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TitleCritical events in mechanically ventilated patients
Author(s)Portela, Filipe
Santos, Manuel
Machado, José Manuel
Abelha, António
Silva, Álvaro
Rua, Fernando
KeywordsCritical Events
Intensive Care
Ventilated Patients
Data Acquisition
Real - Time
Streaming Data
Issue date2016
PublisherSpringer Verlag
JournalAdvances in Intelligent Systems and Computing
CitationPortela, F., Santos, M. F., Machado, J., Abelha, A., Silva, Á., & Rua, F. (2016). Critical Events in Mechanically Ventilated Patients. In New Advances in Information Systems and Technologies (pp. 589-598). Springer International Publishing
Abstract(s)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.
TypeConference paper
Publisher version
AccessOpen access
Appears in Collections:CAlg - Livros e capítulos de livros/Books and book chapters

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