Crit Care Resusc
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Recently there has been increased focus on improved detection and management of deteriorating patients in Australian hospitals. Since the introduction of the medical emergency team (MET) model there has been an increased role for intensive care unit staff in responding to deterioration of patients in hospital wards. Review and management of MET patients differs from the traditional model of ward patient review, as ICU staff may not know the patient. ⋯ In this article we briefly review the principles of the MET and contend that activation of the MET by ward staff represents a response to a medical crisis. We then outline why MET intervention differs from traditional ward-based doctor-patient encounters, and emphasise the importance of non-technical skills during the MET response. Finally, we suggest ways in which the skills required for crisis resource management within the MET can be taught to ICU staff, and the potential benefits, barriers and difficulties associated with the delivery of such training in New Zealand and Australia.
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To develop an influenza pandemic ICU triage (iPIT) protocol that excludes patients with the highest and lowest predicted mortality rates, and to determine the increase in ICU bed availability that would result. ⋯ The iPIT protocol excludes patients with the lowest and highest ICU mortality, and provides increases in ICU bed availability. Adjusting the lower SOFA score exclusion limit provides a method of escalation or de- escalation to cope with demand.
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Comparative Study
Predicting energy expenditure in sepsis: Harris-Benedict and Schofield equations versus the Weir derivation.
Given the difficulties of using indirect calorimetry in many intensive care units, clinicians routinely employ predictive equations (the Harris-Benedict equation [HBE] and Schofield equation are commonly used) to estimate energy expenditure in critically ill patients. Some extrapolate CO(2) production (V CO(2)) and O(2) consumption (V O(2)) by the Weir derivation to estimate energy expenditure. These derivative methods have not been compared with predictive equations. ⋯ In a cohort of patients with sepsis, TEE values calculated by the HBE and Schofield equation matched reasonably well with MEE values derived from the Weir equation. Correlation was better in patients with less severe sepsis (SIRS and severe sepsis and APACHE II score < 25). Our results suggest that predictive equations have sufficient validity for ongoing regular use in clinical practice.
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To compare patients admitted from the emergency department (ED) directly to a ward (EDWard), the intensive care unit (EDICU) or stepdown (high dependency) unit (EDSDU) with patients admitted via the ED, but whose admission to an ICU (EDWardICU) or SDU (EDWardSDU) was preceded by a ward stay. ⋯ Patients discharged from the ED to a general ward and subsequently to an ICU or SDU had a mortality that exceeded that of ED patients admitted directly to the ICU or SDU. Further investigations are warranted to explain this excess mortality and ascertain the extent of potential preventability.
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There is uncertainty about which end points should be used for Phase II trials in critically ill patients. ⋯ The consensus panel concluded that there are no adequately validated end points for Phase II trials in critically ill patients. However, the following were identified as potential Phase II end points: hospital-free days to Day 90, ICU-free days to Day 28, ventilator-free days to Day 28, cardiovascular support-free days to Day 28, and renal replacement therapy-free days to Day 28. We recommend that these end points be evaluated further.