Artificial intelligence in critically ill diabetic patients: current status and future prospects

Table 1 Clinical uses of artificial intelligence in management of diabetes

AI applications	Examples of AI devices	Clinical uses
Retinal screening	IDx-DR device	Screening and diagnosis of diabetic retinopathy
Clinical diagnosis	Advisor Pro	Detection and monitoring of diabetes and its associated complications. Fine-tuning insulin dose
Patient self-management tools	Medtronic Guardian Connect System, Dexcom G6 CGM systems; Mobile applications	Improve blood glucose control, activity and dietary tracking
Risk stratification	AI using random forest and; gradient boosting techniques	Prediction of new-onset diabetes; Prediction of subpopulations at risk for complications, non-compliance to therapy and hospitalization

AI: Artificial intelligence.

Table 2 Possible critical care applications of artificial intelligence in diabetes management

Blood glucose monitoring and prediction

Detection of adverse glycemic events

Blood glucose control strategies

Insulin bolus calculators and advisory systems

Risk and patient stratification

Table 3 Characteristics of an ideal tool to monitor blood glucose in intensive care unit

Ease to use

Minimal burden on staff

Automated data entry

High rate of adherence

Allow for minimal sampling

Comfortable to use for the patient

Use of a proven algorithm to calculate insulin dosage

Quickly correct hyperglycemia

Consistently maintain glucose within the predetermined optimal range

Ensure minimal glycemic variability

Prevent episodes of hypoglycemia

Provide easy interface with other patient measurements and data

Easy to integrate into existing hospital systems

Avoid the need for repeated data entry

Maintain results in a comprehensive, standardized database to facilitate multi-center comparison

Table 4 Continuous glucose monitoring devices

Type of device	Name of device	Comments
Intravenous	GlucoClear by Edwards Lifesciences; (Irvine, CA)	Approved in Europe
Intravenous	Glysure System by Glysure (Abingdon, UK)	Approved in Europe
Intravenous	Eirus by Maquet Getinge Group (Rastatt, Germany)	Approved in Europe
Intravenous	OptiScanner 5000 by OptiScan; (Hayward, CA)	Approved in EuropeFDA-approved for use in US hospitals
Intravenous	GlucoScout (International Biomedical, Austin, TX)	FDA-approved for use in US hospitals
Intravenous	Dexcom G	FDA-approved and CEA approved
Intravenous	Guardian™ Connect system by Medtronic (San Diego, CA)	FDA-approved for use in US hospitals
Subcutaneous	Freestyle Libre by Abbott Diabetes Care	US FDA approved

FDA: Food and Drug Administration; CEA: Carcinoembryonic antigen.

Table 5 Limitations of artificial intelligence

Factors
Human factors	Inhibition, lack of experience
Technical factors	Cost, availability and implementation
Data limitation	Lack of data in ICU patients, lack of large scale randomized trials
Design limitation	Devices tried in certain patient populations may not be applicable in ICU patients
Ethical	Lack of guidelines

ICU: Intensive care unit.