Using Meal-Based Self-Monitoring of Blood Glucose as a Tool to Improve Outcomes in Pregnancy Complicated By Diabetes

ObjectiveTo review the importance of controlling blood glucose levels and the role of self-monitoring of blood glucose (SMBG) in the management of pregnancy complicated by diabetes.MethodsThis report describes the relationship between hyperglycemia and maternal and neonatal complications, reviews the utility of meal-based SMBG in modifying food choices and adjusting insulin doses, and proposes an algorithm to achieve normoglycemia in pregnancies complicated by diabetes.ResultsThe risk of diabetes-related complications in pregnancy is more strongly associated with 1-hour post-prandial plasma glucose concentrations than with fasting plasma glucose levels. SMBG strategies that incorporate postprandial glucose testing provide better glycemic control and greater reductions in risk of complications than does preprandial glucose testing alone. Although the optimal timing and frequency of SMBG remain controversial, available clinical evidence supports testing 4 times per day (before breakfast and 1 hour after each meal) in women with gestational diabetes managed by medical nutrition therapy only and 6 times per day (before and 1 hour after each meal) in pregnant women treated with insulin.ConclusionMeal-based SMBG is a valuable tool for improving outcomes in pregnancy complicated by diabetes. The lessons learned in this setting should have relevance to the general population of patients with diabetes, in whom microvascular and macrovascular complications are the outcomes of importance. (Endocr Pract. 2008; 14:239-247)     

Glycated Albumin at 4 Weeks Correlates with A1C Levels at 12 Weeks and Reflects Short-Term Glucose Fluctuations

Objective: Evaluate the performance of glycated albumin (GA) monitoring by comparing it to other measures of glycemic control during intensification of antidiabetic therapy.Methods: This 12-week, prospective, multicenter study compared the diagnostic clinical performance of GA to glycated hemoglobin A1C (A1C), fructosamine corrected for albumin (FRA), fasting plasma glucose (FPG), and mean blood glucose (MBG) estimated from self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) in 30 patients with suboptimally controlled type 1 or 2 diabetes.Results: Mean A1C decreased from 9.5% to 8.1%. Mean SMBG correlated closely with CGM (Pearson r = 0.783 for daily estimates and r = 0.746 for weekly estimates, P<.0001). Both GA and FRA levels significantly correlated with changes from baseline in A1C and mean weekly SMBG (P<.001). The lowest observed median GA occurred at 4 weeks, followed by a small increase and then a slight reduction, mirroring changes in overall mean SMBG values. The median A1C fell throughout the treatment period, failing to reflect short-term changes in SMBG. A ≥1% reduction in GA at 4 weeks was significantly associated with a ≥0.5% change in A1C at 12 weeks (odds ratio &lsqb;OR] = 19.0, 95% confidence interval &lsqb;CI]: 1.4, 944, P = .018).Conclusion: In patients receiving glucose-lowering therapy, changes in GA at 4 weeks were concordant with changes in A1C at 12 weeks, and both GA and FRA more accurately reflected short-term blood glucose fluctuations than A1C.Abbreviations: A1C = glycated hemoglobin A1C ARIC = Atherosclerosis Risk in Communities CGM = continuous glucose monitoring FPG = fasting plasma glucose FRA = fructosamine corrected for albumin GA = glycated albumin MBG = mean blood glucose OR = odds ratio SMBG = self-monitoring of blood glucose     

Continuous Glucose Monitoring: A Consensus Conference of the American Association of Clinical Endocrinologists and American College of Endocrinology

