title: Management of insulin therapy in urban diabetes patients is facilitated by use of an intelligent dosing system.
abstract: The Intelligent Dosing System (IDS, Dimensional Dosing Systems, Inc., Wexford, PA) is a software suite that incorporates patient-specific, dose-response data in a mathematical model, and then calculates the new dose of agent needed to achieve the next desired therapeutic goal. We evaluated use of the IDS for titrating insulin therapy. The IDS was placed on handheld platforms and provided to practitioners to use in adjusting total daily insulin dose. Fasting glucose, random glucose, and hemoglobin A1c were used as markers against which insulin could be adjusted. Values of markers expected at the next follow-up visit, as predicted by the model, were compared with levels actually observed. For 264 patients, 334 paired visits were analyzed. Average age was 54 years, diabetes' duration was 10 years, and body mass index was 33.2 kg/m(2); 57% were female, 88% were African American, and 92% had type 2 diabetes. The correlation between IDS suggested and actual prescribed total daily dose was high (r = 0.99), suggesting good acceptability of the IDS by practitioners. Significant decreases in fasting glucose, random glucose, and hemoglobin A1c levels were seen (all P < 0.0001). No significant difference between average expected and observed follow-up fasting glucose values was found (145 vs. 149 mg/dL, P = 0.42), and correlation was high (r = 0.79). Mean observed random glucose value at follow-up was comparable to the IDS predicted level (167 vs. 168 mg/dL, P = 0.97), and correlation was high (r = 0.73). Observed follow-up hemoglobin A1c was higher than the value expected (7.9% vs. 7.4%, P < 0.0055), but correlation was good (r = 0.70). These analyses suggest the IDS is a useful adjunct for decisions regarding insulin therapy even when using a variety of markers of glucose control, and can be used by practitioners to assist in attainment of glycemic goals.
authors.affiliation: Division of Endocrinology, Mayo Clinic, Scottsdale, Arizona 85259, USA. Cook.Curtiss@mayo.edu
authors.forename: Curtiss B
authors.initials: CB
authors.lastname: Cook
authors.forename: Linda J
authors.initials: LJ
authors.lastname: Mann
authors.forename: Esther C
authors.initials: EC
authors.lastname: King
authors.forename: Katina M
authors.initials: KM
authors.lastname: New
authors.forename: Pamela S
authors.initials: PS
authors.lastname: Vaughn
authors.forename: Faye D
authors.initials: FD
authors.lastname: Dames
authors.forename: Virginia G
authors.initials: VG
authors.lastname: Dunbar
authors.forename: Jane M
authors.initials: JM
authors.lastname: Caudle
authors.forename: Circe
authors.initials: C
authors.lastname: Tsui
authors.forename: Christopher D
authors.initials: CD
authors.lastname: George
authors.forename: John P
authors.initials: JP
authors.lastname: McMichael
mesh_terms: D001185:Artificial Intelligence; D001786:Blood Glucose / Q000032:analysis*; D003922:Diabetes Mellitus, Type 1 / Q000188:drug therapy*; D004867:Equipment Design; D006801:Humans; D007328:Insulin / Q000008:administration & dosage / Q000627:therapeutic use; D007332:Insulin Infusion Systems; D018670:Monitoring, Ambulatory / Q000379:methods; D014481:United States; D014486:United States Food and Drug Administration
chemical_list: D001786:Blood Glucose; D007328:Insulin