Document Detail


Management of insulin therapy in urban diabetes patients is facilitated by use of an intelligent dosing system.
MedLine Citation:
PMID:  15198835     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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:
Curtiss B Cook; Linda J Mann; Esther C King; Katina M New; Pamela S Vaughn; Faye D Dames; Virginia G Dunbar; Jane M Caudle; Circe Tsui; Christopher D George; John P McMichael
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Diabetes technology & therapeutics     Volume:  6     ISSN:  1520-9156     ISO Abbreviation:  Diabetes Technol. Ther.     Publication Date:  2004 Jun 
Date Detail:
Created Date:  2004-06-16     Completed Date:  2005-06-30     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  100889084     Medline TA:  Diabetes Technol Ther     Country:  United States    
Other Details:
Languages:  eng     Pagination:  326-35     Citation Subset:  IM    
Affiliation:
Division of Endocrinology, Mayo Clinic, Scottsdale, Arizona 85259, USA. Cook.Curtiss@mayo.edu
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MeSH Terms
Descriptor/Qualifier:
Artificial Intelligence
Blood Glucose / analysis*
Diabetes Mellitus, Type 1 / drug therapy*
Equipment Design
Humans
Insulin / administration & dosage,  therapeutic use
Insulin Infusion Systems*
Monitoring, Ambulatory / methods
United States
United States Food and Drug Administration
Chemical
Reg. No./Substance:
0/Blood Glucose; 11061-68-0/Insulin
Comments/Corrections
Comment In:
Diabetes Technol Ther. 2004 Jun;6(3):336-8   [PMID:  15198836 ]
Diabetes Technol Ther. 2004 Dec;6(6):868-73   [PMID:  15684641 ]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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