601 resultados para Medical Monitoring


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This paper describes the experimental evaluation of a novel Autonomous Surface Vehicle capable of navigating complex inland water reservoirs and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran is capable of collecting water column profiles whilst in motion. It is also directly integrated with a reservoir scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper describes the onboard vehicle navigation and control algorithms as well as obstacle avoidance strategies. Experimental results are shown demonstrating its ability to maintain track and avoid obstacles on a variety of large-scale missions and under differing weather conditions, as well as its ability to continuously collect various water quality parameters complimenting traditional manual monitoring campaigns.

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This paper describes a novel Autonomous Surface Vehicle capable of navigating throughout complex inland water storages and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran can collect this information throughout the water column whilst the vehicle is moving. A unique feature of this ASV is its integration into a storage scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper provides an overview of the vehicle design and operation including control, laser-based obstacle avoidance, and vision-based inspection capabilities. Experimental results are shown illustrating its ability to continuously collect key water quality parameters and compliment intensive manual monitoring campaigns.

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Aim The aim of this study was to establish intensive care unit nurses’ knowledge of delirium within an acute tertiary hospital within South East Asia. Background Delirium is a common, life threatening and often preventable cause of morbidity and mortality among older patients. Undetected and untreated delirium is a catalyst to increased mortality, morbidity, functional decline and results in increased requirement for nursing care, healthcare expense and hospital length of stay. However, despite effective assessment tools to identify delirium in the acute setting, there still remains an inability of ICU nurses’ to accurately identify delirium in the critically ill patient especially that of hypoactive delirium. Method A purposive sample of 53 staff nurses from a 13-bedded medical intensive care unit within an acute tertiary teaching hospital in South East Asia were asked to participate. A 40 item 5-point Likert scale questionnaire was employed to determine the participants’ knowledge of the signs and symptoms; the risk factors and negative outcomes of delirium. Results The overall positively answered mean score was 27 (67.3%) out of a possible 40 questions. Mean scores for knowledge of signs and symptoms, risk factors and negative outcomes were 9.52 (63.5%, n = 15), 11.43 (63.5%, n = 17) and 6.0 (75%, n = 8), respectively. Conclusion Whilst the results of this study are similar to others taken from a western perspective, it appeared that the ICU nurses in this study demonstrated limited knowledge of the signs and symptoms, risk factors and negative outcomes of delirium in the critically patient. The implications for practice of this are important given the outcomes of untreated delirium.

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Background Less invasive methods of determining cardiac output are now readily available. Using indicator dilution technique, for example has made it easier to continuously measure cardiac output because it uses the existing intra-arterial line. Therefore gone is the need for a pulmonary artery floatation catheter and with it the ability to measure left atrial and left ventricular work indices as well the ability to monitor and measure a mixed venous saturation (SvO2). Purpose The aim of this paper is to put forward the notion that SvO2 provides valuable information about oxygen consumption and venous reserve; important measures in the critically ill to ensure oxygen supply meets cellular demand. In an attempt to portray this, a simplified example of the septic patient is offered to highlight the changing pathophysiological sequelae of the inflammatory process and its importance for monitoring SvO2. Relevance to clinical practice SvO2 monitoring, it could be argued, provides the gold standard for assessing arterial and venous oxygen indices in the critically ill. For the bedside ICU nurse the plethora of information inherent in SvO2 monitoring could provide them with important data that will assist in averting potential problems with oxygen delivery and consumption. However, it has been suggested that central venous saturation (ScvO2) might be an attractive alternative to SvO2 because of its less invasiveness and ease of obtaining a sample for analysis. There are problems with this approach and these are to do with where the catheter tip is sited and the nature of the venous admixture at this site. Studies have shown that ScvO2 is less accurate than SvO2 and should not be used as a sole guiding variable for decision-making. These studies have demonstrated that there is an unacceptably wide range in variance between ScvO2 and SvO2 and this is dependent on the presenting disease, in some cases SvO2 will be significantly lower than ScvO2. Conclusion Whilst newer technologies have been developed to continuously measure cardiac output, SvO2 monitoring is still an important adjunct to clinical decision-making in the ICU. Given the information that it provides, seeking alternatives such as ScvO2 or blood samples obtained from femorally placed central venous lines, can unnecessarily lead to inappropriate treatment being given or withheld. Instead when using ScvO2, trending of this variable should provide clinical determinates that are useable for the bedside ICU nurse, remembering that in most conditions SvO2 will be approximately 16% lower.

