977 resultados para ADAPTIVE SUPPORT VENTILATION
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Acknowledgements This work received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (Grant reference HR09011) and contributing institutions.
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Aims/purpose: Getting off the ventilator is an important patient-centred outcome for patients with acute respiratory failure. It signifies an improvement in patient condition, enables easier communication, reduces fear and anxiety and consequently a reduced requirement for sedatives. Weaning from ventilation therefore is a core ICU nursing task that is addressed in this presentation.
Presentation description: There are different schools of thought on when ventilator weaning begins including: (a) from intubation with titration of support; and (b) only when the patient’s condition improves. There are also different schools of thought on how to wean including gradual reductions in ventilator support to: (a) a low level consistent with extubation; or (b) to a level to attempt a spontaneous breathing trial followed by extubation if successful. Regardless of the approach, what is patient-relevant is the need to determine early when the patient may be ‘ready’ to discontinue ventilation. This time point can be assessed using simple criteria and should involve all ICU staff to the level of their experience. This presentation challenges the notion that only senior nurses or nurses with a ‘weaning course’ should be involved in the weaning process and proposes opportunities for engaging nurses with all levels of experience.
Conclusion: An ICU nursing taskforce that is focused and engaged in determining patient readiness for weaning can make a strong contribution to patient-relevant outcomes.
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Background: Non-invasive ventilation (NIV) is increasingly used in patients with Acute Respiratory Distress Syndrome (ARDS). Whether, during NIV, the categorization of ARDS severity based on the PaO2/FiO2 Berlin criteria is useful is unknown. The evidence supporting NIV use in patients with ARDS remains relatively sparse.
Methods: The Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study described the management of patients with ARDS. This sub-study examines the current practice of NIV use in ARDS, the utility of the PaO2/FiO2 ratio in classifying patients receiving NIV and the impact of NIV on outcome.
Results: Of 2,813 patients with ARDS, 436 (15.5%) were managed with NIV on days 1 and 2 following fulfillment of diagnostic criteria. Classification of ARDS severity based on PaO2/FiO2 ratio was associated with an increase in intensity of ventilatory support, NIV failure, and Intensive Care Unit (ICU) mortality. NIV failure occurred in 22.2% of mild, 42.3% of moderate and 47.1% of patients with severe ARDS. Hospital mortality in patients with NIV success and failure was 16.1 % and 45.4%, respectively. NIV use was independently associated with increased ICU (HR 1.446; [1.159-1.805]), but not hospital mortality. In a propensity matched analysis, ICU mortality was higher in NIV than invasively ventilated patients with a PaO2/FiO2 lower than 150 mmHg.
Conclusions: NIV was used in 15% of patients with ARDS, irrespective of severity category. NIV appears to be associated with higher ICU mortality in patients with a PaO2/FiO2 lower than 150 mmHg.
Trial Registration: ClinicalTrials.gov NCT02010073
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Primary objective: To examine emotional coping and support needs in children of persons with acquired brain injury, with a view to understanding what interventions would be helpful for these children. Design: The study was qualitative, using a thematic analysis approach. Methods and procedure: Six children between 9 and 18 years of age, six parents (three with ABI), and three support workers were interviewed either at home or at a support centre, using a semi-structured interview guide. Results: Children reported using a variety of adaptive and maladaptive emotional coping strategies, but were consistent in expressing a need for credible validation, i.e. sharing experiences with peers. The results are presented under four overarching themes: difficulties faced; emotions experienced; coping strategies; and reported support needs. Conclusions: The results reveal an interaction between the child’s experiences of complex loss that is difficult to acknowledge, emotional distancing between parent and child, and the children’s need for credible validation. All children expressed a desire for talking to peers in a similar situation to themselves, but had not had this opportunity. Interventions should set up such peer interaction to create credible validation for the specific distress suffered by this population.
