Accuracy of continuous glucose monitoring during differing exercise conditions.

AIM Depending on intensity, exercise may induce a strong hormonal and metabolic response, including acid-base imbalances and changes in microcirculation, potentially interfering with the accuracy of continuous glucose monitoring (CGM). The present study aimed at comparing the accuracy of the Dexcom G4 Platinum (DG4P) CGM during continuous moderate and intermittent high-intensity exercise (IHE) in adults with type 1 diabetes (T1DM). METHODS Ten male individuals with well-controlled T1DM (HbA1c 7.0±0.6% [54±6mmol/mol]) inserted the DG4P sensor 2 days prior to a 90min cycling session (50% VO2peak) either with (IHE) or without (CONT) a 10s all-out sprint every 10min. Venous blood samples for reference glucose measurement were drawn every 10min and euglycemia (target 7mmol/l) was maintained using an oral glucose solution. Additionally, lactate and venous blood gas variables were determined. RESULTS Mean reference blood glucose was 7.6±0.2mmol/l during IHE and 6.7±0.2mmol/l during CONT (p<0.001). IHE resulted in significantly higher levels of lactate (7.3±0.5mmol/l vs. 2.6±0.3mmol/l, p<0.001), while pH values were significantly lower in the IHE group (7.27 vs. 7.38, p=0.001). Mean absolute relative difference (MARD) was 13.3±2.2% for IHE and 13.6±2.8% for CONT suggesting comparable accuracy (p=0.90). Using Clarke Error Grid Analysis, 100% of CGM values during both IHE and CONT were in zones A and B (IHE: 77% and 23%; CONT: 78% and 22%). CONCLUSIONS The present study revealed good and comparable accuracy of the DG4P CGM system during intermittent high intensity and continuous moderate intensity exercise, despite marked differences in metabolic conditions. This corroborates the clinical robustness of CGM under differing exercise conditions. CLINICAL TRIAL REGISTRATION NUMBER ClinicalTrials.gov NCT02068638.

SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients

SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

Assessment of three frequently used blood glucose monitoring devices in clinical routine

Self-monitoring of blood glucose plays an important role in the management of diabetes and has been shown to improve metabolic control. The use of blood glucose meters in clinical practice requires sufficient reliability to allow adequate treatment. Direct comparison of different blood glucose meters in clinical practice, independent of the manufactures is scarce. We, therefore, aimed to evaluate three frequently used blood glucose meters in daily clinical practice.

Influence of time point of calibration on accuracy of continuous glucose monitoring in individuals with type 1 diabetes

Abstract Background and Aims: Data on the influence of calibration on accuracy of continuous glucose monitoring (CGM) are scarce. The aim of the present study was to investigate whether the time point of calibration has an influence on sensor accuracy and whether this effect differs according to glycemic level. Subjects and Methods: Two CGM sensors were inserted simultaneously in the abdomen on either side of 20 individuals with type 1 diabetes. One sensor was calibrated predominantly using preprandial glucose (calibration(PRE)). The other sensor was calibrated predominantly using postprandial glucose (calibration(POST)). At minimum three additional glucose values per day were obtained for analysis of accuracy. Sensor readings were divided into four categories according to the glycemic range of the reference values (low, ≤4 mmol/L; euglycemic, 4.1-7 mmol/L; hyperglycemic I, 7.1-14 mmol/L; and hyperglycemic II, >14 mmol/L). Results: The overall mean±SEM absolute relative difference (MARD) between capillary reference values and sensor readings was 18.3±0.8% for calibration(PRE) and 21.9±1.2% for calibration(POST) (P<0.001). MARD according to glycemic range was 47.4±6.5% (low), 17.4±1.3% (euglycemic), 15.0±0.8% (hyperglycemic I), and 17.7±1.9% (hyperglycemic II) for calibration(PRE) and 67.5±9.5% (low), 24.2±1.8% (euglycemic), 15.5±0.9% (hyperglycemic I), and 15.3±1.9% (hyperglycemic II) for calibration(POST). In the low and euglycemic ranges MARD was significantly lower in calibration(PRE) compared with calibration(POST) (P=0.007 and P<0.001, respectively). Conclusions: Sensor calibration predominantly based on preprandial glucose resulted in a significantly higher overall sensor accuracy compared with a predominantly postprandial calibration. The difference was most pronounced in the hypo- and euglycemic reference range, whereas both calibration patterns were comparable in the hyperglycemic range.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

A Passive Source Localization System for IEEE 802.15.4 Signal

In this work, we provide a passive location monitoring system for IEEE 802.15.4 signal emitters. The system adopts software defined radio techniques to passively overhear IEEE 802.15.4 packets and to extract power information from baseband signals. In our system, we provide a new model based on the nonlinear regression for ranging. After obtaining distance information, a Weighted Centroid (WC) algorithm is adopted to locate users. In WC, each weight is inversely proportional to the nth power of propagation distance, and the degree n is obtained from some initial measurements. We evaluate our system in a 16m-18m area with complex indoor propagation conditions. We are able to achieve a median error of 2:1m with only 4 anchor nodes.

