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     

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     

“Make Everything as Simple as Possible,But Not Simpler”: A Simple Approach is as Good as a Complex Algorithm for Insulin Dose Self-Adjustment

Abbreviations:A1c = glycated hemoglobin A1cDM2 = type 2 diabetes mellitusRCT = randomized controlled trialSMBG = self-monitoring blood glucose     

Associations Between Vitamin D and Microvascular Complications in Middle-Aged And Elderly Diabetic Patients

Objective: The objective of this cross-sectional study was to investigate the association of serum 25-hydroxyvitamin D (25&lsqb;OH]D) levels with estimated glomerular filtration rate (eGFR), albumin/creatinine ratio (ACR), and the prevalence of diabetic retinopathy (DR) in Chinese diabetic adults.Methods: A total of 4,767 diabetic participants were enrolled from seven communities in Shanghai, China, in 2018. Participants underwent several examinations, which included the measurement of anthropometric parameters, blood pressure, glucose, lipid profiles, 25(OH)D, and ACR. DR was detected based on high-quality fundus photographs and remotely read by ophthalmologists.Results: Compared with the first 25(OH)D quartile, participants in the fourth quartile had a lower prevalence of high ACR (odds ratio &lsqb;OR], 0.77; 95% confidence interval &lsqb;CI], 0.61 to 0.96) (P for trend <.01). No association was found between 25(OH)D levels and eGFR. For DR, the OR (95% CI) for DR ranging from 0 to 4 in ordinal logistic regression associated with 25(OH)D was 0.62 (0.47 to 0.82) for the fourth 25(OH)D quartile (P for trend <.01) compared with the first quartile. These associations were all fully adjusted for confounding factors.Conclusion: Lower serum 25(OH)D concentration is significantly associated with increased ACR and higher prevalence of DR in middle-aged and elderly diabetic adults. However, the possibility of a causal relationship between 25(OH)D deficiency and diabetic microvascular complications remains to be demonstrated.Abbreviations: 25(OH)D = 25-hydroxyvitamin D; ACR = albumin/creatinine ratio; BMI = body mass index; CI = confidence interval; DKD = diabetic kidney disease; DR = diabetic retinopathy; eGFR = estimated glomerular filtration rate; HbA1c = glycated hemoglobin; HDL = high-density lipoprotein; LDL = low-density lipoprotein; OR = odds ratio; T2DM = type 2 diabetes mellitus     

Total Body Adiposity,Triglycerides, and Leg Fat are Independent Risk Factors for Diabetic Peripheral Neuropathy in Chinese Patients with type 2 Diabetes Mellitus

