TY - JOUR
T1 - Aortic pulse wave velocity improves cardiovascular event prediction
T2 - An individual participant meta-analysis of prospective observational data from 17,635 subjects
AU - Ben-Shlomo, Yoav
AU - Spears, Melissa
AU - Boustred, Chris
AU - May, Margaret
AU - Anderson, Simon G.
AU - Benjamin, Emelia J.
AU - Boutouyrie, Pierre
AU - Cameron, James
AU - Chen, Chen Huan
AU - Cruickshank, J. Kennedy
AU - Hwang, Shih Jen
AU - Lakatta, Edward G.
AU - Laurent, Stephane
AU - Maldonado, João
AU - Mitchell, Gary F.
AU - Najjar, Samer S.
AU - Newman, Anne B.
AU - Ohishi, Mitsuru
AU - Pannier, Bruno
AU - Pereira, Telmo
AU - Vasan, Ramachandran S.
AU - Shokawa, Tomoki
AU - Sutton-Tyrell, Kim
AU - Verbeke, Francis
AU - Wang, Kang Ling
AU - Webb, David J.
AU - Willum Hansen, Tine
AU - Zoungas, Sophia
AU - McEniery, Carmel M.
AU - Cockcroft, John R.
AU - Wilkinson, Ian B.
PY - 2014/2/25
Y1 - 2014/2/25
N2 - Objectives 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. Background 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. Methods 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. Results 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. Conclusions 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.
AB - Objectives 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. Background 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. Methods 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. Results 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. Conclusions 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.
KW - cardiovascular disease
KW - meta-analysis
KW - prognostic factor
KW - pulse wave velocity
UR - http://www.scopus.com/inward/record.url?scp=84896709653&partnerID=8YFLogxK
U2 - 10.1016/j.jacc.2013.09.063
DO - 10.1016/j.jacc.2013.09.063
M3 - Article
C2 - 24239664
AN - SCOPUS:84896709653
SN - 0735-1097
VL - 63
SP - 636
EP - 646
JO - Journal of the American College of Cardiology
JF - Journal of the American College of Cardiology
IS - 7
ER -