title: Nasogastric aspiration as an indicator for feed absorption in model-based glycemic control in neonatal intensive care.
abstract: BACKGROUND
  STAR (stochastic targeted) is a glycemic control model-based framework for critically ill neonates that has shown benefits in reducing hypoglycemia and hyperglycemia. STAR uses a stochastic matrix method to forecast future changes in a patient's insulin sensitivity and then applies this result to a physiological model to select an optimal insulin treatment. Nasogastric aspiration may be used as an indicator to suggest periods of care when enteral feed absorption is compromised, improving the performance of glycemic control. An analysis has been carried out to investigate the effect of poorly absorbed feeds on glycemic control.
  
  
  METHODS
  Clinical data were collected from eight patients on insulin therapy and enteral feed, which included large or significantly milky aspirates. Patients had a median gestational age of 25 weeks and postnatal age of 5.5 days. Virtual patients were created using the NICING model, and insulin sensitivity (SI) profiles were fit. Alternative feed profiles were generated whereby enteral feed absorption was redistributed with time to account for poor feed absorption. The effect of poor feed absorption, as indicated by aspirates, is investigated.
  
  
  RESULTS
  The average percentage change of SI 4 h before a significant aspirate was 1.16%, and 1.49% in the 4 h following the aspirate. No distinct relationship was found between the fractional change in SI and the volume of the aspirate. Accounting for aspirates had a clinically negligible impact on glycemic control in virtual trials.
  
  
  CONCLUSIONS
  Accounting for aspirates by manipulating enteral feed profiles had a minimal influence on both modeling and controlling glycemia in neonates. The impact of this method is clinically insignificant, suggesting that a population constant for the rate of glucose absorption in the gut adequately models feed absorption within the STAR framework.
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand. cameron.gunn@canterbury.ac.nz
authors.forename: Cameron A
authors.initials: CA
authors.lastname: Gunn
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Dickson
authors.forename: James N
authors.initials: JN
authors.lastname: Hewett
authors.forename: Adrienne
authors.initials: A
authors.lastname: Lynn
authors.forename: Hamish J
authors.initials: HJ
authors.lastname: Rose
authors.forename: Sooji H
authors.initials: SH
authors.lastname: Clarkson
authors.forename: Geoffrey M
authors.initials: GM
authors.lastname: Shaw
authors.forename: J Geoffrey
authors.initials: JG
authors.lastname: Chase
mesh_terms: D001786:Blood Glucose / Q000032:analysis; D003422:Critical Care / Q000379:methods; D016638:Critical Illness; D004750:Enteral Nutrition; D005260:Female; D006801:Humans; D006943:Hyperglycemia / Q000517:prevention & control*; D007003:Hypoglycemia / Q000517:prevention & control; D007231:Infant, Newborn; D007234:Infant, Premature; D007328:Insulin / Q000008:administration & dosage*; D015931:Intensive Care, Neonatal / Q000379:methods*; D007408:Intestinal Absorption / Q000502:physiology*; D007441:Intubation, Gastrointestinal; D008297:Male; D015233:Models, Statistical; D013396:Suction
chemical_list: D001786:Blood Glucose; D007328:Insulin