Objective: To evaluate the risk factors associated with diabetic peripheral neuropathy (DPN) in Chinese patients with type 2 diabetes mellitus (T2DM).Methods: Between January 2014 and December 2017, 107 participants who had obesity with T2DM and 349 participants who had normal weight with T2DM, matched for age, sex, and duration of diabetes, were recruited. The clinical and biochemical parameters were measured in each patient. DPN was diagnosed based on neuropathy symptom score and neuropathy deficit score. Motor and sensory nerve conduction velocities were measured by electromyography. Body fat mass was estimated by dual-energy X-ray absorptiometry, while hepatic steatosis was evaluated by ultrasonography.Results: The group with obesity had a significant higher prevalence of DPN (66.62%) than that (46.99%) of the group with normal weight. Compared to the patients with normal weight, the sural sensory nerve in the right lower limbs of the patients with obesity was more susceptible to damage. Hypertriglyceridemia in the patients with obesity was a significant independent risk factor for DPN (odds ratio &lsqb;OR], 3.90 &lsqb;95% confidence interval (CI), 1.01 to 15.02]; P = .04), while the duration of diabetes (OR, 1.33 &lsqb;95% CI, 1.07 to 1.65]; P<.01) and leg subcutaneous fat mass (OR, 0.72 &lsqb;95% CI, 0.57 to 0.90]; P<.01) in the patients with normal weight were independent risk factors for DPN. The presence of obesity alone in patients with T2DM could predict high DPN risk (OR, 3.09 &lsqb;95% CI, 1.11 to 8.65]; P = .04).Conclusion: Reducing total body adiposity and triglyceride levels, as well as avoiding leg subcutaneous fat atrophy, could be new prevention strategies for DPN in Chinese patients with T2DM.Abbreviations: ALB = albumin; ALT = alanine transaminase; AST = aspartate transaminase; AUC = area under the curve; AUCc-p/AUCglu = AUC of C-peptide/AUC of glucose; BMI = body mass index; BP = blood pressure; CI = confidence interval; Cr = creatinine; DBP = diastolic blood pressure; DPN = diabetic peripheral neuropathy; FC-P = fasting C-peptide; FPG = fasting plasma glucose; FFA = free fatty acid; γ-GGT = γ-glutamyl transferase; HbA1c = glycated hemoglobin A1c; HDL-C = high-density-lipoprotein cholesterol; ISI = insulin sensitivity index; ISSI-2 = insulin secretion-sensitivity index-2; LDL-C = low-density-lipoprotein cholesterol; MNCS = motor nerve conduction velocity; OGTT = oral glucose tolerance test; PG = plasma glucose; SAT = subcutaneous adipose tissue; SBP = systolic blood pressure; SNCS = sensory nerve conduction velocity; T2DM = type 2 diabetes mellitus; TC = total cholesterol; TG = triglyceride; UA = uric acid; VAT = visceral adipose tissue; WC = waist circumference     

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     

Impaired Awareness of Hypoglycemia Continues to be a Risk Factor for Severe Hypoglycemia Despite the Use of Continuous Glucose Monitoring System in Type 1 Diabetes

Objective: Impaired awareness of hypoglycemia (IAH) is a risk factor for severe hypoglycemia in patients with type 1 diabetes (T1D) not using a continuous glucose monitoring (CGM) system. The current study investigated the prevalence of IAH and its relationship with severe hypoglycemia in T1D patients using CGM systems.Methods: This cross-sectional observational study enrolled 135 patients with T1D and ongoing real-time CGM use. A survey was conducted to assess hypoglycemia awareness with the Gold, Clarke, and Pedersen-Bjergaard questionnaires and the 6-month history of severe hypoglycemia. Other diabetes histories and the CGM glucose data were collected.Results: The Gold, Clarke, and Pedersen-Bjergaard questionnaires demonstrated the overall prevalence of IAH/abnormal awareness to be 33.3%, 43.7%, and 77.0%, respectively. Participant age and duration of T1D were consistently related to IAH or hypoglycemia unawareness with all three questionnaires (P<.05). Amongst the patients using CGM for >6 months, 24.5% were found to have at least one episode of severe hypoglycemia in the preceding 6 months. IAH identified by the Gold and Clarke questionnaires and hypoglycemia unawareness identified by the Pedersen-Bjergaard questionnaire were related to 6-, 4.63-, and 5.83-fold increased risk of severe hypoglycemia (P = .001, .004, and .013), respectively. IAH identified by the Gold/Clarke questionnaires was associated with a longer duration of CGM glucose <54 mg/dL and higher glucose coefficients of variation (P<.05).Conclusion: IAH is highly prevalent and related to a higher risk for severe hypoglycemia in T1D patients using CGM.Abbreviations: CGM = continuous glucose monitoring; CI = confidence interval; HAAF = hypoglycemia-associated autonomic failure; HbA1c = hemoglobin A1C; IAH = impaired awareness of hypoglycemia; T1D = type 1 diabetes     

Glycemic Effects Of Sglt-2 Inhibitor Canagliflozin In Type 1 Diabetes Patients Using The Dexcom G4 Platinum Cgm

