Effect of 'FenuflakesTM' on 24-hour glycemic variability in adults with type 2 diabetes: A randomized crossover continuous glucose monitoring study.

Background: A recent report was published on the contribution of fasting plasma glucose (FPG) and postprandial glucose (PPG) to HbA1c and time in range (%TIR) in people with type 2 diabetes on multiple daily injection regimens using prandial Humalog® (Lispro). We extended this analysis to type 1 diabetes (T1D) using data from people randomized to 26 weeks of mealtime ultra rapid lispro (URLi; N=451), postmeal URLi (N=329) or mealtime Humalog (N=442) in the phase 3 trial, PRONTO-T1D, and its continuous glucose monitoring (CGM) substudy. Methods: A multivariate regression model was used to quantify the contribution of FPG and PPG change to the change in HbA1c and %TIR. The contribution of PPG relative to FPG was determined. %TIR was derived from 10-point self-monitored blood glucose (SMBG) and CGM data from the CGM substudy. Only results for the mealtime groups are presented here. Results: With URLi treatment, a 1 mmol/L reduction in FPG and PPG was associated with a 0.11% ± standard error 0.02% and 0.09% ± 0.01% reduction in HbA1c, respectively, both p<0.0001, with a contribution of PPG relative to FPG of 82%. Similar results were obtained with Humalog: A 1 mmol/L reduction in FPG and PPG was associated with reduction in HbA1c of 0.12% ± 0.02% and 0.07% ± 0.02%, respectively, both p<0.0001, but the contribution of PPG relative to FPG was 58%. For SMBG-derived %TIR, with URLi treatment, a 1 mmol/L reduction in FPG and PPG was associated with an increase in %TIR of 10.0% ± 0.53% and 8.6% ± 0.47%, respectively, all p<0.0001. Similarly, with Humalog, a 1 mmol/L reduction in FPG and PPG was associated with an increase in %TIR of 9.8% ± 0.56% and 8.6% ± 0.52%, respectively, all p<0.0001 A similar trend was observed with CGM data, although the absolute values of contributions of FPG and PPG differed. Conclusions: Changes in FPG and PPG significantly impacted HbA1c and %TIR in people with T1D, reinforcing the need to manage both FPG and PPG to achieve optimal glycemic control. Disclosure C. Piras de oliveira: Employee; Self; Eli Lilly and Company, Stock/Shareholder; Self; Eli Lilly and Company. M. A. Dellva: Employee; Self; Eli Lilly and Company. J. M. Bue-valleskey: Employee; Self; Eli Lilly and Company. A. M. Chang: Employee; Self; Eli Lilly and Company. F. B. Chigutsa: None. B. Liao: Employee; Self; Eli Lilly and Company. Funding Eli Lilly and Company

The accuracy of the GlucoWatch G2 Biographer (GW2B; Cygnus, Inc., Redwood City, CA) was assessed in children and adolescents with type 1 diabetes mellitus (T1DM). During a 24-h clinical research center stay, 89 children and adolescents with T1DM (3.5-17.7 years old) wore 174 GW2Bs and had frequent serum glucose determinations during the day and night and during insulin-induced hypoglycemia and meal-induced hyperglycemia, resulting in 3672 GW2B-reference glucose pairs. The median relative absolute difference between the GW2B and reference glucose values was 16% (25th, 75th percentiles = 7%, 29%). The proposed International Organisation for Standardisation criteria were met for 60% of sensor values. Accuracy was better at higher serum glucose levels than low glucose levels. Accuracy degraded slightly as the sensor aged. Time of day, subject age, gender, or body mass index did not impact GW2B accuracy. There were no cases of serious skin reactions. Although the accuracy of this generation of sensor does not approach that of current home glucose meters, the majority of sensor glucose values are within 20% of the serum glucose. This level of accuracy may be sufficient for detecting trends and modifying diabetes management. Further longitudinal outpatient studies are needed to assess the utility of the GW2B as a management tool to improve glycemic control and decrease the incidence of severe hypoglycemia in children with diabetes.

Diabetes technology and devices transform the lives of people with diabetes.

