Importance of beta cell mass for glycaemic control in people with type 1 diabetes.

AIMS/HYPOTHESIS: The role of beta cell mass in the balance of glucose control and hypoglycaemic burden in people with type 1 diabetes is unclear. We applied positron emission tomography (PET) imaging with radiolabelled exendin to compare beta cell mass among people with type 1 diabetes and either low glucose variability (LGV) or high glucose variability (HGV). METHODS: All participants with either LGV (n=9) or HGV (n=7) underwent a mixed-meal tolerance test to determine beta cell function and wore a blinded continuous glucose monitor for a week. After an i.v. injection with [68Ga]Ga-NODAGA-exendin-4, PET images were acquired for the quantification of pancreatic uptake of radiolabelled exendin. The mean standardised uptake value (SUVmean) of the pancreas was used to determine the amount of beta cell mass. RESULTS: Participants with LGV had lower HbA1c (46.0 mmol/mol [44.5-52.5] [6.4% (6.3-7)] vs 80 mmol/mol [69.0-110] [9.5% (8.5-12.2)], p=0.001) and higher time in range (TIR) (75.6% [73.5-90.3] vs 38.7% [25.1-48.5], p=0.002) than those with HGV. The SUVmean of the pancreas was higher for the LGV than for the HGV group (5.1 [3.6-5.6] vs 2.9 [2.1-3.4], p=0.008). The AUCC-peptide:AUCglucose ratio was numerically, but not statistically, higher in the LGV compared with the HGV group (2.7×10-2 [6.2×10-4-5.3×10-2] vs 9.3×10-4 [4.7×10-4-5.2×10-3], p=0.21). SUVmean correlated with the AUCC-peptide:AUCglucose ratio (Pearson r=0.64, p=0.01), as well as with the TIR (r=0.64, p=0.01) and the SD of interstitial glucose levels (r=-0.66, p=0.007). CONCLUSION/INTERPRETATION: Our data show higher beta cell mass in people with type 1 diabetes and LGV than in those with HGV, independent of beta cell function.

Effect of short-term use of dapagliflozin on impaired awareness of hypoglycaemia in people with type 1 diabetes.

AIM: Impaired awareness of hypoglycaemia (IAH) affects about 25% of patients with type 1 diabetes (T1DM). IAH can be reversed by strict avoidance of hypoglycaemia for at least 3 weeks. Adjunctive treatment with sodium glucose cotransporter 2 inhibitors may reduce the risk of hypoglycaemia through reduction of glucose variability. We tested the hypothesis that short-term use of dapagliflozin may improve awareness of hypoglycaemia in people with T1DM and IAH. MATERIALS AND METHODS: Fifteen patients with T1DM and IAH were included in this randomized double-blind, placebo-controlled cross-over trial (age 49.7 ± 14.6 years, 40% men, disease duration 24.1 ± 14.2 years, glycated haemoglobin 7.5 ± 0.8% (58.6 ± 8.4 mmol/mol). They were treated with dapagliflozin 10 mg once daily or matching placebo, with a washout period of 2 weeks. At the end of each treatment period, participants underwent a modified hyperinsulinaemic normoglycaemic-hypoglycaemic glucose clamp (glucose nadir 2.5 mmol/L). Blinded continuous glucose monitors were used in the final treatment weeks. RESULTS: Treatment with dapagliflozin significantly improved glycated haemoglobin [-0.32 ± 0.10 vs. 0.22 ± 0.13% (-4.1 ± 0.9 vs. 2.3 ± 1.4 mmol/mol), dapagliflozin vs. placebo, p = .007] and glucose variability (standard deviation, 2.6 ± 0.2 vs. 3.1 ± 0.3 mmol/L, p = .029), but did not affect the frequency of hypoglycaemia. During the hypoglycaemic clamp, dapagliflozin did not affect symptom responses (8.0 ± 3.4 vs. 5.2 ± 1.6, p = .31), but significantly reduced the need for exogenous glucose to maintain hypoglycaemia (3.2 ± 0.3 vs. 4.1 ± 0.4 mg/kg/min, p = .022). CONCLUSIONS: Eight weeks of treatment with dapagliflozin did not restore hypoglycaemic awareness in people with T1DM and impaired awareness of hypoglycaemia, but ameliorated some clinical aspects.