Objective: Limited information is available on chronic use of sodium glucose cotransporter 2 inhibitors in type 1 diabetes (T1D). We conducted a retrospective review of T1D patients on Dexcom G4Platinum continuous glucose monitors (DCGMs) >1 year (mean, 4.6 years) who were prescribed canagliflozin (CANA) 100 mg daily and had a baseline DCGM 30-day download prior to and a second download after at least 1 month (mean, 3.7 months) taking CANA 100 mg daily. The glycemic, weight, and systolic blood pressure (SBP) effects are reported.Methods: We identified 27 patients meeting the selection criteria: 14 men; 25 white; 22 on pump; average T1D duration, 34 years (range, 12 to 48 years); average hemoglobin A1C (A1C), 7.6% (range, 6.1 to 9.8%); 22 with baseline A1C 7.0% or higher. All patients had an estimated glomerular filtration rate (eGFR) at baseline of 60 mL/min/1.73 m² or higher and were normotensive or on stable therapy. On average, 29 days of CGM data was reviewed. Total daily insulin dose (TDD) was available in 21 patients. We identified 27 patients who were judged to be candidates for CANA but did not have any change in glycemic therapy other than insulin adjustment as controls.Results: CANA resulted in significant reductions in mean blood glucose, CGM standard deviation, time in hyperglycemia, A1C, weight, SBP, and TDD, with increased time in target, with minimal increase in hypoglycemia and no significant change in eGFR. Three females developed genital mycotic infections but continued therapy, 2 developed ketoacidosis from insulin interruption.Conclusion: CANA offers promise as adjunct therapy in T1D, though caution is advised.Abbreviations:A1C = hemoglobin A1CCANA = canagliflozinCGM = continuous glucose monitorCSII = continuous subcutaneous insulin infusionDCGM = Dexcom G4Platinum CGMDKA = diabetic ketoacidosisGMI = genital mycotic infectionMG = mean glucosePCGM = personal continuous glucose monitoringSBP = systolic blood pressureSGLT-2i = sodium-glucose cotransporter 2 inhibitorSH = severe hypoglycemiaT2D = type 2 diabetesT1D = type 1 diabetes     

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     

Efficacy and Safety of Ideglira in Older Patients with Type 2 Diabetes

Objective: The efficacy and safety of insulin degludec/liraglutide (IDegLira) in older patients has not yet been reported. This analysis aimed to evaluate the efficacy and safety of IDegLira in patients aged ≥65 years.Methods: A post hoc analysis compared results of patients aged ≥65 versus <65 years from DUAL II, III, and V. These were 26-week, phase 3, randomized, twoarm parallel, treat-to-target trials in patients already taking injectable glucose-lowering agents. We evaluated 311 patients aged <65 and 87 patients aged ≥65 years from DUAL II, 326 patients <65 years and 112 patients ≥65 years from DUAL III, and 412 patients <65 years and 145 patients ≥65 years from DUAL V. Patients were randomized to IDegLira or insulin degludec (DUAL II), IDegLira or unchanged glucagon-like peptide 1–receptor agonist (GLP-1RA) (DUAL III), or IDegLira or IGlar U100 (DUAL V).Results: In patients ≥65 years, hemoglobin A1C decreased to a greater extent with IDegLira than with comparators (estimated treatment differences, -1.0% &lsqb;-1.5; -0.6]_{95% confidence interval &lsqb;CI]}, -0.8% &lsqb;-1.0; -0.5]_{95% CI}, and -0.9% &lsqb;-1.3; -0.6]95%CI) for DUAL II, V, and III, respectively; all P<.001). These mirrored results of patients <65 years of age. Hypoglycemia rates were lower with IDegLira versus basal insulin and higher versus unchanged GLP-1RA (estimated rate ratios, 0.5 &lsqb;0.2; 1.6]_{95% CI} &lsqb;P = .242]; 0.3 &lsqb;0.1; 0.5]_{95% CI} &lsqb;P<.001], and 11.8 &lsqb;3.3; 42.8]_{95% CI} &lsqb;P<.001] for DUAL II, V, and III, respectively).Conclusion: Patients aged ≥65 years on basal insulin or GLP-1RA can improve glycemic control with IDegLira, and it is well tolerated overall.Abbreviations: A1C = hemoglobin A1C; AE = adverse event; CI = confidence interval; Degludec = insulin degludec; EOT = end of trial; ETD = estimated treatment difference; FPG = fasting plasma glucose; GLP-1RA = glucagon-like peptide 1 receptor agonist; IDegLira = insulin degludec/liraglutide; IGlar U100 = insulin glargine 100 U/mL; SU = sulfonylurea; T2D = type 2 diabetes     

