Literature DB >> 19885114

Telemedicine-based KADIS combined with CGMS has high potential for improving outpatient diabetes care.

Eckhard Salzsieder1, Petra Augstein, Lutz Vogt, Klaus-Dieter Kohnert, Peter Heinke, Ernst-Joachim Freyse, Abdel Azim Ahmed, Zakia Metwali, Iman Salman, Omer Attef.   

Abstract

BACKGROUND: The Karlsburg Diabetes Management System (KADIS) was developed over almost two decades by modeling physiological glucose-insulin interactions. When combined with the telemedicine-based communication system TeleDIAB and a continuous glucose monitoring system (CGMS), KADIS has the potential to provide effective, evidence-based support to doctors in their daily efforts to optimize glycemic control.
METHODS: To demonstrate the feasibility of improving diabetes control with the KADIS system, an experimental version of a telemedicine-based diabetes care network was established, and an international, multicenter, pilot study of 44 insulin-treated patients with type 1 and 2 diabetes was performed. Patients were recruited from five outpatient settings where they were treated by general practitioners or diabetologists. Each patient underwent CGMS monitoring under daily life conditions by a mobile monitoring team of the Karlsburg diabetes center at baseline and 3 months following participation in the KADIS advisory system and telemedicine-based diabetes care network. The current metabolic status of each patient was estimated in the form of an individualized "metabolic fingerprint." The fingerprint characterized glycemic status by KADIS-supported visualization of relationships between the monitored glucose profile and causal endogenous and exogenous factors and enabled evidence-based identification of "weak points" in glycemic control. Using KADIS-based simulations, physician recommendations were generated in the form of patient-centered decision support that enabled elimination of weak points. The analytical outcome was provided in a KADIS report that could be accessed at any time through TeleDIAB. The outcome of KADIS-based support was evaluated by comparing glycosylated hemoglobin (HbA1c) levels and 24-hour glucose profiles before and after the intervention.
RESULTS: Application of KADIS-based decision support reduced HbA1c by 0.62% within 3 months. The reduction was strongly related to the level of baseline HbA1c, diabetes type, and outpatient treatment setting. The greatest benefit was obtained in the group with baseline HbA1c levels >9% (1.22% reduction), and the smallest benefit was obtained in the group with baseline HbA1c levels of 6-7% (0.13% reduction). KADIS was more beneficial for patients with type 1 diabetes (0.79% vs 0.48% reduction) and patients treated by general practitioners (1.02% vs 0.26% reduction). Changes in HbA1c levels were paralleled by changes in mean daily 24-hour glucose profiles and fluctuations in daily glucose.
CONCLUSION: Application of KADIS in combination with CGMS and the telemedicine-based communication system TeleDIAB successfully improved outpatient diabetes care and management.

Entities:  

Keywords:  HbA1c; KADIS; advisory system; continuous glucose monitoring; decision support; outpatient diabetes care; telemedicine

Year:  2007        PMID: 19885114      PMCID: PMC2769624          DOI: 10.1177/193229680700100409

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  34 in total

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  9 in total

Review 1.  Smart telemedicine support for continuous glucose monitoring: the embryo of a future global agent for diabetes care.

Authors:  Mercedes Rigla
Journal:  J Diabetes Sci Technol       Date:  2011-01-01

2.  Translation of personalized decision support into routine diabetes care.

Authors:  Petra Augstein; Lutz Vogt; Klaus-Dieter Kohnert; Peter Heinke; Eckhard Salzsieder
Journal:  J Diabetes Sci Technol       Date:  2010-11-01

3.  Continuous Glucose Monitoring: Current Use in Diabetes Management and Possible Future Applications.

Authors:  Martina Vettoretti; Giacomo Cappon; Giada Acciaroli; Andrea Facchinetti; Giovanni Sparacino
Journal:  J Diabetes Sci Technol       Date:  2018-05-22

4.  The Karlsburg Diabetes Management System: translation from research to eHealth application.

Authors:  Eckhard Salzsieder; Petra Augstein
Journal:  J Diabetes Sci Technol       Date:  2011-01-01

5.  Update on mathematical modeling research to support the development of automated insulin delivery systems.

Authors:  Garry M Steil; Brian Hipszer; Jaques Reifman
Journal:  J Diabetes Sci Technol       Date:  2010-05-01

6.  A review of web-assisted interventions for diabetes management: maximizing the potential for improving health outcomes.

Authors:  Linda Lockett Brown; Mia Liza A Lustria; Jenice Rankins
Journal:  J Diabetes Sci Technol       Date:  2007-11

7.  Correlations of glucose levels in interstitial fluid estimated by continuous glucose monitoring systems and venous plasma.

Authors:  Byung-Joon Kim
Journal:  Korean Diabetes J       Date:  2010-12-31

8.  Patient-Tailored Decision Support System Improves Short- and Long-Term Glycemic Control in Type 2 Diabetes.

Authors:  Petra Augstein; Peter Heinke; Lutz Vogt; Klaus-Dieter Kohnert; Eckhard Salzsieder
Journal:  J Diabetes Sci Technol       Date:  2021-05-18

9.  Q-Score: development of a new metric for continuous glucose monitoring that enables stratification of antihyperglycaemic therapies.

Authors:  Petra Augstein; Peter Heinke; Lutz Vogt; Roberto Vogt; Christine Rackow; Klaus-Dieter Kohnert; Eckhard Salzsieder
Journal:  BMC Endocr Disord       Date:  2015-05-01       Impact factor: 2.763

  9 in total

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