Article (Scientific journals)
Reducing the impact of insulin sensitivity variability on glycaemic outcomes using separate stochastic models within the STAR glycaemic protocol.
Thomas, Felicity; Pretty, Christopher G.; Fisk, Liam et al.
2014In BioMedical Engineering OnLine, 13, p. 43
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Keywords :
Aged; Blood Glucose/metabolism; Critical Illness; Female; Humans; Insulin Resistance; Intensive Care Units; Male; Middle Aged; Models, Biological; Stochastic Processes
Abstract :
[en] BACKGROUND: The metabolism of critically ill patients evolves dynamically over time. Post critical insult, levels of counter-regulatory hormones are significantly elevated, but decrease rapidly over the first 12-48 hours in the intensive care unit (ICU). These hormones have a direct physiological impact on insulin sensitivity (SI). Understanding the variability of SI is important for safely managing glycaemic levels and understanding the evolution of patient condition. The objective of this study is to assess the evolution of SI over the first two days of ICU stay, and using this data, propose a separate stochastic model to reduce the impact of SI variability during glycaemic control using the STAR glycaemic control protocol. METHODS: The value of SI was identified hourly for each patient using a validated physiological model. Variability of SI was then calculated as the hour-to-hour percentage change in SI. SI was examined using 6 hour blocks of SI to display trends while mitigating the effects of noise. To reduce the impact of SI variability on achieving glycaemic control a new stochastic model for the most variable period, 0-18 hours, was generated. Virtual simulations were conducted using an existing glycaemic control protocol (STAR) to investigate the clinical impact of using this separate stochastic model during this period of increased metabolic variability. RESULTS: For the first 18 hours, over 80% of all SI values were less than 0.5 x 10(-3) L/mU x min, compared to 65% for >18 hours. Using the new stochastic model for the first 18 hours of ICU stay reduced the number of hypoglycaemic measurements during virtual trials. For time spent below 4.4, 4.0, and 3.0 mmol/L absolute reductions of 1.1%, 0.8% and 0.1% were achieved, respectively. No severe hypoglycaemic events (BG < 2.2 mmol/L) occurred for either case. CONCLUSIONS: SI levels increase significantly, while variability decreases during the first 18 hours of a patients stay in ICU. Virtual trials, using a separate stochastic model for this period, demonstrated a reduction in variability and hypoglycaemia during the first 18 hours without adversely affecting the overall level of control. Thus, use of multiple models can reduce the impact of SI variability during model-based glycaemic control.
Disciplines :
Anesthesia & intensive care
Author, co-author :
Thomas, Felicity
Pretty, Christopher G.
Fisk, Liam
Shaw, Geoffrey M.
Chase, J. Geoffrey
Desaive, Thomas  ;  Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Thermodynamique des phénomènes irréversibles
Language :
English
Title :
Reducing the impact of insulin sensitivity variability on glycaemic outcomes using separate stochastic models within the STAR glycaemic protocol.
Publication date :
2014
Journal title :
BioMedical Engineering OnLine
eISSN :
1475-925X
Publisher :
BioMed Central, United Kingdom
Volume :
13
Pages :
43
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 15 September 2014

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