Gestational Weight Gain as an Independent Risk Factor for Macrosomia in Women with Intermediate State Gestational Blood Glucose

Objective: Macrosomia is closely associated with gestational diabetes mellitus (GDM) but its relationship with maternal intermediate state gestational blood glucose (ISGBG; normal fasting blood glucose and 7.8 mmol/L <1 hour blood glucose &lsqb;BG] <10 mmol/L or 6.7 mmol/L <2 hour BG <8.5 mmol/L) is unclear. Here, we analyzed the clinical characteristics and pregnancy outcomes and explored risk factors for macrosomia in women with ISGBG.Methods: A total of 847 women with normal glucose tolerance gestation, 330 with ISGBG, and 99 with GDM were included. Maternal and fetal clinical data were collected and 3-point BG following oral glucose tolerance test, fasting insulin, glycated hemoglobin, and blood lipids profile were measured.Results: The incidence rate of macrosomia among the neonates of women with ISGBG was as high as 10.9%. In the ISGBG group, prepregnancy body mass index (BMI), gestational weight gain (GWG) and the proportion of women with excessive GWG (eGWG) were significantly higher in women with macrosomia compared with those who delivered a normal weight neonate. In women with ISGBG, neonate weight was positively correlated with maternal prepregnancy weight (r = 0.183, P<.01), prepregnancy BMI (r = 0.135, P<.01), and GWG (r = 0.255, P<.01), and negatively correlated with high-density lipoprotein cholesterol (r = -0.172, P<.01). Nonetheless, only eGWG was an independent risk factor (odds ratio = 3.18, 95% confidence interval = 1.26 to 7.88, P<.05) for macrosomia. The risk of macrosomia in pregnant women with prepregnancy BMI <25 kg/m² or BMI ≥25 kg/m² and eGWG was 3.39 and 3.27 times, respectively.Conclusion: The incidence rate of macrosomia is increased in women with ISGBG and eGWG is the strongest independent risk factor. In order to reduce the risk for macrosomia, timely lifestyle intervention to promote appropriate weight gain during pregnancy deserves evaluation.Abbreviations: AUC = area under the curve; BG = blood glucose; 1 hour BG = 1 hour blood glucose after OGTT; 2 hour BG = 2 hour blood glucose after OGTT; BMI = body mass index; CI = confidence interval; eGWG = excessive gestational weight gain; FBG = fasting blood glucose; FINS = fasting insulin; GDM = gestational diabetes mellitus; HbA1c = glycated hemoglobin; HDL-C = high-density lipoprotein cholesterol; HOMA-IR = homeostasis model assessment of insulin resistance index; ISGBG = intermediate state gestation blood glucose; LDL-C = low-density lipoprotein cholesterol; Ln = natural logarithm; MLBW = mature low birth weight; NGTG = normal glucose tolerance gestation; OGTT = oral glucose tolerance test; OR = odds ratio; SD = standard deviation     

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     

Ideglira is Associated With Improved Short-Term Clinical Outcomes and Cost Savings Compared With Insulin Glargine U100 Plus Insulin Aspart in the U.S.