PLACENTAL GLUCOSE TRANSPORTER (GLUT)-1 REGULATION IN PREECLAMPSIA

PLACENTAL GLUCOSE TRANSPORTER (GLUT)-1 REGULATION IN PREECLAMPSIA Camilla Marini a,b, Benjamin P. Lüscher a,b, Marianne J€orger-Messerli a,b, Ruth Sager a,b, Xiao Huang c, Jürg Gertsch c, Matthias A. Hediger c, Christiane Albrecht c, Marc U. Baumann a,c, Daniel V. Surbek a,c a Department of Obstetrics and Gynecology, University Hospital of Bern, Bern, Switzerland, Switzerland; b Department of Clinical Research, University of Bern, Bern, Switzerland, Switzerland; c Institute for Biochemistry and Molecular Medicine, University of Bern, Bern, Switzerland, Switzerland Objectives: Glucose is a primary energy source for the fetus. The absence of significant gluconeogenesis in the fetus means that the fetal up-take of this vital nutrient is dependent on maternal supply and subsequent transplacental transport. Altered expression and/or function of placental transporters may affect the intrauterine environment and could compromise fetal and mother well-being. We speculated that pre-eclampsia (PE) impairs the placental glucose transport system. Methods: Placentae were obtained after elective caesarean sections following normal pregnancies and pre-eclamptic pregnancies. Syncytial basal membrane (BM) and apical microvillus membrane (MVM) fractions were prepared using differential ultra-centrifugation and magnesium precipitation. Protein expression was assessed by western blot analysis. mRNA levels in whole villous tissue lysate were quantified by real-time PCR. To assess glucose transport activity a radiolabeled substrate up-take assay and a transepithelial transport model using primary cytotrophoblasts were established. Results: GLUT1 mRNA expression was not changed in PE when compared to control, whereas protein expression was significantly down-regulated. Glucose up-take into syncytial microvesicles was reduced in PE compared to control. In a transepithelial transport model, phloretinmediated inhibition of GLUT1 at the apical side of primary cytotrophoblasts showed a 44% of reduction of transepithelial glucose transport at IC50. Conclusions: GLUT1 is down-regulated on protein and functional level in PE compared to control. Altering glucose transport activity by inhibition of apical GLUT-1 indicates that transplacental glucose transport might be regulated on the apical side of the syncytiotrophoblast. These results might help to understand better the regulation of GLUT1 transporter and maybe in future to develop preventive strategies to modulate the fetal programming and thereby reduce the incidence of disease for both the mother and her child later in life.

Placental Glucose Transporter (GLUT1) Expression in Pre-Eclampsia

Placental Glucose Transporter (GLUT1) Expression in Pre- Eclampsia. INTRODUCTION: Glucose is the most important substrate for fetal growth. Indeed, there is no significant de novo glucose synthesis in the fetus and the fetal up-take of glucose rely on maternal supply and transplacental transport. Therefore, a defective placental transporter system may affect the intrauterine environment compromising fetal as well as mother well-being. On this line, we speculated that the placental glucose transport system could be impaired in pre-eclampsia (PE). METHODS: Placentae were obtained after elective caesarean sections following normal pregnancies and pre-eclamptic pregnancies. Syncytial basal membrane (BM) and apical microvillus membrane (MVM) fractions were prepared using differential ultra-centrifugation and magnesium precipitation. Protein expression was assessed by western blot. mRNA levels were quantified by quantitative real-time PCR. A radiolabeled substrate up-take assay was established to assess glucose transport activity. FACS analysis was performed to check the shape of MVM. Statistical analysis was performed using one way ANOVA test. RESULTS: GLUT1 protein levels were down-regulated (70%; P<0.01) in pre-eclamptic placentae when compared to control placentae. This data is in line with the reduced glucose up-take in MVM prepared from preeclamptic placentae. Of note, the mRNA levels of GLUT1 did not change between placentae affected by PE and normal placentae, suggesting that the levels of GLUT1 are post-transcriptionally regulated. FACS analysis on MVM vesicles from both normal placentae and pre-eclamptic placentae showed equal heterogeneity in the complexes formed. This excluded the possibility that the altered glucose up-take observed in pre-eclamptic MVM was caused by a different shape of these vesicles. CONCLUSIONS: Protein and functional studies of GLUT1 in MVM suggest that in pre-eclampsia the glucose transport between mother and fetus might be defective. To further investigate this important biological aspect we will increase the number of samples obtained from patients and use primary cells to study trans epithelial transport system in vitro.

