Literature DB >> 19926921

Relationship between clinical markers of glycemia and glucose excursion evaluated by continuous glucose monitoring (CGM).

Tomoko Suwa1, Akio Ohta, Tomoya Matsui, Rieko Koganei, Hiroyuki Kato, Takehiro Kawata, Yukiyoshi Sada, Satoshi Ishii, Akihiko Kondo, Kaori Murakami, Takuyuki Katabami, Yasushi Tanaka.   

Abstract

In order to evaluate the relationship between clinical markers of glycemia and glucose excursion, we performed 48-hour continuous glucose monitoring (CGM) in 43 diabetic patients. For the clinical markers, HbA(1c), glycoalbumin (GA), and 1,5-anhydroglucitol (1,5-AG) were measured, and for the parameters of glucose excursion from CGM, average glucose (AG), standard deviation of glucose (SD), the area under the curve for glucose levels >180 mg/dL (AUC(>180)), and the difference between the maximum and minimum glucose levels during 48 hours (DeltaG(48hr)) were analyzed. All patients were treated without any changes of the dosages of oral anti-diabetic agents or insulin for at least the previous 3 months with coefficient of variation (CV) of HbA(1c) less than 4 %. In results, while HbA(1c) did not show any single correlation with AG, SD, AUC(>180), or DeltaG(48hr), both GA and 1,5-AG were significantly related to all these parameters. Furthermore, GA significantly correlated to all CGM parameters, and SD significantly correlated to GA in multiple regression analyses. These results suggest that GA may be a different marker from HbA(1c) for diabetic complications, because GA, but not HbA(1c), may reflect not only short-term average glucose but also fluctuation of glucose.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19926921     DOI: 10.1507/endocrj.k09e-234

Source DB:  PubMed          Journal:  Endocr J        ISSN: 0918-8959            Impact factor:   2.349


  30 in total

Review 1.  Subcellular localization of guanylate cyclase.

Authors:  H Kimura; F Murad
Journal:  Life Sci       Date:  1975-09-15       Impact factor: 5.037

2.  Utility of glycated albumin for the diagnosis of diabetes mellitus in a Japanese population study: results from the Kyushu and Okinawa Population Study (KOPS).

Authors:  N Furusyo; T Koga; M Ai; S Otokozawa; T Kohzuma; H Ikezaki; E J Schaefer; J Hayashi
Journal:  Diabetologia       Date:  2011-09-27       Impact factor: 10.122

3.  The establishment of biological reference intervals of nontraditional glycemic markers in a Chinese population.

Authors:  Qiang Zhou; De-Bao Shi; Li-Ying Lv
Journal:  J Clin Lab Anal       Date:  2016-11-17       Impact factor: 2.352

4.  Comparison of two assays for serum 1,5-anhydroglucitol.

Authors:  Elizabeth Selvin; Gregory P Rynders; Michael W Steffes
Journal:  Clin Chim Acta       Date:  2011-01-14       Impact factor: 3.786

5.  Racial differences in glycemic markers: a cross-sectional analysis of community-based data.

Authors:  Elizabeth Selvin; Michael W Steffes; Christie M Ballantyne; Ron C Hoogeveen; Josef Coresh; Frederick L Brancati
Journal:  Ann Intern Med       Date:  2011-03-01       Impact factor: 25.391

6.  Serum glycated albumin as a new glycemic marker in pediatric diabetes.

Authors:  Ji Woo Lee; Hyung Jin Kim; Young Se Kwon; Yong Hoon Jun; Soon Ki Kim; Jong Weon Choi; Ji Eun Lee
Journal:  Ann Pediatr Endocrinol Metab       Date:  2013-12-31

Review 7.  Advantages and pitfalls of fructosamine and glycated albumin in the diagnosis and treatment of diabetes.

Authors:  Elisa Danese; Martina Montagnana; Antonio Nouvenne; Giuseppe Lippi
Journal:  J Diabetes Sci Technol       Date:  2015-01-14

8.  Evaluation of glycemic variability in well-controlled type 2 diabetes mellitus.

Authors:  Suk Chon; Yun Jung Lee; Gemma Fraterrigo; Paolo Pozzilli; Moon Chan Choi; Mi-Kwang Kwon; Sang Ouk Chin; Sang Youl Rhee; Seungjoon Oh; Young-Seol Kim; Jeong-Taek Woo
Journal:  Diabetes Technol Ther       Date:  2013-04-25       Impact factor: 6.118

Review 9.  Beyond HbA1c and glucose: the role of nontraditional glycemic markers in diabetes diagnosis, prognosis, and management.

Authors:  Christina M Parrinello; Elizabeth Selvin
Journal:  Curr Diab Rep       Date:  2014       Impact factor: 4.810

10.  New indices for predicting glycaemic variability.

Authors:  Akifumi Ogawa; Akinori Hayashi; Eriko Kishihara; Sonomi Yoshino; Akihiro Takeuchi; Masayoshi Shichiri
Journal:  PLoS One       Date:  2012-09-27       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.