Current opinion in critical care
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Infections remain an important threat for critically ill patients, and the emergence of antibiotic resistance is increasingly hampering successful treatment. In this review, new aspects of the diagnosis and prevention of ventilator-associated pneumonia and of strategies of antibiotic use to limit the development and spread of resistance are described. ⋯ Recent developments in diagnosis, treatment, and prevention of ventilator-associated pneumonia and strategies to reduce emergence of antibiotic resistance have been reviewed. Whether changes in antibiotic policy will reduce the emergence of antibiotic resistance remains to be determined. In this area, methodologic problems that have been overlooked in many studies have been addressed recently. These issues must be clarified to provide reliable data on the effects of interventions in hospital settings.
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Elevated levels of cardiac troponins, indicative of the presence of cardiac injury, have been reported in critically ill patients. In this review, the incidence, significance, and clinical relevance of elevated troponin levels among this group of patients will be discussed. ⋯ Elevated troponin levels are not only present in patients suffering from acute coronary syndromes but can also be present in critically ill patients. Even minor elevations are specific for myocardial injury. However, every elevated troponin level in the critically ill patient should not be rigorously diagnosed or treated as a myocardial infarction.
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Curr Opin Crit Care · Oct 2004
ReviewSimulation in critical care and trauma education and training.
To review theory and practice of simulation technology in critical care and trauma training. ⋯ Simulation appears poised to revolutionize education, training, and credentialing in critical care, surgery, and anesthesiology. However, advances in computing and technology have outpaced the evaluative and validation studies of simulation-based education.
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Decisions made in critical care are often complicated, requiring an in-depth understanding of the relations between complex diseases, available interventions, and patients with a wide range of characteristics. Standard modeling techniques such as decision trees and statistical modeling have difficulty in capturing these interactions as the complexity of the problem increases. ⋯ Simulation models provide useful tools for organizing and analyzing the interactions between therapies, tradeoffs, and outcomes.