841 resultados para Continuous Subcutaneous Glucose Monitoring System


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Background Although both strength training (ST) and endurance training (ET) seem to be beneficial in type 2 diabetes mellitus (T2D), little is known about post-exercise glucose profiles. The objective of the study was to report changes in blood glucose (BG) values after a 4-month ET and ST programme now that a device for continuous glucose monitoring has become available. Materials and methods Fifteen participants, comprising four men age 56.5 +/- 0.9 years and 11 women age 57.4 +/- 0.9 years with T2D, were monitored with the MiniMed (Northridge, CA, USA) continuous glucose monitoring system (CGMS) for 48 h before and after 4 months of ET or ST. The ST consisted of three sets at the beginning, increasing to six sets per week at the end of the training period, including all major muscle groups and ET performed with an intensity of maximal oxygen uptake of 60% and a volume beginning at 15 min and advancing to a maximum of 30 min three times a week. Results A total of 17 549 single BG measurements pretraining (619.7 +/- 39.8) and post-training (550.3 +/- 30.1) were recorded, correlating to an average of 585 +/- 25.3 potential measurements per participant at the beginning and at the end of the study. The change in BG-value between the beginning (132 mg dL(-1)) and the end (118 mg dL(-1)) for all participants was significant (P = 0.028). The improvement in BG-value for the ST programme was significant (P = 0.02) but for the ET no significant change was measured (P = 0.48). Glycaemic control improved in the ST group and the mean BG was reduced by 15.6% (Cl 3-25%). Conclusion In conclusion, the CGMS may be a useful tool in monitoring improvements in glycaemic control after different exercise programmes. Additionally, the CGMS may help to identify asymptomatic hypoglycaemia or hyperglycaemia after training programmes.

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Background: This pilot study aimed to verify if glycemic control can be achieved in type 2 diabetes patients after acute myocardial infarction (AMI), using insulin glargine (iGlar) associated with regular insulin (iReg), compared with the standard intensive care unit protocol, which uses continuous insulin intravenous delivery followed by NPH insulin and iReg (St. Care). Patients and Methods: Patients (n = 20) within 24 h of AMI were randomized to iGlar or St. Care. Therapy was guided exclusively by capillary blood glucose (CBG), but glucometric parameters were also analyzed by blinded continuous glucose monitoring system (CGMS). Results: Mean glycemia was 141 +/- 39 mg/dL for St. Care and 132 +/- 42 mg/dL for iGlar by CBG or 138 +/- 35 mg/dL for St. Care and 129 +/- 34 mg/dL for iGlar by CGMS. Percentage of time in range (80-180 mg/dL) by CGMS was 73 +/- 18% for iGlar and 77 +/- 11% for St. Care. No severe hypoglycemia (<= 40 mg/dL) was detected by CBG, but CGMS indicated 11 (St. Care) and seven (iGlar) excursions in four subjects from each group, mostly in sulfonylurea users (six of eight patients). Conclusions: This pilot study suggests that equivalent glycemic control without increase in severe hyperglycemia may be achieved using iGlar with background iReg. Data outputs were controlled by both CBG and CGMS measurements in a real-life setting to ensure reliability. Based on CGMS measurements, there were significant numbers of glycemic excursions outside of the target range. However, this was not detected by CBG. In addition, the data indicate that previous use of sulfonylurea may be a potential major risk factor for severe hypoglycemia irrespective of the type of insulin treatment.

