Carotid Resistance and Pulsatility: Non-Invasive Markers for Diabetes Mellitus-Related Vascular Diseases

颈动脉阻力和搏动性:糖尿病相关血管疾病的非侵入性标志物

阅读:1

Abstract

Background: Diabetes mellitus (DM) is a major determinant of aging-related vascular diseases. The arterial pulsatility index (PI) and resistance index (RI) are biomarkers of vascular aging. The available data regarding DM with arterial PI and RI are limited. The specific aim of this study was to explore the relationships between DM and the segment-specific PI and RI of the extracranial carotid arteries. Methods: We enrolled 402 DM cases and 3416 non-DM controls from a community-based cohort. Each subject's blood flow velocities in the extracranial common (CCA), internal (ICA), and external (ECA) carotid arteries were measured by color Doppler ultrasonography and used to calculate PIs and RIs. Results: The DM cases had significantly higher age-sex-adjusted means of carotid RIs and PIs than the non-DM controls (all p-values < 0.005). After controlling for the effects of conventional cardio-metabolic risk factors, all carotid RIs and PIs remained significantly correlated with higher odds ratios (ORs) of having DM. The relationships with DM were stronger and more significant for the ECA RI and PI. The multivariable-adjusted ORs were 1.36 (95% confidence interval [CI], 1.21~1.54, p = 3.9 × 10(-7)) and 1.30 (95% CI, 1.17~1.45, p = 8.7 × 10(-7)) for 1.0 SD increases in the ECA RI and PI, respectively. Compared to the best fit model of conventional cardio-metabolic risk factors, the additions of the ECA RI and PI significantly increased the area under the receiver operating characteristic curve by 0.85% (95% CI, 0.11~1.59%; p = 0.023) and 0.69% (95% CI, 0.01~1.37%; p = 0.046), respectively. Conclusions: This study shows significantly positive associations between DM and carotid RIs and PIs. Carotid RIs and PIs are potential biomarkers for DM-related vascular diseases.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。