国家神经系统疾病临床医学研究中心数据管理与共享系统

Data Management And Sharing System of China National Clinical Research Center for Neurological Diseases

《国家中心数据管理与共享系统操作说明书 —— 研究者部分》

Relation of Ideal Cardiovascular Health Metrics to Asymptomatic Polyvascular Disease in a Chinese Population

第一作者：Qian Zhang,Ruixuan Jiang

通讯作者：Xingquan Zhao,Shouling Wu

Ideal Cardiovascular Health Metrics; CVH; Asymptom

基本信息

2017-08-01

已发表文章

发表杂志：American Journal of Cardiology

发表类型: Original Contributions

影响因子(IF): 2.778

PMID: 28599801 Pubmed原文链接 全文下载

主要研究背景及目的

Atherosclerosis is a systemic disease with manifestations in multiple vascular beds. Ideal cardiovascular health (CVH) metrics relate to cardiovascular and cerebrovascular disease. However, the relation between ideal CVH metrics and asymptomatic polyvascular disease (polyVD) is unknown.

方法

We collected information on the 7 CVH metrics among 5,224 par- ticipants aged ‡40 years from 2010 to 2011. Intracranial artery stenosis, extracranial artery stenosis, and lower extremity artery disease were detected by transcranial Doppler, duplex sonography, and by calculating ankle-brachial index. Ordinal logistic regression and linear models were used to analyze the relation between ideal CVH metrics and polyVD.

结论

In conclusion, we observed a significant inverse gradient association between the number of ideal CVH metrics and prevalence of asymptomatic polyVD.

主要结果

PolyVD was identified in 158 (3%) participants. We observed a significant inverse gradient relation between the number of ideal CVH metrics and prevalence of polyVD after adjustment for potential confounders. The adjusted odds ratios and 95% confidence intervals were 0.824 (0.657 to 1.032), 0.641 (0.511 to 0.804), 0.538 (0.423 to 0.684), 0.583 (0.442 to 0.769), and 0.530 (0.348 to 0.808) for those having 2, 3, 4, 5, and 6 or 7 ideal CVH metrics, respectively, compared with those having 0 or 1 ideal CVH metric (p-trend <0.0001). Similarly, a larger number of ideal CVH metrics was associated with a lower prevalence of polyVD in the linear models (adjusted b coefficient L0.030, 95% confidence interval L0.041 to L0.020). Stratification for gender and age yielded consistent results in all subgroups except for women subgroup.