Validation of a model-based virtual trials method for tight glycemic control in intensive care.
about
A controlled study of the effectiveness of an adaptive closed-loop algorithm to minimize corticosteroid-induced stress hyperglycemia in type 1 diabetes.Reducing the impact of insulin sensitivity variability on glycaemic outcomes using separate stochastic models within the STAR glycaemic protocol.Untangling glycaemia and mortality in critical careContinuous glucose control in the ICU: report of a 2013 round table meeting.Data entry errors and design for model-based tight glycemic control in critical care.Evolution of insulin sensitivity and its variability in out-of-hospital cardiac arrest (OHCA) patients treated with hypothermia.Virtual environment to quantify the influence of colour stimuli on the performance of tasks requiring attention.Physiological modeling, tight glycemic control, and the ICU clinician: what are models and how can they affect practice?Stochastic targeted (STAR) glycemic control: design, safety, and performance.Interface design and human factors considerations for model-based tight glycemic control in critical carePilot study of the SPRINT glycemic control protocol in a Hungarian medical intensive care unit.Nasogastric aspiration as an indicator for feed absorption in model-based glycemic control in neonatal intensive care.On the problem of patient-specific endogenous glucose production in neonates on stochastic targeted glycemic control.Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.Pilot proof of concept clinical trials of Stochastic Targeted (STAR) glycemic control.Safety, efficacy and clinical generalization of the STAR protocol: a retrospective analysis.Variability of insulin sensitivity during the first 4 days of critical illness: implications for tight glycemic control.Continuous Glucose Monitoring Measures Can Be Used for Glycemic Control in the ICU: An In-Silico Study.Nutrition delivery of a model-based ICU glycaemic control system.Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them.Improving glycemic control in critically ill patients: personalized care to mimic the endocrine pancreas
P2860
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P2860
Validation of a model-based virtual trials method for tight glycemic control in intensive care.
description
2010 nî lūn-bûn
@nan
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
2010年论文
@zh
2010年论文
@zh-cn
name
Validation of a model-based vi ...... mic control in intensive care.
@ast
Validation of a model-based vi ...... mic control in intensive care.
@en
type
label
Validation of a model-based vi ...... mic control in intensive care.
@ast
Validation of a model-based vi ...... mic control in intensive care.
@en
prefLabel
Validation of a model-based vi ...... mic control in intensive care.
@ast
Validation of a model-based vi ...... mic control in intensive care.
@en
P2093
P2860
P356
P1476
Validation of a model-based vi ...... emic control in intensive care
@en
P2093
Aaron J Le Compte
Fatanah Suhaimi
Geoffrey M Shaw
Jean-Charles Preiser
Jessica Lin
Katherine T Moorhead
Sophie Penning
Thomas Desaive
P2860
P2888
P356
10.1186/1475-925X-9-84
P577
2010-12-14T00:00:00Z
P6179
1017196133