title: Computerized generation of circadian sensor modal days with continuous glucose monitoring for comparison of various insulin regimens based on insulin glargine in type 1 diabetes.
abstract: OBJECTIVE
  Our aims were (1) to design and standardize a statistical approach for data reduction in continuous glucose monitoring, allowing comparison of circadian glycemic patterns in therapeutic subcohorts of patients with type 1 diabetes, and (2) to investigate the applicability of this approach for CGMS assessment in clinical study of basal insulin replacement quality with various timings of basal injections (pre-breakfast, dinner, bedtime) of a new insulin analog.
  
  
  METHODS
  Prospective randomized three-arm parallel study with switch over after 6 months for another 3 months of free choice injection time point (options pre-breakfast, pre-dinner and bedtime) of the new insulin analog in 16 type 1 diabetic subjects on functional insulin treatment (FIT: basal, prandial and correctional dosages). CGMS was used at the end of each follow up period of a clinical study. Representative daily profiles were off-line computed as "circadian sensor modal days" for each insulin regimen consisting of consecutive means of hourly glucose values.
  
  
  RESULTS
  Although the overall quality of glycemic control (HbAIC) for different regimens did not reach statistical differences, CGMS displayed slightly divergent maximal swings in the course of glycemia (p=0.04-0.08) and allowed--with delineated data reduction procedure--a reliable between treatment comparison.
  
  
  CONCLUSIONS
  Off-line computation of "hourly circadian sensor modal days" for data reduction can be effectively used with CGMS for description of circadian glycemic patterns in type 1 diabetes.
authors.affiliation: Institute of Biomedical Engineering & Physics, University of Vienna, Vienna, Austria. k.howorka@bmtp.akh-wien.ac.at
authors.forename: K
authors.initials: K
authors.lastname: Howorka
authors.forename: J
authors.initials: J
authors.lastname: Pumprla
authors.forename: M
authors.initials: M
authors.lastname: Gabriel
authors.forename: H
authors.initials: H
authors.lastname: Thoma
authors.forename: A
authors.initials: A
authors.lastname: Schabmann
mesh_terms: D000328:Adult; D000704:Analysis of Variance; D001786:Blood Glucose / Q000032:analysis*; D002940:Circadian Rhythm; D003199:Computer Systems; D003922:Diabetes Mellitus, Type 1 / Q000097:blood* / Q000188:drug therapy*; D005260:Female; D006801:Humans; D007279:Injections, Subcutaneous; D007328:Insulin / Q000008:administration & dosage* / Q000031:analogs & derivatives*; D000069036:Insulin Glargine; D049528:Insulin, Long-Acting; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000379:methods*
chemical_list: D001786:Blood Glucose; D007328:Insulin; D049528:Insulin, Long-Acting; D000069036:Insulin Glargine