Objective: In the DUAL (Dual Action of Liraglutide and Insulin Degludec in Type 2 Diabetes) VII trial, IDegLira (a combination of insulin degludec and liraglutide) was compared with insulin glargine U100 plus insulin aspart. Both treatment approaches achieved similar glycemic control, but there were differences in hypoglycemia, changes in body weight, and injection frequency. The aim of the present analysis was to assess the short-term cost effectiveness of IDegLira versus insulin glargine U100 plus insulin aspart for treatment of patients with type 2 diabetes mellitus not meeting glycemic targets on basal insulin in the U.S. setting.Methods: A cost-utility model was developed to evaluate the clinical and economic outcomes associated with the 2 treatments over a 1-year time horizon, capturing the impact on quality of life of hypoglycemic events, body mass index, and injection frequency. Costs were captured from a healthcare payer perspective in 2017 U.S. dollars ($).Results: IDegLira was associated with improved quality of life by 0.12 quality-adjusted life years compared with insulin glargine U100 plus insulin aspart. The key drivers of this difference were reduced injection frequency and hypoglycemic events avoided. IDegLira was associated with increased annual drug costs, but this was entirely offset by reduced needle costs and reduced costs of self-monitoring of blood glucose testing. IDegLira was associated with total annual cost savings of $743 per patient.Conclusion: IDegLira was found to improve quality-adjusted life expectancy and reduce costs when compared with insulin glargine U100 plus insulin aspart for treatment of patients with type 2 diabetes not achieving glycemic control on basal insulin in the U.S. setting.Abbreviations: ADA = American Diabetes Association; BMI = body mass index; CI = confidence interval; DUAL = Dual Action of Liraglutide and Insulin Degludec in Type 2 Diabetes; GLP-1 = glucagon-like peptide-1; HbA1c = glycated hemoglobin; ICER = incremental cost-effectiveness ratio; IU = international units; QALY = quality-adjusted life year; SMBG = self-monitoring of blood glucose     

Hba1C Control And Cost-Effectiveness in Patients With Type 2 Diabetes Mellitus Initiated On Canagliflozin or A Glucagon-Like Peptide 1 Receptor Agonist in A Real-World Setting

Objective: To compare glycated hemoglobin (HbA1c) control and medication costs between patients with type 2 diabetes mellitus (T2DM) treated with canagliflozin 300 mg (CANA) or a glucagon-like peptide 1 receptor agonist (GLP-1 RA) in a real-world setting.Methods: Adults with T2DM newly initiated on CANA or a GLP-1 RA (index date) were identified from IQVIA™ Real-World Data Electronic Medical Records U.S. database (March 29, 2012–April 30, 2016). Inverse probability of treatment weighting accounted for differences in baseline characteristics. HbA1c levels at 3-month intervals were compared using generalized estimating equations. Medication costs used wholesale acquisition costs.Results: For both cohorts (CANA: n = 11,435; GLP-1 RA: n = 11,582), HbA1c levels decreased at 3 months postindex and remained lower through 30 months. Absolute changes in mean HbA1c from index to 3 months postindex for CANA and GLP-1 RA were -1.16% and -1.21% (patients with baseline HbA1c ≥7% &lsqb;53 mmol/mol]); -1.54% and -1.51% (patients with baseline HbA1c ≥8% &lsqb;64 mmol/mol]); and -2.13% and -1.99% (patients with baseline HbA1c ≥9% &lsqb;75 mmol/mol]), respectively. Postindex, CANA patients with baseline HbA1c ≥7% had similar HbA1c levels at each interval versus GLP-1 RA patients, except 9 months (mean HbA1c, 7.75% &lsqb;61 mmol/mol] vs. 7.86% &lsqb;62 mmol/mol]; P = .0305). CANA patients with baseline HbA1c ≥8% and ≥9% had consistently lower HbA1c numerically versus GLP-1 RA patients and statistically lower HbA1c at 9 (baseline HbA1c ≥8% or ≥9%), 27, and 30 months (baseline HbA1c ≥9%). Continuous 12-month medication cost $3,326 less for CANA versus GLP-1 RA.Conclusion: This retrospective study demonstrated a similar evolution of HbA1c levels among CANA and GLP-1 RA patients in a real-world setting. Lower medication costs suggest CANA is economically dominant over GLP-1 RA (similar effectiveness, lower cost).Abbreviations:AHA = antihyperglycemic agentBMI = body mass indexCANA = canagliflozin 300 mgDCSI = diabetes complications severity indexeGFR = estimated glomerular filtration rateEMR = electronic medical recordGLP-1 RA = glucagon-like peptide 1 receptor agonistHbA1c = glycated hemoglobinICD-9-CM = International Classification of Diseases–Ninth Revision–Clinical ModificationICD-10-CM = International Classification of Diseases–Tenth Revision–Clinical ModificationIPTW = inverse probability of treatment weightingITT = intent-to-treatMPR = medication possession ratioPDC = proportion of days coveredPS = propensity scorePSM = propensity score matchingQuan-CCI = Quan-Charlson comorbidity indexSGLT2 = sodium-glucose cotransporter 2T2DM = type 2 diabetes mellitusWAC = wholesale acquisition cost     

