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Updated: May 5, 2026
Pulse Wave Velocity Testing in the Baltimore Longitudinal Study of Aging
Published on: February 7, 2014
Aortic pulse wave velocity improves cardiovascular event prediction: an individual participant meta-analysis of
Yoav Ben-Shlomo1, Melissa Spears1, Chris Boustred1
1School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.
Insights
Aortic pulse wave velocity (aPWV) significantly improves cardiovascular disease (CVD) risk prediction beyond traditional factors. This marker aids in identifying high-risk individuals for targeted management strategies.
Area of Science:
- Cardiovascular Medicine
- Medical Diagnostics
Background:
- Aortic pulse wave velocity (aPWV) is a potential predictor of cardiovascular disease (CVD).
- Previous studies were underpowered to confirm aPWV's predictive value across diverse subgroups.
Purpose of the Study:
- To assess if aPWV enhances cardiovascular disease (CVD) event prediction beyond established risk factors.
- To evaluate aPWV's utility in identifying at-risk populations for proactive CVD management.
Main Methods:
- Systematic review and individual participant data analysis from 16 studies.
- Utilized Cox proportional hazard and random effect models to pool data on aPWV and CVD outcomes.
- Analyzed associations across various demographic and clinical subgroups.
Main Results:
- A total of 17,635 participants were included, with 1,785 (10%) experiencing a CVD event.
- Increased aPWV was significantly associated with higher risks of coronary heart disease, stroke, and overall CVD events.
- aPWV remained an independent predictor of CVD events after adjusting for conventional risk factors, with improved risk reclassification observed in some subgroups.
Conclusions:
- Incorporating aPWV into risk prediction models improves their fit and aids in reclassifying risk for future CVD events.
- aPWV can facilitate better identification of high-risk populations requiring intensified CVD risk factor management.
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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