Effect of lactate administration on cerebral blood flow during hypoglycemia in people with type 1 diabetes.

INTRODUCTION: Impaired awareness of hypoglycemia, clinically reflected by the inability to timely detect hypoglycemia, affects approximately 25% of the people with type 1 diabetes. Both altered brain lactate handling and increased cerebral blood flow (CBF) during hypoglycemia appear to be involved in the pathogenesis of impaired awareness of hypoglycemia. Here we examine the effect of lactate on CBF during hypoglycemia. RESEARCH DESIGN AND METHODS: Nine people with type 1 diabetes and normal awareness of hypoglycemia underwent two hyperinsulinemic euglycemic-hypoglycemic (3.0 mmol/L) glucose clamps in a 3T MR system, once with sodium lactate infusion and once with sodium chloride infusion. Global and regional changes in CBF were determined using pseudocontinuous arterial spin labeling. RESULTS: Lactate (3.3±0.6 vs 0.9±0.2 mmol/L during lactate infusion vs placebo infusion, respectively) suppressed the counter-regulatory hormone responses to hypoglycemia. Global CBF increased considerably in response to intravenous lactate infusion but did not further increase during hypoglycemia. Lactate also blunted the hypoglycemia-induced regional redistribution of CBF towards the thalamus. CONCLUSIONS: Elevated lactate levels enhance global CBF and blunt the thalamic CBF response during hypoglycemia in patients with type 1 diabetes, mimicking observations of impaired awareness of hypoglycemia. These findings suggest that alteration of CBF associated with lactate may play a role in some aspects of the development of impaired awareness of hypoglycemia. TRIAL REGISTRATION NUMBER: NCT03730909.

High prevalence of impaired awareness of hypoglycemia and severe hypoglycemia among people with insulin-treated type 2 diabetes: The Dutch Diabetes Pearl Cohort.

OBJECTIVE: People with type 2 diabetes on insulin are at risk for hypoglycemia. Recurrent hypoglycemia can cause impaired awareness of hypoglycemia (IAH), and increase the risk for severe hypoglycemia. The aim of this study was to assess the prevalence and determinants of self-reported IAH and severe hypoglycemia in a Dutch nationwide cohort of people with insulin-treated type 2 diabetes. RESEARCH DESIGN AND METHODS: Observational study of The Dutch Diabetes Pearl, a cohort of people with type 2 diabetes treated in primary, secondary and tertiary diabetes care centers. The presence of IAH and the occurrence of severe hypoglycemia in the past year, defined as an event requiring external help to recover, were assessed using the validated Dutch version of the Clarke questionnaire. In addition, clinical variables were collected including age, diabetes duration, hemoglobin A1c, ethnicity and education. RESULTS: 2350 people with type 2 diabetes on insulin were included: 59.1% men, mean age 61.1±10.4 years, mean diabetes duration 14.8±9.2 years and 79.5% on basal-bolus therapy. A total of 229 patients (9.7%) were classified as having IAH and 742 patients (31.6%) reported severe hypoglycemia. Increased odds for IAH were found with complex insulin regimens and lower odds with having a partner and body mass index ≥30 kg/m2. Severe hypoglycemia was associated with complex insulin regimens, non-Caucasian ethnicity and use of psychoactive drugs, and inversely with metformin use. CONCLUSIONS: In this nationwide cohort, almost one out of ten people with type 2 diabetes on insulin had IAH and >30% had a history of severe hypoglycemia in the past year.

Effect of the GLP-1 Receptor Agonist Exenatide on Impaired Awareness of Hypoglycemia in Type 1 Diabetes: A Randomized Controlled Trial.