1,5-Anhydroglucitol and Neonatal Complications in Pregnancy Complicated by Diabetes

Objective: To determine the association of 1,5-anhydroglucitol (1,5-AG) with neonatal birth weight (NBW) and neonatal hypoglycemia (+NH) in pregnancies complicated by diabetes.Methods: We assessed a retrospective cohort of 102 females, 17 with gestational diabetes (GDM), 48 with type 1 diabetes mellitus (T1DM), and 37 with type 2 diabetes mellitus (T2DM). 1,5-AG and glycated hemoglobin A1C (A1C) values throughout pregnancy were extracted. Linear regression was used to assess their association with NBWs z-scores adjusting for maternal age, ethnicity and body mass index (BMI). +NH was defined by a note in the infant record, glucose <1.7 mmol/L in the first 24 h, or <2.5 mmol/L in the first 48 h after birth. A t test or Welch's approximate t test was used to compare the mean 1,5-AG and A1C of mothers with +NH versus those without (-NH), adjusted for gestational age and analyzed by diabetes type and across trimesters.Results: Mean 1,5-AG significantly differed across groups: T1DM 3.77 ± 2.82 μg/mL, T2DM 5.73 ± 4.38 μg/mL, GDM 8.89 ± 4.39 μg/mL (P<.0001), suggesting less glucose exposure in GDM relative to T1DM or T2DM. A negative linear association was found between mean 1,5-AG and z-scores (R= -0.28, P = .005. In contrast, the association between mean A1C and z-scores was weaker (R = 0.15, P = .14). The mean 1,5-AG tended to be lower in the +NH cohort versus -NH (P = .08), and this was statistically significant (P = .01) among subjects with GDM.Conclusion: The association of 1,5-AG with complications related to glycemic exposure supports the notion of its utility as an adjunct glycemic biomarker in pregnancies complicated by diabetes and across trimesters.Abbreviations: 1,5-AG = 1,5-anhydroglucitol A1C = glycated hemoglobin A1C BMI = body mass index CGM = continuous glucose monitoring GDM = gestational diabetes mellitus LGA = large for gestational age MICC = maternal and infant care unit NBW = neonatal birth weight NH = neonatal hypoglycemia PPH = postprandial hyperglycemia SMBG = self-monitoring of blood glucose T1DM = type 1 diabetes mellitus T2DM = type 2 diabetes mellitus     

The Association of Decreased Serum Gdnf Level with Hyperglycemia and Depression in Type 2 Diabetes Mellitus