Objective/Methods: Barriers to continuous glucose monitoring (CGM) use continue to hamper adoption of this valuable technology for the management of diabetes. The American Association of Clinical Endocrinologists and the American College of Endocrinology convened a public consensus conference February 20, 2016, to review available CGM data and propose strategies for expanding CGM access.Results: Conference participants agreed that evidence supports the benefits of CGM in type 1 diabetes and that these benefits are likely to apply whenever intensive insulin therapy is used, regardless of diabetes type. CGM is likely to reduce healthcare resource utilization for acute and chronic complications, although real-world analyses are needed to confirm potential cost savings and quality of life improvements. Ongoing technological advances have improved CGM accuracy and usability, but more innovations in human factors, data delivery, reporting, and interpretation are needed to foster expanded use. The development of a standardized data report using similar metrics across all devices would facilitate clinician and patient understanding and utilization of CGM. Expanded CGM coverage by government and private payers is an urgent need.Conclusion: CGM improves glycemic control, reduces hypoglycemia, and may reduce overall costs of diabetes management. Expanding CGM coverage and utilization is likely to improve the health outcomes of people with diabetes.Abbreviations:A1C = glycated hemoglobinAACE = American Association of Clinical EndocrinologistsACE = American College of EndocrinologyASPIRE = Automation to Simulate Pancreatic Insulin ResponseCGM = continuous glucose monitoringHRQOL = health-related quality of lifeICER = incremental cost-effectiveness ratioJDRF = Juvenile Diabetes Research FoundationMARD = mean absolute relative differenceMDI = multiple daily injectionsQALY = quality-adjusted life yearsRCT = randomized, controlled trialSAP = sensor-augmented pumpSMBG = self-monitoring of blood glucoseSTAR = Sensor-Augmented Pump Therapy for A1C ReductionT1D = type 1 diabetesT2D = type 2 diabetes     

A pilot study to stabilize normoglycemia during an educational camp for children and adolescents with type 1 diabetes mellitus

Background: Children and adolescents with type 1 diabetes mellitus (DM) who participate in diabetes camps do not often achieve stable, normoglycemic control, largely because changes in the campers' activity levels and food options necessitate adjustments to their insulin use and nutritional therapies. It would seem logical, with the abundance of diabetes education and professional consultation freely available at these camps, that the glycemic levels of these young campers could approach normal values.Objective: This informal study was designed to explore the feasibility of safely achieving stable, short-term normo-glycemic control in children and adolescents with recent-onset type 1 DM attending a diabetes camp.Methods: A multidisciplinary team worked with children and adolescents 6 to 18 years of age during a residential 3-day/2-night diabetes camp. Demographic data were compiled from the application forms completed by the campers and signed by the campers and their parents. The staff functioned in 2 distinct roles: as managers (securing time, task, technique, and territory boundaries) and as consultants (addressing participants' educational, social, and emotional needs). The staff supported the campers in their attempts to quickly and safely achieve tight normoglycemic control (ie, 71–99 mg/dL) and stability (ie, an estimated mean amplitude of glycemic excursion [eMAGE] score ≤95) through their firsthand experience with self-directed learning methods, basal-bolus insulin analogue therapy, and a diet low in concentrated carbohydrates (CHOs). Campers chose foods from meal buffets, calculated preprandial and complementary doses of ultra-rapid insulin, and participated in physical exercise and self-monitoring of blood glucose (SMBG) at will. SMBG values retained in each camper's combined glucose/ketone monitor furnished statistical data. Initial and final glycosylated hemoglobin values were not measured because 3 days of glycemic control—at any BG level—would not be expected and have not been reported to produce significant changes. No follow-up of the campers was planned or possible.Results: Six boys and 3 girls (aged 8–17 years; mean [SD] age, 11.8 [2.6] years; mean duration of diabetes, 1.62 [0.88] years) agreed to participate in the study. All but 1 of the campers were preadolescents. Mean BG levels on arrival and departure were 209 (101.5) and 81 (12.8) mg/dL, respectively (P < 0.003). The mean 3-day BG level was 95 (21.2) mg/dL. The 3-day mean eMAGE score (66.5 [28.1]) indicated stable glycemic control. Seven of the 9 campers (78%) returned to the camp the following year (2007).Conclusions: Combining self-directed educational methods for learning diabetes self-management with insulin analogues in a basal-bolus therapy regimen, ad libitum physical activity and SMBG, and a diet low in concentrated CHOs, campers rapidly established routinely normal daily mean BG levels and glycemic stability.     

Blood glucose discrimination training in insulin-dependent diabetes mellitus (IDDM) patients

Self-management of insulin-dependent diabetes mellitus (IDDM) is dependent on a negative feedback loop of blood glucose (BG) fluctuations, which in turn directs treatment decisions to maintain normal BG. Although this feedback is typically accomplished by self-monitoring of blood glucose (SMBG), SMBG has limitations, and patients often rely on what their BG "feels" like. Two studies were performed to evaluate whether patients could learn to more accurately "feel"/discriminate their BG on the basis of internal cues or internal plus external BG cues. In Study I, BG Awareness Training significantly improved pre- to posttreatment BG estimation accuracy, relative to a control group. Study II replicated BG Awareness Training efficacy in improving BG estimation accuracy. Improvement in estimation accuracy was related only to initial accuracy; those who were initially less accurate improved the most. This improvement was represented in a 31% reduction in dangerous BG estimation errors and a 9% increase in accurate estimates. Resulting estimations were, however, still significantly less accurate than SMBG at the end of training.     

