title: [Analytic design and clinical application of an intelligent control system for pharmacotherapy with insulin--2].
abstract: To determine whether insulin dosage recommendations provided by a computer system are as effective as those given by human experts, we developed an intelligent control system and prospectively studied its use in 42 type-1 diabetics attending a diabetes education center. Control algorithms were based on blood glucose self-monitoring and included parameter estimations to determine glucose metabolism. The algorithms were implemented in a vest pocket-sized system. Over a period of 32 days, 21 patients used the computer to determine the necessary dose of insulin, while a second group of 21 patients followed the recommendations of the diabetes specialists. Baseline HbA1 levels (9.8 +/- 1.6 vs 9.9 +/- 1.6%) were identical in the two groups. The mean serum glucose over the last two weeks of the study was lower in the computer group (151.3 +/- 25.2 vs 165.7 +/- 36.0 mg/dl; p < 0.01) although the rates of hypoglycaemic episodes were equal (1.7 vs 2.3%). Metabolic control, measured by the day-to-day standard deviation of the serum glucose (46.8 +/- 14.4 vs 50.4 +/- 16.2 mg/dl; p < 0.01), was more stable in the computer group. We conclude that metabolic control and safety were comparable in the two groups, and suggest that such an intelligent control system may be of benefit for use at home, when the help of doctors or diabetes educators is not available.
authors.affiliation: Medizinische Klinik I, Medizinische Universität Lübeck, Deutschland.
authors.forename: A
authors.initials: A
authors.lastname: Peters
authors.forename: W
authors.initials: W
authors.lastname: Kerner
mesh_terms: D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D001786:Blood Glucose / Q000032:analysis; D015190:Blood Glucose Self-Monitoring / Q000295:instrumentation*; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000188:drug therapy*; D004360:Drug Therapy, Computer-Assisted / Q000295:instrumentation*; D004734:Energy Metabolism / Q000502:physiology; D005103:Expert Systems; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D007328:Insulin / Q000008:administration & dosage*; D008297:Male; D008838:Microcomputers; D008875:Middle Aged
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin; D007328:Insulin
vernacular_title: Analytisches Design und klinische Anwendung eines lernfähigen Regelsystems für die Pharmakotherapie mit Insulin--Teil 2.