Journal of critical care
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Journal of critical care · Aug 2012
A model to predict short-term death or readmission after intensive care unit discharge.
Early unplanned readmission to the intensive care unit (ICU) carries a poor prognosis, and post-ICU mortality may be related, in part, to premature ICU discharge. Our objectives were to identify independent risk factors for early post-ICU readmission or death and to construct a prediction model. ⋯ Among patients without treatment-limitation decisions and discharged alive from the ICU, 3.0% died or were readmitted within 7 days. Independent risk factors were indicators of patients' severity and discharge at night. Our prediction model should be evaluated in other ICU populations.
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Journal of critical care · Aug 2012
The early phase of human sepsis is characterized by a combination of apoptosis and proliferation of T cells.
T cell activation as well as unresponsiveness has been described in separate studies in sepsis. Our aim was to establish the coexistence of both T cell fate in human sepsis. ⋯ Concomitant T cell proliferation and T cell apoptosis are observed in human sepsis, being related to a different pathway.
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Journal of critical care · Aug 2012
Model for End-Stage Liver Disease score for predicting outcome in critically ill medical patients with liver cirrhosis.
We hypothesized that the Model for End-Stage Liver Disease (MELD) score at admission to the intensive care unit (ICU) can predict in-hospital mortality for patients with liver cirrhosis. We also tested the MELD-natremia (Na) score and compared the predictive value of the 2 models. ⋯ The MELD scoring system provides useful prognostic information for critically ill patients with liver cirrhosis admitted to an ICU. The MELD and MELD-Na scores had similar predictive value.
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Journal of critical care · Aug 2012
Prognostic models based on administrative data alone inadequately predict the survival outcomes for critically ill patients at 180 days post-hospital discharge.
There is interest in evaluating the quality of critical care by auditing patient outcomes after hospital discharge. Risk adjustment using acuity of illness scores, such as Acute Physiology and Chronic Health Evaluation (APACHE III) scores, derived from clinical databases is commonly performed for in-hospital mortality outcome measures. However, these clinical databases do not routinely track patient outcomes after hospital discharge. Linkage of clinical databases to administrative data sets that maintain records on patient survival after discharge can allow for the measurement of survival outcomes of critical care patients after hospital discharge while using validated risk adjustment methods. ⋯ The addition of APACHE III scores to administrative data substantially improved model performance to the level of the clinical model. Although linking data systems requires some investment, having the ability to evaluate case ascertainment and accurately risk adjust outcomes of intensive care patients after discharge will add valuable insights into clinical audit and decision-making processes.