BackgroundRapid conversion from prediabetes to diabetes and frequent postprandial hyperglycemia (PPHG) is seen in Asian Indians. These should be the target of dietary strategies.ObjectivesWe hypothesized that dietary intervention of preloading major meals with almonds in participants with prediabetes will decrease overall glycemia and PPHG.DesignThe study included two phases: (1) an oral glucose tolerance test (OGTT)-based crossover randomized control study, the effect of a single premeal almond load (20 g) given before OGTT was evaluated (n = 60, 30 each period). (2) The continuous glucose monitoring system (CGMS)-based study for 3 days including premeal almond load before three major meals was a free-living, open-labeled, crossover randomized control trial, where control and premeal almond load diets were compared for glycaemic control (n = 60, 30 in each period). The study was registered at clinicaltrials.gov (registration no. NCT04769726).ResultsIn the OGTT-based study phase, the overall AUC for blood glucose, serum insulin, C-peptide, and plasma glucagon post-75 g oral glucose load was significantly lower for treatment vs. control diet (p < 0.001). Specifically, with the former diet, PPHG was significantly lower (18.05% in AUC on OGTT, 24.8% at 1-h, 28.9% at 2-h post OGTT, and 10.07% during CGMS). The CGMS data showed that premeal almond load significantly improved 24-glucose variability; SD of mean glucose concentration and mean of daily differences. Daily glycaemic control improved significantly as per the following: mean 24-h blood glucose concentration (M), time spent above 7.8 mmol/L of blood glucose, together with the corresponding AUC values. Premeal almond load significantly decreased following: overall hyperglycemia (glucose AUC), PPHG, peak 24-h glycaemia, and minimum glucose level during night.ConclusionIncorporation of 20 g of almonds, 30 min before each major meal led to a significant decrease in PPHG (as revealed in OGTT-based study phase) and also improved insulin, C-peptide, glucagon levels, and improved glucose variability and glycemic parameters on CGMS in participants with prediabetes.Clinical trial registryThe study was registered at clinicaltrials.gov (registration no. NCT04769726).

In recent years, meters for continuous monitoring of interstitial fluid glucose have been introduced to help people with type 1 diabetes mellitus (T1DM) to achieve better control of their disease. The objective of this project was to summarise the evidence on the clinical effectiveness and cost-effectiveness of the MiniMed(®) Paradigm™ Veo system (Medtronic Inc., Northridge, CA, USA) and the Vibe™ (Animas(®) Corporation, West Chester, PA, USA) and G4(®) PLATINUM CGM (continuous glucose monitoring) system (Dexcom Inc., San Diego, CA, USA) in comparison with multiple daily insulin injections (MDIs) or continuous subcutaneous insulin infusion (CSII), both with either self-monitoring of blood glucose (SMBG) or CGM, for the management of T1DM in adults and children. A systematic review was conducted in accordance with the principles of the Centre for Reviews and Dissemination guidance and the National Institute for Health and Care Excellence Diagnostic Assessment Programme manual. We searched 14 databases, three trial registries and two conference proceedings from study inception up to September 2014. In addition, reference lists of relevant systematic reviews were checked. In the absence of randomised controlled trials directly comparing Veo or an integrated CSII + CGM system, such as Vibe, with comparator interventions, indirect treatment comparisons were performed if possible. A commercially available cost-effectiveness model, the IMS Centre for Outcomes Research and Effectiveness diabetes model version 8.5 (IMS Health, Danbury, CT, USA), was used for this assessment. This model is an internet-based, interactive simulation model that predicts the long-term health outcomes and costs associated with the management of T1DM and type 2 diabetes. The model consists of 15 submodels designed to simulate diabetes-related complications, non-specific mortality and costs over time. As the model simulates individual patients over time, it updates risk factors and complications to account for disease progression. Fifty-four publications resulting from 19 studies were included in the review. Overall, the evidence suggests that the Veo system reduces hypoglycaemic events more than other treatments, without any differences in other outcomes, including glycated haemoglobin (HbA1c) levels. We also found significant results in favour of the integrated CSII + CGM system over MDIs with SMBG with regard to HbA1c levels and quality of life. However, the evidence base was poor. The quality of the included studies was generally low, often with only one study comparing treatments in a specific population at a specific follow-up time. In particular, there was only one study comparing Veo with an integrated CSII + CGM system and only one study comparing Veo with a CSII + SMBG system in a mixed population. Cost-effectiveness analyses indicated that MDI + SMBG is the option most likely to be cost-effective, given the current threshold of £30,000 per quality-adjusted life-year gained, whereas integrated CSII + CGM systems and Veo are dominated and extendedly dominated, respectively, by stand-alone, non-integrated CSII with CGM. Scenario analyses did not alter these conclusions. No cost-effectiveness modelling was conducted for children or pregnant women. The Veo system does appear to be better than the other systems considered at reducing hypoglycaemic events. However, in adults, it is unlikely to be cost-effective. Integrated systems are also generally unlikely to be cost-effective given that stand-alone systems are cheaper and, possibly, no less effective. However, evidence in this regard is generally lacking, in particular for children. Future trials in specific child, adolescent and adult populations should include longer term follow-up and ratings on the European Quality of Life-5 Dimensions scale at various time points with a view to informing improved cost-effectiveness modelling. PROSPERO Registration Number CRD42014013764. The National Institute for Health Research Health Technology Assessment programme.

