Critical care : the official journal of the Critical Care Forum
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Comparative Study
Patients' recollections of experiences in the intensive care unit may affect their quality of life.
We wished to obtain the experiences felt by patients during their ICU stay using an original questionnaire and to correlate the memories of those experiences with health-related quality of life (HR-QOL). ⋯ This study suggests that neuropsychological consequences of critical illness, in particular the recollection of ICU experiences, may influence subsequent HR-QOL.
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Acid-base abnormalities are common in the critically ill. The traditional classification of acid-base abnormalities and a modern physico-chemical method of categorizing them will be explored. Specific disorders relating to mortality prediction in the intensive care unit are examined in detail. Lactic acidosis, base excess, and a strong ion gap are highlighted as markers for increased risk of death.
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Comparative Study
Intensive care unit-acquired urinary tract infections in a regional critical care system.
Few studies have evaluated urinary tract infections (UTIs) specifically acquired within intensive care units (ICUs), and the effect of such infections on patient outcome is unclear. The objectives of this study were to describe the occurrence, microbiology, and risk factors for acquiring UTIs in the ICU and to determine whether these infections independently increase mortality. ⋯ Development of an ICU-acquired UTI is common in critically ill patients. Although a marker of increased morbidity associated with critical illness, it is not a significant attributable cause of mortality.
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Comment Comparative Study
Artificial neural networks as prediction tools in the critically ill.
The past 25 years have witnessed the development of improved tools with which to predict short-term and long-term outcomes after critical illness. The general paradigm for constructing the best known tools has been the logistic regression model. Recently, a variety of alternative tools, such as artificial neural networks, have been proposed, with claims of improved performance over more traditional models in particular settings. However, these newer methods have yet to demonstrate their practicality and usefulness within the context of predicting outcomes in the critically ill.
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Cardiovascular failure is one of the central therapeutic problems in patients with severe infection. Although norepinephrine is a potent and, in most cases, highly effective vasopressor agent, very high dosages leading to significant side effects can be necessary to stabilize advanced shock. As a supplementary vasopressor, arginine vasopressin can reverse hemodynamic failure and significantly decrease norepinephrine dosages. Whether the promising possibility of 'bridging' advanced septic shock when the benefit/risk ratio of catecholamine therapy leaves a clinically tolerable range may improve quantitative and qualitative patient outcome can only be determined by a large, prospective, randomized study.