Effects of daily glucose fluctuations on the healing response to everolimus-eluting stent implantation as assessed using continuous glucose monitoring and optical coherence tomography. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Kuroda, Masaru; Shinke, Toshiro; Otake, Hiromasa; Sugiyama, Daisuke; Takaya, Tomofumi; Takahashi, Hachidai; Terashita, Daisuke; Uzu, Kenzo; Tahara, Natsuko; Kashiwagi, Daiji; Kuroda, Koji; Shinkura, Yuto; Nagasawa, Yoshinori; Sakaguchi, Kazuhiko; Hirota, Yushi; Ogawa, Wataru; Hirata, Ken-ichi
• Is Part Of: Cardiovascular diabetology. Volume 15:Issue 1(2016)
• Page Start: 1
• Page End: 14
• Publication Date: 2016-12
• Subjects: Glucose fluctuation -- Continuous glucose monitoring -- Mean amplitude of glycemic excursion -- Optical coherence tomography; Diabetes -- Complications -- Periodicals; Cardiovascular system -- Diseases -- Complications -- Periodicals; Cardiovascular system -- Diseases -- Prevention -- Periodicals; 616.462
• DOI: 10.1186/s12933-016-0395-4
• Languages: English
• ISSNs: 1475-2840

Abstract

Abstract Background Several studies have revealed that glucose fluctuations provoke oxidative stress that leads to endothelial cell dysfunction, progression of coronary atherosclerosis, and plaque vulnerability. However, little is known regarding their effect on neointimal growth after stenting in patients with coronary artery disease (CAD). We aimed to investigate the effects of glucose fluctuations on neointimal growth after everolimus-eluting stent (EES) implantation. Methods This study examined 50 patients who underwent a 9-month follow-up using optical coherence tomography (OCT) after EES implantation. Glucose fluctuation was expressed as the mean amplitude of glycemic excursion (MAGE), and was determined via continuous glucose monitoring before stenting. At the OCT follow-up, we evaluated the percentage of uncovered struts and three-dimensional uniformity of neointimal distribution by calculating the mean neointimal thickness (NIT) within 360 equally-spaced radial sectors for every 1-mm cross-sectional OCT analysis, and assessed the incidence of major adverse cardiovascular events (MACE). Results We evaluated 60 lesions in 50 patients. Linear mixed effect models were used to explore the influence of different variables on variability in NIT and the percentage of uncovered struts and to adjust for covariates. Univariate analysis showed that MAGE was most strongly correlated with the previously mentioned OCT measurements (coefficient β ± standard error = 0.267 ± 0.073 and 0.016 ± 0.003, t = 3.668 and 6.092, both P < 0.001, respectively). In multivariate analysis, MAGE had the strongest effect on variability in NIT (coefficient β ± standard error = 0.239 ± 0.093, P = 0.014) and the percentage of uncovered struts (coefficient β ± standard error = 0.019 ± 0.004, P < 0.001). Five lesions in four patients required target lesion revascularization (10.0 %) at a mean duration of 9 months after EES implantation. Compared to non-MACE cases, cases of MACE exhibited a significantly higher MAGE (99 vs. 68; P = 0.004), maximum NIT (580 vs. 330 µm; P = 0.002), and variability in NIT (100 vs. 65; P = 0.007), although there was no significant difference in these groups' HbA1c levels. Conclusions Glucose fluctuation may affect vessel healing after EES implantation in patients with CAD who are receiving lipid-lowering therapy. Therefore, glucose fluctuations may be an important target for secondary prevention after coronary stenting, which is independent of dyslipidemia control.