a prospective study from adolescence to adulthood

Aim

The aim was to study the longitudinal relationship between plantar fascia thickness (PFT) as a measure of tissue glycation and microvascular (MV) complications in young persons with type 1 diabetes (T1DM).

Methods

We conducted a prospective longitudinal cohort study of 152 (69 male) adolescents with T1DM who underwent repeated MV complications assessments and ultrasound measurements of PFT from baseline (1997–2002) until 2008. Retinopathy was assessed by 7-field stereoscopic fundal photography and nephropathy by albumin excretion rate (AER) from three timed overnight urine specimens. Longitudinal analysis was performed using generalized estimating equations (GEE).

Results

Median (interquartile range) age at baseline was 15.1 (13.4–16.8) years, and median follow-up was 8.3 (7.0–9.5) years, with 4 (3–6) visits per patient. Glycemic control improved from baseline to final visit [glycated hemoglobin (HbA1c) 8.5% to 8.0%, respectively; p = .004]. Prevalence of retinopathy increased from 20% to 51% (p < .001) and early elevation of AER (>7.5 µg/min) increased from 26% to 29% (p = .2). A greater increase in PFT (mm/year) was associated with retinopathy at the final assessment (ΔPFT 1st vs. 2nd–4th quartiles, χ² = 9.87, p = .02). In multivariate GEE, greater PFT was longitudinally associated with retinopathy [odds ratio (OR) 4.6, 95% confidence interval (CI) 2.0–10.3] and early renal dysfunction (OR 3.2, CI 1.3–8.0) after adjusting for gender, blood pressure standard deviation scores, HbA1c, and total cholesterol.

Conclusions

In young people with T1DM, PFT was longitudinally associated with retinopathy and early renal dysfunction, highlighting the importance of early glycemic control and supporting the role of metabolic memory in MV complications. Measurement of PFT by ultrasound offers a noninvasive estimate of glycemic burden and tissue glycation.     

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.     

Postprandial Glycemic Excursions with the Use of a Closed-Loop Platform in Subjects with Type 1 Diabetes: A Pilot Study

Background

The aim of this study was to evaluate the efficacy of a proportional derivative algorithm closed-loop system to control postprandial glucose concentrations in subjects with type 1 diabetes.

Methods

Six subjects treated with continuous subcutaneous insulin infusion received a standardized meal on three days. The first day served as control, the second day as learning experiment for the algorithm, and the third day to compare the closed loop to the control day. Venous blood glucose was measured as reference until 300 min postprandially. The artificial pancreas platform consisted of a subcutaneous continuous glucose monitor (CGM), the GlucoDay^® S (Menarini Diagnostics), two D-Tron+ pumps (Disetronic Medical Systems) for subcutaneous insulin, and glucagon administration connected to a personal computer.

Results

One subject was excluded due to technical failure of the CGM. Two of five subjects were male, mean age was 50.8 years (range 38–60), and mean hemoglobin A1c was 8.7% (range 7.0–12.2). The mean postprandial venous blood glucose concentration of day 1 was 205 mg/dl (range 94–265 mg/dl) compared with 128 mg/dl (range 128–158 mg/dl) on day 3 (p = .14). Percentage of time spent in euglycemia postprandially on day 1 was 31% versus 60% on day 3 (p = .08). Time spent below 3.9 mmol/liter (70 mg/dl) was 19% on day 1 compared with 11% on day 3 (p = 1.0). Time above 10 mmol/liter (180 mg/dl) on day 1 was 60% versus 29% on day 3 (p = .22).

Conclusion

The artificial pancreas provided comparable postprandial glycemic control to usual care.     

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.     

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.     

Concealed Maternal Blood Glucose Excursions Correlate with Birth Weight Centile

Background

The objective of this study was to test the hypothesis that maternal blood glucose excursions correlate with deviation from optimized birth weight.

Methods

Patients were recruited for 3-day continuous glucose monitoring (CGM) plus self-blood glucose monitoring followed by routine diabetes screening at 26-28 weeks gestation. Patients and caregivers were blinded to CGM results. The magnitude and duration of blood glucose (BG) excursions were measured as a “glycemia index.” A customized birth weight centile was calculated.

