Juneja D, Deepak D, Nasa P. What, why and how to monitor blood glucose in critically ill patients. World J Diabetes 2023; 14(5): 528-538 [PMID: 37273246 DOI: 10.4239/wjd.v14.i5.528]
Corresponding Author of This Article
Deven Juneja, DNB, FCCP, MBBS, Director, Institute of Critical Care Medicine, Max Super Speciality Hospital, Saket, 1 Press Enclave Road, New Delhi 110017, India. devenjuneja@gmail.com
Research Domain of This Article
Critical Care Medicine
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Can reduce contact of care-givers reducing cross infections and risk to care-givers
Evolving clinical evidence (especially in critically ill patients)
Invasive device, risk of infection when using intravenous devices
Table 4 Suggested targets for various glycemic indices in critically ill patients
Glycemic indices
Suggested targets
Blood glucose
140-180 mg/dL
Time in range
More than 70%
Glycaemic gap
Less than 25.89 mg/dL in type 2 diabetics
Less than 40 mg/dL in community acquired pneumonia
Glycaemic lability
Below median (40 mmol/L2/h/week)
Stress hyperglycaemia ratio
Less than 1.14 in sepsis patients
Mean amplitude of glycaemic excursions
Less than 65 mg/dl in sepsis patients
Coefficient of variation
Less than 36%
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
Citation: Juneja D, Deepak D, Nasa P. What, why and how to monitor blood glucose in critically ill patients. World J Diabetes 2023; 14(5): 528-538