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Background There are few data regarding the effectiveness of remote monitoring for older people with heart failure. We conducted a post-hoc sub-analysis of a previously published large Cochrane systematic review and meta-analysis of relevant randomized controlled trials to determine whether structured telephone support and telemonitoring were effective in this population. Methods A post hoc sub-analysis of a systematic review and meta-analysis that applied the Cochrane methodology was conducted. Meta-analyses of all-cause mortality, all-cause hospitalizations and heart failure-related hospitalizations were performed for studies where the mean or median age of participants was 70 or more years. Results The mean or median age of participants was 70 or more years in eight of the 16 (n=2,659/5,613; 47%) structured telephone support studies and four of the 11 (n=894/2,710; 33%) telemonitoring studies. Structured telephone support (RR 0.80; 95% CI=0.63-1.00) and telemonitoring (RR 0.56; 95% CI=0.41-0.76) interventions reduced mortality. Structured telephone support interventions reduced heart failure-related hospitalizations (RR 0.81; 95% CI=0.67-0.99). Conclusion Despite a systematic bias towards recruitment of individuals younger than the epidemiological average into the randomized controlled trials, older people with heart failure did benefit from structured telephone support and telemonitoring. These post-hoc sub-analysis results were similar to overall effects observed in the main meta-analysis. While further research is required to confirm these observational findings, the evidence at hand indicates that discrimination by age alone may be not be appropriate when inviting participation in a remote monitoring service for heart failure.

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Background Through clinical observation nursing staff of an inpatient rehabilitation unit identified a link between incontinence and undiagnosed urinary tract infections (UTIs). Further, clinical observation and structured continence management led to the realisation that urinary incontinence often improved, or resolved completely, after treatment with antibiotics. In 2009 a small study found that 30% of admitted rehabilitation patients had an undiagnosed UTI, with the majority admitted post-orthopaedic fracture. We suspected that the frequent use of indwelling urinary catheters (IDCs) in the orthopaedic environment may have been a contributing factor. Therefore, a second, more thorough, study was commenced in 2010 and completed in 2011. Aim The aim of this study was to identify what proportion of patients were admitted to one rehabilitation unit with an undiagnosed UTI over a 12-month period. We wanted to identify and highlight the presence of known risk factors associated with UTI and determine whether urinary incontinence was associated with the presence of UTI. Methods Data were collected from every patient that was admitted over a 12-month period (n=140). The majority of patients were over the age of 65 and had an orthopaedic fracture (36.4%) or stroke (27.1%). Mid-stream urine (MSU) samples, routinely collected and sent for culture and sensitivity as part of standard admission procedure, were used by the treating medical officer to detect the presence of UTI. A data collection sheet was developed, reviewed and trialled, before official data collection commenced. Data were collected as part of usual practice and collated by a research assistant. Inferential statistics were used to analyse the data. Results This study found that 25 (17.9%) of the 140 patients admitted to rehabilitation had an undiagnosed UTI, with a statistically significant association between prior presence of an IDC and the diagnosis of UTI. Urinary incontinence improved after the completion of treatment with antibiotics. Results further demonstrated a significant association between the confirmation of a UTI on culture and sensitivity and the absence of symptoms usually associated with UTI, such as burning or stinging on urination. Overall, this study suggests careful monitoring of urinary symptoms in patients admitted to rehabilitation, especially in patients with a prior IDC, is warranted.