Results

Twenty-three patients consented, 21 completed the study: 5 diabetic and 16 nondiabetic individuals. The duration of CGM was 72 (±7.2) hours, and each patient performed self-BG monitoring ≥3 times per day. All diabetic and 10 nondiabetic patients had several measured BG excursions above 130 mg/dl. A positive correlation was observed between birth weight centile and glycemia index above 130 (p < 0.03); the trend persisted for nondiabetic patients alone (p < 0.05). No significant correlation was noted between birth weight centile and average 3-day CGM values, 3-day fasting BG, average 3-day self-BG monitoring values, or diabetes screening BG value.

Conclusions

The glycemia index has a better correlation with birth weight centile than BG measured by conventional methods in a mixed diabetic and nondiabetic population. Fetal exposure to maternal blood glucose excursions correlates positively with fetal growth, even in nondiabetic patients with apparently normal glucose tolerance.     

Hypoglycemia impairs quality of blood glucose simulation in a clinical decision support system

Background

Clinical decision support systems allow for decisions based on blood glucose simulations. The DiasNet simulation tool is based on accepted principles of physiology and simulates blood glucose concentrations accurately in type 1 diabetes mellitus (T1DM) patients during periods without hypoglycemia, but deviations appear after hypoglycemia, possibly because of the long-term glucose counter-regulation to hypoglycemia. The purpose of this study was to evaluate the impact of hypoglycemia on blood glucose simulations.

Method

Continuous glucose monitoring (CGM) data and diary data (meals, insulin, self-monitored blood glucose) were collected for 2 to 5 days from 17 T1DM patients with poor glycemic control. Hypoglycemic episodes [CGM glucose <63 mg/dl (3.5 mmol/liter) for ≥20 min] were identified in valid (well-calibrated) CGM data. For 24 hours after each hypoglycemic episode, a simulated (DiasNet) glucose profile was compared to the CGM glucose.

Results

A total of 52 episodes of hypoglycemia were identified in valid data. All subjects had at least one hypoglycemic episode. Ten episodes of hypoglycemia from nine subjects were eligible for analysis. The CGM glucose was significantly (p < .05) higher than simulated blood glucose for a period of 13 h, beginning 8 h after hypoglycemia onset.

Conclusions

The present data show that hypoglycemia introduces substantial and systematic simulation errors for up to 24 h after hypoglycemia. This underlines the need for further evaluation of mechanisms behind this putative long-term glucose counter-regulation to hypoglycemia. When using blood glucose simulations in decision support systems, the results indicate that simulations for several hours following a hypoglycemic event may underestimate glucose levels by 100 mg/dl (5.6 mmol/liter) or more.     

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.     

Serum Total Adiponectin Is Associated with Impaired Glucose Tolerance in Asian Indian Females but Not in Males

Objective

Adiponectin may play a role in the development of type 2 diabetes and cardiovascular disease (CVD). However, little is known about the relationship between adiponectin and impaired glucose tolerance (IGT). We investigated the association between adiponectin and IGT and between adiponectin and cardiovascular risk factors among subjects with IGT.

Research Design and Methods

Subjects with normal glucose tolerance (NGT)(n = 571) and impaired glucose tolerance (n = 167) were recruited from the Chennai Urban Rural Epidemiology Study in south India. Serum total adiponectin levels were measured using a radioimmunoassay (Linco Research, St. Charles, MO). High sensitivity C-reactive protein (hsCRP) was estimated by nephelometry.

Results

In sex-stratified analyses, adiponectin was significantly associated with IGT in females [odds ratio (OR): 0.93, 95% confidence interval (CI): 0.872–0.991, p = 0.026] after controlling for age, waist circumference, blood pressure, alcohol consumption, smoking, lipid profile, and glycemic indices; in males there was no significant association (OR = 0.90, 95% CI: 0.798–1.012, p = 0.078). In prediabetic females, adiponectin was not associated with any CVD risk factors (age, waist circumference, blood pressure, cholesterol, triglyceride, high-density lipoprotein, low-density lipoprotein, fasting glucose, fasting insulin, and insulin resistance level), but was associated negatively with 2-hour postplasma glucose levels (r = –0.243, p < 0.05) and hsCRP (r = –0.219, p < 0.05) after adjusting for demographic and biomedical indices. No associations with CVD risk factors were observed in males with IGT.

Conclusion

Serum total adiponectin levels are associated with IGT, 2-hour postplasma glucose, and hsCRP in Asian Indian females but not in males.     

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.