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 PereiraRamachandran 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

Research output: Contribution to journalArticlepeer-review


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
Issue number7
Early online date13 Nov 2013
Publication statusPublished - 25 Feb 2014


  • Aorta
  • Cardiovascular Diseases
  • Humans
  • Observational Study as Topic
  • Predictive Value of Tests
  • Prospective Studies
  • Pulse Wave Analysis


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