CONTEXT: Impaired awareness of hypoglycemia (IAH), resulting from habituation to recurrent hypoglycemia, can be reversed by strict avoidance of hypoglycemia. Adjunctive treatment with glucagon-like peptide-1 receptor agonists may reduce glucose variability, hence lower the risk of hypoglycemia and improve awareness. The aim of our study was to investigate the effect of exenatide on awareness of hypoglycemia in patients with type 1 diabetes and IAH. METHODS: This was a randomized double-blind, placebo-controlled crossover trial. Ten patients with type 1 diabetes and IAH were included [age, 38.5 ± 4.4 years; 40% males; glycated hemoglobin 7.2% ± 0.4% (55.2 ± 4.8 mmol/mol)]. Patients were treated with exenatide 5 µg twice daily (first two weeks), followed by 10 µg twice daily (remaining four weeks) or matching placebo, with a four-week washout period. Patients wore blinded glucose sensors in the final weeks and modified hyperinsulinemic normoglycemic-hypoglycemic glucose clamps (nadir 2.5 mmol/L) were performed at the end of each treatment period. RESULTS: Treatment with exenatide caused body weight to decrease compared with placebo (-3.9 ± 0.9 vs 0.6 ± 1.2 kg, P = 0.047). Exenatide did not change mean 24-hour glucose levels (8.3 ± 0.4 vs 8.5 ± 0.3 mmol/L, exenatide vs placebo, P = 0.64), median (interquartile range) percentage of time spent in hypoglycemia [15.5 (4.5, 25.5) vs 7.8 (4.4, 17.1)%, P = 0.11] and frequency of hypoglycemia (15.8 ± 3.7 vs 12.1 ± 3.5, P = 0.19). Symptom scores in response to clamped hypoglycemia were similar between exenatide [median change 1.0 (-1.5, 7.0)] and placebo [4.5 (1.5, 5.8), P = 0.08]. CONCLUSIONS: Six weeks of treatment with exenatide did not improve awareness of hypoglycemia in patients with type 1 diabetes and IAH.

Effect of Automated Bolus Calculation on Glucose Variability and Quality of Life in Patients With Type 1 Diabetes on CSII Treatment.

PURPOSE: Automated bolus calculation may benefit patients with poorly controlled type 1 diabetes who are relatively new to continuous subcutaneous insulin infusion (CSII). This study investigated the effect of automated bolus calculation on glucose variability, glucose control, and diabetes-related quality of life in patients with reasonably well-controlled type 1 diabetes, accustomed to treatment with CSII for several years. METHODS: This open-label, single-center study included 32 patients (mean age, 45.9 [15.1] years; 34% male; disease duration, 27.3 [12.9] years; glycosylated hemoglobin [HbA1c] level, 64.6 [12.5] mmol/mol [8.1% (1.1%)]; CSII treatment, 9.0 [7.8] years) who were randomly assigned to receive 4 months' treatment with a bolus calculator (n = 14) or continuation of standard care without a bolus calculator (n = 18). All participants received dietary counseling on carbohydrate counting. Primary outcome was glucose variability, as assessed by the SD of 7-point glucose profiles. Secondary outcomes included HbA1c, rate of (severe) hypoglycemia, and diabetes-related quality of life. FINDINGS: After 4 months of follow-up, glucose variability had improved in the bolus calculator group compared with the control group (change, -0.8 [0.9] vs 0.1 [0.9] mmol/L; P = 0.030). Mean glucose levels did not change in either group (0.4 [1.1] vs 0.3 [0.9] mmol/L; P = 0.95). There were also no differences in change in hypoglycemia rate (-0.6 [1.6] vs -0.4 [1.6] event per patient per week; P = 0.67), HbA1c value (-0.5 [6.6] vs -4.9 [10.6] mmol/mol; P = 0.21), or diabetes-related quality of life between the bolus calculator group and the control group. IMPLICATIONS: Use of a bolus calculator modestly improved glucose variability in this relatively small group of patients with longstanding type 1 diabetes on CSII but did not affect other parameters of glycemic control or diabetes-related quality of life.