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Improving Safety of Glucose Control in Intensive Care using Virtual Patients and Simulated Clinical Trials
Author(s) -
Liam Fisk,
Aaron J. Le Compte,
Geoffrey M. Shaw,
J. Geoffrey Chase
Publication year - 2012
Publication title -
journal of healthcare engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.509
H-Index - 29
eISSN - 2040-2309
pISSN - 2040-2295
DOI - 10.1260/2040-2295.3.3.415
Subject(s) - clinical trial , medicine , intensive care medicine , patient safety , control (management) , intensive care , medical emergency , computer science , health care , artificial intelligence , economics , economic growth
Despite the potential clinical benefits of normalizing blood glucose in critically ill patients, the risk of hypoglycemia is a major barrier to widespread clinical adoption of accurate glycemic control. To compare five glucose control protocols, a validated insulin-glucose system model was employed to perform simulated clinical trials. STAR, SPRINT, UNC, Yale and Glucontrol protocols were assessed over a medical-surgical intensive care unit patient cohort. Results were interpreted separately for patients with low to high sensitivity to insulin, and low to high variability in metabolic state. STAR and SPRINT provided good glucose control with risk of severe hypoglycemia less than 0.05% across all patient groups. UNC also achieved good control for patients with low and medium levels of insulin sensitivity (SI), but risk of severe hypoglycemia was raised for patients with high SI. Glucontrol showed degradation of performance for patients with high metabolic variability

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