Literature DB >> 17271031

Adaptive bolus-based set-point regulation of hyperglycemia in critical care.

J Lin1, J G Chase, G M Shaw, C V Doran, C E Hann, M B Robertson, P M Browne, T Lotz, G C Wake, B Broughton.   

Abstract

Critically ill patients are often hyperglycemic and extremely diverse in their dynamics. Consequently, fixed protocols and sliding scales can result in error and poor control. A two-compartment glucose-insulin system model that accounts for time-varying insulin sensitivity and endogenous glucose removal, along with two different saturation kinetics is developed and verified in proof-of-concept clinical trials for adaptive control of hyperglycemia. The adaptive control algorithm monitors the physiological status of a critically ill patient, allowing real-time tight glycemic regulation. The bolus-based insulin administration approach is shown to result in safe, targeted stepwise glycemic reduction for three critically ill patients.

Entities:  

Year:  2004        PMID: 17271031     DOI: 10.1109/IEMBS.2004.1403972

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  The parameter Houlihan: A solution to high-throughput identifiability indeterminacy for brutally ill-posed problems.

Authors:  David J Albers; Matthew E Levine; Lena Mamykina; George Hripcsak
Journal:  Math Biosci       Date:  2019-08-24       Impact factor: 2.144

2.  Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and phenotype.

Authors:  David J Albers; Matthew E Levine; Andrew Stuart; Lena Mamykina; Bruce Gluckman; George Hripcsak
Journal:  J Am Med Inform Assoc       Date:  2018-10-01       Impact factor: 4.497

  2 in total

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