Liu, LeiWu, QianshengYan, HongChen, BaoxianZheng, XilongZhou, Qiang2021-01-032021-01-032020-12-30Lei Liu, Qiansheng Wu, Hong Yan, Baoxian Chen, Xilong Zheng, and Qiang Zhou, “Association between Cardiac Autonomic Neuropathy and Coronary Artery Lesions in Patients with Type 2 Diabetes,” Disease Markers, vol. 2020, Article ID 6659166, 6 pages, 2020. doi:10.1155/2020/6659166http://dx.doi.org/10.1155/2020/6659166http://hdl.handle.net/1880/112904https://dx.doi.org/10.11575/PRISM/38496Objective. Cardiac autonomic neuropathy (CAN) is a common and serious complication of diabetes mellitus with various systemic involvements, such as atherosclerotic cardiovascular disease. We aimed to evaluate the association between CAN and coronary artery lesions in patients with type 2 diabetes. Research Design and Methods. We retrospectively reviewed the medical records of 104 patients with type 2 diabetes and coronary artery disease (CAD). We evaluated heart rate variability (HRV) parameters (SDANN, SDNN, and pNN50) to assess cardiac autonomic function. The severity of coronary lesions was assessed by the Gensini scores and the number of affected vessels. Correlation analyses between HRV parameters and the severity of coronary lesions and clinical parameters were performed. Results. Spearman’s correlation analysis showed a significant negative correlation between SDANN and Gensini scores (,). Interestingly, this finding remained significant after adjusting for clinical covariates (,). However, there was no association between HRV parameters and the severity of coronary lesions as assessed by the number of affected vessels. Clinical parameters were not significantly correlated with HRV parameters (all ).Conclusions. Cardiac autonomic neuropathy might be related to the degree of coronary atheromatous burden in patients with type 2 diabetes. Screening for cardiac autonomic neuropathy might potentially be beneficial in the risk stratification of patients with type 2 diabetes.Journal Article2021-01-03enCopyright © 2020 Lei Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.