What, why and how to monitor blood glucose in critically ill patients

Table 5 Possible critical care applications of artificial intelligence in diabetes management

Potential applications	Clinical examples
Blood glucose monitoring and prediction of adverse glycaemic events	Early detection of hypoglycaemia and hyperglycaemias e.g., MD-Logic controller
Blood glucose control strategies	Software-based algorithms for insulin dosing e.g., proportional-integral-derivative models, Glucose Regulation for Intensive Care Patients, and Model predictive controls
Insulin bolus calculators and advisory systems	CGM regulated insulin infusion system predicting hypoglycaemia and regulating insulin doses
	Artificial intelligence based artificial pancreas
Risk and patient stratification	Prediction of sepsis and risk of nosocomial infections
	Risk of renal and cardiac complications like acute kidney injury and myocardial infarction
	Need for ICU admission
	ICU mortality

CGM: Continuous glucose monitoring, ICU: Intensive care unit.