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Objective To evaluate the effect of continuous glucose monitoring system(CGMS) in improving the current status of type 1 diabetes mellitus(T1DM) control and reducing the economic burden of the patients. Methods One hundred and fifteen patients with T1DM were randomly assigned to the CGMS group and the self-monitoring of blood glucose(SMBG) group respectively. The patients in CGMS group were on 72 h CGMS every 6 months, while SMBG group only with SMBG to guide the insulin dose adjustment. The levels of blood glucose and the statistics of the number of hypoglycemia and diabetic ketoacidosis were taken as the main observational indexes every 6 months. The chronic complication and the statistics of the number of hospitalizations and the total cost of treatment were made as the secondary observational index every 12 months. Results 2 h postprandial plasma glucose(2hPG) and mean blood glucose(MBG) in the CGMS group were lower than those in the SMBG group [(10.7±1.9 vs 11.5±2.7) mmol/L, (9.7±0.5 vs 10.6±0.7) mmol/L, P<0.05] in the clinical follow-up visit after 6 months. The per capita number of hypoglycaemia in the CGMS group was lower than that in the SMBG group[(7.9±2.6 vs 9.2±3.4) times, P<0.05]. In the outpatient follow-up re-visit to the patients after 6 months, fasting plasma glucose(FPG), 2hPG, MBG, and HbA1C of the patients in the CGMS group were lower than those in the SMBG group(t=4.71~9.75, P<0.05), the per capita numbers of hypoglycemia and DKA in the CGMS group were lower than those in the SMBG group(t=3.61~4.37, P<0.05). Conclusion The application of real-time continuous glucose monitoring in T1DM outpatient management may reduce the whole-day blood glucose of the patients, decrease the incidence risk of hypoglycemia, and improve the compliance of the treatment while without increasing the economic burden of the disease. (Chin J Endocrinol Metab, 2017, 33: 367-371) Key words: Real-time continuous glucose monitoring system; Diabetes mellitus, type 1; Outpatient management system; Control status; Economic burden of disease

