Author/Authors :
Ben-Shlomo، نويسنده , , Yoav and Spears، نويسنده , , Melissa and Boustred، نويسنده , , Chris and May، نويسنده , , Margaret J. Anderson، نويسنده , , Simon G. and Benjamin، نويسنده , , Emelia J. and Boutouyrie، نويسنده , , Pierre and Cameron، نويسنده , , James and Chen، نويسنده , , Chen-Huan and Cruickshank، نويسنده , , J. Kennedy and Hwang، نويسنده , , Shih-Jen and Lakatta، نويسنده , , Edward G. and Laurent، نويسنده , , Stephane and Maldonado، نويسنده , , Joمo and Mitchell، نويسنده , , Gary F. and Najjar، نويسنده , , Samer S. and Newman، نويسنده , , Anne B. and Ohishi، نويسنده , , Mitsuru and Pannier، نويسنده , , Bruno and Pereira، نويسنده , , Telmo and Vasan، نويسنده , , Ramachandran S. and Shokawa، نويسنده , , Tomoki and Sutton-Tyrell، نويسنده , , Kim and Verbeke، نويسنده , , Francis and Wang، نويسنده , , Kang-Ling and Webb، نويسنده , , David J. and Willum Hansen، نويسنده , , Tine and Zoungas، نويسنده , , Sophia and McEniery، نويسنده , , Carmel M. and Cockcroft، نويسنده , , John R. and Wilkinson، نويسنده , , Ian B.، نويسنده ,
Abstract :
Objectives
al of this study was to determine whether aortic pulse wave velocity (aPWV) improves prediction of cardiovascular disease (CVD) events beyond conventional risk factors.
ound
l 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.
s
ertook 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.
s
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.
sions
eration 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.
