Critical care : the official journal of the Critical Care Forum
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Many approaches have been examined to try to predict patient outcome after cardiopulmonary resuscitation. It has been shown that plasma DNA could predict mortality in critically ill patients but no data are available regarding its clinical value in patients after out-of-hospital cardiac arrest. In this study we investigated whether plasma DNA on arrival at the emergency room may be useful in predicting the outcome of these patients. ⋯ Plasma DNA levels may be a useful biomarker in predicting outcome after out-of hospital cardiac arrest.
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Comparative Study
Nitroglycerin can facilitate weaning of difficult-to-wean chronic obstructive pulmonary disease patients: a prospective interventional non-randomized study.
Both experimental and clinical data give convincing evidence to acute cardiac dysfunction as the origin or a cofactor of weaning failure in patients with chronic obstructive pulmonary disease. Therefore, treatment targeting the cardiovascular system might help the heart to tolerate more effectively the critical period of weaning. This study aims to assess the hemodynamic, respiratory and clinical effects of nitroglycerin infusion in difficult-to-wean patients with severe chronic obstructive pulmonary disease. ⋯ In this clinical setting, nitroglycerin infusion can expedite the weaning by restoring weaning-induced cardiovascular compromise.
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Sepsis is a serious medical condition that requires rapidly administered, appropriate antibiotic treatment. Conventional methods take three or more days for final pathogen identification and antimicrobial susceptibility testing. We organized a prospective observational multicenter study in three study sites to evaluate the diagnostic accuracy and potential clinical utility of the SeptiFast system, a multiplex pathogen detection system used in the clinical setting to support early diagnosis of bloodstream infections. ⋯ This rapid multiplex pathogen detection system complemented traditional culture-based methods and offered some added diagnostic value for the timely detection of causative pathogens, particularly in antibiotic pre-treated patients. Adequately designed intervention studies are needed to prove its clinical effectiveness in improving appropriate antibiotic selection and patient outcomes.
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While animal studies indicate that controlled mechanical ventilation (MV) induces diaphragm weakness and myofiber atrophy, there are no data in humans that confirm MV per se produces diaphragm weakness. Whether or not diaphragm weakness results from MV, sepsis, corticosteroids, hyperglycemia, or a combination of these factors, however, is not the most important issue raised by the recent study from Hermans and colleagues. This study makes an important contribution by providing additional evidence that many critically ill patients have profound diaphragm weakness. If diaphragm weakness of this magnitude is present in most mechanically ventilated patients, a strong argument can be made that respiratory muscle weakness is a major contributor to respiratory failure.
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Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome. ⋯ Here we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients.