title: Predicting Insulin Treatment Scenarios with the Net Effect Method: Domain of Validity.
abstract: A simulation methodology based on the net effect, a signal estimated from continuous glucose monitoring (CGM) and insulin data accounting for sources of glucose variability, for example, meals and exercise, has been proposed. This method has been recently used to "replay" real-life treatment scenarios and determine the minimal level of CGM sensor accuracy required for nonadjunctive use. Given the potential of the net effect method, it is important to assess its domain of validity.
  
  
  
  The UVA/Padova type 1 diabetes simulator is used to generate glucose and insulin data. The net effect signal is estimated and used to predict the glucose profiles resulting from the following therapy modifications: (1) basal insulin increase/decrease, (2) bolus reduction to prevent hypoglycemia, (3) bolus addition after CGM hyperalarms, (4) hypotreatment addition after CGM hypoalarms. Results of the net effect method are compared with the reference provided by the UVA/Padova simulator.
  
  
  
  The net effect method (1) well predicts the effect of small basal insulin adjustments (±10%), but overestimates time in hypo/hyperglycemia for larger adjustments (±50%); (2) underestimates the bolus reduction required to prevent hypoglycemia; (3) underestimates time in hyperglycemia when introducing correction boluses; and (4) overestimates time in hypoglycemia when introducing hypotreatments.
  
  
  
  The net effect method is reliable for small adjustments of basal insulin, while outside this domain of validity it can provide inaccurate results.
authors.affiliation: Department of Information Engineering, University of Padova , Padova, Italy .
authors.forename: Martina
authors.initials: M
authors.lastname: Vettoretti
authors.affiliation: Department of Information Engineering, University of Padova , Padova, Italy .
authors.forename: Andrea
authors.initials: A
authors.lastname: Facchinetti
authors.affiliation: Department of Information Engineering, University of Padova , Padova, Italy .
authors.forename: Giovanni
authors.initials: G
authors.lastname: Sparacino
authors.affiliation: Department of Information Engineering, University of Padova , Padova, Italy .
authors.forename: Claudio
authors.initials: C
authors.lastname: Cobelli
mesh_terms: D001786:Blood Glucose; D003198:Computer Simulation; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000188:drug therapy*; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D007003:Hypoglycemia / Q000517:prevention & control; D007004:Hypoglycemic Agents / Q000627:therapeutic use*; D007328:Insulin / Q000097:blood / Q000627:therapeutic use*; D007332:Insulin Infusion Systems; D008962:Models, Theoretical
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; D007328:Insulin
keywords: CGM nonadjunctive use; Glucose sensor; Insulin therapy; Modeling; Simulation; Type 1 diabetes