EVALUATION OF INSULIN GLARGINE AND EXENATIDE ALONE AND IN COMBINATION: A RANDOMIZED CLINICAL TRIAL WITH CONTINUOUS GLUCOSE MONITORING AND AMBULATORY GLUCOSE PROFILE ANALYSIS.

Objective: Characterize the effectiveness of insulin glargine alone, exenatide alone, or combined in subjects taking stable doses of metformin and evaluate their impact on hemoglobin A1C, hypoglycemia, weight, and glucose variability. Methods: Open-label, randomized, parallel-arm study of adults with type 2 diabetes naïve to both insulin and glucagon-like peptide 1 (GLP-1) agonist who were not at A1C goal despite treatment with metformin. This prospective interventional study employed blinded continuous glucose monitoring ambulatory glucose profile (AGP) reports over 32 weeks. Subjects were randomized to treatment with glargine (Iglar), exenatide (GLP-1), or combination of glargine and exenatide (Iglar + GLP-1). At midpoint, those not at A1C target had the second medication added; those on Iglar + GLP-1 continued therapy optimization. Results: Decreases in A1C were: 7.6 to 6.2% for Iglar + GLP-1, 7.5 to 6.6% for Iglar, and 7.5 to 6.4% for GLP-1. Iglar + GLP-1 achieved A1C targets faster (14 to 16 weeks) but had more hypoglycemia. Hypoglycemia rates increased slightly for all arms. Weight loss was achieved in all regimens including GLP-1. Glucose variability was not reduced to the same extent in the Iglar arm as the GLP-1 arm. Conclusion: Addition of Iglar and/or GLP-1 to metformin for patients not at treatment goal was safe and effective. The order of medication addition needs to consider individualized AGP patterns and goals. Iglar + GLP-1 resulted in rapid A1C lowering, whereas GLP-1 was noted to have less hypoglycemia. Weight loss was most pronounced in GLP-1 monotherapy, suggesting that GLP-1 may mitigate the weight gain of Iglar. Any treatment with GLP-1 showed significant decreases in glucose variability. Abbreviations: A1C = hemoglobin A1c; AGP = ambulatory glucose profile; CGM = continuous glucose monitoring; GLM = general linear model; GLP-1 = glucagon-like peptide 1 (exenatide); Iglar = insulin glargine; SGLT2 = sodium-glucose cotransporter 2; SMBG = self-monitoring blood glucose; SU = sulfonylurea; T2D = type 2 diabetes mellitus.

Diurnal glucose exposure profiles of patients treated with lixisenatide before breakfast or the main meal of the day: An analysis using continuous glucose monitoring.

BACKGROUND: In the parent study of this analysis, patients with type 2 diabetes received lixisenatide before breakfast or the main meal of the day. This substudy was designed to examine the effect of lixisenatide administered before breakfast or the main meal of the day on continuously assessed 24-hour patient glucose profiles. METHODS: A subset of patients from the parent study underwent 2 14-day periods of continuous glucose monitoring (CGM) at the start and end of the 24-week study. Ambulatory glucose profile analysis was used to measure changes over time in detailed aspects of the glucose profiles. The breakfast group consumed a standardized meal during both CGM periods to determine change in 4-hour glycemic response. RESULTS: Data were available for 69 patients in the substudy, 40 from the original breakfast group and 29 from the main meal group. Between baseline and end of study, mean (standard deviation) total glucose exposure decreased from 4198.1 (652.3) to 3681.2 (699.6) mg/dL*24 h in the breakfast group (P < .0001) and from 4127.9 (876.8) to 3880.9 (1165.0) mg/dL*24 h in the main meal group (P = .0224). For patients included in the substudy, HbA1c decreased by approximately 0.6% in both groups. Mean (standard deviation) 4-hour total glucose exposure fell by 168.9 (158.4) mg/dL*4 h (P < .0001) from baseline. CONCLUSIONS: This analysis demonstrates that lixisenatide has beneficial effects on components of the 24-hour glucose profile, which endure beyond the meal at which it is administered. Continuous glucose monitoring analysis detects changes not captured using HbA1c alone.

An overview of continuous glucose monitoring and the ambulatory glucose profile.

Managing diabetes is essentially a balancing act, as patients and physicians work together to control blood glucose levels to avoid the symptoms of and long-term organ damage caused by glucose variability--the often unpredictable fluctuations between levels that are too high (hyperglycemia) and too low (hypoglycemia). For years, self-monitoring of blood glucose levels has been the treatment standard. With newer technology, however, continuous blood glucose monitoring (CGM) is now possible. This article describes CGM, presents evidence about its efficacy, and outlines how visual displays of CGM data can improve clinicians' decisions about therapies.