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Marathon running is growing in popularity, and many diabetic patients are participating in various marathon races all over the world each year. This study aimed to investigate the prevalence and extent of glycemic excursions (hypo- and hyperglycemic) during a marathon run in patients with well-controlled diabetes mellitus using a continuous glucose monitoring system (CGMS). Five subjects with type 1 and one patient with type 2 diabetes mellitus were monitored with the Medtronic MiniMed CGMS during the 2002 Vienna City Marathon (n = 3) or the Fernwarme run (n = 3) long distance runs of 42.19/15.8 km. All six patients finished their course. The CGSM system was well tolerated in all patients over an average duration of 34 +/- 4.0 hours and it did not limit the patients' activities. The mean running time for the Vienna city marathon was 257 +/- 8 min (247 to 274 min) and for the Fernwarme run 134 +/- 118 min (113 to 150 min). A total of 1470 blood glucose measurements (mean 245 readings per subject) were performed. During and after the marathons frequent hypo and hyperglycemic episodes with and without clinical symptoms were measured. Our data confirm that the CGMS may help to identify asymptomatic hypoglycemia or hyperglycemia during and after a long distance run. The system may also be helpful to improve our understanding about the individual changes of glucose during and after a marathon and may protect hypoglycemic or hyperglycemic periods in future races.

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Introducción: El tiempo promedio del efecto máximo de la insulina regular rápida en la glucemia postprandial ha sido considerado durante años de 120 minutos. En pacientes con Diabetes Mellitus (DM) que usan insulinas análogas este tiempo y los factores asociados no se encuentran reportados para ser aplicados en el automonitoreo. El objetivo de este estudio fue calcular el tiempo y factores relacionados al efecto máximo de la insulina en la glucemia postprandial. Metodología: Se desarrolló un estudio longitudinal retrospectivo a partir de una fuente secundaria donde se realizó un análisis descriptivo y bivariado con las variables demográficas y clínicas presentes en la población. Resultados: El tiempo promedio del pico máximo de insulina en pacientes con DM1 fue de 78.4 (DE± 16.512) y DM2 75.01(DE± 12.02) minutos. El 75% de la población con DM1 y el 54.2% en DM2 era de sexo femenino, la edad promedio en DM1 era 42.38 años y en DM2 68 años, en cuanto a la categorización del IMC el 50% de la población en DM1 y el 37.5% en DM2 estaban dentro del rango de obesidad y se encontró una relación con respecto al tipo de comida “desayuno-cena” vs el tiempo promedio del efecto máximo de la insulina calculado para ambos grupos (p:0.010). Conclusiones: El tiempo promedio del efecto máximo de la insulina calculado fue menor al tiempo reportado en la literatura clínica de 120 minutos. El tipo de comida principal mostró una relación con el tiempo promedio del efecto máximo en ambos grupos.

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OBJECTIVE - To evaluate an algorithm guiding responses of continuous subcutaneous insulin infusion (CSII)-treated type 1 diabetic patients using real-time continuous glucose monitoring (RT-CGM). RESEARCH DESIGN AND METHODS - Sixty CSII-treated type 1 diabetic participants (aged 13-70 years, including adult and adolescent subgroups, with A1C =9.5%) were randomized in age-, sex-, and A1C-matched pairs. Phase 1 was an open 16-week multicenter randomized controlled trial. Group A was treated with CSII/RT-CGM with the algorithm, and group B was treated with CSII/RT-CGM without the algorithm. The primary outcome was the difference in time in target (4-10 mmol/l) glucose range on 6-day masked CGM. Secondary outcomes were differences in A1C, low (=3.9 mmol/l) glucose CGM time, and glycemic variability. Phase 2 was the week 16-32 follow-up. Group A was returned to usual care, and group B was provided with the algorithm. Glycemia parameters were as above. Comparisons were made between baseline and 16 weeks and 32 weeks. RESULTS - In phase 1, after withdrawals 29 of 30 subjects were left in group A and 28 of 30 subjects were left in group B. The change in target glucose time did not differ between groups. A1C fell (mean 7.9% [95% CI 7.7-8.2to 7.6% [7.2-8.0]; P <0.03) in group A but not in group B (7.8% [7.5-8.1] to 7.7 [7.3-8.0]; NS) with no difference between groups. More subjects in group A achieved A1C =7% than those in group B (2 of 29 to 14 of 29 vs. 4 of 28 to 7 of 28; P = 0.015). In phase 2, one participant was lost from each group. In group A, A1C returned to baseline with RT-CGM discontinuation but did not change in group B, who continued RT-CGM with addition of the algorithm. CONCLUSIONS - Early but not late algorithm provision to type 1 diabetic patients using CSII/RT-CGM did not increase the target glucose time but increased achievement of A1C =7%. Upon RT-CGM cessation, A1C returned to baseline. © 2010 by the American Diabetes Association.