Objective: Comorbidity of diabetes and depression is a critical problem. Decreased glial-derived neurotrophic factor (GDNF) has been demonstrated in depression, but no evidence of a relationship between GDNF and diabetes has been shown. The present studies were designed to investigate the relationship between GDNF and metabolism.Methods: In Study 1, we performed a case-control study in which subjects with type 2 diabetes mellitus (T2DM), prediabetes (p-DM), and normal glucose tolerance (NGT) were included. In Study 2, we performed a cross-sectional study in 296 patients having pre-existing diabetes in whom the levels of serum GDNF, blood glucose, blood lipids, blood pressure, body mass index, scores from the Patient Health Questionnaire (PHQ-9), the EuroQol-5 scale, and the diabetes distress scale were measured, as well as single-nucleotide polymorphisms of GDNF including rs884344, rs3812047, and rs2075680.Results: In Study 1, serum GDNF concentration was significantly lower in the T2DM group than in the NGT group (NGT: 11.706 ± 3.918 pg/mL; p-DM: 10.736 ± 3.722 pg/mL; type 2 diabetes mellitus &lsqb;T2DM group]: 9.884 ± 2.804 pg/mL, P = .008). In Study 2, significantly decreased serum GDNF levels were observed in subjects with poor glycemic control or depression (glycated hemoglobin &lsqb;HbA1c] <7.0% without depression: 11.524 ± 2.903 pg/mL; HbA1c ≥7.0% without depression: 10.625 ± 2.577 pg/mL; HbA1c <7.0% with depression: 10.355 ± 2.432 pg/mL; HbA1c ≥7.0% with depression: 8.824 ± 2.102 pg/mL, P = .008). Double-factor variance analysis showed that glycemic control and depression were independent factors for the GDNF level. Moreover, the serum GDNF level was significantly inversely associated with the fasting plasma glucose, 2 hours postprandial plasma glucose, HbA1c, and PHQ-9 score.Conclusion: Glycemic dysregulation was an independent factor for the GDNF level. These findings suggest that GDNF level might be involved in the pathophysiology of T2DM and depression through various pathways.Abbreviations: BP = blood pressure; CHO = cholesterol; DDS = diabetes distress scale; DM = diabetes mellitus; EQ-5D = the health-related dimensions of the EuroQol-5 scale; FPG = fasting plasma glucose; GDNF = glial-derived neurotrophic factor; HbA1c = glycated hemoglobin; HDL = high-density lipoprotein; LDL = low-density lipoprotein; NGT = normal glucose tolerance; PHQ-9 = Patient Health Questionnaire; p-DM = prediabetes; PPG = postprandial plasma glucose; SNP = single-nucleotide polymorphism; T2DM = type 2 diabetes mellitus; TG = triglyceride     

Intermittent Intensive Insulin Therapy for Type 2 Diabetes: Effects on Hypoglycemia,Weight Gain,and Quality of Life Over 2 Years

Objective: In early type 2 diabetes (T2DM), the administration of short-term intensive insulin therapy (IIT) can induce glycemic remission for a year thereafter, but this effect ultimately wanes. In this context, intermittently repeating short-term IIT could provide a strategy for maintaining the otherwise transient benefits of this intervention. However, the viability of this strategy would be contingent upon not inducing undesirable effects of insulin therapy such as excessive hypoglycemia and fat deposition. We thus sought to evaluate the effect of administering short-term IIT every 3 months on hypoglycemia, weight gain, and quality of life in early T2DM.Methods: In this 2-year pilot trial, 24 adults with T2DM of 2.0 ± 1.7 years duration and hemoglobin A1c of 6.4 (46 mmol/mol) ± 0.1% were randomized to 3 weeks of IIT (glargine, lispro) followed by either (1), repeat IIT for up to 2 weeks every 3 months or (2), daily metformin. IIT was titrated to target near-normoglycemia (premeal glucose 4 to 6 mmol/L; 2-hour postmeal <8 mmol/L). Participants were assessed every 3 months, with quality of life (QOL) evaluated annually.Results: The rate of hypoglycemia (<3.5 mmol/L) was low in the metformin and intermittent IIT arms (0.37 versus 0.95 events per patient-year; P = .28). There were no differences between the groups in changes over time in overall, central, or hepatic fat deposition (as reflected by weight &lsqb;P = .10], waist-to-hip ratio &lsqb;P = .58], and alanine aminotransferase &lsqb;P = .64], respectively). Moreover, there were no differences between the groups in QOL at 1- and 2-years.Conclusion: Intermittent short-term IIT may be safely administered in early T2DM without excessive adverse impact on hypoglycemic risk, anthropometry, or QOL.Abbreviations: ALT = alanine aminotransferase; HbA1c = hemoglobin A1c; IIT = intensive insulin therapy; ISSI-2 = insulin secretion-sensitivity index-2; OGTT = oral glucose tolerance test; QOL = quality of life; SF-36 = medical outcomes study 36-item short-form health survey; T2DM = type 2 diabetes     