Advances in glucose monitoring: Improving diabetes management through evidence-based medicine.

After 50 years SMBG use remains equivocal. CGM, may face the same fate. While it has been reported that CGM use results in improved HbA1c, the margin is small, and the studies scant. Like SMBG, CGM was introduced as "here's something new, try it." For CGM's potential to be fully realized it must be understood that it can discover underlying metabolic perturbations that would otherwise go undetected; it can measure the frequency, duration, magnitude and distribution of glucose exposure, variability and stability under conditions of daily living which in turn lead to more precise therapies, resulting in improved outcomes.

Evaluating the accuracy, reliability, and clinical applicability of continuous glucose monitoring (CGM): Is CGM ready for real time?

BACKGROUND: This study was designed to assess the accuracy, reliability, and contribution to clinical decision-making of two commercially available continuous glucose monitoring (CGM) devices using a novel analytical approach. STUDY DESIGN: Eleven individuals with type 1 diabetes and five with type 2 diabetes wore a Guardian RT (GRT) (Medtronic Minimed, Northridge, CA) or DexCom STS Continuous Monitoring System (DEX) (San Diego, CA) device for 200 h followed by an 8-h laboratory study. A subset of these subjects wore both devices simultaneously. RESULTS: Subjects produced 1,902 +/- 269 readings during the ambulatory phase. During the laboratory study we found: lag time of 21 +/- 5 min for GRT and 7 +/- 7 min for DEX (P < 0.005); mean absolute relative difference of 19.9% and 16.7%, respectively, for GRT and DEX; and glucose exposure (the ratio of study device/laboratory reference device [YSI Instruments, Inc., Yellow Springs, OH] area under the curve) of 95 +/- 6% for GRT and 101 +/- 13% for DEX. Reliability measured during laboratory study showed 82% for DEX and 99% for GRT. Clarke Error Grid analysis (YSI reference) showed for GRT 59% of values in zone A, 34% in zone B, and 7% in zone D and for DEX 70% in zone A, 28% in zone B, 1% in zone C, and 1% in zone D. Bland-Altman plots (YSI standard) yielded for DEX 3 mg/dL (95% confidence interval, -78 to 84 mg/dL) and for GRT -21 mg/dL (95% confidence interval, -124 to 82 mg/dL). Six of eight subjects completed both home and laboratory simultaneous use of DEX and GRT. Lag times were inconsistent between devices, ranging from 0 to 32 min; area under the curve revealed a tendency for DEX to report higher total glucose exposure than GRT for the same patient. CONCLUSIONS: CGM detects abnormalities in glycemic control in a manner heretofore impossible to obtain. However, our studies revealed sufficient incongruence between simultaneous laboratory blood glucose levels and interstitial fluid glucose (after calibrations) to question the fundamental assumption that interstitial fluid glucose and blood glucose could be made identical by resorting to algorithms based on concurrent blood glucose levels alone.

Characterizing glucose exposure for individuals with normal glucose tolerance using continuous glucose monitoring and ambulatory glucose profile analysis.

BACKGROUND: Efforts to mimic euglycemia depend upon targets from epidemiologic studies that rely on episodic measurements reduced to statistical summaries, leaving open the question, "What is normal glycemia?" We postulated that portrayal of euglycemia was possible through application of continuous glucose monitoring (CGM) and a novel analytical tool, the ambulatory glucose profile (AGP). METHODS: Individuals with normal glucose tolerance (NGT) and with diabetes used CGM for 30 days. AGP analysis, which graphs CGM data by time without regard to date, was used to characterize glucose exposure, variability, and stability. RESULTS: Sixty-two subjects completed the study, employing CGM for 28 +/- 4 days averaging 99 +/- 18 (range, 33-125) readings per day. NGT subjects (n = 32) had a mean CGM of 102 +/- 7 mg/dL, ranging between 94 and 117 mg/dL and averaging 105 +/- 8 mg/dL daytime and 97 +/- 6 mg/dL overnight. Glucose variability, as expressed by the interquartile range, was 21 +/- 4 mg/dL (range, 14-29 mg/dL). Stability in glycemic control (hourly change in the median) for NGT subjects averaged 3 +/- 1 mg/dL/h. Subjects with diabetes (n = 30) were significantly higher on all glycemic characteristics with the exception of the percentage of hypoglycemic (CGM <70 mg/dL) episodes for type 2 diabetes (2.9%), compared to 2.7% for subjects with NGT. CONCLUSIONS: CGM technologies enabled collection of verified data under normal living conditions, providing an exceptional vantage point from which to obtain important clinical information. This will facilitate an understanding of the range of euglycemic patterns, provide a sensitive means of detecting impaired glucose tolerance, and help set realistic treatment goals for individuals with diabetes.