Effect of Gluten-FREE Diet on Metabolic Control and Anthropometric Parameters in Type 1 Diabetes with Subclinical Celiac Disease: A Randomized Controlled Trial

Objective: It is unclear whether the institution of gluten-free diet (GFD) is beneficial in patients with type 1 diabetes (T1DM) and subclinical celiac disease (CD). Our primary objective was to evaluate the effect of GFD on the frequency of hypoglycemia, in patients with T1DM and subclinical CD. Our secondary objective was to investigate the effect of GFD on height, weight, glycosylated hemoglobin (HbA1c), insulin dose requirement, and bone mineral homeostasis.Methods: We carried out a prospective open label randomized controlled trial (RCT). Patients with T1DM and subclinical CD were randomized to receive GFD or a normal diet for 1 year. The primary outcome was the frequency of hypoglycemic episodes (blood glucose <70 mg/dL) measured by self-monitoring of blood glucose (SMBG) at the sixth month of the study in the 2 groups.Results: Screening for CD was carried out in 320 T1DM patients. Thirty eligible patients were randomized to receive GFD (n = 15) or a normal diet (n = 15). The mean number of hypoglycemic episodes/month recorded by SMBG and the mean time spent in hypoglycemia measured by CGM (minutes) in the GFD group versus the non-GFD group at six months was 2.3 minutes versus 3.4 minutes (P = .5) and 124.1 minutes versus 356.9 minutes (P = .1), respectively. The mean number of hypoglycemic episodes/month significantly declined in the GFD group (3.5 episodes at baseline versus 2.3 episodes at the sixth month; P = .03). The mean HbA1c declined by 0.73% in the GFD group and rose by 0.99% in non-GFD group at study completion.Conclusion: This is the first RCT to assess the effect of GFD in T1DM and subclinical CD. A trend towards a decrease in hypoglycemic episodes and better glycemic control was seen in patients receiving GFD.Abbreviations: BMC = bone mineral content; BMI = body mass index; CD = celiac disease; CGM = continuous glucose monitoring; GFD = gluten-free diet; Hb = hemoglobin; HbA1c = glycosylated hemoglobin; iPTH = intact parathyroid hormone; RCT = randomized controlled trial; SMBG = self-monitoring of blood glucose; T1DM = type 1 diabetes mellitus; tTG-IgA = tissue transglutaminase immunoglobulin A     

Hypoglycemia in childhood type 1 diabetes mellitus: Understanding and managing the dark side of intensive insulin therapy

Background: Despite the availability of advanced insulin delivery systems, blood glucose-monitoring equipment, and insulin analogue formulations, hypoglycemia remains a significant concern in the treatment of children and adolescents with type 1 diabetes mellitus (DM). Furthermore, patients who manage their blood glucose levels most effectively may also be the ones at greatest risk for hypoglycemia.Objective: The aim of this article was to review current issues surrounding the pathophysiology and frequency of hypoglycemia in children and adolescents with type 1 DM.Methods: Relevant articles for this review were identified through a search of MEDLINE (1992–2007; English-language articles only). The search terms used were children, adolescents, hypoglycemia, diabetes, insulin, and continuous subcutaneous insulin infusion.Results: The threat of severe hypoglycemia remains a major obstacle to the effective treatment of type 1 DM. Basalbolus therapy, using continuous subcutaneous insulin infusion or multiple daily injections, is the most effective and flexible method available for maintaining good glycemic control in children as well as in adults. Insulin analogues can be used effectively in these regimens and may be helpful toward addressing risks for hypoglycemia. Patient education should also be given a high priority in addressing the risk of hypoglycemia in children and adolescents with type 1 DM. The development of continuous glucose-monitoring systems offers the potential for an even brighter future for this group of patients.Conclusions: Recent advances in DM technology reduce but do not eliminate the risk of hypoglycemia in youth with type 1 DM. These observations underscore the need for a closed-loop insulin delivery system in which the rate of insulin infusion is regulated by real-time changes in glucose concentrations. (Insulin. 2007;2:157–165)Key words: type 1 diabetes mellitus; hypoglycemia; children; adolescents; insulin analogue; continuous subcutaneous insulin infusion; multiple daily injections; basal-bolus therapy.Accepted for publication 09052007     

