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Health technology assessment review: Computerized glucose regulation in the intensive care unit - how to create artificial control

Current care guidelines recommend glucose control (GC) in critically ill patients. To achieve GC, many ICUs have implemented a (nurse-based) protocol on paper. However, such protocols are often complex, time-consuming, and can cause iatrogenic hypoglycemia. Computerized glucose regulation protocols...

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Detalles Bibliográficos
Autores principales: Hoekstra, Miriam, Vogelzang, Mathijs, Verbitskiy, Evgeny, Nijsten, Maarten WN
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2784347/
https://www.ncbi.nlm.nih.gov/pubmed/19849827
http://dx.doi.org/10.1186/cc8023
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author Hoekstra, Miriam
Vogelzang, Mathijs
Verbitskiy, Evgeny
Nijsten, Maarten WN
author_facet Hoekstra, Miriam
Vogelzang, Mathijs
Verbitskiy, Evgeny
Nijsten, Maarten WN
author_sort Hoekstra, Miriam
collection PubMed
description Current care guidelines recommend glucose control (GC) in critically ill patients. To achieve GC, many ICUs have implemented a (nurse-based) protocol on paper. However, such protocols are often complex, time-consuming, and can cause iatrogenic hypoglycemia. Computerized glucose regulation protocols may improve patient safety, efficiency, and nurse compliance. Such computerized clinical decision support systems (Cuss) use more complex logic to provide an insulin infusion rate based on previous blood glucose levels and other parameters. A computerized CDSS for glucose control has the potential to reduce overall workload, reduce the chance of human cognitive failure, and improve glucose control. Several computer-assisted glucose regulation programs have been published recently. In order of increasing complexity, the three main types of algorithms used are computerized flowcharts, Proportional-Integral-Derivative (PID), and Model Predictive Control (MPC). PID is essentially a closed-loop feedback system, whereas MPC models the behavior of glucose and insulin in ICU patients. Although the best approach has not yet been determined, it should be noted that PID controllers are generally thought to be more robust than MPC systems. The computerized Cuss that are most likely to emerge are those that are fully a part of the routine workflow, use patient-specific characteristics and apply variable sampling intervals.
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spelling pubmed-27843472010-10-16 Health technology assessment review: Computerized glucose regulation in the intensive care unit - how to create artificial control Hoekstra, Miriam Vogelzang, Mathijs Verbitskiy, Evgeny Nijsten, Maarten WN Crit Care Review Current care guidelines recommend glucose control (GC) in critically ill patients. To achieve GC, many ICUs have implemented a (nurse-based) protocol on paper. However, such protocols are often complex, time-consuming, and can cause iatrogenic hypoglycemia. Computerized glucose regulation protocols may improve patient safety, efficiency, and nurse compliance. Such computerized clinical decision support systems (Cuss) use more complex logic to provide an insulin infusion rate based on previous blood glucose levels and other parameters. A computerized CDSS for glucose control has the potential to reduce overall workload, reduce the chance of human cognitive failure, and improve glucose control. Several computer-assisted glucose regulation programs have been published recently. In order of increasing complexity, the three main types of algorithms used are computerized flowcharts, Proportional-Integral-Derivative (PID), and Model Predictive Control (MPC). PID is essentially a closed-loop feedback system, whereas MPC models the behavior of glucose and insulin in ICU patients. Although the best approach has not yet been determined, it should be noted that PID controllers are generally thought to be more robust than MPC systems. The computerized Cuss that are most likely to emerge are those that are fully a part of the routine workflow, use patient-specific characteristics and apply variable sampling intervals. BioMed Central 2009 2009-10-16 /pmc/articles/PMC2784347/ /pubmed/19849827 http://dx.doi.org/10.1186/cc8023 Text en Copyright ©2009 Biomed Central Ltd
spellingShingle Review
Hoekstra, Miriam
Vogelzang, Mathijs
Verbitskiy, Evgeny
Nijsten, Maarten WN
Health technology assessment review: Computerized glucose regulation in the intensive care unit - how to create artificial control
title Health technology assessment review: Computerized glucose regulation in the intensive care unit - how to create artificial control
title_full Health technology assessment review: Computerized glucose regulation in the intensive care unit - how to create artificial control
title_fullStr Health technology assessment review: Computerized glucose regulation in the intensive care unit - how to create artificial control
title_full_unstemmed Health technology assessment review: Computerized glucose regulation in the intensive care unit - how to create artificial control
title_short Health technology assessment review: Computerized glucose regulation in the intensive care unit - how to create artificial control
title_sort health technology assessment review: computerized glucose regulation in the intensive care unit - how to create artificial control
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2784347/
https://www.ncbi.nlm.nih.gov/pubmed/19849827
http://dx.doi.org/10.1186/cc8023
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