title: Real-life application and validation of flexible intensive insulin-therapy algorithms in type 1 diabetes patients.
abstract: OBJECTIVE
  Flexible intensive insulin therapy (FIT) has become the reference standard in type 1 diabetes. Besides carbohydrate counting (CHO), it requires the use of algorithms to adjust prandial insulin doses to the number of CHO portions. As recourse to standard algorithms is usual when initiating FIT, the use of personalized algorithms would also allow more precise adjustments to be made. The aim of the present study was to validate personalized prandial algorithms for FIT as proposed by Howorka et al. in 1990.
  
  
  METHODS
  We conducted a 4-month observational study of 35 patients with type 1 diabetes, treated with FIT for at least 6 months, who were already using Howorka's prandial algorithms (meal-related and correctional insulin doses for blood glucose increases induced by CHO). These patients were asked to use a personal digital assistant (PDA) phone with an electronic diary (instead of a paper one) to take advantage of the computerized data-collection system to assess the quality of postprandial metabolic control.
  
  
  RESULTS
  Whatever the number of CHO portions, mean postprandial blood glucose values remained close to the target of 7.8mmol/L, and the compensatory algorithm allowed precise correction of preprandial hyperglycaemia. In fact, the algorithms for meal-related and correctional insulin doses at the end of the study did not differ significantly from those initially calculated, but they generally differed from one patient to another.
  
  
  CONCLUSIONS
  In type 1 diabetic patients treated with FIT, the use of individualized parameters permits fast and accurate adjustment of mealtime insulin doses, leading to good control of the postprandial state.
authors.affiliation: Department of Diabetes, Sud-Francilien Hospital, Bd Henri Dunant, Corbeil-Essonnes, France. sylvia.franc@free.fr
authors.forename: S
authors.initials: S
authors.lastname: Franc
authors.forename: D
authors.initials: D
authors.lastname: Dardari
authors.forename: B
authors.initials: B
authors.lastname: Boucherie
authors.forename: J-P
authors.initials: JP
authors.lastname: Riveline
authors.forename: M
authors.initials: M
authors.lastname: Biedzinski
authors.forename: C
authors.initials: C
authors.lastname: Petit
authors.forename: E
authors.initials: E
authors.lastname: Requeda
authors.forename: P
authors.initials: P
authors.lastname: Leurent
authors.forename: M
authors.initials: M
authors.lastname: Varroud-Vial
authors.forename: G
authors.initials: G
authors.lastname: Hochberg
authors.forename: G
authors.initials: G
authors.lastname: Charpentier
mesh_terms: D000328:Adult; D000465:Algorithms; D000704:Analysis of Variance; D001786:Blood Glucose / Q000378:metabolism; D015190:Blood Glucose Self-Monitoring; D034201:Computers, Handheld; D003922:Diabetes Mellitus, Type 1 / Q000188:drug therapy*; D004040:Dietary Carbohydrates; D004334:Drug Administration Schedule; D005260:Female; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage; D007328:Insulin / Q000008:administration & dosage*; D007332:Insulin Infusion Systems; D008297:Male; D008875:Middle Aged; D019518:Postprandial Period; D057285:Precision Medicine / Q000379:methods*
chemical_list: D001786:Blood Glucose; D004040:Dietary Carbohydrates; D007004:Hypoglycemic Agents; D007328:Insulin