CONTEXT: Elevated blood glucose levels occur frequently in the critically ill. Tight glucose control by intensive insulin treatment markedly improves clinical outcome. OBJECTIVE AND DESIGN: This is a randomized controlled trial comparing blood glucose control by a laptop-based model predictive control algorithm with a variable sampling rate [enhanced model predictive control (eMPC); version 1.04.03] against a routine glucose management protocol (RMP) during the peri- and postoperative periods. SETTING: The study was performed at the Department of Cardiac Surgery, University Hospital. PATIENTS: A total of 60 elective cardiac surgery patients were included in the study. INTERVENTIONS:Elective cardiac surgery and treatment with continuous insulin infusion (eMPC) or continuous insulin infusion combined with iv insulin boluses (RMP) to maintain euglycemia (target range 4.4-6.1 mmol/liter) were performed. There were 30 patients randomized for eMPC and 30 for RMP treatment. Blood glucose was measured in 1- to 4-h intervals as requested by each algorithm during surgery and postoperatively over 24 h. MAIN OUTCOME MEASURES: Mean blood glucose, percentage of time in target range, and hypoglycemia events were used. RESULTS:Mean blood glucose was 6.2 +/- 1.1 mmol/liter in the eMPC vs. 7.2 +/- 1.1 mmol/liter in the RMP group (P < 0.05); percentage of time in the target range was 60.4 +/- 22.8% for the eMPC vs. 27.5 +/- 16.2% for the RMP group (P < 0.05). No severe hypoglycemia (blood glucose < 2.9 mmol/liter) occurred during the study. Mean insulin infusion rate was 4.7 +/- 3.3 IU/h in the eMPC vs. 2.6 +/- 1.7 IU/h in the RMP group (P < 0.05). Mean sampling interval was 1.5 +/- 0.3 h in the eMPC vs. 2.1 +/- 0.2 h in the RMP group (P < 0.05). CONCLUSIONS: Compared with RMP, the eMPC algorithm was more effective and comparably safe in maintaining euglycemia in cardiac surgery patients.
RCT Entities:
CONTEXT: Elevated blood glucose levels occur frequently in the critically ill. Tight glucose control by intensive insulin treatment markedly improves clinical outcome. OBJECTIVE AND DESIGN: This is a randomized controlled trial comparing blood glucose control by a laptop-based model predictive control algorithm with a variable sampling rate [enhanced model predictive control (eMPC); version 1.04.03] against a routine glucose management protocol (RMP) during the peri- and postoperative periods. SETTING: The study was performed at the Department of Cardiac Surgery, University Hospital. PATIENTS: A total of 60 elective cardiac surgery patients were included in the study. INTERVENTIONS: Elective cardiac surgery and treatment with continuous insulin infusion (eMPC) or continuous insulin infusion combined with iv insulin boluses (RMP) to maintain euglycemia (target range 4.4-6.1 mmol/liter) were performed. There were 30 patients randomized for eMPC and 30 for RMP treatment. Blood glucose was measured in 1- to 4-h intervals as requested by each algorithm during surgery and postoperatively over 24 h. MAIN OUTCOME MEASURES: Mean blood glucose, percentage of time in target range, and hypoglycemia events were used. RESULTS: Mean blood glucose was 6.2 +/- 1.1 mmol/liter in the eMPC vs. 7.2 +/- 1.1 mmol/liter in the RMP group (P < 0.05); percentage of time in the target range was 60.4 +/- 22.8% for the eMPC vs. 27.5 +/- 16.2% for the RMP group (P < 0.05). No severe hypoglycemia (blood glucose < 2.9 mmol/liter) occurred during the study. Mean insulin infusion rate was 4.7 +/- 3.3 IU/h in the eMPC vs. 2.6 +/- 1.7 IU/h in the RMP group (P < 0.05). Mean sampling interval was 1.5 +/- 0.3 h in the eMPC vs. 2.1 +/- 0.2 h in the RMP group (P < 0.05). CONCLUSIONS: Compared with RMP, the eMPC algorithm was more effective and comparably safe in maintaining euglycemia in cardiac surgery patients.
Authors: Roman Kulnik; Johannes Plank; Christoph Pachler; Malgorzata E Wilinska; Andrea Groselj-Strele; Doris Röthlein; Matthias Wufka; Norman Kachel; Karl Heinz Smolle; Sabine Perl; Thomas Rudolf Pieber; Roman Hovorka; Martin Ellmerer Journal: J Diabetes Sci Technol Date: 2008-11
Authors: Jan Blaha; Petr Kopecky; Michal Matias; Roman Hovorka; Jan Kunstyr; Tomas Kotulak; Michal Lips; David Rubes; Martin Stritesky; Jaroslav Lindner; Michal Semrad; Martin Haluzik Journal: Diabetes Care Date: 2009-02-05 Impact factor: 17.152