Hyperglycemia Management In Patients With Posttransplantation Diabetes

Objective: Posttransplantation diabetes (PTDM) is a common occurrence after solid-organ transplantation and is associated with increased morbidity, mortality, and health care costs. There is a limited number of studies addressing strategies for hyperglycemia management in this population, with a few articles emerging recently.Methods: We performed a PubMed search of studies published in English addressing hyperglycemia management of PTDM/new-onset diabetes after transplant (NODAT). Relevant cited articles were also retrieved.Results: Most of the 25 publications eligible for review were retrospective studies. Insulin therapy during the early posttransplantation period showed promise in preventing PTDM development. Thiazolidinediones have been mostly shown to exert glycemic control in retrospective studies, at the expense of weight gain and fluid retention. Evidence with metformin, sulfonylureas, and meglitinides is very limited. Incretins have shown promising results in small prospective studies using sitagliptin, linaglitpin, and vildagliptin and a case series using liraglutide.Conclusion: Prospective randomized studies assessing the management of hyperglycemia in PTDM are urgently needed. In the meantime, clinicians need to be aware of the high risk of PTDM and associated complications and current concepts in management.Abbreviations:A1c = glycated hemoglobin A1cCHF = congestive heart failureCNI = calcineurin inhibitorsCS = corticosteroidsDM = diabetes mellitusDPP-4 = dipeptidyl peptidase-4GLP-1 = glucagon-like peptide-1ICU = intensive care unitIGT = impaired glucose toleranceNODAT = new-onset diabetes after transplantationOGTT = oral glucose tolerance testPTDM = posttransplantation diabetesSU = sulfonylureaT2DM = type 2 diabetes mellitusTZD = thiazolidinedione     

Perception of Graduating Endocrinology,Diabetes, and Metabolism Fellows on the Benefits of Wearing A Continuous Glucose Monitor and/or Insulin Pump for Their Education

Objectives: To our knowledge, no prior research has explored the prevalence of wearing continuous glucose monitors (CGMs) and/or insulin pumps among in-training fellows and their perception of doing so as part of their education. Our objectives therefore were to estimate the frequency with which wearing a CGM and/or insulin pump is used as a learning opportunity and explore the main motivators and perception on its value.Methods: A multiple-choice survey that addressed each fellow's level of training, type of fellowship training program, and use of CGM and/or insulin pump was sent to all Accreditation Council for Graduate Medical Education endocrinology, diabetes, and metabolism program coordinators or program directors. We asked them to forward this survey to their graduating fellows. Their perception on the value of wearing these devices was addressed.Results: Fifty-one graduating fellows responded to the survey; 78.43% and 62.5% of them wore a CGM and insulin pump, respectively. A total of 89.48% and 90% of those who wore a CGM and insulin pump, respectively, thought it was above-average value for their education, and the most common reasons were to learn the technical aspects and understand what patients with diabetes go through.Conclusion: Wearing a CGM and/or insulin pump is perceived by endocrinology graduating fellows as valuable to their education, specifically, to learn the technical aspects, understand the patient's experience, and develop empathy.Abbreviations: ACGME = Accreditation Council for Graduate Medical Education; CGM = continuous glucose monitor     

