913 resultados para GLUCOSE MONITORING-SYSTEM


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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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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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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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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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Aim: To evaluate OneTouch® Verio™ test strip performance at hypoglycaemic blood glucose (BG) levels (<3.9mmol/L [<70mg/dL]) at seven clinical studies. Methods: Trained clinical staff performed duplicate capillary BG monitoring system tests on 700 individuals with type 1 and type 2 diabetes using blood from a single fingerstick lancing. BG reference values were obtained using a YSI 2300 STAT™ Glucose Analyzer. The number and percentage of BG values within ±0.83. mmol/L (±15. mg/dL) and ±0.56. mmol/L (±10. mg/dL) were calculated at BG concentrations of <3.9. mmol/L (<70. mg/dL), <3.3. mmol/L (<60. mg/dL), and <2.8. mmol/L (<50. mg/dL). Results: At BG concentrations <3.9. mmol/L (<70. mg/dL), 674/674 (100%) of meter results were within ±0.83. mmol/L (±15. mg/dL) and 666/674 (98.8%) were within ±0.56. mmol/L (±10. mg/dL) of reference values. At BG concentrations <3.3. mmol/L (<60. mg/dL), and <2.8. mmol/L (<50. mg/dL), 358/358 (100%) and 270/270 (100%) were within ±0.56. mmol/L (±10. mg/dL) of reference values, respectively. Conclusion: In this analysis of data from seven independent studies, OneTouch Verio test strips provide highly accurate results at hypoglycaemic BG levels. © 2012 Elsevier Ireland Ltd.

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This thesis discusses various aspects of the integrity monitoring of GPS applied to civil aircraft navigation in different phases of flight. These flight phases include en route, terminal, non-precision approach and precision approach. The thesis includes four major topics: probability problem of GPS navigation service, risk analysis of aircraft precision approach and landing, theoretical analysis of Receiver Autonomous Integrity Monitoring (RAIM) techniques and RAIM availability, and GPS integrity monitoring at a ground reference station. Particular attention is paid to the mathematical aspects of the GPS integrity monitoring system. The research has been built upon the stringent integrity requirements defined by civil aviation community, and concentrates on the capability and performance investigation of practical integrity monitoring systems with rigorous mathematical and statistical concepts and approaches. Major contributions of this research are: • Rigorous integrity and continuity risk analysis for aircraft precision approach. Based on the joint probability density function of the affecting components, the integrity and continuity risks of aircraft precision approach with DGPS were computed. This advanced the conventional method of allocating the risk probability. • A theoretical study of RAIM test power. This is the first time a theoretical study on RAIM test power based on the probability statistical theory has been presented, resulting in a new set of RAIM criteria. • Development of a GPS integrity monitoring and DGPS quality control system based on GPS reference station. A prototype of GPS integrity monitoring and DGPS correction prediction system has been developed and tested, based on the A USN A V GPS base station on the roof of QUT ITE Building.

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One of the main challenges of slow speed machinery condition monitoring is that the energy generated from an incipient defect is too weak to be detected by traditional vibration measurements due to its low impact energy. Acoustic emission (AE) measurement is an alternative for this as it has the ability to detect crack initiations or rubbing between moving surfaces. However, AE measurement requires high sampling frequency and consequently huge amount of data are obtained to be processed. It also requires expensive hardware to capture those data, storage and involves signal processing techniques to retrieve valuable information on the state of the machine. AE signal has been utilised for early detection of defects in bearings and gears. This paper presents an online condition monitoring (CM) system for slow speed machinery, which attempts to overcome those challenges. The system incorporates relevant signal processing techniques for slow speed CM which include noise removal techniques to enhance the signal-to-noise and peak-holding down sampling to reduce the burden of massive data handling. The analysis software works under Labview environment, which enables online remote control of data acquisition, real-time analysis, offline analysis and diagnostic trending. The system has been fully implemented on a site machine and contributing significantly to improve the maintenance efficiency and provide a safer and reliable operation.

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Restoring a large-scale power system has always been a complicated and important issue. A lot of research work has been done on different aspects of the whole power system restoration procedure. However, more time will be required to complete the power system restoration process in an actual situation if accurate and real-time system data cannot be obtained. With the development of the wide area monitoring system (WAMS), power system operators are capable of accessing to more accurate data in the restoration stage after a major outage. The ultimate goal of the system restoration is to restore as much load as possible while in the shortest period of time after a blackout, and the restorable load can be estimated by employing WAMS. Moreover, discrete restorable loads are employed considering the limited number of circuit-breaker operations and the practical topology of distribution systems. In this work, a restorable load estimation method is proposed employing WAMS data after the network frame has been reenergized, and WAMS is also employed to monitor the system parameters in case the newly recovered system becomes unstable again. The proposed method has been validated with the New England 39-Bus system and an actual power system in Guangzhou, China.

