Literature DB >> 17130195

Long-term effect of the Internet-based glucose monitoring system on HbA1c reduction and glucose stability: a 30-month follow-up study for diabetes management with a ubiquitous medical care system.

Jae-Hyoung Cho1, Sang-Ah Chang, Hyuk-Sang Kwon, Yoon-Hee Choi, Seung-Hyun Ko, Sung-Dae Moon, Soon-Jib Yoo, Ki-Ho Song, Hyun-Shik Son, Hee-Seung Kim, Won-Chul Lee, Bong-Yun Cha, Ho-Young Son, Kun-Ho Yoon.   

Abstract

OBJECTIVE: To investigate the long-term effectiveness of the Internet-based glucose monitoring system (IBGMS) on glucose control in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: We conducted a prospective, randomized, controlled trial in 80 patients with type 2 diabetes for 30 months. The intervention group was treated with the IBGMS, while the control group made conventional office visits only. HbA1c (A1C) was performed at 3-month intervals. For measuring of the stability of glucose control, the SD value of A1C levels for each subject was used as the A1C fluctuation index (HFI).
RESULTS: The mean A1C and HFI were significantly lower in the intervention group (n = 40) than in the control group (n = 40). (A1C [mean +/- SD] 6.9 +/- 0.9 vs. 7.5 +/- 1.0%, P = 0.009; HFI 0.47 +/- 0.23 vs. 0.78 +/- 0.51, P = 0.001; intervention versus control groups, respectively). Patients in the intervention group with a basal A1C >or=7% (n = 27) had markedly lower A1C levels than corresponding patients in the control group during the first 3 months and maintained more stable levels throughout the study (P = 0.022). Control patients with a basal A1C <7% (n = 15) showed the characteristic bimodal distribution of A1C levels, whereas the A1C levels in the intervention group remained stable throughout the study with low HFI.
CONCLUSIONS: Long-term use of the IBGMS has proven to be superior to conventional diabetes care systems based on office visits for controlling blood glucose and achieving glucose stability.

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Year:  2006        PMID: 17130195     DOI: 10.2337/dc05-2371

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


  69 in total

Review 1.  Closing the gap: eliminating health care disparities among Latinos with diabetes using health information technology tools and patient navigators.

Authors:  Lenny López; Richard W Grant
Journal:  J Diabetes Sci Technol       Date:  2012-01-01

2.  Rapid improvement of glycemic control in type 2 diabetes using weekly intensive multifactorial interventions: structured glucose monitoring, patient education, and adjustment of therapy-a randomized controlled trial.

Authors:  Augusto Pimazoni-Netto; David Rodbard; Maria Teresa Zanella
Journal:  Diabetes Technol Ther       Date:  2011-07-13       Impact factor: 6.118

3.  Self-monitoring of blood glucose in type 2 diabetes: a new look at published trials.

Authors:  K Kempf; W Neukirchen; S Martin; H Kolb
Journal:  Diabetologia       Date:  2008-02-20       Impact factor: 10.122

4.  Comment on: Davidson MB (2007) The dilemma of self-monitoring of blood glucose. Diabetologia 50:497-499.

Authors:  H Kolb; S Martin; A J Karter
Journal:  Diabetologia       Date:  2007-05-08       Impact factor: 10.122

5.  Definition of information technology architectures for continuous data management and medical device integration in diabetes.

Authors:  M Elena Hernando; Mario Pascual; Carlos H Salvador; Gema García-Sáez; Agustín Rodríguez-Herrero; Iñaki Martínez-Sarriegui; Enrique J Gómez
Journal:  J Diabetes Sci Technol       Date:  2008-09

6.  Value of self-monitoring blood glucose pattern analysis in improving diabetes outcomes.

Authors:  Christopher G Parkin; Jaime A Davidson
Journal:  J Diabetes Sci Technol       Date:  2009-05-01

7.  How our current medical care system fails people with diabetes: lack of timely, appropriate clinical decisions.

Authors:  Mayer B Davidson
Journal:  Diabetes Care       Date:  2009-02       Impact factor: 17.152

8.  Ubiquitous Diabetes Management System via Interactive Communication Based on Information Technologies: Clinical Effects and Perspectives.

Authors:  Jae-Hyoung Cho; Hun-Sung Kim; Jae-Hoon Han; Jin-Hee Lee; Jeong-Ah Oh; Yoon-Hee Choi; Kun-Ho Yoon
Journal:  Korean Diabetes J       Date:  2010-10-31

9.  Effect of Internet therapeutic intervention on A1C levels in patients with type 2 diabetes treated with insulin.

Authors:  Hugh D Tildesley; Adel B Mazanderani; Stuart A Ross
Journal:  Diabetes Care       Date:  2010-08       Impact factor: 19.112

10.  Web-based guided insulin self-titration in patients with type 2 diabetes: the Di@log study. Design of a cluster randomised controlled trial [TC1316].

Authors:  Mariëlle G A Roek; Laura M C Welschen; Piet J Kostense; Jacqueline M Dekker; Frank J Snoek; Giel Nijpels
Journal:  BMC Fam Pract       Date:  2009-06-09       Impact factor: 2.497

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