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As climate change continues to impact socio-ecological systems, tools that assist conservation managers to understand vulnerability and target adaptations are essential. Quantitative assessments of vulnerability are rare because available frameworks are complex and lack guidance for dealing with data limitations and integrating across scales and disciplines. This paper describes a semi-quantitative method for assessing vulnerability to climate change that integrates socio-ecological factors to address management objectives and support decision-making. The method applies a framework first adopted by the Intergovernmental Panel on Climate Change and uses a structured 10-step process. The scores for each framework element are normalized and multiplied to produce a vulnerability score and then the assessed components are ranked from high to low vulnerability. Sensitivity analyses determine which indicators most influence the analysis and the resultant decision-making process so data quality for these indicators can be reviewed to increase robustness. Prioritisation of components for conservation considers other economic, social and cultural values with vulnerability rankings to target actions that reduce vulnerability to climate change by decreasing exposure or sensitivity and/or increasing adaptive capacity. This framework provides practical decision-support and has been applied to marine ecosystems and fisheries, with two case applications provided as examples: (1) food security in Pacific Island nations under climate-driven fish declines, and (2) fisheries in the Gulf of Carpentaria, northern Australia. The step-wise process outlined here is broadly applicable and can be undertaken with minimal resources using existing data, thereby having great potential to inform adaptive natural resource management in diverse locations.
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Non-invasive ventilation (NIV) is the application of a ventilatory support without resorting to invasive methods. Today it’s considered a credible therapeutic option, with enough scientiic evidence to support its application in various situations and clinical settings related to the treatment of acute respiratory disease, as well as chronic respiratory disease. Objectives: Characterize patients undergoing NIV admitted in Unit Intermediate Care (ICU) in the period from October 1st 2015 to June 30th 2016. Methods: Prospective study conducted in ICU between October 2015 and June 2016. In this study were included all patients hospitalized in this unit (ICU) and in that time period a sample of 57 participants was obtained. As data collection instruments we used a questionnaire for sociodemographic and clinical data and the Braden scale. Results: Participants were mostly male 38 (66.7%), the average age 69.5 ± 11.3 years, ranging between 43 and 92 years. They weighed on average 76.6 kg (52 and 150), with an average body mass index of 28.5 kg/m2 (20 to 58.5). With skin intact 28 (49.1%) with abnormal perfusion 12 (21.1%), with altered sensitivity 11 (19.3%) and a high risk of ulcer on the scale of Braden 37 (65%). The admission diagnosis was respiratory failure 33 (57.3%) and had different backgrounds. We used reused mask 53 (93.0%), the average time of NIV was 7.1 days (1-28), 4.8 days of hospitalization (1-18) and an average of 7.8 IPAP pressure. 11 (19.3%) of the participants developed face ulcer pressure.Conclusions: The NIV is used in patients with advanced age, obesity, respiratory failure and high risk of face ulcer development.
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Dissertação para obtenção do grau de Doutor em Design, apresentada na Universidade de Lisboa - Faculdade de Arquitetura.
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Introduction : Les nourrissons, vu la grande compliance de leur cage thoracique, doivent maintenir activement leur volume pulmonaire de fin d’expiration (VPFE). Ceci se fait par interruption précoce de l’expiration, et par le freinage expiratoire au niveau laryngé et par la persistance de la contraction des muscles inspiratoires. Chez les nourrissons ventilés mécaniquement, notre équipe a montré que le diaphragme est activé jusqu’à la fin de l’expiration (activité tonique). Il n’est pas clair si cette activité tonique diaphragmatique compense pour l’absence de freinage laryngé liée à l’intubation endotrachéale. Objectif : Notre objectif est de déterminer si l’activité tonique diaphragmatique persiste après l’extubation chez les nourrissons et si elle peut être observée chez les enfants plus âgés. Méthode : Ceci est une étude observationnelle longitudinale prospective de patients âgés de 1 semaine à 18 ans admis aux soins intensifs pédiatriques (SIP), ventilés mécaniquement pour >24 heures et avec consentement