Andreas Thomas

Prevention of Hypoglycemia by Using Low Glucose Suspend Function in Sensor-Augmented Pump Therapy

BACKGROUND Severe hypoglycemic episodes are a barrier for achieving optimal glycemic control. Sensor-augmented pump (SAP) therapy with insulin in combination with a novel mechanism of automatic insulin shutoff (low glucose suspend [LGS]) can be used to prevent and reduce hypoglycemia. In a prospective study, we investigated the effect of the LGS algorithm on the frequency of hypoglycemia in children and adolescents with type 1 diabetes under real-life conditions. METHODS Twenty-one patients with type 1 diabetes (10.8±3.8 years old, duration of diabetes 5.9±3.0 years, pump therapy for 3.7±1.7 years, glycated hemoglobin level 7.8±1.1%) from three pediatric centers used the Paradigm(®) Veo(™) system (Medtronic Minimed, Northridge, CA) during two subseqent time periods: SAP without LGS for 2 weeks and then SAP with LGS enabled for 6 weeks. The primary objective was to assess the frequency of hypoglycemic episodes when using the LGS feature with an insulin delivery shutoff of a maximum of 2 h at a sensor glucose level below 70 mg/dL (3.9 mmol/L). RESULTS In total, 1,298 LGS alerts occurred (853 shorter than 5 min). Forty-two percent of LGS activations (>5 min) lasted less than 30 min, whereas 24% had a duration of 2 h. The number of hypoglycemic excursions (average/day) was reduced during SAP+LGS (<70 mg/L, 1.27±0.75 vs. 0.95±0.49, P=0.010; ≤40 mg/dL, 0.28±0.18 vs. 0.13±0.14, P=0.005) as was the time spent in hypoglycemia (average minutes/day, 101±68 vs. 58±33, P=0.002) without significant difference in the mean glucose level (145±23 vs. 148±19 mg/dL). No episodes of severe hyperglycemia or diabetic ketoacidosis were observed following LGS activation. CONCLUSIONS The present investigation provides evidence that SAP with LGS reduces the frequency of hypoglycemia without compromising safety.

Cardiac autonomic diabetic neuropathy

Cardiovascular autonomic diabetic neuropathy (CADN) is one of the most common diabetes-associated complications. Disturbed heart rate variability (HRV) is very often the earliest symptom, even in clinically asymptomatic patients. The following article offers a topical overview for those working or interested in the fields of diabetology and cardiology.

Continuous Glucose Monitoring: Evidence and Consensus Statement for Clinical Use

Continuous glucose monitoring (CGM) is an essential tool for modern diabetes therapy. Randomized controlled studies have provided evidence that hemoglobin A1c (HbA1c) results can be improved in patients with type 1 diabetes with elevated baseline HbA1c when using CGM frequently enough and that the frequency and duration of hypoglycemic events can be reduced in patients with satisfactory baseline HbA1c. The CGM group within the Working Group Diabetes Technology (AGDT) of the German Diabetes Association (DDG) has defined evidence-based indications for the practical use of CGM in this consensus statement related to hypoglycemia (frequent, severe, or nocturnal) or hypoglycemia unawareness, insufficient metabolic control despite use of all possible therapeutic options and patient compliance, pregnancy associated with inadequate blood glucose results, and the need for more than 10 blood glucose measurements per day. Contraindications and defined preconditions for the successful use of CGM should be considered.

Differences in Glycemic Variability Between Normoglycemic and Prediabetic Subjects

Objective: So far the criteria for NGT and abnormal glucose tolerance (AGT) are based on HbA1c and 75 g oGTT. We present data on GV and diurnal profiles in stratified cohorts with AGT versus controls. Research designs and methods: 28 NGT, 42 AGT (15 IGT, 11 IFG, 16 CGI) matched for age and BMI classified by 75 g oGTT underwent a CGM with test meal (TM). Diurnal profiles, glucose excursion after TM, and GV (SD, MAGE) were calculated for day 2 and 3. Results: HbA1c, with its values of 5.5 ± 0.37% versus 5.65 ± 0.36%, was within normal range. Average interstitial glucose (AiG) was 5.84 ± 0.52 mmol/l) in NGT and 6.35 ± 0.65 mmol/l in AGT (P = .002). The 2 h incremental area under curve (iAUC) from TM until 2 h after TM was 1.94 ± 1.31 mmol/l*h versus 2.89 ( ± 1.75) mmol/l*h (P = .012), AiG 2 hours after TM was 5.99 ± 1.14 mmol/l*d versus 6.64 ± 1.30 mmol/l (P = .035). Peaks of AiG after TM were 7.69 ± 1.48 mmol/l*d versus 9.18 ± 1.67 mmol/l*d (P = .001). SD was significantly higher for AGT (1.12 ± 0.37 vs. 0.85 ± 0.32 mmol/l, P = .01) and MAGE 2.26 ± 0.84 vs. 1.60 ± 0.69 mmol/l, P = .005). Conclusions: In this comparative analysis NGT and AGT well matched for age, BMI, and comorbidities, CGM revealed significant differences in daytime AiG, pp glucose excursion and postprandial peaks. SD and MAGE was significantly higher for subjects with AGT. I Impaired glucose homeostasis a better characterizes degree of AGTe than HbA1c and 75 g OGTT.

