title: Brain mass estimation by head circumference and body mass methods in neonatal glycaemic modelling and control.
abstract: BACKGROUND
  Hyperglycaemia is a common complication of stress and prematurity in extremely low-birth-weight infants. Model-based insulin therapy protocols have the ability to safely improve glycaemic control for this group. Estimating non-insulin-mediated brain glucose uptake by the central nervous system in these models is typically done using population-based body weight models, which may not be ideal.
  
  
  METHODS
  A head circumference-based model that separately treats small-for-gestational-age (SGA) and appropriate-for-gestational-age (AGA) infants is compared to a body weight model in a retrospective analysis of 48 patients with a median birth weight of 750g and median gestational age of 25 weeks. Estimated brain mass, model-based insulin sensitivity (SI) profiles, and projected glycaemic control outcomes are investigated. SGA infants (5) are also analyzed as a separate cohort.
  
  
  RESULTS
  Across the entire cohort, estimated brain mass deviated by a median 10% between models, with a per-patient median difference in SI of 3.5%. For the SGA group, brain mass deviation was 42%, and per-patient SI deviation 13.7%. In virtual trials, 87-93% of recommended insulin rates were equal or slightly reduced (Δ<0.16mU/h) under the head circumference method, while glycaemic control outcomes showed little change.
  
  
  CONCLUSIONS
  The results suggest that body weight methods are not as accurate as head circumference methods. Head circumference-based estimates may offer improved modelling accuracy and a small reduction in insulin administration, particularly for SGA infants.
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Private Bag, Christchurch, Canterbury 8140, New Zealand. Electronic address: cameron.a.gunn@gmail.com.
authors.forename: Cameron Allan
authors.initials: CA
authors.lastname: Gunn
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Private Bag, Christchurch, Canterbury 8140, New Zealand.
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Dickson
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Private Bag, Christchurch, Canterbury 8140, New Zealand.
authors.forename: Christopher G
authors.initials: CG
authors.lastname: Pretty
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Private Bag, Christchurch, Canterbury 8140, New Zealand.
authors.forename: Jane M
authors.initials: JM
authors.lastname: Alsweiler
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Private Bag, Christchurch, Canterbury 8140, New Zealand.
authors.forename: Adrienne
authors.initials: A
authors.lastname: Lynn
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Private Bag, Christchurch, Canterbury 8140, New Zealand.
authors.forename: Geoffrey M
authors.initials: GM
authors.lastname: Shaw
authors.affiliation: Department of Mechanical Engineering, University of Canterbury, Private Bag, Christchurch, Canterbury 8140, New Zealand.
authors.forename: J Geoffrey
authors.initials: JG
authors.lastname: Chase
mesh_terms: D001724:Birth Weight; D001786:Blood Glucose / Q000378:metabolism; D001921:Brain / Q000473:pathology*; D015331:Cohort Studies; D003198:Computer Simulation; D005260:Female; D006257:Head; D006801:Humans; D006943:Hyperglycemia / Q000097:blood / Q000188:drug therapy* / Q000473:pathology*; D052577:Infant, Extremely Low Birth Weight; D062071:Infant, Extremely Premature; D007231:Infant, Newborn; D007328:Insulin / Q000008:administration & dosage / Q000627:therapeutic use*; D007333:Insulin Resistance; D008297:Male; D008954:Models, Biological; D009929:Organ Size; D012189:Retrospective Studies
chemical_list: D001786:Blood Glucose; D007328:Insulin
keywords: Brain mass; Central nervous system; Glycaemic control; Insulin therapy; Physiological modelling; Preterm infants