Although both strength training (ST) and endurance training (ET) seem to be beneficial in type 2 diabetes mellitus (T2D), little is known about post-exercise glucose profiles. The objective of the study was to report changes in blood glucose (BG) values after a 4-month ET and ST programme now that a device for continuous glucose monitoring has become available. Fifteen participants, comprising four men age 56.5 +/- 0.9 years and 11 women age 57.4 +/- 0.9 years with T2D, were monitored with the MiniMed (Northridge, CA, USA) continuous glucose monitoring system (CGMS) for 48 h before and after 4 months of ET or ST. The ST consisted of three sets at the beginning, increasing to six sets per week at the end of the training period, including all major muscle groups and ET performed with an intensity of maximal oxygen uptake of 60% and a volume beginning at 15 min and advancing to a maximum of 30 min three times a week. A total of 17,549 single BG measurements pretraining (619.7 +/- 39.8) and post-training (550.3 +/- 30.1) were recorded, correlating to an average of 585 +/- 25.3 potential measurements per participant at the beginning and at the end of the study. The change in BG-value between the beginning (132 mg dL(-1)) and the end (118 mg dL(-1)) for all participants was significant (P = 0.028). The improvement in BG-value for the ST programme was significant (P = 0.02) but for the ET no significant change was measured (P = 0.48). Glycaemic control improved in the ST group and the mean BG was reduced by 15.6% (Cl 3-25%). In conclusion, the CGMS may be a useful tool in monitoring improvements in glycaemic control after different exercise programmes. Additionally, the CGMS may help to identify asymptomatic hypoglycaemia or hyperglycaemia after training programmes.

Background: This study was conducted to compare the efficacy and safety of saroglitazar with fenofibrate in Indian diabetic dyslipidemic patients who were on Metformin and Glimepiride.Methods: Adults patients with diabetic dyslipidaemia fulfilling the inclusion criteria were randomized in two groups. Group A patients received metformin (1000 mg/ day) + Glimepiride (4 mg/day) with fenofibrate (160 mg/day), while group B patients received metformin (1000 mg/day) + Glimepiride (4 mg/day) with saroglitazar (4 mg/day). Glycosylated haemoglobin (HbA1C), triglyceride (TG), LDL- cholesterol (LDL-C), HDL-cholesterol (HDL-C) levels were measured at baseline and at 12 weeks. Fasting plasma glucose (FPG) and post prandial plasma glucose (PPPG) were measured at baseline and at 4, 8 and 12 weeks.Results: There was a significant reduction in TG and HbA1C levels at 12 weeks from the baseline value (p=0.001) in both groups. However, there was no significant reduction in TG between the groups at 12 weeks but HbA1C levels in group B decreased significantly compared to group A at 12 weeks. Also, there was a significant reduction in FPG and PPPG levels at 4, 8 and 12 weeks in both groups from their baseline values (p=0.001). The reduction in FPG and PPPG levels in group B was statistically significantly compared to group A at every interval. There was statistically significant change in LDL-C and HDL-C at 12 weeks from baseline in both the groups. Also, there was significant rise in HDL-C in group B when compared to group A.Conclusions: Group B patients on saroglitazar with metformin and Glimepiride showed a significant reduction in HbA1C, FPG and PPG levels compared to group A patients on fenofibrate with metformin and Glimepiride.

Fasting and postprandial plasma glucose contributions to hemoglobin A1c and time in range in people with diabetes on multiple daily injection insulin therapy: Results from the PRONTO-T1D and PRONTO-T2D clinical trials

To evaluate the effect on coagulation and fibrinolysis parameters and on non-conventional cardiovascular risk factors of metformin plus nateglinide or glibenclamide in naïve type 2 diabetes patients. A total of 248 type 2 diabetic patients were enrolled and randomly assigned to receive nateglinide or glibenclamide, and metformin for 12 months. We assessed body mass index (BMI), glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), postprandial plasma glucose (PPG), fasting plasma insulin (FPI), postprandial plasma insulin (PPI), homeostasis model assessment index (HOMA index), lipid profile with lipoprotein (a) [Lp(a)], fibrinogen (Fg), plasminogen activator inhibitor-1 (PAI-1), tissue plasminogen activator (t-PA), homocysteine (Hcy), systolic blood pressure (SBP), diastolic blood pressure (DBP). After 9 months of treatment, both tested drug combinations were similarly associated with a significant reduction in FPG (nateglinide, -17.2%; glibenclamide, -16.9%, both p<0.05) compared to the baseline, while HbA1c (-17.3%, p<0.05) and PPG (-15.2%, p<0.05) significantly decreased only in the nateglinide group. After one year of treatment, compared to the baseline the nateglinide group showed a significant reduction in HbA1c (-21%, p<0.01), FPG (-20.7%), p<0.01, PPG (-21.5%, p<0.05), HOMA index (-25.4%, p<0.05); the glibenclamide group, showed a significant reduction in HbA1c (-11%, p<0.05), FPG (-23.2%, p<0.05), PPG (-11.2%, p<0.05), and HOMA index (-23.9%, p<0.05) but to a minor extent. Moreover, the HbA1c difference value from baseline observed in the nateglinide-treated group was significantly higher than that observed in the glibenclamide group. Therefore the nateglinide-treated patients showed a significant reduction in some prothrombotic parameters (PAI-1=-19%, Lp(a)=-31%, and Hcy=-32.3%, all p<0.05), whereas the glibenclamide-treated patients did not. Nateglinide appears to improve glycemic control as well as the levels of some prothrombotic parameters compared to glibenclamide when administered in combination with metformin.

