Optimal management of the critically Ill: Anaesthesia, monitoring, data capture, and point-of-care technological practices in ovine models of critical care

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Chemonges, Saul
Shekar, Kiran
Tung, John-Paul
Dunster, Kimble R
Diab, Sara
Platts, David
Watts, Ryan P
Gregory, Shaun D
Foley, Samuel
Simonova, Gabriela
McDonald, Charles
Hayes, Rylan
Bellpart, Judith
Timms, Daniel
Chew, Michelle
Fung, Yoke L
Toon, Michael
Maybauer, Marc O
Fraser, John F
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2014
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Abstract

Animal models of critical illness are vital in biomedical research. They provide possibilities for the investigation of pathophysiological processes that may not otherwise be possible in humans. In order to be clinically applicable, the model should simulate the critical care situation realistically, including anaesthesia, monitoring, sampling, utilising appropriate personnel skill mix, and therapeutic interventions. There are limited data documenting the constitution of ideal technologically advanced large animal critical care practices and all the processes of the animal model. In this paper, we describe the procedure of animal preparation, anaesthesia induction and maintenance, physiologic monitoring, data capture, point-of-care technology, and animal aftercare that has been successfully used to study several novel ovine models of critical illness. The relevant investigations are on respiratory failure due to smoke inhalation, transfusion related acute lung injury, endotoxin-induced proteogenomic alterations, haemorrhagic shock, septic shock, brain death, cerebral microcirculation, and artificial heart studies. We have demonstrated the functionality of monitoring practices during anaesthesia required to provide a platform for undertaking systematic investigations in complex ovine models of critical illness.

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BioMed Research International

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2014

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© 2014 Saul Chemonges et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Biological sciences

Information and computing sciences

Medical biotechnology not elsewhere classified

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