title: Association of glycemic variability and the presence and severity of coronary artery disease in patients with type 2 diabetes.
abstract: BACKGROUND
  Glucose variability is one of components of the dysglycemia in diabetes and may play an important role in development of diabetic vascular complications. The objective of this study was to assess the relationship between glycemic variability determined by a continuous glucose monitoring (CGM) system and the presence and severity of coronary artery disease (CAD) in patients with type 2 diabetes mellitus (T2DM).
  
  
  METHODS
  In 344 T2DM patients with chest pain, coronary angiography revealed CAD (coronary stenosis ≥ 50% luminal diameter narrowing) in 252 patients and 92 patients without CAD. Gensini score was used to assess the severity of CAD. All participants' CGM parameters and biochemical characteristics were measured at baseline.
  
  
  RESULTS
  Diabetic patients with CAD were older, and more were male and cigarette smokers compared with the controls. Levels of the mean amplitude of glycemic excursions (MAGE) (3.7 ± 1.4 mmol/L vs. 3.2 ± 1.2 mmol/L, p < 0.001), postprandial glucose excursion (PPGE) (3.9 ± 1.6 mmol/L vs. 3.6 ± 1.4 mmol/L, p = 0.036), serum high-sensitive C-reactive protein (hs-CRP) (10.7 ± 12.4 mg/L vs. 5.8 ± 6.7 mg/L, p < 0.001) and creatinine (Cr) (87 ± 23 mmol/L vs. 77 ± 14 mmol/L, p < 0.001) were significantly higher in patients with CAD than in patients without CAD. Gensini score closely correlated with age, MAGE, PPGE, hemoglobin A1c (HbA1c), hs-CRP and total cholesterol (TC). Multivariate analysis indicated that age (p < 0.001), MAGE (p < 0.001), serum levels of HbA1c (p = 0.022) and hs-CRP (p = 0.005) were independent determinants for Gensini score. Logistic regression analysis revealed that MAGE ≥ 3.4 mmol/L was an independent predictor for CAD. The area under the receiver-operating characteristic curve for MAGE (0.618, p = 0.001) was superior to that for HbA1c (0.554, p = 0.129).
  
  
  CONCLUSIONS
  The intraday glycemic variability is associated with the presence and severity of CAD in patients with T2DM. Effects of glycemic excursions on vascular complications should not be neglected in diabetes.
authors.affiliation: Department of Cardiology, Beijing Anzhen Hospital of Capital Medical University, Beijing, China.
authors.forename: Gong
authors.initials: G
authors.lastname: Su
authors.forename: Shuhua
authors.initials: S
authors.lastname: Mi
authors.forename: Hong
authors.initials: H
authors.lastname: Tao
authors.forename: Zhao
authors.initials: Z
authors.lastname: Li
authors.forename: Hongxia
authors.initials: H
authors.lastname: Yang
authors.forename: Hong
authors.initials: H
authors.lastname: Zheng
authors.forename: Yun
authors.initials: Y
authors.lastname: Zhou
authors.forename: Changsheng
authors.initials: C
authors.lastname: Ma
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism*; D016009:Chi-Square Distribution; D002681:China; D017023:Coronary Angiography; D023921:Coronary Stenosis / Q000097:blood / Q000000981:diagnostic imaging / Q000209:etiology*; D003430:Cross-Sectional Studies; D048909:Diabetes Complications / Q000097:blood / Q000000981:diagnostic imaging / Q000209:etiology*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000150:complications*; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory; D016017:Odds Ratio; D011237:Predictive Value of Tests; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D013997:Time Factors
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human