parental. L’activité électrique du diaphragme (AEdi) a été enregistrée à l’aide d’une sonde nasogastrique spécifique à 4 moments durant le séjour aux SIP : en phase aigüe, pré et post-extubation et au congé. L’AEdi a été analysée de façon semi-automatique. L’AEdi tonique a été définie comme l’AEdi durant le dernier quartile de l’expiration. Résultats : 55 patients avec un âge médian de 10 mois (écart interquartile: 1-48) ont été étudiés. Chez les nourrissons (<1an, n=28), l’AEdi tonique en pourcentage de l’activité inspiratoire était de 48% (30-56) en phase aigüe, 38% (25-44) pré-extubation, 28% (17-42) post-extubation et 33% (22-43) au congé des SIP (p<0.05, ANOVA, avec différence significative entre enregistrements 1 et 3-4). Aucun changement significatif n’a été observé pré et post-extubation. L’AEdi tonique chez les patients plus âgés (>1an, n=27) était négligeable en phases de respiration normale (0.6mcv). Par contre, une AEdi tonique significative (>1mcv et >10%) a été observée à au moins un moment durant le séjour de 10 (37%) patients. La bronchiolite est le seul facteur indépendant associé à l’activité tonique diaphragmatique. Conclusion : Chez les nourrissons, l’AEdi tonique persiste après l’extubation et elle peut être réactivée dans certaines situations pathologiques chez les enfants plus âgés. Elle semble être un indicateur de l’effort du patient pour maintenir son VPFE. D’autres études devraient être menées afin de déterminer si la surveillance de l’AEdi tonique pourrait faciliter la détection de situations de ventilation inappropriée.
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To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.
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As users continually request additional functionality, software systems will continue to grow in their complexity, as well as in their susceptibility to failures. Particularly for sensitive systems requiring higher levels of reliability, faulty system modules may increase development and maintenance cost. Hence, identifying them early would support the development of reliable systems through improved scheduling and quality control. Research effort to predict software modules likely to contain faults, as a consequence, has been substantial. Although a wide range of fault prediction models have been proposed, we remain far from having reliable tools that can be widely applied to real industrial systems. For projects with known fault histories, numerous research studies show that statistical models can provide reasonable estimates at predicting faulty modules using software metrics. However, as context-specific metrics differ from project to project, the task of predicting across projects is difficult to achieve. Prediction models obtained from one project experience are ineffective in their ability to predict fault-prone modules when applied to other projects. Hence, taking full benefit of the existing work in software development community has been substantially limited. As a step towards solving this problem, in this dissertation we propose a fault prediction approach that exploits existing prediction models, adapting them to improve their ability to predict faulty system modules across different software projects.
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Over the last decade, there has been a trend where water utility companies aim to make water distribution networks more intelligent in order to improve their quality of service, reduce water waste, minimize maintenance costs etc., by incorporating IoT technologies. Current state of the art solutions use expensive power hungry deployments to monitor and transmit water network states periodically in order to detect anomalous behaviors such as water leakage and bursts. However, more than 97% of water network assets are remote away from power and are often in geographically remote underpopulated areas, facts that make current approaches unsuitable for next generation more dynamic adaptive water networks. Battery-driven wireless sensor/actuator based solutions are theoretically the perfect choice to support next generation water distribution. In this paper, we present an end-to-end water leak localization system, which exploits edge processing and enables the use of battery-driven sensor nodes. Our system combines a lightweight edge anomaly detection algorithm based on compression rates and an efficient localization algorithm based on graph theory. The edge anomaly detection and localization elements of the systems produce a timely and accurate localization result and reduce the communication by 99% compared to the traditional periodic communication. We evaluated our schemes by deploying non-intrusive sensors measuring vibrational data on a real-world water test rig that have had controlled leakage and burst scenarios implemented.
