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J Am Coll Cardiol. 2014 Feb 25;63(7):636-646. doi: 10.1016/j.jacc.2013.09.063. Epub 2013 Nov 13.

Aortic pulse wave velocity improves cardiovascular event prediction: an individual participant meta-analysis of prospective observational data from 17,635 subjects.

Author information

1
School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom. Electronic address: y.ben-shlomo@bristol.ac.uk.
2
School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.
3
Institute of Cardiovascular Sciences, University of Manchester, United Kingdom.
4
National Heart Lung and Blood Institute and Boston University's Framingham Heart Study, Cardiology Section, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts.
5
INSERM U 970, Paris-Descartes University, Hopital Europeen Georges Pompidou, Assistance Publique Hopitaux de Paris, Paris, France.
6
Monash Cardiovascular Research Centre, MonashHEART and Monash University Department of Medicine (MMC), Melbourne, Australia.
7
School of Medicine, National Yang-Ming University, Taipei, Taiwan.
8
King's College & King's Health Partners, St. Thomas' & Guy's Hospital, London, United Kingdom.
9
Branch of Population Sciences, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, Maryland.
10
Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, Maryland.
11
Instituto de Investigação e Formação Cardiovascular, Penacova, Portugal.
12
Cardiovascular Engineering, Inc., Norwood, Massachusetts.
13
Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, Maryland; MedStar Heart Research Institute, Washington, DC.
14
Center for Aging and Population Health, Pittsburgh, Pennsylvania.
15
Department of Geriatric Medicine, Osaka University, Osaka, Japan.
16
Centre d'Investigations Preventives et Cliniques, Paris, France.
17
Escola Superior de Tecnologia da Saúde de Coimbra, Coimbra, Portugal.
18
National Heart Lung and Blood Institute and Boston University's Framingham Heart Study, Department of Medicine, Boston University, Boston, Massachusetts.
19
Department of Molecular and Internal Medicine, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan.
20
Department of Nephrology, Ghent University Hospital, Ghent, Belgium.
21
University/BHF Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom.
22
Research Center for Prevention and Health, Glostrup Hospital, Glostrup and Steno Diabetes Center, Glostrup, Denmark.
23
School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
24
Clinical Pharmacology Unit, University of Cambridge, Cambridge, United Kingdom.
25
Wales Heart Research Institute, Cardiff, United Kingdom.

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.

KEYWORDS:

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

PMID:
24239664
PMCID:
PMC4401072
DOI:
10.1016/j.jacc.2013.09.063
[Indexed for MEDLINE]
Free PMC Article

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