Monitoring the temporal development of natural hazard risks as a basis indicator for climate change adaptation.

The potential effects of climatic changes on natural risks are widely discussed. But the formulation of strategies for adapting risk management practice to climate changes requires knowledge of the related risks for people and economic values. The main goals of this work were (1) the development of a method for analysing and comparing risks induced by different natural hazard types, (2) highlighting the most relevant natural hazard processes and related damages, (3) the development of an information system for the monitoring of the temporal development of natural hazard risk and (4) the visualisation of the resulting information for the wider public. A comparative exposure analysis provides the basis for pointing out the hot spots of natural hazard risks in the province of Carinthia, Austria. An analysis of flood risks in all municipalities provides the basis for setting the priorities in the planning of flood protection measures. The methods form the basis for a monitoring system that periodically observes the temporal development of natural hazard risks. This makes it possible firstly to identify situations in which natural hazard risks are rising and secondly to differentiate between the most relevant factors responsible for the increasing risks. The factors that most influence the natural risks could be made evident.

GoCARB: Smartphone-App zur Kohlenhydratberechnung bei Typ-1-Diabetes

Smartphone-App zur Kohlenhydratberechnung Neue Technologien wie Blutzuckersensoren und moderne Insulinpumpen prägten die Therapie des Typ-1-Diabetes (T1D) in den letzten Jahren in wesentlichem Ausmaß. Smartphones sind aufgrund ihrer rasanten technischen Entwicklung eine weitere Plattform für Applikationen zur Therapieunterstützung bei T1D. GoCARB Hierbei handelt es sich um ein zur Kohlenhydratberechnung entwickeltes System für Personen mit T1D. Die Basis für Endanwender stellt ein Smartphone mit Kamera dar. Zur Berechnung werden 2 mit dem Smartphone aus verschiedenen Winkeln aufgenommene Fotografien einer auf einem Teller angerichteten Mahlzeit benötigt. Zusätzlich ist eine neben dem Teller platzierte Referenzkarte erforderlich. Die Grundlage für die Kohlenhydratberechnung ist ein Computer-Vision-gestütztes Programm, das die Mahlzeiten aufgrund ihrer Farbe und Textur erkennt. Das Volumen der Mahlzeit wird mit Hilfe eines dreidimensional errechneten Modells bestimmt. Durch das Erkennen der Art der Mahlzeiten sowie deren Volumen kann GoCARB den Kohlenhydratanteil unter Einbeziehung von Nährwerttabellen berechnen. Für die Entwicklung des Systems wurde eine Bilddatenbank von mehr als 5000 Mahlzeiten erstellt und genutzt. Resümee Das GoCARB-System befindet sich aktuell in klinischer Evaluierung und ist noch nicht für Patienten verfügbar.

[New insights into diagnosis and management of gestational diabetes mellitus: recommendations of the Swiss Society for Endocrinology and Diabetes]

Physiology and current knowledge about gestational diabetes which led to the adoption of new diagnostic criterias and blood glucose target levels during pregnancy by the Swiss Society for Endocrinology and Diabetes are reviewed. The 6th International Workshop Conference on Gestational Diabetes mellitus in Pasedena (2008) defined new diagnostic criteria based on the results of the HAPO-Trial. These criteria were during the ADA congress in New Orleans in 2009 presented. According to the new criteria there is no need for screening, but all pregnant women have to be tested with a 75 g oral glucose tolerance test between the 24th and 28th week of pregnancy. The new diagnostic values are very similar to the ones previously adopted by the ADA with the exception that only one out of three values has to be elevated in order to make the diagnosis of gestational diabetes. Due to this important difference it is very likely that gestational diabetes will be diagnosed more frequently in the future. The diagnostic criteria are: Fasting plasma glucose > or = 5.1 mmol/l, 1-hour value > or = 10.0 mmol/l or 2-hour value > or = 8.5 mmol/l. Based on current knowledge and randomized trials it is much more difficult to define glucose target levels during pregnancy. This difficulty has led to many different recommendations issued by diabetes societies. The Swiss Society of Endocrinology and Diabetes follows the arguments of the International Diabetes Federation (IDF) that self-blood glucose monitoring itself lacks precision and that there are very few randomized trials. Therefore, the target levels have to be easy to remember and might be slightly different in mmol/l or mg/dl. The Swiss Society for Endocrinology and Diabetes adopts the tentative target values of the IDF with fasting plasma glucose values < 5.3 mM and 1- and 2-hour postprandial (after the end of the meal) values of < 8.0 and 7.0 mmol/l, respectively. The last part of these recommendations deals with the therapeutic options during pregnancy (nutrition, physical exercise and pharmaceutical treatment). If despite lifestyle changes the target values are not met, approximately 25 % of patients have to be treated pharmaceutically. Insulin therapy is still the preferred treatment option, but metformin (and as an exception glibenclamide) can be used, if there are major hurdles for the initiation of insulin therapy.

