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Background: Hypoglycemia is common in individuals with type 1 diabetes, especially during exercise. We investigated the accuracy of two different continuous glucose monitoring systems during exercise-related hypoglycemia in an experimental setting., Materials and Methods: Fifteen individuals with type 1 diabetes participated in two separate euglycemic-hypoglycemic clamp days (Clamp-exercise and Clamp-rest) including five phases: 1) baseline euglycemia, 2) plasma glucose (PG) decline ± exercise, 3) 15-minute hypoglycemia ± exercise, 4) 45-minute hypoglycemia, and 5) recovery euglycemia. Interstitial PG levels were measured every five minutes, using Dexcom G6 (DG6) and FreeStyle Libre 1 (FSL1). Yellow Springs Instruments 2900 was used as PG reference method, enabling mean absolute relative difference (MARD) assessment for each phase and Clarke error grid analysis for each day., Results: Exercise had a negative effect on FSL1 accuracy in phase 2 and 3 compared to rest (ΔMARD = +5.3 percentage points [(95% CI): 1.6, 9.1] and +13.5 percentage points [6.4, 20.5], respectively). In contrast, exercise had a positive effect on DG6 accuracy during phase 2 and 4 compared to rest (ΔMARD = -6.2 percentage points [-11.2, -1.2] and -8.4 percentage points [-12.4, -4.3], respectively). Clarke error grid analysis showed a decrease in clinically acceptable treatment decisions during Clamp-exercise for FSL1 while a contrary increase was observed for DG6., Conclusion: Physical exercise had clinically relevant impact on the accuracy of the investigated continuous glucose monitoring systems and their ability to accurately detect hypoglycemia., Competing Interests: SE is currently employed by Novo Nordisk and holds stock in Novo Nordisk. UP-b has served on advisory boards for and/or received lecture fees from Novo Nordisk and Sanofi. FK has served on advisory panels at, been part of speaker’s bureaus for, served as a consultant to, and/or received research support from AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Gubra, MSD/Merck, Novo Nordisk, Sanofi, ShouTi, Zealand Pharma and Zucara. TV has served on scientific advisory panels at, been part of speaker’s bureaus for, served as a consultant to, and/or received research support from Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Gilead, GSK, Mundipharma, MSD/Merck, Novo Nordisk, Sanofi, and Sun Pharmaceuticals. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Maytham, Hagelqvist, Engberg, Forman, Pedersen-Bjergaard, Knop, Vilsbøll and Andersen.)

Aim: To investigate the impact of hypoglycaemia, hyperglycaemia and glycaemic variability on arrhythmia susceptibility in people with type 1 diabetes., Materials and Methods: Thirty adults with type 1 diabetes were included in a 12-month observational exploratory study. Daytime and night-time incident rate ratios (IRRs) of arrhythmias were determined for hypoglycaemia (interstitial glucose [IG] <3.9 mmol/L), hyperglycaemia (IG >10.0 mmol/L) and glycaemic variability (standard deviation and coefficient of variation)., Results: Hypoglycaemia was not associated with an increased risk of arrhythmias compared with euglycaemia and hyperglycaemia combined (IG ≥ 3.9 mmol/L). However, during daytime, a trend of increased risk of arrhythmias was observed when comparing time spent in hypoglycaemia with euglycaemia (IRR 1.08 [95% CI: 0.99-1.18] per 5 minutes). Furthermore, during daytime, both the occurrence and time spent in hyperglycaemia were associated with an increased risk of arrhythmias compared with euglycaemia (IRR 2.03 [95% CI: 1.21-3.40] and IRR 1.07 [95% CI: 1.02-1.13] per 5 minutes, respectively). Night-time hypoglycaemia and hyperglycaemia were not associated with the risk of arrhythmias. Increased glycaemic variability was not associated with an increased risk of arrhythmias during daytime, whereas a reduced risk was observed during night-time., Conclusions: Acute hypoglycaemia and hyperglycaemia during daytime may increase the risk of arrhythmias in individuals with type 1 diabetes. However, no such associations were found during night-time, indicating diurnal differences in arrhythmia susceptibility., (© 2023 John Wiley & Sons Ltd.)

