Journal Article Comparison of the relationship between multiple parameters of glycemic variability and coronary plaque vulnerability assessed by virtual histology-intravascular ultrasound

Otowa-Suematsu, Natsu  ,  Sakaguchi, Kazuhiko  ,  Komada, Hisako  ,  Nakamura, Tomoaki  ,  Sou, Anna  ,  Hirota, Yushi  ,  Kuroda, Masaru  ,  Shinke, Toshiro  ,  Hirata, Ken-ichi  ,  Ogawa, Wataru

9 ( 3 )  , pp.610 - 615 , 2018-05 , Wiley
Aims/Introduction Increased glycemic variability is an important contributing factor to coronary artery disease. Although various parameters of glycemic variability can be derived by continuous glucose monitoring, the clinical relevance of individual parameters has remained unclear. We have now analyzed the relationship of such parameters to coronary plaque vulnerability. Materials and Methods The standard deviation of glucose levels (SD glucose), mean amplitude of glycemic excursions (MAGE), continuous overlapping net glycemic action calculated every 1 h (CONGA-1) and mean of daily differences (MODD) were calculated from continuous glucose monitoring data for 53 patients hospitalized for percutaneous coronary intervention. The relationship of these parameters to the percentage necrotic core of total plaque volume (%NC) as assessed by virtual histology-intravascular ultrasound (a predictor of coronary plaque rupture) was evaluated. Results All parameters of glycemic variability were significantly correlated with %NC, with correlation coefficients of 0.593, 0.626, 0.318, and 0.388 for log(SD glucose), log(MAGE), CONGA-1 and log(MODD), respectively. Simple linear regression analysis showed that the coefficients of determination for %NC and either log(SD glucose; 0.352) or log(MAGE; 0.392) were greater than those for %NC and either CONGA-1 (0.101) or log(MODD; 0.151), whereas the residual sums of squares for the former relationships (1045.1 and 979.5, respectively) were smaller than those for the latter (1449.3 and 1369.6, respectively). Conclusions The present data suggest that SD glucose and MAGE are more highly correlated with coronary plaque vulnerability than are CONGA-1 and MODD, and are thus likely better predictors of coronary artery disease.

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