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Introduction : Les nourrissons, vu la grande compliance de leur cage thoracique, doivent maintenir activement leur volume pulmonaire de fin d’expiration (VPFE). Ceci se fait par interruption précoce de l’expiration, et par le freinage expiratoire au niveau laryngé et par la persistance de la contraction des muscles inspiratoires. Chez les nourrissons ventilés mécaniquement, notre équipe a montré que le diaphragme est activé jusqu’à la fin de l’expiration (activité tonique). Il n’est pas clair si cette activité tonique diaphragmatique compense pour l’absence de freinage laryngé liée à l’intubation endotrachéale. Objectif : Notre objectif est de déterminer si l’activité tonique diaphragmatique persiste après l’extubation chez les nourrissons et si elle peut être observée chez les enfants plus âgés. Méthode : Ceci est une étude observationnelle longitudinale prospective de patients âgés de 1 semaine à 18 ans admis aux soins intensifs pédiatriques (SIP), ventilés mécaniquement pour >24 heures et avec consentement parental. L’activité électrique du diaphragme (AEdi) a été enregistrée à l’aide d’une sonde nasogastrique spécifique à 4 moments durant le séjour aux SIP : en phase aigüe, pré et post-extubation et au congé. L’AEdi a été analysée de façon semi-automatique. L’AEdi tonique a été définie comme l’AEdi durant le dernier quartile de l’expiration. Résultats : 55 patients avec un âge médian de 10 mois (écart interquartile: 1-48) ont été étudiés. Chez les nourrissons (<1an, n=28), l’AEdi tonique en pourcentage de l’activité inspiratoire était de 48% (30-56) en phase aigüe, 38% (25-44) pré-extubation, 28% (17-42) post-extubation et 33% (22-43) au congé des SIP (p<0.05, ANOVA, avec différence significative entre enregistrements 1 et 3-4). Aucun changement significatif n’a été observé pré et post-extubation. L’AEdi tonique chez les patients plus âgés (>1an, n=27) était négligeable en phases de respiration normale (0.6mcv). Par contre, une AEdi tonique significative (>1mcv et >10%) a été observée à au moins un moment durant le séjour de 10 (37%) patients. La bronchiolite est le seul facteur indépendant associé à l’activité tonique diaphragmatique. Conclusion : Chez les nourrissons, l’AEdi tonique persiste après l’extubation et elle peut être réactivée dans certaines situations pathologiques chez les enfants plus âgés. Elle semble être un indicateur de l’effort du patient pour maintenir son VPFE. D’autres études devraient être menées afin de déterminer si la surveillance de l’AEdi tonique pourrait faciliter la détection de situations de ventilation inappropriée.
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That humans and animals learn from interaction with the environment is a foundational idea underlying nearly all theories of learning and intelligence. Learning that certain outcomes are associated with specific actions or stimuli (both internal and external), is at the very core of the capacity to adapt behaviour to environmental changes. In the present work, appetitive and aversive reinforcement learning paradigms have been used to investigate the fronto-striatal loops and behavioural correlates of adaptive and maladaptive reinforcement learning processes, aiming to a deeper understanding of how cortical and subcortical substrates interacts between them and with other brain systems to support learning. By combining a large variety of neuroscientific approaches, including behavioral and psychophysiological methods, EEG and neuroimaging techniques, these studies aim at clarifying and advancing the knowledge of the neural bases and computational mechanisms of reinforcement learning, both in normal and neurologically impaired population.
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Numerous types of acute respiratory failure are routinely treated using non-invasive ventilatory support (NIV). Its efficacy is well documented: NIV lowers intubation and death rates in various respiratory disorders. It can be delivered by means of face masks or head helmets. Currently the scientific community’s interest about NIV helmets is mostly focused on optimising the mixing between CO2 and clean air and on improving patient comfort. To this end, fluid dynamic analysis plays a particularly important role and a two- pronged approach is frequently employed. While on one hand numerical simulations provide information about the entire flow field and different geometries, they exhibit require huge temporal and computational resources. Experiments on the other hand help to validate simulations and provide results with a much smaller time investment and thus remain at the core of research in fluid dynamics. The aim of this thesis work was to develop a flow bench and to utilise it for the analysis of NIV helmets. A flow test bench and an instrumented mannequin were successfully designed, produced and put into use. Experiments were performed to characterise the helmet interface in terms of pressure drop and flow rate drop over different inlet flow rates and outlet pressure set points. Velocity measurements by means of Particle Image Velocimetry were performed. Pressure drop and flow rate characteristics from experiments were contrasted with CFD data and sufficient agreement was observed between both numerical and experimental results. PIV studies permitted qualitative and quantitative comparisons with numerical simulation data and offered a clear picture of the internal flow behaviour, aiding the identification of coherent flow features.
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