Severe hypoglycemic episodes: a persistent threat for children with Type 1 diabetes mellitus and their families

Severe Hypoglycemia: Is It Still a Threat for Children and Adolescents With Type 1 Diabetes?

Severe hypoglycemia is defined as a condition with serious cognitive dysfunction, such as a convulsion and coma, requiring external help from other persons. This condition is still lethal and is reported to be the cause of death in 4-10% in children and adolescents with type 1 diabetes. The incidence of severe hypoglycemia in the pediatric population was previously reported as high as more than 50-100 patient-years; however, there was a decline in the frequency of severe hypoglycemia during the past decades, and relationship with glycemic control became weaker than previously reported. A lot of studies have shown the neurological sequelae with severe hypoglycemia as cognitive dysfunction and abnormalities in brain structure. This serious condition also provides negative psychosocial outcomes and undesirable compensatory behaviors. Various possible factors, such as younger age, recurrent hypoglycemia, nocturnal hypoglycemia, and impaired awareness of hypoglycemia, are possible risk factors for developing severe hypoglycemia. A low HbA_1c level is not a predictable value for severe hypoglycemia. Prevention of severe hypoglycemia remains one of the most critical issues in the management of pediatric patients with type 1 diabetes. Advanced technologies, such as continuous glucose monitoring (CGM), intermittently scanned CGM, and sensor-augmented pump therapy with low-glucose suspend system, potentially minimize the occurrence of severe hypoglycemia without worsening overall glycemic control. Hybrid closed-loop system must be the most promising tool for achieving optimal glycemic control with preventing the occurrence of severe hypoglycemia in pediatric patients with type 1 diabetes.

An Economic Evaluation of Continuous Glucose Monitoring for People with Type 1 Diabetes and Impaired Awareness of Hypoglycaemia within North West London Clinical Commissioning Groups in England

To assess the economic impact of providing real time continuous glucose monitoring (CGM) for people with type 1 diabetes (T1D) and impaired awareness of hypoglycaemia (IAH) within North West (NW) London clinical commissioning groups (CCGs). Methods: The eligible population for CGM and inputs for the economic budget impact model developed were derived from published data. The model includes cost of CGM; cost savings associated with lower hypoglycaemia related hospital admissions, accidents and emergency visits; self-monitoring of blood glucose (SMBG) strip usage; and glycated haemoglobin (HbA1c) reduction-related avoided complications and insulin pump use. Results: The cost of CGM for T1D-IAH (n=3,036) in the first year is £10,770,671 and in the fourth year is £11,329,095. The combined cost off-sets related to reduced hypoglycaemia admissions, SMBG strip usage and complications are £8,116,912 and £8,741,026 in years one and four, respectively. The net budget impact within the NW London CCGs is £2,653,760; £2,588,068 in years one and four respectively. Conclusions: Introduction of CGM for T1D-IAH patients will have a minimal budget impact on NW London CCGs, driven by cost of CGM and offsets from lower hypoglycaemia-related costs, reduced SMBG strip usage, avoided HbA1c-related complications and lower insulin pump use.

Immunotherapy for type 1 diabetes

INTRODUCTION

Although many approaches have been tested to overcome the insulin dependence caused by the pancreatic β-cells destruction observed in individuals affected by type 1 diabetes (T1D), medical research has largely failed to halt the onset or to reverse T1D.

METHODS

In this work, the state of the art of immunotherapy will be examined, and the most important achievement in the field will be critically discussed. Particularly, we will focus on the clinical aspect, thus avoiding the tedious preclinical work done in NOD mice, which has been so poorly translated to the bedside.

CONCLUSIONS

Stem cell therapies achieved thus this far the most promising results, while immune ablation and standard immunosuppressants did not maintain the premises of preclinical results. The next step will be to generate a feasible and safe clinical approach in order to cure the thousands of patients affected by T1D.

Drug-related risk of severe hypoglycaemia in observational studies: a systematic review and meta-analysis

BACKGROUND

Diabetes mellitus (DM) leads to multiple complications, including severe hypoglycaemia events (SHEs). SHEs can impact a patient's quality of life and compliance and may directly result in additional costs to the health care system. The aim of this review was to evaluate the risk of severe hypoglycaemia in patients with type 1 (T1) and 2 (T2) DM as observed in everyday clinical practice for various drug regimens.

METHODS

We conducted a systematic review of observational (retrospective or prospective) studies in the MEDLINE, Embase, and Cochrane Library databases that covered at least 100 children or adults with T1/T2 DM. In T1 DM, basal-bolus/pre-mix insulin (human or analogue) and insulin pump were reviewed, and in T2 DM, basal-bolus/pre-mix insulin (human or analogue), oral antidiabetic drugs supported with basal insulin (human or analogue), sulfonylureas in monotherapy, and combined oral treatment were reviewed. In order to estimate SHE rates, we extracted data on the time horizon of the study, number of patients, number of SHEs, and number of patients experiencing at least one SHE. We used a random effects model to estimate the annual SHE rate. We considered the risk for other antidiabetic medications in T2 DM to be negligible and the results of our main review yielded no observational data for premixes in T1 DM so they were assessed based on relative rates taken from additional systematic reviews. The study, being a desk research, did not involve any human subjects (including human material or human data) and no ethical committee approval was asked for. For the same reason there was no need to collect informed consent for participation in the study.

