Aortic Pulse Wave Velocity Improves Cardiovascular Event Prediction An Individual Participant Meta-Analysis of Prospective Observational Data From 17,635 Subjects

作者：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; Vasan, Ramachandran S.; Shokawa, Tomoki; Sutton-Tyrell, Kim; Verbeke, Francis; Wang, Kang-Ling; Webb, David J.

来源：Journal of the American College of Cardiology, 2014, 63(7): 636-646.

DOI：10.1016/j.jacc.2013.09.063

• cardiovascular disease
• meta-analysis
• prognostic factor
• pulse wave velocity

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.

• 出版日期2014-2-25