Diabetes in the Caribbean: Trouble in paradise

Background: Many developing countries, including countries of the English-speaking Caribbean, are undergoing an epidemiologic transition and experiencing rapid increases in the prevalence of diabetes.Objectives: This article examines the epidemiology of diabetes, the types of diabetes, the etiologic factors and complications of diabetes, and the public health burden associated with diabetes in the Caribbean.Methods: An extensive PubMed literature search was conducted for the period 1951 to 2008 using the search terms diabetes, glucose intolerance, Caribbean, Jamaica, Barbados, Trinidad, Bahamas, Guyana, and the names of all the other English-speaking Caribbean countries.Results: Four hundred articles were identified in the literature search. Of these, 131 original articles were selected for inclusion in this review. Prevalence rates for diabetes ranged from 11% to 18% of the population in several countries. The prevalence of atypical diabetes (ketosis-prone diabetes) may be declining because of increases in the proportions of the population with type 2 diabetes mellitus. Ecologic studies show an east-to-west gradient from West Africa to the Caribbean for obesity and obesity-related diseases. The steep increase in the prevalence of obesity and the increase in sedentarism in Caribbean societies are the main risk factors driving the diabetes epidemic. The roles of early-life origins (specifically, in infants with low birth weight and rapid catch-up growth and/or macrosomic infants) and genetic factors await further clarification in this population. Diabetic foot, nephropathy, and stroke are common complications.Conclusions: In the English-speaking Caribbean, diabetes is a major public health burden that threatens the gross domestic product of these developing island nations. Macroeconomic initiatives are needed to start the combat against diabetes.     

The Role of Glucagon in the Pathophysiology and Management of Diabetes

Objective: There is general recognition that insulin and glucagon are the main hormones involved in the pathophysiology of diabetes, but the role of glucagon in diabetes is complex and in some circumstances controversial. The increasing appreciation of the role of glucagon in currently used hypoglycemic agents and the ongoing development of glucagon-targeted therapies underscores glucagon's important contribution in optimizing diabetes management. The current review provides a background on glucagon physiology and pathophysiology and an update for investigators, endocrinologists, and other healthcare providers on glucagon-modulating therapies.Methods: A literature review was conducted utilizing published literature in PubMed and AccessMedicine including the years 1922–2015 using the following key words: glucagon, bihormonal, diabetes mellitus, glucagon antagonists, glucagon-targeted therapies.Results: Glucagon is a counterregulatory hormone that promotes hepatic glucose production, thus preventing hypoglycemia in normal physiology. In patients with diabetes mellitus, glucagon secretion may be unregulated, which contributes to problems with glucose homeostasis. Several of the most effective therapies for diabetes have been found to suppress glucagon secretion or action, which may contribute to their success. Additionally, glucagon-specific targeted therapies, such as glucagon receptor antagonists, are being studied at a basic and clinical level.Conclusion: Glucagon plays an important role in contributing to hyperglycemia in patients with diabetes. Utilizing hypoglycemic agents that decrease glucagon secretion or inhibit glucagon action can help improve glycemic control, making these agents a valuable resource in diabetes therapy.Abbreviations:cAMP = cyclic adenosine monophosphateDPP-4 = dipeptidyl peptidase 4GLP-1 = glucagon-like peptide 1GR^-/- = glucagon receptor knockoutGR-ASO = antisense oligonucleotides targeted against the glucagon receptorHbA1c = hemoglobin A1cHGP = hepatic glucose productionSGLT-2 = sodium-glucose cotrans-porter 2T1DM = type 1 diabetes mellitusT2DM = type 2 diabetes mellitus     

How Patients With Type 1 Diabetes Translate Continuous Glucose Monitoring Data into Diabetes Management Decisions

Objective: To understand how patients use continuous glucose monitoring (CGM) data in their diabetes management.Methods: We surveyed patients who regularly used CGM (>6 days per week), using 70 questions, many scenario-based. The survey had 6 sections: patient characteristics, general CGM use, hypoglycemia prevention and management, hyperglycemia prevention and management, insulin dosing adjustments (both for incidental hyperglycemia not at meals and at mealtimes), and real-time use versus retrospective analysis.Results: The survey was completed by 222 patients with type 1 diabetes. In response to a glucose of 220 mg/dL, the average correction dose adjustment based on rate of change arrows varied dramatically. Specifically, when the CGM device showed 2 arrows up (glucose increasing >3 mg/dL/minute), respondents stated they would increase their correction bolus, on average, by 140% (range, 0 to 600%). Conversely, 2 arrows down (glucose decreasing >3 mg/dL/minute) caused respondents to reduce their dose by 42%, with 24% omitting their dose entirely. Furthermore, 59% of respondents stated they would delay a meal in response to rapidly rising glucose, whereas 60% would wait until after a meal to bolus in response to falling glucose levels. With a glucose value of 120 mg/dL and a falling glucose trend, 70% of respondents would prophylactically consume carbohydrates to avoid hypoglycemia.Conclusion: CGM users utilize CGM data to alter multiple aspects of their diabetes care, including insulin dose timing, dose adjustments, and in hypoglycemia prevention. The insulin adjustments are much larger than common recommendations. Additional studies are needed to determine appropriate insulin adjustments based on glucose trend data.Abbreviations: A_1c = hemoglobin A_1c CGM = continuous glucose monitoring ROC = rate of change SMBG = self-monitored blood glucose     

