title: Predictive Value of Carotid Distensibility Coefficient for Cardiovascular Diseases and All-Cause Mortality: A Meta-Analysis.
abstract: OBJECTIVE
  The aim of the present study is to determine the pooled predictive value of carotid distensibility coefficient (DC) for cardiovascular (CV) diseases and all-cause mortality.
  
  
  BACKGROUND
  Arterial stiffness is associated with future CV events. Aortic pulse wave velocity is a commonly used predictor for CV diseases and all-cause mortality; however, its assessment requires specific devices and is not always applicable in all patients. In addition to the aortic artery, the carotid artery is also susceptible to atherosclerosis, and is highly accessible because of the surficial property. Thus, carotid DC, which indicates the intrinsic local stiffness of the carotid artery and may be determined using ultrasound and magnetic resonance imaging, is of interest for the prediction. However, the role of carotid DC in the prediction of CV diseases and all-cause mortality has not been thoroughly characterized, and the pooled predictive value of carotid DC remains unclear.
  
  
  METHODS
  A meta-analysis, which included 11 longitudinal studies with 20361 subjects, was performed.
  
  
  RESULTS
  Carotid DC significantly predicted future total CV events, CV mortality and all-cause mortality. The pooled risk ratios (RRs) of CV events, CV mortality and all-cause mortality were 1.19 (1.06-1.35, 95%CI, 9 studies with 18993 subjects), 1.09 (1.01-1.18, 95%CI, 2 studies with 2550 subjects) and 1.65 (1.15-2.37, 95%CI, 6 studies with 3619 subjects), respectively, for the subjects who had the lowest quartile of DC compared with their counterparts who had higher quartiles. For CV events, CV mortality and all-cause mortality, a decrease in DC of 1 SD increased the risk by 13%, 6% and 41% respectively, whereas a decrease in DC of 1 unit increased the risk by 3%, 1% and 6% respectively.
  
  
  CONCLUSIONS
  Carotid DC is a significant predictor of future CV diseases and all-cause mortality, which may facilitate the identification of high-risk patients for the early diagnosis and prompt treatment of CV diseases.
authors.affiliation: Medical Research Center, Changsha Central Hospital, Changsha, Hunan, China.
authors.forename: Chuang
authors.initials: C
authors.lastname: Yuan
authors.affiliation: Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China.|Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
authors.affiliation: Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China.
authors.forename: Michael
authors.initials: M
authors.lastname: Ying
mesh_terms: D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000401:mortality* / Q000503:physiopathology; D002339:Carotid Arteries / Q000503:physiopathology*; D002423:Cause of Death; D003187:Compliance; D006801:Humans; D009026:Mortality