RESULTS

We identified 76 observational studies encompassing 707,722.30 patient-years. The estimated annual SHE rate varied from 0.168 (95 % CI 0.123-0.237) for insulin pump up to 1.628 for biphasic human insulin in T1 DM patients, and from 0.0035 for oral antidiabetic drugs up to 0.554 (95 % CI 0.157-7.534) for basal-bolus with human insulin in T2 DM patients.

CONCLUSIONS

Our review indicates that SHE rates differ between patients depending on treatment regimen. However, SHEs are also driven by other factors. Proper modelling techniques are needed to use various types of information in published studies.

HypoDE: Research Design and Methods of a Randomized Controlled Study Evaluating the Impact of Real-Time CGM Usage on the Frequency of CGM Glucose Values <55 mg/dl in Patients With Type 1 Diabetes and Problematic Hypoglycemia Treated With Multiple Daily Injections

Systems for continuous glucose monitoring (CGM) have been available for a number of years, and numerous clinical studies have been performed with them. Interestingly, in many of these studies patients with an increased risk of hypoglycemic events were excluded. In addition, in most studies subjects were using a pump for insulin delivery. Therefore our knowledge about the benefit of CGM in patients employing multiple daily injections (MDI) of insulin is limited, especially when it comes to a reduction in the risk of low glucose events in high-risk individuals. We are planning to run a 26-week randomized controlled study in Germany (HypoDE, Hypoglycemia in Deutschland) that is focused on evaluating if such a reduction can be observed in patients on MDI with an increased risk of low glucose events. In all, 160 patients will participate in the study, randomized into the intervention group and control group. Ideally one would study if the frequency of severe hypoglycemic events is different between both groups. However, this would require such a large sample size and study duration, so for pragmatic reasons we will use low glucose levels <55 mg/dl (measured by CGM) for at least 20 minutes as a risk marker for severe hypoglycemic events. The results from the HypoDE study shall help determine the advantage of using CGM in subjects with type 1 diabetes with an increased risk of low glucose events treated with MDI.

Minimizing morbidity of hypoglycemia in diabetes: a review of mini-dose glucagon

Type 1 diabetes is a common chronic disease of childhood and one of the most difficult conditions to manage. Advances in insulin formulations and insulin delivery devices have markedly improved the ability to achieve normal glucose homeostasis. However, hypoglycemia remains the primary limiting factor in achieving normoglycemia and is a frequent complication in children with acute gastroenteritis and/or poor oral intake. In situations of impaired carbohydrate intake or absorption, glucagon therapy is the only out-of-hospital treatment option available to families and caregivers. Glucagon is recommended for the treatment of severe hypoglycemia and rapidly increases blood glucose by increasing hepatic glucose production from glycogenolysis. Mini-dose glucagon is a widely utilized off-label treatment for managing mild or impending hypoglycemia and is administered as a small subcutaneous injection. It was initially described for use in children who were unable to tolerate or absorb oral carbohydrates but not in need of advanced medical care. Yet, mini-dose glucagon may be useful in any individual with relative insulin excess. The regimen aims to prevent severe hypoglycemic episodes and is safe, effective, and easily administered by patients and caregivers in the out-of-hospital setting. By empowering patients and their families, this important tool could help to alleviate the physical, psychosocial, and financial burden evolving from impending hypoglycemia.

Hypoglycemia induced by insulin as a triggering factor of cognitive deficit in diabetic children

This paper provides an overview of insulin-induced hypoglycemia as a triggering factor of cognitive deficit in children with type 1 diabetes mellitus. For this purpose, databases from 1961 to 2013 were used with the objective of detecting the primary publications that address the impact of hypoglycemia on cognitive performance of diabetic children. The results obtained from experimental animals were excluded. The majority of studies demonstrated that the cognitive deficit in diabetic children involves multiple factors including duration, intensity, severity, and frequency of hypoglycemia episodes. Additionally, age at the onset of type 1 diabetes also influences the cognitive performance, considering that early inception of the disease is a predisposing factor for severe hypoglycemia. Furthermore, the results suggest that there is a strong correlation between brain damage caused by hypoglycemia and cognitive deterioration. Therefore, a more cautious follow-up and education are needed to impede and treat hypoglycemia in children with diabetes mellitus.

Hypoglycemia Early Alarm Systems Based On Multivariable Models

Hypoglycemia is a major challenge of artificial pancreas systems and a source of concern for potential users and parents of young children with Type 1 diabetes (T1D). Early alarms to warn the potential of hypoglycemia are essential and should provide enough time to take action to avoid hypoglycemia. Many alarm systems proposed in the literature are based on interpretation of recent trends in glucose values. In the present study, subject-specific recursive linear time series models are introduced as a better alternative to capture glucose variations and predict future blood glucose concentrations. These models are then used in hypoglycemia early alarm systems that notify patients to take action to prevent hypoglycemia before it happens. The models developed and the hypoglycemia alarm system are tested retrospectively using T1D subject data. A Savitzky-Golay filter and a Kalman filter are used to reduce noise in patient data. The hypoglycemia alarm algorithm is developed by using predictions of future glucose concentrations from recursive models. The modeling algorithm enables the dynamic adaptation of models to inter-/intra-subject variation and glycemic disturbances and provides satisfactory glucose concentration prediction with relatively small error. The alarm systems demonstrate good performance in prediction of hypoglycemia and ultimately in prevention of its occurrence.