Global diabetes landscape—type 2 diabetes mellitus in South Asia: Epidemiology,risk factors,and control

Background: Type 2 diabetes mellitus (DM) is a new epidemic in South Asia and is the result of societal influences and changing lifestyles. Epidemiologic studies suggest that the prevalence of DM has increased exponentially in urban and rural populations.Objective: This study was conducted to determine trends in the prevalence of DM in various countries in South Asia.Methods: We performed an extensive, systematic MEDLINE search for primary articles that reported on the epidemiology of DM in South Asia. Additional articles were obtained from personal collections and references cited in the primary articles. No formal meta-analysis was performed because of differing methodologies and diagnostic criteria.Results: Epidemiologic studies conducted in India during the 1960s and 1970s, using random and postload blood glucose estimations, reported DM in 1% to 4% of urban populations and 1% to 2% of rural populations. More standardized epidemiologic studies in adults since the late 1980s reported DM in 5% to 15% of urban populations, 4% to 6% of semiurban populations, and 2% to 5% of rural populations. A significantly increasing trend has been observed in urban populations (exponential trend R² = 0.74), whereas the increase is slower (R² = 0.29) in rural populations. The diabetes scenario is similar in other South Asian countries. Current prevalence rates are 5% to 16% in urban areas and 2% to 8% in rural areas. Risk factors for DM in this region are increasing sedentariness, dietary excess, obesity (especially high waist-to-hip ratio), low birth weight, and genetic influences.Conclusions: DM is a major public health problem in South Asia. The prevalence is higher in urban areas than in rural areas and is increasing. Population-based measures to control the epidemic of DM include avoidance of adiposity through enhanced physical activity and regulated calorie intake. A comprehensive national chronic care program is needed.     

Management of Diabetes During Air Travel: A Systematic Literature Review of Current Recommendations and their Supporting Evidence

Objective: Individuals with diabetes are increasingly seeking pretravel advice, but updated professional recommendations remain scant. We performed a systematic review on diabetes management during air travel to summarize current recommendations, assess supporting evidence, and identify areas of future research.Methods: A systematic review of the English literature on diabetes management during air travel was undertaken utilizing PubMed and MEDLINE. Publications regarding general travel advice; adjustment of insulin and noninsulin therapies; and the use of insulin pumps, glucometers and subcutaneous glucose sensors at altitude were included. Gathered information was used to create an updated summary of glucose-lowering medication adjustment during air travel.Results: Sixty-one publications were identified, most providing expert opinion and few offering primary data (47 expert opinion, 2 observational studies, 2 case reports, 10 device studies). General travel advice was uniform, with increasing attention to preflight security. Indications for oral antihyperglycemic therapy adjustments varied. There were few recommendations on contemporary agents and on nonhypoglycemic adverse events. There was little consensus on insulin adjustment protocols, many antedating current insulin formulations. Most publications advocated adjusting insulin pump time settings after arrival; however, there was disagreement on timing and rate adjustments. Glucometers and subcutaneous glucose sensors were reported to be less accurate at altitude, but not to an extent that would preclude their clinical use.Conclusion: Recommendations for diabetes management during air travel vary significantly and are mostly based on expert opinion. Data from systematic investigation on glucose-lowering medication adjustment protocols may support the development of a future consensus statement.Abbreviations:CSII = continuous subcutaneous insulin infusion (device)DPP-4 = dipeptidyl peptidase 4EGA = error grid analysisGDH = glucose dehydrogenaseGOX = glucose oxidaseGLP1 = glucagon-like peptide-1NPH = neutral protamine HagedornSGLT2 = sodium-glucose cotransporter-2     

Antepartum glucose tolerance test results as predictors of type 2 diabetes mellitus in women with a history of gestational diabetes mellitus: A systematic review

