title: In silico evaluation of a control system and algorithm for automated insulin infusion in the ICU setting.
abstract: BACKGROUND
  It is known that tight control of glucose in the Intensive Care Unit reduces morbidity and mortality not only in diabetic patients but also in those non-diabetics who become transiently hyperglycemic. Taking advantage of a recently marketed subcutaneous glucose sensor we designed an Automatic Insulin Infusion System (AIIS) for inpatient treatment, and tested its stability under simulated clinical conditions.
  
  
  METHODS
  The system included: reference glucose, glucose sensor, insulin and glucose infusion controllers and emergency infusion logic. We carried out computer simulations using Matlab/Simulink, in both common and worst-case conditions.
  
  
  RESULTS
  The system was capable of controlling glucose levels without entering in a phase of catastrophic instability, even under severe simulated challenges. Care was taken to include in all simulations the 5-10 minute delay of the subcutaneous glucose signal when compared to the real-time serum glucose signal, a well-known characteristic of all subcutaneous glucose sensors.
  
  
  CONCLUSIONS
  When tested in-Silico, a commercially available subcutaneous glucose sensor allowed the stable functioning of a proportional-derivative Automatic Insulin Infusion System, which was able to maintain glucose within acceptable limits when using a well-established glucose response model simulating a patient. Testing of the system in vivo using animal models is now warranted.
authors.affiliation: Department of Electrical Engineering, College of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile.
authors.forename: José L
authors.initials: JL
authors.lastname: Ortiz
authors.forename: Marcelo W
authors.initials: MW
authors.lastname: Guarini
authors.forename: Gisella R
authors.initials: GR
authors.lastname: Borzone
authors.forename: Pablo R
authors.initials: PR
authors.lastname: Olmos
mesh_terms: D000465:Algorithms; D001331:Automation; D001786:Blood Glucose / Q000378:metabolism; D019295:Computational Biology; D003920:Diabetes Mellitus / Q000097:blood / Q000188:drug therapy; D005947:Glucose / Q000008:administration & dosage; D006801:Humans; D007332:Insulin Infusion Systems; D007362:Intensive Care Units; D015203:Reproducibility of Results; D012984:Software
chemical_list: D001786:Blood Glucose; D005947:Glucose