Aortic pulse wave velocity improves cardiovascular event prediction

An individual participant meta-analysis of prospective observational data from 17,635 subjects

Yoav Ben-Shlomo*, Melissa Spears, Chris Boustred, Margaret May, Simon G. Anderson, Emelia J. Benjamin, Pierre Boutouyrie, James Cameron, Chen Huan Chen, J. Kennedy Cruickshank, Shih Jen Hwang, Edward G. Lakatta, Stephane Laurent, João Maldonado, Gary F. Mitchell, Samer S. Najjar, Anne B. Newman, Mitsuru Ohishi, Bruno Pannier, Telmo Pereira & 11 others Ramachandran S. Vasan, Tomoki Shokawa, Kim Sutton-Tyrell, Francis Verbeke, Kang Ling Wang, David J. Webb, Tine Willum Hansen, Sophia Zoungas, Carmel M. McEniery, John R. Cockcroft, Ian B. Wilkinson

*Corresponding author for this work

Research output: Contribution to journalArticle

795 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)636-646
Number of pages11
JournalJournal of the American College of Cardiology
Volume63
Issue number7
DOIs
Publication statusPublished - 25 Feb 2014
Externally publishedYes

Keywords

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

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