ArticleJournal of diabetes science and technology2008
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.
Article in Journal of diabetes science and technology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01164423 (Monocentric, Open Study to Investigate the Feasibility of Blood Glucose Control With the Space TGC System), which is not on this map. Cited by 10 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Monocentric, Open Study to Investigate the Feasibility of Blood Glucose Control With the Space TGC System (With Incorporated Software-algorithm eMPC) in Medical ICU Patients
Who cites it
10 citing papers in PubMed.
- Comparison of Space Glucose Control and Routine Glucose Management Protocol for Glycemic Control in Critically Ill Patients: A Prospective, Randomized Clinical Study.Chinese medical journal · 2017Trial
- A stepwise approach toward closed-loop blood glucose control for intensive care unit patients: results from a feasibility study in type 1 diabetic subjects using vascular microdialysis with infrared spectrometry and a model predictive control algorithm.Journal of diabetes science and technology · 2011Trial
- Evaluation of the Space GlucoseControl System for Managing Stress-Induced Hyperglycemia in ICU Patients: Efficacy and Safety AssessmentEndocrine, metabolic & immune disorders drug targets · 2026Article
- Fully automated life support: an implementation and feasibility pilot study in healthy pigs.Intensive care medicine experimental · 2018Article
- Safety, efficacy and clinical generalization of the STAR protocol: a retrospective analysis.Annals of intensive care · 2016Article
- A comparison of two insulin infusion protocols in the medical intensive care unit by continuous glucose monitoring.Annals of intensive care · 2016Article
- Space GlucoseControl system for blood glucose control in intensive care patients--a European multicentre observational study.BMC anesthesiology · 2016Observational
- Glucose control in intensive care: usability, efficacy and safety of Space GlucoseControl in two medical European intensive care units.BMC endocrine disorders · 2014Article
- AP@home: a novel European approach to bring the artificial pancreas home.Journal of diabetes science and technology · 2011Article
- An evaluation of "I, Pancreas" algorithm performance in silico.Journal of diabetes science and technology · 2009Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsThis 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).
resultsThe 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.
conclusionsDespite 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.
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