Genetic testing for glucokinase mutations in clinically selected patients with MODY: a worthwhile investment

The differential diagnosis for children with diabetes includes a group of monogenic diabetic disorders known as maturity-onset diabetes of the young (MODY). So far, six underlying gene defects have been identified. The most common subtypes are caused by mutations in the genes encoding the transcription factor HNF-1a (MODY 3) and the glycolytic enzyme glucokinase (GCK) (MODY 2). MODY 2 is the most benign form of diabetes as the threshold for glucose sensing is elevated resulting in mild, regulated hyperglycemia. MODY 2 may usually be treated with diet alone without risk of microvascular complications. Patients with MODY usually present as children or young adults. Genetic testing for MODY in diabetic subjects is often not performed because of the costs and its unavailability in Switzerland. We describe the impact of the genetic analysis for MODY 2 on diabetes management and treatment costs in a five-year-old girl. The patient and her diabetic mother were both found to have a heterozygous missense mutation (V203A) in the glucokinase gene. The five-year-old girl was started on insulin therapy for her diabetes but because her HbA1c remained between 5.8-6.4% (reference 4.1-5.7%) and her clinical presentation suggested MODY insulin was discontinued. She is now well controlled on a carbohydrate controlled diet regimen only. Omission of insulin treatment made regular blood glucose monitoring unnecessary and removed her risk of hypoglycemia. Costs for the genetic analysis were 500 Euro. At our centre costs for diabetes care of a patient with type 1 diabetes are approximately 2050 Euro/year compared to 410 Euro/year for the care of a patient with MODY 2. In addition, a diagnosis of MODY 2 may reassure patients and their families, as microvascular complications are uncommon. Thus there are both health and financial benefits in diagnosing MODY 2. We recommend genetic testing for MODY 2 in clinically selected patients even though this analysis is currently not available in Switzerland and costs are not necessarily covered by the health insurances.

Children's and adolescent's self - assessment of metabolic control versus professional judgment: a cross-sectional retrospective and prospective cohort study

BACKGROUND Morbidity and mortality in T1DM depend on metabolic control, which is assessed by HbA1c measurements every 3-4 months. Patients' self-perception of glycemic control depends on daily blood glucose monitoring. Little is known about the congruence of patients' and professionals' perception of metabolic control in T1DM. OBJECTIVE To assess the actual patients' self-perception and objective assessment (HbA1c) of metabolic control in T1DM children and adolescents and to investigate the possible factors involved in any difference. METHODS Patients with T1DM aged 8 - 18 years were recruited in a cross-sectional, retrospective and prospective cohort study. Data collection consisted of clinical details, measured HbA1c, self-monitored blood glucose values and questionnaires assessing self and professionals' judgment of metabolic control. RESULTS 91 patients participated. Mean HbA1c was 8.03%. HbA1c was higher in patients with a diabetes duration > 2 years (p = 0.025) and in patients of lower socioeconomic level (p = 0.032). No significant correlation was found for self-perception of metabolic control in well and poorly controlled patients. We found a trend towards false-positive memory of the last HbA1c in patients with a HbA1c > 8.5% (p = 0.069) but no difference in patients' knowledge on target HbA1c between well and poorly controlled patients. CONCLUSIONS T1DM patients are aware of a target HbA1c representing good metabolic control. Ill controlled patients appear to have a poorer recollection of their HbA1c. Self-perception of actual metabolic control is similar in well and poorly controlled T1DM children and adolescents. Therefore, professionals should pay special attention that ill controlled T1DM patients perceive their HbA1c correctly.