Literature DB >> 27811342

Model-based glycaemic control: methodology and initial results from neonatal intensive care.

Jennifer L Dickson1, J Geoffrey Chase2, Adrienne Lynn3, Geoffrey M Shaw4.   

Abstract

Very/extremely premature infants often experience glycaemic dysregulation, resulting in abnormally elevated (hyperglycaemia) or low (hypoglycaemia) blood glucose (BG) concentrations, due to prematurity, stress, and illness. STAR-GRYPHON is a computerised protocol that utilises a model-based insulin sensitivity parameter to directly tailor therapy for individual patients and their changing conditions, unlike other common insulin protocols in this cohort. From January 2013 to January 2015, 13 patients totalling 16 hyperglycaemic control episodes received insulin under STAR-GRYPHON. A significant improvement in control was achieved in comparison to a retrospective cohort, with a 26% absolute improvement in BG within the targeted range and no hypoglycaemia. This improvement was obtained predominantly due to the reduction of hyperglycaemia (%BG>10.0 mmol/l: 5.6 vs. 17.7%, p<0.001), and lowering of the median per-patient BG [6.9 (6.1-7.9) vs. 7.8 (6.6-9.1) mmol/l, p<0.001, Mann-Witney U test]. While cohort-wide control results show good control overall, there is high intra-patient variability in BG behaviour, resulting in overly conservative treatments for some patients. Patient insulin sensitivity differs between and within patients over time, with some patients having stable insulin sensitivity, while others change rapidly. These results demonstrate the trade-off between safety and performance in a highly variable and fragile cohort.

Entities:  

Keywords:  glycaemic control; insulin sensitivity; model-based control; physiological modelling; premature infant; stochastic forecasting

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Year:  2017        PMID: 27811342     DOI: 10.1515/bmt-2016-0051

Source DB:  PubMed          Journal:  Biomed Tech (Berl)        ISSN: 0013-5585            Impact factor:   1.411


  1 in total

Review 1.  Improving glycemic control in critically ill patients: personalized care to mimic the endocrine pancreas.

Authors:  J Geoffrey Chase; Thomas Desaive; Julien Bohe; Miriam Cnop; Christophe De Block; Jan Gunst; Roman Hovorka; Pierre Kalfon; James Krinsley; Eric Renard; Jean-Charles Preiser
Journal:  Crit Care       Date:  2018-08-02       Impact factor: 9.097

  1 in total

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