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Cited by 1,835Cardiovascular Health and Disease PreventionCardiovascular Function and Risk FactorsCardiovascular Disease and Adiposity

The DOI matches its Crossref record; 59 of the 60 references it cites were found in a registry or an index.

Aortic Pulse Wave Velocity Improves Cardiovascular Event Prediction

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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, João, 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., Willum Hansen, Tine, Zoungas, Sophia, McEniery, Carmel M., Cockcroft, John R., Wilkinson, Ian B.·2014·Journal of the American College of Cardiology
DOI 10.1016/j.jacc.2013.09.063PMC PMC4401072
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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.

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Authors
Ben-Shlomo, Y., Spears, M., Boustred, C., May, M., Anderson, S. G., Benjamin, E. J., Boutouyrie, P., Cameron, J., Chen, C.-H., Cruickshank, J. K., Hwang, S.-J., Lakatta, E. G., Laurent, S., Maldonado, J., Mitchell, G. F., Najjar, S. S., Newman, A. B., Ohishi, M., Pannier, B., Pereira, T., Vasan, R. S., Shokawa, T., Sutton-Tyrell, K., Verbeke, F., Wang, K.-L., Webb, D. J., Willum Hansen, T., Zoungas, S., McEniery, C. M., Cockcroft, J. R., & Wilkinson, I. B.
Affiliations
  • University of Bristol (GB)
  • University of Manchester (GB)
  • Boston University (US)
  • Inserm (FR)
  • Monash Medical Centre (AU)
  • National Yang Ming University (TW)
  • Guy's Hospital (GB)
  • National Heart, Lung, and Blood Institute (US)
  • National Institutes of Health (US)
  • University of Pittsburgh (US)
  • The University of Osaka (JP)
  • Escola Superior de Tecnologia da Saúde de Coimbra (PT)
  • Hiroshima University (JP)
  • Ghent University Hospital (BE)
  • The Queen's Medical Research Institute (GB)
  • Monash University (AU)
  • University of Cambridge (GB)
ORCID
Venue
Journal of the American College of Cardiology
Publisher
Elsevier BV
Published
2014-02
Volume
63
Issue
7
Pages
636-646
ISSN
0735-1097 (ISSN-L)
DOI
10.1016/j.jacc.2013.09.063
PMC
PMC4401072
OpenAlex
W2143691602
Cited by
1,835
References
60
Citations by year
2026: 105 · 2025: 132 · 2024: 151 · 2023: 134 · 2022: 178 · 2021: 179 · 2020: 169 · 2019: 162 · 2018: 144 · 2017: 145 · 2016: 128 · 2015: 133 · 2014: 73
FWCI
75.98
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of the American College of Cardiology (publishedVersion)
  • PubMed (publishedVersion)
  • Research Explorer (The University of Manchester) (publishedVersion)
  • PubMed Central (acceptedVersion)
  • Ghent University Academic Bibliography (Ghent University) (submittedVersion)
  • Research Portal (King's College London) (submittedVersion)
  • Explore Bristol Research (submittedVersion)
  • Bristol Research (University of Bristol) (submittedVersion)
Funders
  • National Institutes of Health Research Methods Training Fellowship
  • AtCor and Esaote
  • National Institutes of Health.
  • HeartWare Inc.
  • British Heart Foundation
  • Cambridge Biomedical Research Centre
Topics
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Disease Prevention
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Function and Risk Factors
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Disease and Adiposity
Keywords
aortic pulse wave velocity, cardiovascular risk prediction, coronary artery disease, stroke, cardiovascular events, risk reclassification, atherosclerosis, diabetes mellitus, hypertension, risk stratification, sex differences, subgroup analysis, cardiovascular risk factors, cardiovascular risk prediction models
MeSH terms
Aorta, Cardiovascular Diseases, Humans, Predictive Value of Tests, Prospective Studies, Pulse Wave Analysis, Observational Studies as Topic

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