Discrepancies Between Blood Glucose and Interstitial Glucose—Technological Artifacts or Physiology: Implications for Selection of the Appropriate Therapeutic Target:

Background: For decades, the major source of information used to make therapeutic decisions by patients with diabetes has been glucose measurements using capillary blood samples. Knowledge gained from clinical studies, for example, on the impact of metabolic control on diabetes-related complications, is based on such measurements. Different to traditional blood glucose measurement systems, systems for continuous glucose monitoring (CGM) measure glucose in interstitial fluid (ISF). The assumption is that glucose levels in blood and ISF are practically the same and that the information provided can be used interchangeably. Thus, therapeutic decisions, that is, the selection of insulin doses, are based on CGM system results interpreted as though they were blood glucose values. Methods: We performed a more detailed analysis and interpretation of glucose profiles obtained with CGM in situations with high glucose dynamics to evaluate this potentially misleading assumption. Results: Considering physical activity, hypoglycemic episodes, and meal-related differences between glucose levels in blood and ISF uncover clinically relevant differences that can make it risky from a therapeutic point of view to use blood glucose for therapeutic decisions. Conclusions: Further systematic and structured evaluation as to whether the use of ISF glucose is more safe and efficient when it comes to acute therapeutic decisions is necessary. These data might also have a higher prognostic relevance when it comes to long-term metabolic consequences of diabetes. In the long run, it may be reasonable to abandon blood glucose measurements as the basis for diabetes management and switch to using ISF glucose as the appropriate therapeutic target.

Prediction of the Risk to Develop Diabetes-Related Late Complications by Means of the Glucose Pentagon Model: Analysis of Data from the Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study

Background: By taking parameters into account that describe the variability of continuously monitored glucose and long-term metabolic control [hemoglobin A1c (HbA1c)], the glucose pentagon model (GPM) allows characterization of the glucose profile of individual patients with diabetes in a graphical format. A glycemic risk parameter (GRP) derived from this model might allow a better prognosis of the risk to develop diabetes-related complications than the HbA1c. Methods: To evaluate this hypothesis, we analyzed a subset of data from the Juvenile Diabetes Research Foundation continuous glucose monitoring (CGM) study. The values of the different parameters that are integrated in the GPM were extracted automatically from CGM profiles registered before and after 6 months by means of the Medtronic CGM system in 108 patients. Results: In these patients, the significant reduction in HbA1c from 7.4% to 7.0% was accompanied by a reduction in glycemia from 164 to 156 mg/dl, standard deviation from 61 to 57 mg/dl, area under the curve >160 mg/dl 29.2 to 23.1, and time per day >160 mg/dl 634 to 576 min. This led to a subsequent reduction in GRP from 3.3 to 2.7; this decrease by 18.2% was significantly larger than that in HbA1c by 8.6% (p < .001). Changes in individual GPMs/GRPs support this observation. They also show the impact of high glycemic variability on GPM/GRP. Conclusions: Our analysis of data of a study with a considerable sample size and study duration showed that the GPM is not only helpful for rapid assessment of individual glycemic profiles and how therapeutic interventions influence these, but also appears to provide a better prognosis of the risk to develop late complications than the HbA1c per se. However, it is also clear that a true validation of such a model requires performance of a long-term study in a large number of patients with diabetes.