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Anthropogenic elemental mercury (Hg0) emission is a serious worldwide environmental problem due to the extreme toxicity of the heavy metal to humans, plants and wildlife. Development of an accurate and cheap microsensor based online monitoring system which can be integrated as part of Hg0 removal and control processes in industry is still a major challenge. Here, we demonstrate that forming Au nanospike structures directly onto the electrodes of a quartz crystal microbalance (QCM) using a novel electrochemical route results in a self-regenerating, highly robust, stable, sensitive and selective Hg0 vapor sensor. The data from a 127 day continuous test performed in the presence of volatile organic compounds and high humidity levels, showed that the sensor with an electrodeposted sensitive layer had 260% higher response magnitude, 3.4 times lower detection limit (,22 mg/m3 or ,2.46 ppbv) and higher accuracy (98% Vs 35%) over a Au control based QCM (unmodified) when exposed to a Hg0 vapor concentration of 10.55 mg/m3 at 1016C. Statistical analysis of the long term data showed that the nano-engineered Hg0 sorption sites on the developed Au nanospikes sensitive layer play a critical role in the enhanced sensitivity and selectivity of the developed sensor towards Hg0 vapor.

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This article reports the main features of an innovative full-scale Structural Health Monitoring (SHM) system which has been implemented onto a landmark building on QUT Gardens Point Campus and its efficacy in capturing the recent Queensland earthquakes although they occurred almost 300 km away from where the system is located.

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Many fisheries worldwide have adopted vessel monitoring systems (VMS) for compliance purposes. An added benefit of these systems is that they collect a large amount of data on vessel locations at very fine spatial and temporal scales. This data can provide a wealth of information for stock assessment, research, and management. However, since most VMS implementations record vessel location at set time intervals with no regard to vessel activity, some methodology is required to determine which data records correspond to fishing activity. This paper describes a probabilistic approach, based on hidden Markov models (HMMs), to determine vessel activity. A HMM provides a natural framework for the problem and, by definition, models the intrinsic temporal correlation of the data. The paper describes the general approach that was developed and presents an example of this approach applied to the Queensland trawl fishery off the coast of eastern Australia. Finally, a simulation experiment is presented that compares the misallocation rates of the HMM approach with other approaches.

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Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

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Background. Patients with type 1 diabetes are at markedly increased risk of vascular complications. In this respect it is noteworthy that hyperglycaemia that is shown to cause endothelial dysfunction, has clearly been shown to be a risk factor for diabetic microvascular disease. However, the role of hyperglycaemia as a predictor of macrovascular disease is not as clear as for microvascular disease, although type 1 diabetes itself increases the risk of cardiovascular disease substantially. Furthermore, it is not known whether it is the short-term or the long-term hyperglycaemia that confers possible risk. In addition, the role of glucose variability as a predictor of complications is to a large extent unexplored. Interestingly, although hyperglycaemia increases the risk of pre-eclampsia in women with type 1 diabetes, it is unclear whether pre-eclampsia, a condition characterized by endothelial dysfunction, is also a risk factor for microvascular complication, diabetic nephropathy. Aims. This doctoral thesis investigated the role of acute hyperglycaemia and glucose variability on arterial stiffness and cardiac ventricular repolarisation in male patients with type 1 diabetes as well as in healthy male volunteers. The thesis also explored whether acute hyperglycaemia leads to an inflammatory response, endothelial dysfunction and oxidative stress. Finally, the role of pre-eclampsia, as a predictor of diabetic nephropathy in type 1 diabetes was examined. Subjects and methods. In order to study glucose variability and the daily glycaemic control, 22 male patients with type 1 diabetes, without any diabetic complications, were monitored for 72-h with a continuous glucose monitoring system. At the end of the 72-h glucose monitoring period a 2-h hyperglycaemic clamp was performed both in the patients with type 1 diabetes and in the 13 healthy age-matched male volunteers. Blood pressure, arterial stiffness and QT time were measured to detect vascular changes during acute hyperglycaemia. Blood samples were drawn at baseline (normoglycaemia) and during acute hyperglycaemia. In another patient sample, women with type 1 diabetes were followed during their pregnancy and restudied eleven years later to elucidate the role of pre-eclampsia and pregnancy-induced hypertension as potential risk factors for diabetic nephropathy. Results and conclusions. Acute hyperglycaemia increased arterial stiffness as well as caused a disturbance in the myocardial ventricular repolarisation, emphasizing the importance of a strict daily glycaemic control in male patients with type 1 diabetes. An inflammatory response was also observed during acute hyperglycaemia. Furthermore, a high mean daily blood glucose but not glucose variability per se is associated with arterial stiffness. While glucose variability in turn correlated with central blood pressure, the results suggest that the glucose metabolism is closely linked to the haemodynamic changes in male patients with uncomplicated type 1 diabetes. Notably, the results are not directly applicable to females. Finally, a history of a pre-eclamptic pregnancy, but not pregnancy-induced hypertension was associated with increased risk of diabetic nephropathy.