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Environmental monitoring is becoming critical as human activity and climate change place greater pressures on biodiversity, leading to an increasing need for data to make informed decisions. Acoustic sensors can help collect data across large areas for extended periods making them attractive in environmental monitoring. However, managing and analysing large volumes of environmental acoustic data is a great challenge and is consequently hindering the effective utilization of the big dataset collected. This paper presents an overview of our current techniques for collecting, storing and analysing large volumes of acoustic data efficiently, accurately, and cost-effectively.

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This paper presents the prototype of an information retrieval system for medical records that utilises visualisation techniques, namely word clouds and timelines. The system simplifies and assists information seeking tasks within the medical domain. Access to patient medical information can be time consuming as it requires practitioners to review a large number of electronic medical records to find relevant information. Presenting a summary of the content of a medical document by means of a word cloud may permit information seekers to decide upon the relevance of a document to their information need in a simple and time effective manner. We extend this intuition, by mapping word clouds of electronic medical records onto a timeline, to provide temporal information to the user. This allows exploring word clouds in the context of a patient’s medical history. To enhance the presentation of word clouds, we also provide the means for calculating aggregations and differences between patient’s word clouds.

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Management of the industrial nations' hazardous waste is a current and exponentially increasing, global threatening situation. Improved environmental information must be obtained and managed concerning the current status, temporal dynamics and potential future status of these critical sites. To test the application of spatial environmental techniques to the problem of hazardous waste sites, as Superfund (CERCLA) test site was chosen in an industrial/urban valley experiencing severe TCE, PCE, and CTC ground water contamination. A paradigm is presented for investigating spatial/environmental tools available for the mapping, monitoring and modelling of the environment and its toxic contaminated plumes. This model incorporates a range of technical issues concerning the collection of data as augmented by remotely sensed tools, the format and storage of data utilizing geographic information systems, and the analysis and modelling of environment through the use of advance GIS analysis algorithms and geophysic models of hydrologic transport including statistical surface generation. This spatial based approach is evaluated against the current government/industry standards of operations. Advantages and lessons learned of the spatial approach are discussed.

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Experience gained from numerous projects conducted by the U.S. Environmental Protection Agency's (EPA) Environmental Monitoring Systems Laboratory in Las Vegas, Nevada has provided insight to functional issues of mapping, monitoring, and modeling of wetland habitats. Three case studies in poster form describe these issues pertinent to managing wetland resources as mandated under Federal laws. A multiphase project was initiated by the EPA Alaska operations office to provide detailed wetland mapping of arctic plant communities in an area under petroleum development pressure. Existing classification systems did not meet EPA needs. Therefore a Habitat Classification System (HCS) derived from aerial photography was compiled. In conjunction with this photointerpretive keys were developed. These products enable EPA personnel to map large inaccessible areas of the arctic coastal plain and evaluate the sensitivity of various wetland habitats relative to petroleum development needs.

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Across the lifespan traumatic experiences are common with more people experiencing such events than not. Within the context of being a medical professional trauma may result from a direct experience (e.g., in a person’s personal life) but may also occur vicariously. For example, a medical professional may be traumatized during the course of their employ as they come to the aid of a trauma survivor. Although there can be long term negative sequale for trauma survivors (e.g., PTSD, depression), the majority of people who experience trauma, vicariously or otherwise, are resilient to long term effects and some people grow or develop beyond their pre-event level of functioning. Therefore, in addition to interest in antecedents and correlates of pathology, research examining the predictors and correlates of resilience and growth has gained notable attention. In this chapter the fundamental assumptions of the salutogenic theory are discussed. Salutogenisis refers to the study of the origins of health and to that end has a goal to determine factors involved in promoting and maintaining health. The chapter then goes on to describe posttraumatic growth, a term used to denote positive post-trauma changes as well as resilience including discussion of the similarities and differences between these two constructs. Ways of promoting growth and resilience in medical professionals are then identified. The chapter concludes with discussion of ways in which individuals can enhance their potential for growth and also of ways in which the organization they work for can best facilitate and promote resilience and growth in its employees.

