Stochastic insulin sensitivity models for tight glycaemic control
Hyperglycaemia is prevalent in critical care, and tight control reduces mortality. Targeted glycaemic control can be achieved by frequent fitting and prediction of a modelled insulin sensitivity index, SI. However, this parameter varies significantly in the critically ill as their condition evolves. A 3-D stochastic model of hourly SI variability is constructed using retrospective data from 18 critical care patients. The model provides a blood glucose level probability distribution one hour following an intervention, enabling accurate prediction and more optimal glycaemic control.
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