Impact of variation in patient response on model-based control of glycaemia in critically ill patients

Critically ill patients commonly experience stress-induced hyperglycaemia, and several studies have shown tight glycaemic control (TGC) can reduce patient mortality. However, tight control is often difficult to achieve due to conflicting drug therapies and evolving patient condition. Thus, a number of studies have failed to achieve TGC possibly due to use of fixed insulin dosing protocols over adaptive patient-specific methods. Model-based targeted glucose control can adapt insulin and dextrose interventions to match identified patient sensitivity. This study explores the impact on control of assuming patient response to insulin is constant versus time-varying. Simulated trials of glucose control were performed on adult and neonatal virtual patient cohorts. Results indicate assumptions of constant insulin sensitivity can lead to significantly increased rates of hypoglycaemia, a commonly cited issue preventing increased adoption of tight glycaemic control in critical care. It is clear that adaptive, patient-specific, approaches are better able to manage interand intrapatient variability than typical, fixed protocols.