Background: Women with a history of gestational diabetes mellitus (GDM) are at high risk for type 2 diabetes mellitus (T2DM).Objective: We reviewed prospective studies of antepartum glucose tolerance test results as risk factors for development of T2DM among women with a history of GDM.Methods: We searched 4 electronic databases and hand-searched 13 journals for literature published through January 2007. The search strategy consisted of medical subject headings and text words for GDM, T2DM, and other relevant terms. Articles were excluded for the following reasons: (1) not written in English; (2) no human data; (3) no original data; (4) <90% of sample was diagnosed with GDM without a separate analysis for women with GDM; (5) case report or series; (6) diagnosis of GDM not based on 3-hour 100-g oral glucose tolerance test (OGTT) or 2-hour 75-g OGTT; (7) T2DM not evaluated as outcome; (8) no relative measure of association or incidence reported; or (9) design did not address antepartum OGTT as a predictor of T2DM. Two investigators independently reviewed citations, performed serial data abstraction on full articles, and assessed the quality of each article. Data were abstracted for study participants and characteristics, T2DM diagnosis, length of follow-up, regression model covariates, and measures of association and variability.Results: Of 11,400 unique citations, we identified 11 articles that evaluated antepartum glucose testing and risk of T2DM in women with a history of GDM. Five studies found that the fasting blood glucose (FBG) on the antepartum diagnostic OGTT was a significant predictor of T2DM (odds ratio [OR] range: 11.1–21.0; relative risk [RR] range: 1.37–1.5; relative hazard [RH] = 2.47). Risk of incident T2DM was predicted by the antepartum 2-hour OGTT plasma glucose in 3 studies (OR range: 1.02–1.03; RR = 1.3) and by the antepartum OGTT glucose AUC in 3 other studies (OR range: 3.64–15; RH = 2.13). Overall, study quality was limited by high losses to follow-up (>20% in 6 studies) and short duration. Few studies adjusted for adiposity, an established diabetes risk factor.Conclusion: FBG, OGTT 2-hour blood glucose, and OGTT glucose AUC appeared to be strong and consistent predictors of subsequent T2DM among women who met diagnostic criteria for GDM using the OGTT.     

Integrated Insulin Pump and Continuous Glucose Monitoring Technology in Diabetes Care Today: A Perspective of Real-Life Experience With the Minimed™ 670G Hybrid Closed-Loop System

Objective: Intensive glucose management with insulin pump and continuous glucose monitoring therapy in insulin-treated patients with diabetes poses many challenges in all aspects of daily life. Automated insulin delivery (AID) is the ultimate goal of insulin replacement therapy to reduce the burden of managing this condition. Many systems are being tested in the clinical research setting, and one hybrid closed-loop (HCL) system has received Food and Drug Administration (FDA) approval for use in type 1 diabetes patients above the age of 14 years.Methods: Literature review and clinical practice experience from the Diabetes and Technology Program at an academic medical center.Results: This review outlines recent advances in AID systems, focusing on the FDA-approved MiniMed™ 670G HCL system and the real-life experience 1-year post-release in an academic medical center with over 60 patients on this system. The unique challenges of adapting to this new system outside the clinical trial setting are highlighted, and a training protocol designed specifically for the onboarding of first-time users is described.Conclusion: HCL insulin therapy offers several advantages, at the same time posing unique challenges to the user. Systematic training of patients with diabetes transitioning to this system is essential for retention and success of use.Abbreviations: AID = automated insulin delivery; CGM = continuous glucose monitoring; FDA = Food and Drug Administration; HbA1c = glycated hemoglobin; HCL = hybrid closed-loop; ICR = insulin to carbohydrate ratio; SAP = sensor augmented pump; T1DM = type 1 diabetes     

Self Blood Glucose Monitoring Underestimates Hyperglycemia And Hypoglycemia As Compared To Continuous Glucose Monitoring In Type 1 And Type 2 Diabetes

