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

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. Several studies have shown that aPWV may be a useful risk factor for predicting CVD, but they have been underpowered to exami...

Full description

Saved in:
Bibliographic Details
Published in:Journal of the American College of Cardiology Vol. 63; no. 7; p. 636
Main Authors: 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
Format: Journal Article
Language:English
Published: United States 25.02.2014
Subjects:
Aorta - physiology
Cardiovascular Diseases - diagnosis
Cardiovascular Diseases - epidemiology
Cardiovascular Diseases - physiopathology
Humans
Observational Studies as Topic
Predictive Value of Tests
Prospective Studies
Pulse Wave Analysis - methods
meta-analysis
cardiovascular disease
prognostic factor
pulse wave velocity
ISSN:1558-3597, 1558-3597
Online Access:Get more information
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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. 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. 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. 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. 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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
ObjectType-Review-3
content type line 23
ObjectType-Undefined-4
ISSN:1558-3597
1558-3597
DOI:10.1016/j.jacc.2013.09.063