Reference : Tight Glycemic Control in Intensive Care: From engineering to clinical practice change
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/2268/92781
Tight Glycemic Control in Intensive Care: From engineering to clinical practice change
English
Chase, J. G. [ > > ]
Le Compte, A. J. [ > > ]
Evans, A. [ > > ]
Ward, L. [ > > ]
Steel, J. [ > > ]
Tan, C. S. [ > > ]
Pretty, C. G. [ > > ]
Penning, Sophie mailto [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > Thermodynamique des phénomènes irréversibles >]
Desaive, Thomas mailto [Université de Liège - ULg > Département d'astrophys., géophysique et océanographie (AGO) > Thermodynamique des phénomènes irréversibles >]
Shaw, G. M. [ > > ]
2011
5th European Conference of the International Federation for Medical and Biological Engineering
Yes
Yes
International
5th European Conference of the International Federation for Medical and Biological Engineering
14-18 September, 2011
Budapest
Hungary
[en] ICU ; hypoglycemia ; clinical trials ; modelling ; control systems ; glycemic control ; TGC
[en] Tight glycemic control (TGC) is prevalent in critical care. Providing safe, effective TGC has proven very difficult to achieve with clinically derived protocols. The prob-lem is exacerbated by extreme patient variability and the need to minimize clinical effort and burden. These ingredients make an ideal scenario for model-based methods to provide opti-mised solutions. This paper presents the development, clinical-ly validated virtual trials optimisation, and initial clinical implementation of a stochastic targeted (STAR) TGC method and framework. It is compared to a prior successful, model-derived, less flexible and dynamic TGC protocol (SPRINT). The use of stochastic models to safely forecast a range of glu-cose outcomes over 1-3 hours ensures better performance, more dynamic use of the range of insulin and nutrition inputs and thus better glycemic performance and safety from hypo-glycemia, the latter of which was reduced by 3.0x times. Hence, the paper presents an overall engineering approach to TGC from engineering models to clinical implementation and ongo-ing clinical practice change.
http://hdl.handle.net/2268/92781

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