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Aortic pulse wave velocity improves cardiovascular event prediction: an individual participant meta-analysis of prospective observational data from 17,635 subjects.

Authors :
Ben-Shlomo, Yoav
Spears, Melissa
Boustred, Chris
May, Margaret
Anderson, Simon G
Benjamin, Emelia J
Boutouyrie, Pierre
Cameron, James
Chen, Chen-Huan
Cruickshank, J Kennedy
Hwang, Shih-Jen
Lakatta, Edward G
Laurent, Stephane
Maldonado, Joao
Mitchell, Gary F
Najjar, Samer S
Newman, Anne B
Ohishi, Mitsuru
Pannier, Bruno
Pereira, Telmo
Source :
Journal of the American College of Cardiology (JACC). Feb2014, Vol. 63 Issue 7, p636-646. 11p.
Publication Year :
2014

Abstract

<bold>Objectives: </bold>The goal of this study was to determine whether aortic pulse wave velocity (aPWV) improves prediction of cardiovascular disease (CVD) events beyond conventional risk factors.<bold>Background: </bold>Several studies have shown that aPWV may be a useful risk factor for predicting CVD, but they have been underpowered to examine whether this is true for different subgroups.<bold>Methods: </bold>We undertook a systematic review and obtained individual participant data from 16 studies. Study-specific associations of aPWV with CVD outcomes were determined using Cox proportional hazard models and random effect models to estimate pooled effects.<bold>Results: </bold>Of 17,635 participants, a total of 1,785 (10%) had a CVD event. The pooled age- and sex-adjusted hazard ratios (HRs) per 1-SD change in loge aPWV were 1.35 (95% confidence interval [CI]: 1.22 to 1.50; p < 0.001) for coronary heart disease, 1.54 (95% CI: 1.34 to 1.78; p < 0.001) for stroke, and 1.45 (95% CI: 1.30 to 1.61; p < 0.001) for CVD. Associations stratified according to sex, diabetes, and hypertension were similar but decreased with age (1.89, 1.77, 1.36, and 1.23 for age ≤50, 51 to 60, 61 to 70, and >70 years, respectively; pinteraction <0.001). After adjusting for conventional risk factors, aPWV remained a predictor of coronary heart disease (HR: 1.23 [95% CI: 1.11 to 1.35]; p < 0.001), stroke (HR: 1.28 [95% CI: 1.16 to 1.42]; p < 0.001), and CVD events (HR: 1.30 [95% CI: 1.18 to 1.43]; p < 0.001). Reclassification indices showed that the addition of aPWV improved risk prediction (13% for 10-year CVD risk for intermediate risk) for some subgroups.<bold>Conclusions: </bold>Consideration of aPWV improves model fit and reclassifies risk for future CVD events in models that include standard risk factors. aPWV may enable better identification of high-risk populations that might benefit from more aggressive CVD risk factor management. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07351097
Volume :
63
Issue :
7
Database :
Academic Search Index
Journal :
Journal of the American College of Cardiology (JACC)
Publication Type :
Academic Journal
Accession number :
104027670
Full Text :
https://doi.org/10.1016/j.jacc.2013.09.063