Objective: When glucose records from self blood glucose monitoring (SBGM) do not reflect estimated average glucose from glycosylated hemoglobin (HgBA1) or when patients' clinical symptoms are not explained by their SBGM records, clinical management of diabetes becomes a challenge. Our objective was to determine the magnitude of differences in glucose values reported by SBGM versus those documented by continuous glucose monitoring (CGM).Methods: The CGM was conducted by a clinical diabetes educator (CDE)/registered nurse by the clinic protocol, using the Medtronic iPRO2™ system. Patients continued SBGM and managed their diabetes without any change. Data from 4 full days were obtained, and relevant clinical information was recorded. De-identified data sets were provided to the investigators.Results: Data from 61 patients, 27 with type 1 diabetes (T1DM) and 34 with T2DM were analyzed. The lowest, highest, and average glucose recorded by SBGM were compared to the corresponding values from CGM. The lowest glucose values reported by SBGM were approximately 25 mg/dL higher in both T1DM (P = .0232) and T2DM (P = .0003). The highest glucose values by SBGM were approximately 30 mg/dL lower in T1DM (P = .0005) and 55 mg/dL lower in T2DM (P<.0001). HgBA1c correlated with the highest and average glucose by SBGM and CGM. The lowest glucose values were seen most frequently during sleep and before breakfast; the highest were seen during the evening and postprandially.Conclusion: SBGM accurately estimates the average glucose but underestimates glucose excursions. CGM uncovers glucose patterns that common SBGM patterns cannot.Abbreviations: CDE = certified diabetes educator; CGM = continuous glucose monitoring; HgBA1c = glycosylated hemoglobin; MAD = mean absolute difference; SBGM = self blood glucose monitoring; T1DM = type 1 diabetes; T2DM = type 2 diabetes     

Real-World Implications of Hybrid Close Loop (Hcl) Insulin Delivery System

Objective: Clinical trial data demonstrates improved glycemic control with hybrid close loop (HCL) insulin delivery systems, yet limited real-world data exists. Data from the inaugural cohort of patients initiating a HCL system (Medtronic MiniMed™ 670G, Medtronic Canada, Brampton, ON) at a university medical center was used to examine real-world utilization and glycemic control following a standardized implementation process.Methods: Data from 34 adult patients with type 1 diabetes were obtained from pump downloads at 4 time points: (1) previous insulin pump, (2) HCL in manual-mode, (3) 2 weeks after HCL auto-mode transition, and (4) 6 to 12 weeks after initiation of HCL. In-person training by certified diabetes educators was performed across 3 sessions with phone and electronic messaging following auto-mode start.Results: Mean self-monitored blood glucose (SMBG) per day increased from 5.15 baseline to 6.49 at 6 to 12 weeks (P<.05) with 3.26 sensor calibrations per day. Time-in-auto-mode was 79.3% at 2 weeks and 72.3% at final follow-up, with 82% of patients spending >50% of time in auto-mode. There were 8.2 auto-mode exits over the final 14-day download. Time-in-target was 67.3% in manual-mode, 73.4% at 2 weeks (P = .09), and 71.7% by 6 to 12 weeks (P = .06). Hemoglobin A1c (HbA1c) decreased by 0.51% (P = .02), while total daily dose and % basal did not change. Patients with HbA1c <7.0% (53 mmol/mol) at baseline spent more time-in-target than those with HbA1c ≥7.0% (53 mmol/mol; 78.0% versus 67.5%) despite spending less time-in-auto-mode (66.5% versus 74.8%).Conclusion: These data illustrate real-world implementation of HCL technology using a structured education program within a major medical center. Overall benefit may vary based on baseline characteristics such as HbA1c.Abbreviations: CDE = certified diabetes educator; HbA1c = hemoglobin A1c; HCL = hybrid closed loop; SMBG = self-monitored blood glucose     

Managing Diabetes in the Heat: Potential Issues and Concerns

ObjectiveTo review issues surrounding manage- ment of diabetes mellitus during times of extreme high temperatures.MethodsMaterials used for this article were identi- fied through a search of MEDLINE publications from 1966 to 2009. We chose English-language articles by using terms that cross-referenced diabetes mellitus, hot tempera- ture, heat, desert, and insulin.ResultsPersons with diabetes may have greater sus- ceptibility to adverse effects from heat (ie, increased num- ber of emergency department visits and hospitalizations, increased occurrence of dehydration and electrolyte abnor- malities, and higher death rate) than persons without dia- betes. Alterations in glucose homeostasis may occur, and changes in insulin kinetics and stability are possible. The impact of heat exposure on equipment performance (eg, glucometers) must be considered.ConclusionsHaving diabetes places a person at risk for heat-related health problems. Physicians must be aware of possible complications that diabetic patients may encounter in summer heat to prevent problems. Patient educational materials should be developed relating to self- management skills in the heat, and the topic should be in- cluded in standard diabetes education programs when ap- plicable. (Endocr Pract. 2010;16:506-511)