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Published on: May 3, 2018
Predictive Value of Carotid Distensibility Coefficient for Cardiovascular Diseases and All-Cause Mortality: A
Chuang Yuan1, Jing Wang2,3, Michael Ying2
1Medical Research Center, Changsha Central Hospital, Changsha, Hunan, China.
Insights
Carotid distensibility coefficient (DC) significantly predicts cardiovascular diseases and mortality. Lower carotid DC indicates higher risk, aiding early identification and treatment of high-risk patients.
Area of Science:
- Vascular Biology and Medicine
- Cardiovascular Disease Risk Assessment
- Biomarkers for Atherosclerosis
Background:
- Arterial stiffness is a known risk factor for cardiovascular (CV) events and mortality.
- Carotid distensibility coefficient (DC) reflects local arterial stiffness and is accessible via imaging.
- The predictive value of carotid DC for CV diseases and mortality requires further clarification.
Purpose of the Study:
- To determine the pooled predictive value of carotid distensibility coefficient (DC) for cardiovascular diseases and all-cause mortality.
- To assess the association between carotid DC and future adverse CV outcomes.
- To evaluate carotid DC as a potential biomarker for cardiovascular risk stratification.
Main Methods:
- A meta-analysis was conducted.
- Included 11 longitudinal studies with a total of 20,361 participants.
- Analyzed the predictive value of carotid DC for CV events, CV mortality, and all-cause mortality.
Main Results:
- Carotid DC was a significant predictor of total CV events, CV mortality, and all-cause mortality.
- Lowest quartile of DC was associated with increased risk ratios for CV events (1.19), CV mortality (1.09), and all-cause mortality (1.65).
- A 1 SD decrease in DC increased risk by 13% for CV events, 6% for CV mortality, and 41% for all-cause mortality.
Conclusions:
- Carotid DC is a significant predictor of future cardiovascular diseases and all-cause mortality.
- Carotid DC can aid in identifying high-risk individuals for early diagnosis and treatment.
- This finding supports the use of carotid DC in cardiovascular risk assessment.
Aims:
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.
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