Diabetes Technology & TherapeuticsVol. 2, No. supplement 1 Orginal ArticlesContinuous Glucose Monitoring in Previously Unstudied Population SubgroupsTodd M. Gross and Anna ter VeerTodd M. GrossSearch for more papers by this author and Anna ter VeerSearch for more papers by this authorPublished Online:5 Jul 2004https://doi.org/10.1089/15209150050214096AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail FiguresReferencesRelatedDetailsCited byA Standard Approach to Continuous Glucose Monitor Data in Pregnancy for the Study of Fetal Growth and Infant Outcomes Teri L. Hernandez and Linda A. Barbour29 January 2013 | Diabetes Technology & Therapeutics, Vol. 15, No. 2Continuous Glucose Monitoring in Pregnancy: New Frontiers in Clinical Applications and Research1 November 2012 | Journal of Diabetes Science and Technology, Vol. 6, No. 6The Correlation and Accuracy of Glucose Levels between Interstitial Fluid and Venous Plasma by Continuous Glucose Monitoring SystemKorean Diabetes Journal, Vol. 34, No. 6Continuous Glucose Monitoring System in Free-Living Healthy Subjects: Results from a Pilot Study Giuseppe Derosa, Sibilla A.T. Salvadeo, Roberto Mereu, Angela D'Angelo, Leonardina Ciccarelli, Mario N. Piccinni, Ilaria Ferrari, Alessia Gravina, Pamela Maffioli, and Carmine Tinelli6 March 2009 | Diabetes Technology & Therapeutics, Vol. 11, No. 3Preclinical In Vivo Study of a Fluorescence Affinity Sensor for Short-Term Continuous Glucose Monitoring in a Small and Large Animal Model Ralph Dutt-Ballerstadt, Colton Evans, Ashok Gowda, and Roger McNichols13 September 2010 | Diabetes Technology & Therapeutics, Vol. 10, No. 6How to Assess and Compare the Accuracy of Continuous Glucose Monitors? I.M.E. Wentholt, A.A.M. Hart, J.B.L. Hoekstra, and J.H. DeVries8 February 2008 | Diabetes Technology & Therapeutics, Vol. 10, No. 2Future Management Approaches12 July 2013Accuracy of continuous nocturnal glucose monitoring after 48 and 72 hours in type 2 diabetes patients on combined oral and insulin therapyDiabetes & Metabolism, Vol. 30, No. 6Nocturnal hypoglycaemia in type 1 diabetes?consequences and assessment1 January 2004 | Diabetes/Metabolism Research and Reviews, Vol. 20, No. S2The Continuous Glucose Monitoring System During Pregnancy of Women with Type 1 Diabetes Mellitus: Accuracy Assessment Anneloes Kerssen, Harold W. De Valk, and Gerard H.A. Visser12 October 2004 | Diabetes Technology & Therapeutics, Vol. 6, No. 5The Public Health Impact of the MiniMed Continuous Glucose Monitoring System (CGMS®)—An Assessment of the Literature Dale R. Tavris and Azadeh Shoaibi25 August 2004 | Diabetes Technology & Therapeutics, Vol. 6, No. 4Experience with the Continuous Glucose Monitoring System® in a Medical Intensive Care Unit Philip A. Goldberg, Mark D. Siegel, Raymond R. Russell, Robert S. Sherwin, Joshua I. Halickman, Dawn A. Cooper, James D. Dziura, and Silvio E. Inzucchi5 July 2004 | Diabetes Technology & Therapeutics, Vol. 6, No. 3Glucose sensors: toward closed loop insulin deliveryEndocrinology and Metabolism Clinics of North America, Vol. 33, No. 1Enregistrement de la glycémie en continu : quelles retombées ?Annales d'Endocrinologie, Vol. 65Performance assessment of the Medtronic-MiniMed Continuous Glucose Monitoring System and its use for measurement of glycaemic control in Type 1 diabetic subjectsDiabetic Medicine, Vol. 20, No. 12The Accuracy of the CGMS™ in Children with Type 1 Diabetes: Results of the Diabetes Research in Children Network (DirecNet) Accuracy Study5 July 2004 | Diabetes Technology & Therapeutics, Vol. 5, No. 5Accuracy of the continuous glucose monitoring system in inpatient and outpatient conditionsDiabetes & Metabolism, Vol. 29, No. 2Clinical Performance of CGMS in Type 1 Diabetic Patients Treated by Continuous Subcutaneous Insulin Infusion Using Insulin AnalogsDiabetes Care, Vol. 26, No. 3Biosensors for in vivo glucose measurement: can we cross the experimental stageBiosensors and Bioelectronics, Vol. 17, No. 11-12Reproducibility of Glucose Measurements Using the Glucose SensorDiabetes Care, Vol. 25, No. 7Continuous Monitoring of the Subcutaneous Glucose Level in Freely Moving Normal and Diabetic Rats and in Humans with Type 1 Diabetes Reza Jamali, Johnny Ludvigsson, and Simin Mohseni5 July 2004 | Diabetes Technology & Therapeutics, Vol. 4, No. 3What's ahead in glucose monitoring?30 June 2015 | Postgraduate Medicine, Vol. 109, No. 4New technologies and therapeutic approaches for the management of pediatric diabetesCurrent Diabetes Reports, Vol. 1, No. 1 Volume 2Issue supplement 1Dec 2000 To cite this article:Todd M. Gross and Anna ter Veer.Continuous Glucose Monitoring in Previously Unstudied Population Subgroups.Diabetes Technology & Therapeutics.Dec 2000.27-34.http://doi.org/10.1089/15209150050214096Published in Volume: 2 Issue supplement 1: July 5, 2004PDF download