Cheiroarthropathy: A Common Disorder in Patients in the T1D Exchange

Objective: Diabetic cheiroarthropathy is a long-term complication of diabetes that causes significant morbidity and can impair functional abilities. It has not been well studied in individuals with type 1 diabetes (T1D). The T1D Exchange registry provided an opportunity to assess the frequency of cheiroarthropathy and related characteristics.Methods: An internet-based survey was sent to 6,199 registry participants ≥18 years old, with 1,911 (31%) responding (62% female, 90% non-Hispanic White, mean age 40 years, median diabetes duration 20 years, mean glycated hemoglobin &lsqb;HbA1c] 7.7% &lsqb;61 mmol/mol]).Results: A total of 586 (31%) adults reported a diagnosis of ≥1 upper extremity disorder: 293 (15%) reported frozen shoulder, 293 (15%) trigger finger, 261 (14%) carpal tunnel, and 92 (5%) Dupuytren contracture, with 281 (15%) reporting ≥2 disorders. Those with upper extremity joint disorders were more likely older (P<.001) and had longer duration of diabetes (P<.001) than those without. HbA1c levels at the time of survey completion were 7.6% in participants with cheiroarthropathy versus 7.8% (62 mmol/mol) in participants without cheiroarthropathy.Conclusion: Cheiroarthropathy is common in adults with T1D. Additional research is needed to understand the pathogenesis and risk factors for this disorder. Standards of care for early recognition and treatment of diabetic cheiroarthropathy are also needed, particularly for adults with long-term diabetes. Improved awareness of cheiroarthropathy signs and symptoms of is needed so that patients can be identified and seek treatment before the condition causes disability.Abbreviations: BMI = body mass index; CGM = continuous glucose monitor; DCCT/EDIC = Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications; HbA1C = glycated hemoglobin; T1D = type 1 diabetes; T2D = type 2 diabetes     

Lack of Correlation Between 1,5-Anhydroglucitol Assay and Oral Glucose Tolerance Test in Patients with Cystic Fibrosis

ObjectiveTo determine whether the 1,5-anhydroglucitol (1,5-AG) assay, which reflects serum glucose levels during the preceding 2 weeks, could be used as an alternative to the current standard screening test for cystic fibrosis-related diabetes (CFRD)—the oral glucose tolerance test (OGTT).MethodsSerum 1,5-AG, hemoglobin A1c (A1C), fructosamine, and glucose at various time intervals during the OGTT were measured in 10 patients, 19 to 36 years old, with cystic fibrosis. Correlation coefficients were calculated to compare 1,5-AG with A1C, fructosamine, and serum glucose levels during the OGTT, and the mean 1,5- AG, A1C, and fructosamine for normal glucose tolerance, impaired glucose tolerance (IGT), and CFRD were compared statistically.ResultsOn the basis of the 120-minute OGTT, 1 of the 10 study subjects had CFRD and 4 had IGT. The mean 1,5-AG for patients with normal glucose tolerance was not significantly different from that for patients with IGT (P = .063). The 1,5-AG value was not significantly correlated with serum glucose during the OGTT, A1C, or fructosamine.ConclusionIn this pilot study, we found no significant correlation between 1,5-AG and glucose values during the OGTT or between 1,5-AG and other glycemic markers.Hence, the utility of the 1,5-AG assay for screening for CFRD in the population of patients with cystic fibrosis may be limited. (Endocr Pract. 2010;16:167-170)