Glycaemic data from 30 critically ill patient episodes was used to fit a model of glucose dynamics. In this model, insulin sensitivity (SI) is identified ...
Conclusions This study presented a new strategy for observing how the level of parameterisation and basis function order affects accuracy of future predictions ...
Background: Glycaemic control (GC) in critical care can reduce mortality and improve clinical outcomes. Model based GC allows personalised and effective ...
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What's the difference between insulin resistance and insulin sensitivity?
What is the blood glucose control in critically ill patients?
Hence, variability of insulin sensitivity can cause variable glycemia. This study quantifies and compares the daily evolution of insulin sensitivity level and ...
Missing: precise variance
Accurate and precise prediction of insulin sensitivity variance in critically ill patients. R Langdon, PD Docherty, EJ Mansell, JG Chase. Biomedical Signal ...
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May 15, 2023 · AI using a convolutional neural network has been shown to be highly accurate in predicting mortality in critically ill diabetes patients with ...
Missing: variance | Show results with:variance
Targeted glycemic control in critical care patients can be achieved by frequent fitting and prediction of a patient's modelled insulin sensitivity index, SI.
Missing: precise | Show results with:precise
This study examines the likelihood and evolution of overall and hypoglycemia-inducing variability of insulin sensitivity in ICU patients based on diagnosis ...
This study examines the likelihood and evolution of overall and hypoglycemia-inducing variability of insulin sensitivity in ICU patients based on diagnosis and ...
Feb 27, 2024 · The aim of this study was to assess the feasibility and accuracy of real-time continuous glucose monitoring (CGM) in ICU patients after major ...
Missing: variance | Show results with:variance