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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.

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In the structural health monitoring (SHM) field, long-term continuous vibration-based monitoring is becoming increasingly popular as this could keep track of the health status of structures during their service lives. However, implementing such a system is not always feasible due to on-going conflicts between budget constraints and the need of sophisticated systems to monitor real-world structures under their demanding in-service conditions. To address this problem, this paper presents a comprehensive development of a cost-effective and flexible vibration DAQ system for long-term continuous SHM of a newly constructed institutional complex with a special focus on the main building. First, selections of sensor type and sensor positions are scrutinized to overcome adversities such as low-frequency and low-level vibration measurements. In order to economically tackle the sparse measurement problem, a cost-optimized Ethernet-based peripheral DAQ model is first adopted to form the system skeleton. A combination of a high-resolution timing coordination method based on the TCP/IP command communication medium and a periodic system resynchronization strategy is then proposed to synchronize data from multiple distributed DAQ units. The results of both experimental evaluations and experimental–numerical verifications show that the proposed DAQ system in general and the data synchronization solution in particular work well and they can provide a promising cost-effective and flexible alternative for use in real-world SHM projects. Finally, the paper demonstrates simple but effective ways to make use of the developed monitoring system for long-term continuous structural health evaluation as well as to use the instrumented building herein as a multi-purpose benchmark structure for studying not only practical SHM problems but also synchronization related issues.

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Background. Continuous subcutaneous insulin infusion (CSII) treatment among children with type 1 diabetes is increasing in Sweden. However, studies evaluating glycaemic control in children using CSII show inconsistent results. Omitting bolus insulin doses using CSII may cause reduced glycaemic control among adolescents. The distribution of responsibility for diabetes self-management between children and parents is often unclear and needs clarification. There is much published support for continued parental involvement and shared diabetes management during adolescence. Guided Self-Determination (GSD) is an empowerment-based, person-centred, reflection and problem solving method intended to guide the patient to become self-sufficient and develop life skills for managing difficulties in diabetes self-management. This method has been adapted for adolescents and parents as Guided Self-Determination-Young (GSD-Y). This study aims to evaluate the effect of an intervention with GSD-Y in groups of adolescents starting on insulin pumps and their parents on diabetes-related family conflicts, perceived health and quality of life (QoL), and metabolic control. Here, we describe the protocol and plans for study enrolment. Methods. This study is designed as a randomized, controlled, prospective, multicentre study. Eighty patients between 12-18 years of age who are planning to start CSII will be included. All adolescents and their parents will receive standard insulin pump training. The education intervention will be conducted when CSII is to be started and at four appointments in the first 4 months after starting CSII. The primary outcome is haemoglobin A1c levels. Secondary outcomes are perceived health and QoL, frequency of blood glucose self-monitoring and bolus doses, and usage of carbohydrate counting. The following instruments will be used to evaluate perceived health and QoL: Disabkids, 'Check your health', the Diabetes Family Conflict Scale and the Swedish Diabetes Empowerment Scale. Outcomes will be evaluated within and between groups by comparing data at baseline, and at 6 and 12 months after starting treatment. Results and discussion. In this study, we will assess the effect of starting an insulin pump together with the model of Guided Self-Determination to determine whether this approach leads to retention of improved glycaemic control, QoL, responsibility distribution and reduced diabetes-related conflicts in the family. Trial registration: Current controlled trials: ISRCTN22444034

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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.

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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.

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Resumen de la comunicación presentada en PIC2015 – the 14th International Congress on Combustion By-Products and Their Health Effects, Umeå, Sweden, 14-17 June 2015.