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Generalisability of a Virtual Trials Method for Glycaemic Control in Intensive Care

Authors :
Kent W. Stewart
Thomas Desaive
Marine Flechet
Jennifer L. Dickson
Christopher G. Pretty
Bernard Lambermont
Sophie Penning
Geoffrey M. Shaw
Balázs Benyó
J. Geoffrey Chase
Source :
IEEE Transactions on Biomedical Engineering. 65:1543-1553
Publication Year :
2018
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2018.

Abstract

Background : Elevated blood glucose (BG) concentrations (Hyperglycaemia) are a common complication in critically ill patients. Insulin therapy is commonly used to treat hyperglycaemia, but metabolic variability often results in poor BG control and low BG (hypoglycaemia). Objective: This paper presents a model-based virtual trial method for glycaemic control protocol design, and evaluates its generalisability across different populations. Methods: Model-based insulin sensitivity (SI) was used to create virtual patients from clinical data from three different ICUs in New Zealand, Hungary, and Belgium. Glycaemic results from simulation of virtual patients under their original protocol (self-simulation) and protocols from other units (cross simulation) were compared. Results: Differences were found between the three cohorts in median SI and inter-patient variability in SI. However, hour-to-hour intra-patient variability in SI was found to be consistent between cohorts. Self and cross-simulation results were found to have overall similarity and consistency, though results may differ in the first 24–48 h due to different cohort starting BG and underlying SI. Conclusions and Significance: Virtual patients and the virtual trial method were found to be generalisable across different ICUs. This virtual trial method is useful for in silico protocol design and testing, given an understanding of the underlying assumptions and limitations of this method.

Details

ISSN :
15582531 and 00189294
Volume :
65
Database :
OpenAIRE
Journal :
IEEE Transactions on Biomedical Engineering
Accession number :
edsair.doi.dedup.....1c861b0d1619e959c4b6b745b8236a6c
Full Text :
https://doi.org/10.1109/tbme.2017.2686432