Eating vegetables before carbohydrates improves postprandial glucose excursions

This study aimed at evaluating and comparing the performance of a new generation of continuous glucose monitoring (CGM) system versus other CGM systems, under daily lifelike conditions. A total of 10 subjects (7 female) were enrolled in this study. Each subject wore two Dexcom G4™ CGM systems in parallel for the sensor lifetime specified by the manufacturer (7 days) to allow assessment of sensor-to-sensor precision. Capillary blood glucose (BG) measurements were performed at least once per hour during daytime and once at night. Glucose excursions were induced on two occasions. Performance was assessed by calculating the mean absolute relative difference (MARD) between CGM readings and paired capillary BG readings and precision absolute relative difference (PARD), i.e., differences between paired CGM readings. Overall aggregate MARD was 11.0% (n = 2392). Aggregate MARD for BG &lt;70 mg/dl was 13.7%; for BG between 70 and 180 mg/dl, MARD was 11.4%; and for BG &gt;180 mg/dl, MARD was 8.5%. Aggregate PARD was 7.3%, improving from 11.6% on day 1 to 5.2% on day 7. The Dexcom G4 CGM system showed good overall MARD compared with results reported for other commercially available CGM systems. In the hypoglycemic range, where CGM performance is often reported to be low, the Dexcom G4 CGM system achieved better MARD than that reported for other CGM systems in the hypoglycemic range. In the hyperglycemic range, the MARD was comparable to that reported for other CGM systems, whereas during induced glucose excursions, the MARD was similar or slightly worse than that reported for other CGM systems. Overall PARD was 7.3%, improving markedly with sensor life time.

Efficacy of folic acid and enalapril combined therapy on reduction of blood pressure and plasma glucose: A multicenter, randomized, double-blind, parallel-controlled, clinical trial