5 resultados para Critical clearing time

em Universidade do Minho


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Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.

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The evolution of the construction caused a need to use more effective equipments, capable of meeting the increasingly demanding deadlines for the completion of works. In this context, the safety and efficiency of equipment have become key aspects in order to optimize the execution time of the works, as well as reducing labor costs and loss of materials. With the evolution of construction and construction processes, cranes have come to represent a signal of the construction of buildings, revealing to be, in most of the cases, the main equipment of construction sites. Currently, some engineers revels some apprehension regarding the use and handling of cranes which is natural and acceptable, since an equipment failure can lead to serious or fatal accidents. The factors affecting safety management of the cranes in construction sites were investigated, identified, classified and evaluated according to their degree of importance, through interviews with representatives of the general contractors of a set of selected construction sites.

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The analysis of journalistic discourse and its social embeddedness has known significant advances in the last two decades, especially due to the emergence and development of Critical Discourse Analysis. However, three important aspects remain under-researched: the time plane in discourse analysis, the discursive strategies of social actors, and the extra- and supra-textual effects of mediated discourse. Firstly, understanding the biography of public matters requires a longitudinal examination of mediated texts and their social contexts but most forms of analysis of journalistic discourse do not account for the time sequence of texts and its implications. Secondly, as the media representation of social issues is, to a large extent, a function of the discursive construction of events, problems and positions by social actors, the discursive strategies that they employ in a variety of arenas and channels ‘‘before’’ and ‘‘after’’ journalistic texts need to be examined. Thirdly, the fact that many of the modes of operation of discourse are extra- or supra-textual calls for a consideration of various social processes ‘‘outside’’ the text. This paper aims to produce a theoretical and methodological contribution to the integration of these issues in discourse analysis by proposing a framework that combines a textual dimension with a contextual one

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Mechanical Ventilation is an artificial way to help a Patient to breathe. This procedure is used to support patients with respiratory diseases however in many cases it can provoke lung damages, Acute Respiratory Diseases or organ failure. With the goal to early detect possible patient breath problems a set of limit values was defined to some variables monitored by the ventilator (Average Ventilation Pressure, Compliance Dynamic, Flow, Peak, Plateau and Support Pressure, Positive end-expiratory pressure, Respiratory Rate) in order to create critical events. A critical event is verified when a patient has a value higher or lower than the normal range defined for a certain period of time. The values were defined after elaborate a literature review and meeting with physicians specialized in the area. This work uses data streaming and intelligent agents to process the values collected in real-time and classify them as critical or not. Real data provided by an Intensive Care Unit were used to design and test the solution. In this study it was possible to understand the importance of introduce critical events for Mechanically Ventilated Patients. In some cases a value is considered critical (can trigger an alarm) however it is a single event (instantaneous) and it has not a clinical significance for the patient. The introduction of critical events which crosses a range of values and a pre-defined duration contributes to improve the decision-making process by decreasing the number of false positives and having a better comprehension of the patient condition.

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The data acquisition process in real-time is fundamental to provide appropriate services and improve health professionals decision. In this paper a pervasive adaptive data acquisition architecture of medical devices (e.g. vital signs, ventilators and sensors) is presented. The architecture was deployed in a real context in an Intensive Care Unit. It is providing clinical data in real-time to the INTCare system. The gateway is composed by several agents able to collect a set of patients’ variables (vital signs, ventilation) across the network. The paper shows as example the ventilation acquisition process. The clients are installed in a machine near the patient bed. Then they are connected to the ventilators and the data monitored is sent to a multithreading server which using Health Level Seven protocols records the data in the database. The agents associated to gateway are able to collect, analyse, interpret and store the data in the repository. This gateway is composed by a fault tolerant system that ensures a data store in the database even if the agents are disconnected. The gateway is pervasive, universal, and interoperable and it is able to adapt to any service using streaming data.