Physician pay-for-performance. Implementation and research issues.

Recent research underscores the gaps that exist between evidence-based medical practices and the care that many patients actually receive. Recognizing this, large purchasers are experimenting with new reimbursement arrangements called pay-for-performance (P4P) that tie a portion of payments for physician services to measures of quality. Agency theory, from the discipline of economics, provides a perspective on the challenges P4P is likely to encounter. The focus of most P4P initiatives on medical group performance raises additional questions about its potential effectiveness as a catalyst for change.

First Clinical Experience with Retrospective Flash Glucose Monitoring (FGM) Analysis in South Africa: Characterizing Glycemic Control with Ambulatory Glucose Profile.

BACKGROUND: In 2014, an innovative blinded continuous glucose monitoring system was introduced with automated ambulatory glucose profile (AGP) reporting. The clinical use and interpretation of this new technology has not previously been described. Therefore we wanted to understand its use in characterizing key factors related to glycemic control: glucose exposure, variability, and stability, and risk of hypoglycemia in clinical practice. METHODS: Clinicians representing affiliated diabetes centers throughout South Africa were trained and subsequently were given flash glucose monitoring readers and 2-week glucose sensors to use at their discretion. After patient use, sensor data were collected and uploaded for AGP reporting. RESULTS: Complete data (sensor AGP with corresponding clinical information) were obtained for 50 patients with type 1 (70%) and type 2 diabetes (30%), irrespective of therapy. Aggregated analysis of AGP data comparing patients with type 1 versus type 2 diabetes, revealed that despite similar HbA1c values between both groups (8.4 ± 2 vs 8.6 ± 1.7%, respectively), those with type 2 diabetes had lower mean glucose levels (9.2 ± 3 vs 10.3 mmol/l [166 ± 54 vs 185 mg/dl]) and lower indices of glucose variability (3.0 ± 1.5 vs 5.0 ± 1.9 mmol/l [54 ± 27 vs 90 ± 34.2 mg/dl]). This highlights key areas for future focus. CONCLUSIONS: Using AGP, the characteristics of glucose exposure, variability, stability, and hypoglycemia risk and occurrence were obtained within a short time and with minimal provider and patient input. In a survey at the time of the follow-up visit, clinicians indicated that aggregated AGP data analysis provided important new clinical information and insights.

Diurnal Glycemic Patterns during an 8-Week Open-Label Proof-of-Concept Trial of Empagliflozin in Type 1 Diabetes.

BACKGROUND: We recently reported improved glycemic control with reduced insulin dose in subjects with type 1 diabetes treated with the sodium glucose co-transporter-2 inhibitor empagliflozin. To further characterize the effects, we analyzed diurnal glycemic patterns by continuous glucose monitoring (CGM). METHODS: In an 8-week single-arm open-label pilot study of empagliflozin, we compared ambulatory glucose profiles produced from CGM data during 2-week intervals in a placebo run-in baseline period, end-of-treatment, and post-treatment. Change in glycemic exposure was evaluated by area under the median curve according to time of day (AUCTOTAL 12:00am-11:55pm; AUCDAY 7:05am-10:55pm, AUCNIGHT 11:00pm-7:00am), as well as glycemic variability, glycemic stability and time-in-target (≥70 to ≤140mg/dL). RESULTS: The 40 patients (26 on insulin pump) were aged 24±5 years and BMI 24.5±3.2 kg/m2. Consistent with the observed HbA1c decrease (8.0±0.9% to 7.6±0.9%, p<0.0001), normalized AUCTOTAL CGM decreased from 153.7±25.4 to 149.0±30.2mg/dL∙h at end-of-treatment (p = 0.31), and significantly increased post-treatment (164.1±29.5mg/dL∙h, p = 0.02). The numerical decrease in normalized AUCNIGHT (152.0±36.6 to 141.9±34.4mg/dL∙h, p = 0.13) exceeded AUCDAY (154.5±24.5 to 152.6±30.4mg/dL∙h, p = 0.65). Trends toward lower glycemic variability (83.1±18.9 to 75.6±28.6mg/dL, p = 0.06) and little change in glycemic stability (10.8±3.6 to 10.3±4.5mg/dL/h, p = 0.51) were observed. When empagliflozin was discontinued, these worsened relative to baseline (89.3±19.3mg/dL, p = 0.04 and 11.8±3.7mg/dL/hr, p = 0.08). Time-in-target numerically increased (40.2±11.9 to 43.1±13.5%, p = 0.69) at end-of-treatment but reversed post-treatment. Findings were similar on stratification of pump and MDI subjects. CONCLUSIONS: We observed that empagliflozin was associated with patterns of improved nighttime glycemia more prominent than daytime. TRIAL REGISTRATION: Clinicaltrials.gov NCT01392560.