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Background Cancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities. Aims In this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated. Method A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes. Results Death certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM) classifier achieved best performance with an overall F-measure of 0.9866 when evaluated on a set of 5,000 free-text death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032) and false negative rate (0.0297) while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers. Conclusion The selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with an SVM classifier.

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Increasing the importance and use of infrastructures such as bridges, demands more effective structural health monitoring (SHM) systems. SHM has well addressed the damage detection issues through several methods such as modal strain energy (MSE). Many of the available MSE methods either have been validated for limited type of structures such as beams or their performance is not satisfactory. Therefore, it requires a further improvement and validation of them for different types of structures. In this study, an MSE method was mathematically improved to precisely quantify the structural damage at an early stage of formation. Initially, the MSE equation was accurately formulated considering the damaged stiffness and then it was used for derivation of a more accurate sensitivity matrix. Verification of the improved method was done through two plane structures: a steel truss bridge and a concrete frame bridge models that demonstrate the framework of a short- and medium-span of bridge samples. Two damage scenarios including single- and multiple-damage were considered to occur in each structure. Then, for each structure, both intact and damaged, modal analysis was performed using STRAND7. Effects of up to 5 per cent noise were also comprised. The simulated mode shapes and natural frequencies derived were then imported to a MATLAB code. The results indicate that the improved method converges fast and performs well in agreement with numerical assumptions with few computational cycles. In presence of some noise level, it performs quite well too. The findings of this study can be numerically extended to 2D infrastructures particularly short- and medium-span bridges to detect the damage and quantify it more accurately. The method is capable of providing a proper SHM that facilitates timely maintenance of bridges to minimise the possible loss of lives and properties.

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Measurement of the moisture variation in soils is required for geotechnical design and research because soil properties and behavior can vary as moisture content changes. The neutron probe, which was developed more than 40 years ago, is commonly used to monitor soil moisture variation in the field. This study reports a full-scale field monitoring of soil moisture using a neutron moisture probe for a period of more than 2 years in the Melbourne (Australia) region. On the basis of soil types available in the Melbourne region, 23 sites were chosen for moisture monitoring down to a depth of 1500 mm. The field calibration method was used to develop correlations relating the volumetric moisture content and neutron counts. Observed results showed that the deepest “wetting front” during the wet season was limited to the top 800 to 1000 mm of soil whilst the top soil layer down to about 550mmresponded almost immediately to the rainfall events. At greater depths (550 to 800mmand below 800 mm), the moisture variations were relatively low and displayed predominantly periodic fluctuations. This periodic nature was captured with Fourier analysis to develop a cyclic moisture model on the basis of an analytical solution of a one-dimensional moisture flow equation for homogeneous soils. It is argued that the model developed can be used to predict the soil moisture variations as applicable to buried structures such as pipes.

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Phase behavior of CO2 confined in porous fractal silica with volume fraction of SiO2 φs = 0.15 was investigated using small-angle neutron scattering (SANS) and ultrasmall-angle neutron scattering (USANS) techniques. The range of fluid densities (0<(FCO2)bulk<0.977 g/cm3) and temperatures (T=22 °C, 35 and 60 °C) corresponded to gaseous, liquid, near critical and supercritical conditions of the bulk fluid. The results revealed formation of a dense adsorbed phase in small pores with sizes D<40 A° at all temperatures. At low pressure (P <55 bar, (FCO2)bulk <0.2 g/cm3) the average fluid density in pores may exceed the density of bulk fluid by a factor up to 6.5 at T=22 °C. This “enrichment factor” gradually decreases with temperature, however significant fluid densification in small pores still exists at temperature T=60°C, i.e., far above the liquid-gas critical temperature of bulk CO2 (TC=31.1 °C). Larger pores are only partially filled with liquid-like adsorbed layer which coexists with unadsorbed fluid in the pore core. With increasing pressure, all pores become uniformly filled with the fluid, showing no measurable enrichment or depletion of the porous matrix with CO2.