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Publications (3)3.86 Total impact

  • Article: Efficacy and safety of glucose control with Space GlucoseControl in the medical intensive care unit--an open clinical investigation.
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    ABSTRACT: We aimed to investigate the performance of the Space GlucoseControl system (SGC) (B. Braun, Melsungen, Germany) in medical critically ill patients. The SGC is a nurse-driven, computer-assisted device for glycemic control combining infusion pumps with the enhanced Model Predictive Control algorithm. The trial was designed as a single-center, open clinical investigation in a nine-bed medical intensive care unit in a tertiary center in Graz, Austria. Efficacy was assessed by percentage of time within the target range (4.4-8.3 mmol/L; primary end point), mean blood glucose, and sampling interval. Safety was assessed by the number of hypoglycemic episodes (≤2.2 mmol/L). Twenty mechanically ventilated patients (age, 63±16 years; body mass index, 31.0±10.7 kg/m(2); Acute Physiology and Chronic Health Evaluation II score, 25.4±6.3; 14 males; six with diabetes) were included for a period of 7.0±3.6 days. Time within target range was 83.4±8.9% (mean±SD), and mean arterial blood glucose was 6.8±0.4 mmol/L. No severe hypoglycemic episodes (<2.2 mmol/L) occurred, and the percentage of time within 2.2 and 3.3 mmol/L was low (0.03±0.07%). The sampling interval was 2.0±0.4 h. The mean insulin dose was 93.5±80.1 IU/day, and the adherence to the given insulin dose advice was high (98.3%). A total of 11 unintended therapy interruptions (0.08 events/treatment day) caused by software problems occurred in four patients. SGC is a safe and efficient method to control blood glucose in critically ill patients in the medical intensive care unit.
    Diabetes Technology &amp Therapeutics 06/2012; 14(8):690-5. · 1.93 Impact Factor
  • Article: Hospital glucose control: safe and reliable glycemic control using enhanced model predictive control algorithm in medical intensive care unit patients.
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    ABSTRACT: The aim of this study was to investigate the performance of the enhanced Model Predictive Control (eMPC) algorithm for glycemic control in medical critically ill patients for the whole length of intensive care unit (ICU) stay. The trial was designed as a single-center, open, noncontrolled clinical investigation in a nine-bed medical ICU in a tertiary teaching hospital. In 20 patients, blood glucose (BG) was controlled with a laptop-based bedside version of the eMPC. Efficacy was assessed by percentage of time within the target range (4.4-6.1 mM; primary end point), mean BG, and BG sampling interval. Safety was assessed by the number of severe hypoglycemic episodes (<2.2 mM). Twenty patients (69 +/- 11 years old; body mass index, 27.4 +/- 4.5 kg/m(2); APACHE II, 25.5 +/- 5.2) were included for a period of 7.3 days (median; interquartile range, 4.4-10.2 days) in the study. Time within target range was 58.12 +/- 10.05% (mean +/- SD). For all patients with at least 7 days in the ICU, there was no statistically significant difference between the daily mean percentage of times in target range in respect of the averages. Mean arterial BG was 5.8 +/- 0.5 mM, insulin requirement was 101.3 +/- 50.7 IU/day, and mean carbohydrate intake (enteral and parenteral nutrition) was 176.4 +/- 61.9 g/day. Three hypoglycemic episodes occurred in three subjects, corresponding to a rate of 0.02 per treatment day. In our single-center, noncontrolled study the eMPC algorithm was a safe and reliable method to control BG in critically medical ICU patients for the whole length of ICU stay.
    Diabetes Technology &amp Therapeutics 05/2010; 12(5):405-12. · 1.93 Impact Factor
  • Article: Evaluation of implementation of a fully automated algorithm (enhanced model predictive control) in an interacting infusion pump system for establishment of tight glycemic control in medical intensive care unit patients.
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    ABSTRACT: The objective of this study was to investigate the performance of a newly developed decision support system for the establishment of tight glycemic control in medical intensive care unit (ICU) patients for a period of 72 hours. This was a single-center, open, non-controlled feasibility trial including 10 mechanically ventilated ICU patients. The CS-1 decision support system (interacting infusion pumps with integrated enhanced model predictive control algorithm and user interface) was used to adjust the infusion rate of administered insulin to normalize blood glucose. Efficacy and safety were assessed by calculating the percentage of values within the target range (80-110 mg/dl), hyperglycemic index, mean glucose, and hypoglycemic episodes (<40 mg/dl). The percentage of values in time in target was 47.0% (+/-13.0). The average blood glucose concentration and hyperglycemic index were 109 mg/dl (+/-13) and 10 mg/dl (+/-9), respectively. No hypoglycemic episode (<40 mg/dl) was detected. Eleven times (1.5% of all given advice) the nurses did not follow and, thus, overruled the advice of the CS-1 system. Several technical malfunctions of the device (repetitive error messages and missing data in the data log) due to communication problems between the new hardware components are shortcomings of the present version of the device. As a consequence of these technical failures of system integration, treatment had to be stopped ahead of schedule in three patients. Despite technical malfunctions, the performance of this prototype CS-1 decision support system was, from a clinical point of view, already effective in maintaining tight glycemic control. Accordingly, and with technical improvement required, the CS-1 system has the capacity to serve as a reliable tool for routine establishment of glycemic control in ICU patients.
    Journal of diabetes science and technology 11/2008; 2(6):963-70.