Measuring and managing hyperglycemia in pregnancy: from glycosuria to continuous blood glucose monitoring.

The need to accurately detect and monitor hyperglycemia in pregnancy is becoming more apparent as the incidence of pregestational and gestational diabetes is increasing, especially among adolescents. The risk of adverse perinatal outcome is markedly worsened when pregnancy is complicated by elevated blood glucose. The appropriate management of both pregestational and gestational diabetes as it relates to blood glucose targets is clear. In the past 5 years, a number of studies have concluded that tight glycemic control throughout pregnancy significantly reduces both fetal and maternal risk. These studies have proposed blood glucose targets between 70 to 120 mg/dL. They have concluded that blood glucose levels should be the basis of moving rapidly to more effective treatments. The key to this approach is the adoption of blood glucose monitoring as an integral part of the treatment regimen. To assure sufficient data on which clinical decisions are made, the type of device, frequency of monitoring, and interpretation of results need to be carefully considered.

Diabetes in the Hispanic population. High risk warrants targeted screening and treatment.

As the Hispanic population in the United States increases, more primary care physicians are being challenged to address the high incidence of diabetes and related metabolic disorders in Hispanic American patients. A variety of genetic, environmental, and socioeconomic factors contribute to this group's high susceptibility to diabetes. In this article, Drs Idrogo and Mazze discuss diagnosis of diabetes in Hispanic patients, as well as culturally sensitive screening and treatment strategies.

A feasibility study of a 3-day basal-bolus insulin delivery device in individuals with type 2 diabetes.

OBJECTIVE: This study tested the feasibility of transition from multiple daily injections (MDI) to a 3-day, basal-bolus insulin delivery device (PaQ) for type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: Twenty MDI-treated individuals with T2D with HbA(1c) ≤9% (75 mmol/mol) were enrolled in a single-center, single-arm pilot study, lasting three 2-week periods: baseline (MDI), transition to PaQ, and PaQ therapy. Feasibility of use, glycemic control, safety, and patient satisfaction were assessed. RESULTS: Nineteen participants transitioned to PaQ treatment and demonstrated competency in assembling, placing, and using the device. Self-monitored blood glucose and blinded continuous glucose-monitoring data showed glycemic control similar to MDI. Study participants reported high satisfaction and device acceptance. CONCLUSIONS: PaQ treatment is both feasible and acceptable in individuals with T2D. Transition from MDI is easy and safe. PaQ treatment might lead to better therapy adherence and improvements in glycemic control and clinical outcomes.

Diurnal glucose profiles using continuous glucose monitoring to identify the glucose-lowering characteristics of colesevelam HCl (Welchol).

OBJECTIVES: The study's purpose was to identify the antihyperglycemic affects of colesevelam-HCl (C-HCl) by characterizing the diurnal and postprandial glucose patterns in type 2 diabetic subjects treated concomitantly with metformin, sulfonylurea, or a combination of metformin/sulfonylurea. A secondary aim was to determine whether C-HCl significantly increased the risk of hypoglycemia. METHODS: A prospective, randomized, double-blind, placebo-controlled, crossover study employing continuous glucose monitoring (CGM) with ambulatory glucose profile (AGP) analysis was undertaken. Fifteen males and 6 females, age 60 ± 8 years, treated with metformin (n = 8), sulfonylurea (n = 2), or combination (n = 11) participated. RESULTS: Treatment with C-HCl led to reductions in glycated hemoglobin (HbA1c) (7.5 ± 0.3 to 7.0 ± 0.4% P<.0001), LDL (90.9 ± 18.6 to 68.9 ± 15.2 mg/dL, P<.0007) and total cholesterol (169.2 ± 24.4 to 147.8 ± 21.5 mg/dL, P<.001). Significantly lower normalized diurnal (21 mg/dL/hour, P = .0006), nocturnal (19 mg/dL/hour, P = .0005), and daytime (22 mg/dL/hour, P = .0008) glucose exposure was detected immediately upon C-HCl administration. Additionally, there was a significant (P<.004) decline in postprandial glucose excursions (averaging 15% or -36 mg/dL/hour) pronounced at dinner following C-HCl administration. There was a nonsignificant increase in the incidence of hypoglycemia (0.4-1%), with no difference due to antihyperglycemic medications. CONCLUSIONS: AGP analysis of CGM visually and quantitatively showed immediate and midterm impacts of C-HCl on basal and postprandial glucose patterns. This suggests a multifactorial glucose-lowering mechanism for C-HCl affecting both meal-related and basal glucose levels.

Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the ambulatory glucose profile.

Underutilization of glucose data and lack of easy and standardized glucose data collection, analysis, visualization, and guided clinical decision making are key contributors to poor glycemic control among individuals with type 1 diabetes mellitus. An expert panel of diabetes specialists, facilitated by the International Diabetes Center and sponsored by the Helmsley Charitable Trust, met in 2012 to discuss recommendations for standardizing the analysis and presentation of glucose monitoring data, with the initial focus on data derived from continuous glucose monitoring systems. The panel members were introduced to a universal software report, the Ambulatory Glucose Profile, and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. This article provides a summary of the topics and issues discussed during the meeting and presents recommendations from the expert panel regarding the need to standardize glucose profile summary metrics and the value of a uniform glucose report to aid clinicians, researchers, and patients.

Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the Ambulatory Glucose Profile (AGP).

Abstract Underutilization of glucose data and lack of easy and standardized glucose data collection, analysis, visualization, and guided clinical decision making are key contributors to poor glycemic control among individuals with type 1 diabetes. An expert panel of diabetes specialists, facilitated by the International Diabetes Center and sponsored by the Helmsley Charitable Trust, met in 2012 to discuss recommendations for standardization of analysis and presentation of glucose monitoring data, with the initial focus on data derived from CGM systems. The panel members were introduced to a universal software report, the Ambulatory Glucose Profile (AGP), and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. This paper provides a summary of the topics and issues discussed during the meeting and presents recommendations from the expert panel regarding the need to standardize glucose profile summary metrics and the value of a uniform glucose report to aid clinicians, researchers, and patients.

Measuring glucose exposure and variability using continuous glucose monitoring in normal and abnormal glucose metabolism in pregnancy.

UNLABELLED: In pregnancy complicated by diabetes periods of hyperglycemia lead to accelerated fetal growth, resulting in a large for gestational age (LGA), or macrosomic, infant. Consequently, our aim was to measure the average volatility or variability in glucose control in women with and without diabetes in pregnancy. METHODS: Continuous glucose monitoring (CGM) was employed in 82 pregnant study subjects to collect and record unbiased self-monitored glucose values. We obtained results from 51 women with normal glucose tolerance in pregnancy (NGTP), 25 gestational diabetes (GDM) and 6 women with pregestational diabetes (PreGD) between 18 and 45 (32 ± 6) years of age. RESULTS: Significant differences (p < 0.001) were found in glucose exposure between NGT and all but PreGD; whereas the percent of time in hypoglycemia was significantly (p < 0.0001) higher in all pregnancy groups when compared to the nonpregnant sample. We conclude that CGM confirmed that diurnal glucose patterns differ throughout the day by 20% when pregnant and nonpregnant states are compared. Indeed, maintenance of a narrow range in pregnancy is characteristic in women without diabetes, and CGM throughout pregnancy is critical, if mimicking normal glucose patterns is to be achieved.

International Forum for the Advancement of Diabetes Research and Care, April 29-30, 2011, Athens, Greece.

The International Forum for the Advancement of Diabetes Research and Care brought together distinguished international experts in diabetes to discuss diverse trends and emerging issues in diabetes therapy and management. The plenary sessions on the first day focused on trends in insulin therapy, the role of glucagon-like peptide-1 receptor agonists in diabetes treatment, the relationship between diabetes and cardiovascular risk, and the challenges associated with the development of clinically relevant treatment guidelines. Interactive breakout sessions addressed the following topics: microvascular complications of diabetes; the need for a team approach to patient education; optimal management of Asian people with diabetes; the role of continuous glucose monitoring in assessing glucose variability; and lessons learned from biosimilar drugs. The plenary sessions on the second day covered self-monitoring of blood glucose, treatment and prevention of type 1 diabetes, and future directions for diabetes therapy. The meeting represented an excellent forum for the presentation of new research and the exchange of ideas aimed at improving outcomes for people with diabetes.