Aims: To investigate changes in cardiac repolarisation during exercise-related hypoglycaemia compared to hypoglycaemia induced at rest in people with type 1 diabetes., Material and Methods: In a randomised crossover study, 15 men with type 1 diabetes underwent two separate hyperinsulinaemic euglycaemic-hypoglycaemic clamp experiments during Holter-ECG monitoring. One experiment included a bout of moderate-intensity cycling exercise (60 min) along with declining plasma glucose (PG; Clamp-exercise). In the other experiment, hypoglycaemia was induced with the participants at rest (Clamp-rest). We studied QTc interval, T-peak to T-end (Tpe) interval and hormonal responses during three steady-state phases: (i) baseline (PG 4.0-8.0 mmol/L); (ii) hypoglycaemic phase (PG <3.0 mmol/L); and (iii) recovery phase (PG 4.0-8.0 mmol/L)., Results: Both QTc interval and Tpe interval increased significantly from baseline during the hypoglycaemic phase but with no significant difference between test days. These changes were accompanied by an increase in plasma adrenaline and a decrease in plasma potassium on both days. During the recovery phase, ΔQTc interval was longer during Clamp-rest compared to Clamp-exercise, whereas ΔTpe interval remained similar on the two test days., Conclusions: We found that both exercise-related hypoglycaemia and hypoglycaemia induced at rest can cause QTc-interval prolongation and Tpe-interval prolongation in people with type 1 diabetes. Thus, both scenarios may increase susceptibility to ventricular arrhythmias., (© 2023 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Background: Insulin-treated patients with type 2 diabetes (T2D) are at risk of hypoglycemia, which is associated with an increased risk of cardiovascular disease and mortality. Using a long-term monitoring approach, we investigated the association between episodes of hypoglycemia, glycemic variability and cardiac arrhythmias in a real-life setting., Methods: Insulin-treated patients with T2D (N = 21, [mean ± SD] age 66.8 ± 9.6 years, BMI 30.1 ± 4.5 kg/m 2 , HbA1c 6.8 ± 0.4% [51.0 ± 4.8 mmol/mol]) were included for a one-year observational study. Patients were monitored with continuous glucose monitoring ([mean ± SD] 118 ± 6 days) and an implantable cardiac monitor (ICM) during the study period., Results: Time spend in hypoglycemia was higher during nighttime than during daytime ([median and interquartile range] 0.7% [0.7-2.7] vs. 0.4% [0.2-0.8]). The ICMs detected 724 episodes of potentially clinically significant arrhythmias in 12 (57%) participants, with atrial fibrillation and pauses accounting for 99% of the episodes. No association between hypoglycemia and cardiac arrhythmia was found during daytime. During nighttime, subject-specific hourly incidence of cardiac arrhythmias tended to increase with the occurrence of hypoglycemia (incident rate ratio [IRR] 1.70 [95% CI 0.36-8.01]) but only slightly with increasing time in hypoglycemia (IRR 1.04 [95% CI 0.89-1.22] per 5 min). Subject-specific incidence of cardiac arrhythmias during nighttime increased with increasing glycemic variability as estimated by coefficient of variation whereas it decreased during daytime (IRR 1.33 [95% CI 1.05-1.67] and IRR 0.77 [95% CI 0.59-0.99] per 5% absolute increase, respectively)., Conclusions: Cardiac arrhythmias were common in insulin-treated patients with T2D and were associated with glycemic variability, whereas arrhythmias were not strongly associated with hypoglycemia., Trial Registration: NCT03150030, ClinicalTrials.gov, registered May 11, 2017. https://clinicaltrials.gov/ct2/show/NCT03150030., (© 2021. The Author(s).)

Background: Hypoglycemia is common in individuals with type 1 diabetes, especially during exercise. We investigated the accuracy of two different continuous glucose monitoring systems during exercise-related hypoglycemia in an experimental setting. Materials and methods: Fifteen individuals with type 1 diabetes participated in two separate euglycemic-hypoglycemic clamp days (Clamp-exercise and Clamp-rest) including five phases: 1) baseline euglycemia, 2) plasma glucose (PG) decline ± exercise, 3) 15-minute hypoglycemia ± exercise, 4) 45-minute hypoglycemia, and 5) recovery euglycemia. Interstitial PG levels were measured every five minutes, using Dexcom G6 (DG6) and FreeStyle Libre 1 (FSL1). Yellow Springs Instruments 2900 was used as PG reference method, enabling mean absolute relative difference (MARD) assessment for each phase and Clarke error grid analysis for each day. Results: Exercise had a negative effect on FSL1 accuracy in phase 2 and 3 compared to rest (ΔMARD = +5.3 percentage points [(95% CI): 1.6, 9.1] and +13.5 percentage points [6.4, 20.5], respectively). In contrast, exercise had a positive effect on DG6 accuracy during phase 2 and 4 compared to rest (ΔMARD = -6.2 percentage points [-11.2, -1.2] and -8.4 percentage points [-12.4, -4.3], respectively). Clarke error grid analysis showed a decrease in clinically acceptable treatment decisions during Clamp-exercise for FSL1 while a contrary increase was observed for DG6. Conclusion: Physical exercise had clinically relevant impact on the accuracy of the investigated continuous glucose monitoring systems and their ability to accurately detect hypoglycemia. [ABSTRACT FROM AUTHOR]

Objective: Sulfonylureas are first-line treatment of hepatocyte nuclear factor 1-α (HNF1A) diabetes (maturity-onset diabetes of the young type 3), but many patients do not achieve optimal glycemic control without episodes of hypoglycemia. We investigated the combination of the sulfonylurea glimepiride and the dipeptidyl peptidase 4 inhibitor linagliptin versus glimepiride monotherapy with respect to glycemic variability, glycemic control, and risk of hypoglycemia.Research Design and Methods: In a randomized, double-blinded, crossover trial, patients with HNF1A diabetes (n = 19; mean ± SD age 43 ± 14 years, BMI 24.8 ± 2.8 kg/m2, and glycated hemoglobin [HbA1c] 7.4 ± 0.2% [57.1 ± 7.3 mmol/mol]) were randomly assigned to treatment with glimepiride + linagliptin 5 mg (16 weeks), washout (4 weeks), and glimepiride + placebo (16 weeks) (or vice versa). Glimepiride was titrated targeting a fasting plasma glucose of 4.5-6.0 mmol/L without hypoglycemia. Treatments were evaluated by continuous glucose monitoring (CGM), HbA1c, and meal test.Results: Compared with glimepiride + placebo, glimepiride + linagliptin did not significantly improve the primary end point, mean amplitude of glycemic excursions (MAGE) (mean difference -0.7 mmol/L, P = 0.1540), but displayed significant reductions in coefficient of variation on CGM (-3.6%, P = 0.0401), HbA1c (-0.5%, P = 0.0048), and glimepiride dose (-0.7 mg/day, P = 0.0099). β-cell glucose sensitivity (assessed as C-peptide-to-glucose ratio) during meal test improved with glimepiride + linagliptin. Incidences of hypoglycemia were similar with both treatments.Conclusions: Linagliptin as add-on treatment to glimepiride improved glycemic variability and control without increasing risk of hypoglycemia in patients with HNF1A diabetes. [ABSTRACT FROM AUTHOR]