OBJECTIVE: To examine the practical difficulties in managing hyperglycaemia in critical illness and to present recently developed model-based glycaemic management protocols to provide tight control. BACKGROUND: Hyperglycaemia is prevalent in critical care. Current published protocols require significant added clinical effort and have highly variable results. No currently published methods successfully address the practical clinical difficulties and patient variation, while also providing safe, tight control. METHODS: We developed a unique model-based approach that manages both nutritional inputs and exogenous insulin infusions. Computerised glycaemic control methods and proof-of-concept clinical trial results are presented. The protocol has been simplified to a set of tables and adopted as a clinical practice change. Eight pilot test cases are presented to demonstrate the overall approach. RESULTS: Computerised control methods lowered blood glucose (BG) levels to the range 4.0-6.1 mmol/L within 10 hours. Over 90% of pre-set hourly blood glucose targets were achieved within measurement error. Eight pilot tests of the simplified, table-based SPRINT protocol, covering 1651 patient-hours produced an average BG level of 5.7 mmol/L (SD, 0.9 mmol/L). BG levels were in the 4.0-6.1 mmol/L band for 60% of the controlled time. Just under 90% of measurements were in the range 4.0-7.0 mmol/L, with 96% in the range 4.0-7.75 mmol/L. There were no hypoglycaemic episodes, with a minimum glucose level of 3.2 mmol/L, and no additional clinical intervention was required. SUMMARY: The overall approach of modulating nutrition as well as insulin challenges the current practice of relying on insulin alone to reduce glycaemic levels, which often results in large variability and poor control. The protocol was developed from model-based analysis and proof-of-concept clinical trials, and then generalised to a simple, clinical practice improvement. The results show extremely tight control within safe glycaemic bands.
OBJECTIVE: To examine the practical difficulties in managing hyperglycaemia in critical illness and to present recently developed model-based glycaemic management protocols to provide tight control. BACKGROUND: Hyperglycaemia is prevalent in critical care. Current published protocols require significant added clinical effort and have highly variable results. No currently published methods successfully address the practical clinical difficulties and patient variation, while also providing safe, tight control. METHODS: We developed a unique model-based approach that manages both nutritional inputs and exogenous insulin infusions. Computerised glycaemic control methods and proof-of-concept clinical trial results are presented. The protocol has been simplified to a set of tables and adopted as a clinical practice change. Eight pilot test cases are presented to demonstrate the overall approach. RESULTS: Computerised control methods lowered blood glucose (BG) levels to the range 4.0-6.1 mmol/L within 10 hours. Over 90% of pre-set hourly blood glucose targets were achieved within measurement error. Eight pilot tests of the simplified, table-based SPRINT protocol, covering 1651 patient-hours produced an average BG level of 5.7 mmol/L (SD, 0.9 mmol/L). BG levels were in the 4.0-6.1 mmol/L band for 60% of the controlled time. Just under 90% of measurements were in the range 4.0-7.0 mmol/L, with 96% in the range 4.0-7.75 mmol/L. There were no hypoglycaemic episodes, with a minimum glucose level of 3.2 mmol/L, and no additional clinical intervention was required. SUMMARY: The overall approach of modulating nutrition as well as insulin challenges the current practice of relying on insulin alone to reduce glycaemic levels, which often results in large variability and poor control. The protocol was developed from model-based analysis and proof-of-concept clinical trials, and then generalised to a simple, clinical practice improvement. The results show extremely tight control within safe glycaemic bands.
Authors: J Geoffrey Chase; Christopher G Pretty; Leesa Pfeifer; Geoffrey M Shaw; Jean-Charles Preiser; Aaron J Le Compte; Jessica Lin; Darren Hewett; Katherine T Moorhead; Thomas Desaive Journal: Crit Care Date: 2010-08-12 Impact factor: 9.097
Authors: J Geoffrey Chase; Aaron LeCompte; Geoffrey M Shaw; Amy Blakemore; Jason Wong; Jessica Lin; Christopher E Hann Journal: J Diabetes Sci Technol Date: 2008-07
Authors: Christopher G Pretty; Aaron J Le Compte; J Geoffrey Chase; Geoffrey M Shaw; Jean-Charles Preiser; Sophie Penning; Thomas Desaive Journal: Ann Intensive Care Date: 2012-06-15 Impact factor: 6.925
Authors: Christopher E Hann; J Geoffrey Chase; Michael F Ypma; Jos Elfring; Noorhafiz Mohd Nor; Piers Lawrence; Geoffrey M Shaw Journal: Open Med Inform J Date: 2008-05-27
Authors: Saeid Eslami; Nicolette F de Keizer; Evert de Jonge; Marcus J Schultz; Ameen Abu-Hanna Journal: Crit Care Date: 2008-11-11 Impact factor: 9.097