The control of blood glucose in the critical diabetic patient: a neuro-fuzzy method

• Published in: Journal of diabetes and its complications Vol. 15; no. 2; pp. 80 - 87
• Main Authors: Dazzi, Davide, Taddei, Francesco, Gavarini, Alessandra, Uggeri, Enzo, Negro, Roberto, Pezzarossa, Antonio
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 01.03.2001; Elsevier Science
• Subjects: Adult; Aged; Algorithms; Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy; Biological and medical sciences; Blood Glucose - metabolism; Computerized, statistical medical data processing and models in biomedicine; Critical care; Critical Illness; Diabetes mellitus; Diabetes Mellitus - blood; Diabetes Mellitus - drug therapy; Emergency and intensive care: endocrinopathies; Endocrine emergencies; Female; Fuzzy Logic; GIK; Glucose; Glucose - administration & dosage; Glucose control systems; Humans; Infusions, Intravenous; Insulin; Insulin - administration & dosage; Insulin - therapeutic use; Intensive care medicine; Male; Medical sciences; Middle Aged; Models and simulation; Nerve Net; Neural networks; Sensitivity and Specificity; Time Factors; Fuzzy logic; Endocrine emergencies; Neural networks; Diabetes mellitus; Glucose control systems; Critical care; GIK; Glucose; Insulin; Endocrinopathy; Human; Pancreatic hormone; Replacement therapy; Critically ill; Modeling; Chemotherapy; Hypoglycemic agent; Fuzzy algorithm; Adult; Therapeutic protocol; Dose; Elderly; Glycemia
• ISSN: 1056-8727; 1873-460X
• DOI: 10.1016/S1056-8727(00)00137-9

Conventional algorithms for regulating insulin infusion rates in those critical diabetic patients submitted to parenteral glucose and insulin infusions do not allow to approach near normal blood glucose (BG) levels since traditional control systems are not fully effective in complex nonlinear systems as BG control is. Thus, we applied fuzzy logic principles and neural network techniques to modify intravenous insulin administration rates during glucose infusion. Forty critically ill, fasted diabetic subjects submitted to glucose and potassium infusion entered the study. They were randomly assigned to two treatment regimes: in group A, insulin infusion rates were adjusted, every 4 h at any step between −1.5 and +1.5 U/h, according to a neuro-fuzzy nomogram; in control group B, insulin infusion rates were modified according to a conventional algorithm. In group A, BG was lowered below 10 mmol/l faster than in group B (8.2±0.7 vs. 13±1.8 h, P<.02). Mean BG was 7.8±0.2 in group A and 10.6±0.3 mmol/l in group B ( P<.00001). BG values below 4.4 mmol/l were: A=5.8% and B=10.2%. BG values lower than 2.5 mmol/l had never been observed. In conclusion, the neuro-fuzzy control system is effective in improving the BG control in critical diabetic patients without increasing either the number of BG determinations or the risk of hypoglycemia.