Real-life data of hypoglycemic events in children and adolescents with type 1 diabetes.

INTRODUCTION: Hypoglycemia composes an always present risk in the treatment of type 1 diabetes (T1D) and can be a fatal complication. Many studies on hypoglycemic events are based on self-reported data or focused on the aggregated time below range. We have processed continuous glucose monitoring (CGM) data in children and adolescents with T1D in order to examine all occurring hypoglycemic events. RESEARCH DESIGN AND METHODS: CGM data (mean 168±3 days) from 214 children and adolescents with T1D were analyzed using computer-based algorithms. Patients were divided into three groups based on estimated HbA1c (eHbA1c): (1) ≤48 mmol/mol (n=58); (2) 49-64 mmol/mol (n=113); (3) ≥65 mmol/mol (n=43). The groups were compared concerning descriptive data and CGM metrics with emphasis on the frequency of hypoglycemic events. RESULTS: Only one self-reported event of severe hypoglycemia was registered, while 54 390 hypoglycemic events (<3.9 mmol/L (<70 mg/dL)) were identified from CGM data out of which 11 740 were serious (<3.0 mmol/L (<54 mg/dL)). On average there were 1.5±0.1 hypoglycemic events per 24 hours out of which 1.2±0.1 were mild (3.0-3.9 mmol/L) and 0.3±0.02 serious. Group 1 had a higher frequency of both total and mild hypoglycemic events compared with both groups 2 and 3. However, the frequency of serious hypoglycemic events was similar in all groups. A negative correlation was observed for eHbA1c and total daily and mild hypoglycemic events (r=-0.57 and r=-0.66, respectively, p<0.0001), whereas for serious hypoglycemic events there was only a borderline significance (r=-0.13, p=0.05). CONCLUSIONS: This study shows that hypoglycemic events are a frequent phenomenon in children and adolescents with T1D, occurring regardless of overall metabolic control. Although patients with an HbA1c ≤48 mmol/mol had a higher frequency of mild hypoglycemic events there was no increase in serious hypoglycemic events.

Classification of Hypoglycemic Events in Type 1 Diabetes Using Machine Learning Algorithms.

INTRODUCTION: To improve the utilization of continuous- and flash glucose monitoring (CGM/FGM) data we have tested the hypothesis that a machine learning (ML) model can be trained to identify the most likely root causes for hypoglycemic events. METHODS: CGM/FGM data were collected from 449 patients with type 1 diabetes. Of the 42,120 identified hypoglycemic events, 5041 were randomly selected for classification by two clinicians. Three causes of hypoglycemia were deemed possible to interpret and later validate by insulin and carbohydrate recordings: (1) overestimated bolus (27%), (2) overcorrection of hyperglycemia (29%) and (3) excessive basal insulin presure (44%). The dataset was split into a training (n = 4026 events, 304 patients) and an internal validation dataset (n = 1015 events, 145 patients). A number of ML model architectures were applied and evaluated. A separate dataset was generated from 22 patients (13 'known' and 9 'unknown') with insulin and carbohydrate recordings. Hypoglycemic events from this dataset were also interpreted by five clinicians independently. RESULTS: Of the evaluated ML models, a purpose-built convolutional neural network (HypoCNN) performed best. Masking the time series, adding time features and using class weights improved the performance of this model, resulting in an average area under the curve (AUC) of 0.921 in the original train/test split. In the dataset validated by insulin and carbohydrate recordings (n = 435 events), i.e. 'ground truth,' our HypoCNN model achieved an AUC of 0.917. CONCLUSIONS: The findings support the notion that ML models can be trained to interpret CGM/FGM data. Our HypoCNN model provides a robust and accurate method to identify root causes of hypoglycemic events.

GABA induces a hormonal counter-regulatory response in subjects with long-standing type 1 diabetes.

INTRODUCTION: Experimentally, gamma-aminobutyric acid (GABA) has been found to exert immune-modulatory effects and induce beta-cell regeneration, which make it a highly interesting substance candidate for the treatment of type 1 diabetes (T1D). In many countries, including those in the European Union, GABA is considered a pharmaceutical drug. We have therefore conducted a safety and dose escalation trial with the first controlled-release formulation of GABA, Remygen (Diamyd Medical). RESEARCH DESIGN AND METHODS: Six adult male subjects with long-standing T1D (age 24.8±1.5 years, disease duration 14.7±2.2 years) were enrolled in an 11-day dose escalation trial with a controlled-release formulation of GABA, Remygen. Pharmacokinetics, glucose control and hormonal counter-regulatory response during hypoglycemic clamps were evaluated at every dose increase (200 mg, 600 mg and 1200 mg). RESULTS: During the trial there were no serious and only a few, transient, adverse events reported. Without treatment, the counter-regulatory hormone response to hypoglycemia was severely blunted. Intake of 600 mg GABA more than doubled the glucagon, epinephrine, growth hormone and cortisol responses to hypoglycemia. CONCLUSIONS: We find that the GABA treatment was well tolerated and established a counter-regulatory response to hypoglycemia in long-standing T1D. Further studies regarding not only the clinical potential of Remygen for beta-cell regeneration but also its potential use as hypoglycemic prophylaxis are warranted. TRAIL REGISTRATION NUMBER: NCT03635437 and EudraCT2018-001115-73.

Endogenous Levels of Gamma Amino-Butyric Acid Are Correlated to Glutamic-Acid Decarboxylase Antibody Levels in Type 1 Diabetes.

Gamma-aminobutyric acid (GABA) is an important inhibitory neurotransmitter in the central nervous system (CNS) and outside of the CNS, found in the highest concentrations in immune cells and pancreatic beta-cells. GABA is gaining increasing interest in diabetes research due to its immune-modulatory and beta-cell stimulatory effects and is a highly interesting drug candidate for the treatment of type 1 diabetes (T1D). GABA is synthesized from glutamate by glutamic acid decarboxylase (GAD), one of the targets for autoantibodies linked to T1D. Using mass spectrometry, we have quantified the endogenous circulating levels of GABA in patients with new-onset and long-standing T1D and found that the levels are unaltered when compared to healthy controls, i.e., T1D patients do not have a deficit of systemic GABA levels. In T1D, GABA levels were negatively correlated with IL-1 beta, IL-12, and IL-15 15 and positively correlated to levels of IL-36 beta and IL-37. Interestingly, GABA levels were also correlated to the levels of GAD-autoantibodies. The unaltered levels of GABA in T1D patients suggest that the GABA secretion from beta-cells only has a minor impact on the circulating systemic levels. However, the local levels of GABA could be altered within pancreatic islets in the presence of GAD-autoantibodies.