Literature DB >> 12766106

Intensified blood glucose monitoring improves glycemic control in stable, insulin-treated veterans with type 2 diabetes: the Diabetes Outcomes in Veterans Study (DOVES).

Glen H Murata1, Jayendra H Shah, Richard M Hoffman, Christopher S Wendel, Karen D Adam, Patricia A Solvas, Syed U Bokhari, William C Duckworth.   

Abstract

OBJECTIVE: To examine the effect of intensified self-monitored blood glucose (SMBG) testing on glycemic control. RESEARCH DESIGN AND METHODS: Subjects with stable, insulin-treated type 2 diabetes performed SMBG using an electronic blood glucose meter before all meals and at bedtime for 8 weeks. Baseline data were collected on demographics, clinical characteristics, diet, and exercise. HbA(1c) was measured at baseline, at 4 weeks, and at 8 weeks. After the intensified monitoring period, subjects resumed their usual monitoring. HbA(1c) was then measured at 24, 37, and 52 weeks. Multivariate linear regression was used to determine the effect of monitoring on glycemic control.
RESULTS: A total of 201 subjects completed the monitoring period. The baseline HbA(1c) (8.10 +/- 1.67%) decreased during the monitoring period by 0.30 +/- 0.68% (P < 0.001) at 4 weeks and by 0.36 +/- 0.88% (P < 0.001) at 8 weeks. Although entry HbA(1c) and compliance independently predicted the week 8 HbA(1c) (r = 0.862, P < 0.001), standardized regression analysis found that compliance with the SMBG protocol influenced the week 8 HbA(1c) more than age, sex, BMI, exercise level, carbohydrate consumption, or treatment intensity at baseline. However, SMBG benefited only subjects whose testing compliance exceeded 75% or with an entry HbA(1c) >8.0%. Decreases in HbA(1c) (-0.31 +/- 1.17%, P = 0.001) persisted in the 159 subjects followed for 52 weeks.
CONCLUSIONS: Intensified blood glucose monitoring improved glycemic control in a large cohort of stable, insulin-treated veterans with type 2 diabetes. SMBG provided a strong stimulus for improved self-care resulting in clinically important and sustained reductions in HbA(1c).

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Year:  2003        PMID: 12766106     DOI: 10.2337/diacare.26.6.1759

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


  36 in total

1.  Self-monitoring of blood glucose in type 2 diabetes and long-term outcome: an epidemiological cohort study.

Authors:  S Martin; B Schneider; L Heinemann; V Lodwig; H-J Kurth; H Kolb; W A Scherbaum
Journal:  Diabetologia       Date:  2005-12-17       Impact factor: 10.122

2.  Self-monitoring of blood glucose and glycaemic control in type 2 diabetes.

Authors:  Anders Tengblad; Ewa Grodzinsky; Kjell Lindström; Sigvard Mölstad; Lars Borgquist; Carl Johan Ostgren
Journal:  Scand J Prim Health Care       Date:  2007-09       Impact factor: 2.581

3.  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

4.  A cause-and-effect-based mathematical curvilinear model that predicts the effects of self-monitoring of blood glucose frequency on hemoglobin A1c and is suitable for statistical correlations.

Authors:  Paul C Davidson; Bruce W Bode; R Dennis Steed; Harry R Hebblewhite
Journal:  J Diabetes Sci Technol       Date:  2007-11

5.  Randomized studies are needed to assess the true role of self-monitoring of blood glucose in noninsulin-treated type 2 diabetes.

Authors:  Christopher G Parkin; David Price
Journal:  J Diabetes Sci Technol       Date:  2007-07

6.  Systematic review of use of blood glucose test strips for the management of diabetes mellitus.

Authors: 
Journal:  CADTH Technol Overv       Date:  2010-06-01

7.  A randomised, controlled trial of self-monitoring of blood glucose in patients with type 2 diabetes receiving conventional insulin treatment.

Authors:  Michael A Nauck; Burkhard Haastert; Christoph Trautner; Ulrich A Müller; Matthias A Nauck; Lutz Heinemann
Journal:  Diabetologia       Date:  2014-01-21       Impact factor: 10.122

Review 8.  Japanese Clinical Practice Guideline for Diabetes 2019.

Authors:  Eiichi Araki; Atsushi Goto; Tatsuya Kondo; Mitsuhiko Noda; Hiroshi Noto; Hideki Origasa; Haruhiko Osawa; Akihiko Taguchi; Yukio Tanizawa; Kazuyuki Tobe; Narihito Yoshioka
Journal:  Diabetol Int       Date:  2020-07-24

9.  "Symptom-based insulin adjustment for glucose normalization" (SIGN) algorithm: a pilot study.

Authors:  Joyce Yu-Chia Lee; Keith Tsou; Jiahui Lim; Feaizen Koh; Sooim Ong; Sabrina Wong
Journal:  Diabetes Technol Ther       Date:  2012-10-04       Impact factor: 6.118

10.  Public policy implications for using remote monitoring technology to treat diabetes.

Authors:  Stephen J Ubl
Journal:  J Diabetes Sci Technol       Date:  2007-05
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