The Development of New Composite Metrics for the Comprehensive Analytic and Visual Assessment of Hypoglycemia Using the Hypo-Triad

Background: Quantifying hypoglycemia has traditionally been limited to using the frequency of hypoglycemic events during a given time interval using data from blood glucose (BG) testing. However, continuous glucose monitoring (CGM) captures three parameters—a Hypo-Triad—unavailable with BG monitoring that can be used to better characterize hypoglycemia: area under the curve (AUC), time (duration of hypoglycemia), and frequency of daily episodes below a specified threshold. Methods: We developed two new analytic metrics to enhance the traditional Hypo-Triad of CGM-derived data to more effectively capture the intensity of hypoglycemia (IntHypo) and overall hypoglycemic environment called the “hypoglycemia risk volume” (HypoRV). We reanalyzed the CGM data from the ASPIRE In-Home study, a randomized, controlled trial of a sensor-integrated pump system with a low glucose threshold suspend feature (SIP+TS), using these new metrics and compared them to standard metrics of hypoglycemia. Results: IntHypo and HypoRV provide additional insights into the benefit of a SIP+TS system on glycemic exposure when compared to the standard reporting methods. In addition, the visual display of these parameters provides a unique and intuitive way to understand the impact of a diabetes intervention on a cohort of subjects as well as on individual patients. Conclusion: The IntHypo and HypoRV are new and enhanced ways of analyzing CGM-derived data in diabetes intervention studies which could lead to new insights in diabetes management. They require validation using existing, ongoing, or planned studies to determine whether they are superior to existing metrics.

The Comprehensive Glucose Pentagon: A Glucose-Centric Composite Metric for Assessing Glycemic Control in Persons With Diabetes

Background: Composite metrics have the potential to provide more complete and clinically useful information about glycemic control than traditional individual metrics such as hemoglobin A1C, %/time/area under curve of hypoglycemia and hyperglycemia. Methods: Using five key metrics that are derived from continuous glucose monitoring, we developed a new, multicomponent composite metric, the Comprehensive Glucose Pentagon (CGP) that demonstrates glycemic control both numerically and visually. Two of its axes are composite metrics—the intensity of hypoglycemia and intensity of hyperglycemia. This approach eliminates the use of the surrogate marker, hemoglobin A1C (A1C), and replaces it with glucose-centric metrics. Results: We reanalyzed the data from two randomized control trials, the STAR 3 and ASPIRE In-Home studies using the CGP. It provided new insights into the effect of sensor-augmented pumping (SAP) in the STAR 3 trial and sensor-integrated pumping with low-glucose threshold suspend (SIP+TS) in the ASPIRE In-Home trial. Conclusions: The CGP has the potential to enable health care providers, investigators and patients to better understand the components of glycemic control and the effect of various interventions on the individual elements of that control. This can be done on a daily, weekly, or monthly basis. It also allows direct comparison of the effects on different interventions among clinical trials which is not possible using A1C alone. This new composite metric approach requires validation to determine if it provides a better predictor of long-term outcomes than A1C and/or better predictor of severe hypoglycemia than the low blood glucose index (LBGI).

Options for the Development of Noninvasive Glucose Monitoring: Is Nanotechnology an Option to Break the Boundaries?

Nowadays nanotechnology has many applications in products used in various areas of daily life; however, this technology has also an option in modern medicine and pharmacy. Therefore, this technology is also an attractive option for the field of diagnosis and treatment of diabetes. Many people with diabetes measure their blood glucose levels regularly to determine the insulin dose. Ideally glucose values would be measured noninvasively (NI). However, none of all the NI approaches studied in the past decades enabled reliable NI measurements under all daily life conditions. Particularly an unfavorable signal-to-noise ratio turned out to be problematic. Based on the known physical possibilities for NI glucose monitoring the focus of this review is on nanotechnology approaches. Functional prototypes exist for some of these that showed promising results under defined laboratory conditions, indicating a good sensitivity and selectivity for glucose. On the second hand is to optimize the technological process of manufacturing. In view of the rapid progress in micro- and nanoelectronics hopefully NI glucose monitoring systems can be developed in the near future.

Nanotechnological Approach to the Treatment of Diabetes

Nanotechnology in diabetes research has facilitated the evolution of novel glucose measurement and insulin delivery systems. As type 1 diabetes mellitus needs treatment with insulin from the very beginning on, the objective of any kind of diabetes therapy is to reach nearly physiological glucose levels. The current view points toward a continuous insulin infusion by means of an insulin pump. It is desirable then, that a glucose sensor would automatically control the insulin supply, given that an insulin pump works only manually. Worldwide diabetes research activities at its interface with nanotechnology have created devices at the micro- or nanoscale by which the experimental approach toward an artificial pancreas is already put in practice. The article discusses some aspects of conventional glucose sensors, as well as basic concepts and developments in the field of nanotechnology and their application in the field of diabetes research. Some types of nanoscale sensors and functionalized nanostructures as insulin-delivery systems are looked at, that could act as an artificial pancreas.