Current opinion in critical care
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Community-acquired pneumonia remains a prevalent and potentially life-threatening infection. In general, the disease is considered severe when inpatient care including ICU admission is required, and this often suggests a poorer prognosis. Severe community-acquired pneumonia continues to be an important subject of research from different perspectives, including assessment of illness severity, etiology, diagnostic tests, and treatment options. The aim of this descriptive review is to comment on the results of the relevant original articles in this area published since April 1, 2003. ⋯ The usefulness of inflammatory markers to assess the outcome of the disease is unclear. Data on severity scores are conclusive and different validated and simple predictive rules are available for the classification of patients into risk classes. Therapeutic strategies that have been investigated confirm the impact of adequate empiric antibiotic treatment on clinical outcome and the equivalence between short and long courses in the duration of therapy. A definitive beneficial effect of early administration of antimicrobials or the knowledge of the etiology of pneumonia on the clinical course of the disease has not been demonstrated.
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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.
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Despite substantial advances in our understanding of the biology of sepsis and inflammation, improvements in clinical outcomes have been more sporadic and, with few notable exceptions, are related to improvements in supportive care rather than to specific therapies. As a result, morbidity, mortality, and cost remain high. Investigation into the genetic determinants of this response span a broad spectrum and include those aimed at deciphering the mechanisms and involved pathways on a molecular level, to those aiming to identify how genetic variation may be clinically important. While it is clear that gene sequencing and manipulation of experimental models have provided insight into the biology of the inflammatory response to infection, these technologies and their application to the study of naturally occurring human genetic variation have yet to provide the same insight or clinical benefit. The purpose of this review is to summarize what is known about the genetic determinants of the inflammatory response. We make particular reference to this broad scope of investigation introduced above but with a focus on the present status of studies examining the role of human genetic variation in the risk for and outcome from severe bacterial infection, or sepsis. ⋯ Naturally occurring genetic variants in important inflammatory mediators such as TNF-alpha and TLR4 appear to alter inflammatory responses in numerous experimental and a few clinical models of inflammation. However, inconsistencies exist in the literature regarding the association between these genetic variants and disease (eg, sepsis) susceptibility and prognosis. The main limitations relate to the translation of experimental observations into reproducible genotype-phenotype associations. The reasons for these are multifactorial and include deficiencies in study design (insufficient sample size), and the complexities introduced by background genetic heterogeneity.