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Updated: Mar 22, 2026
Pulse Wave Velocity Testing in the Baltimore Longitudinal Study of Aging
Published on: February 7, 2014
Prognostic significance of mechanical biomarkers derived from pulse wave analysis for predicting long-term
Hao-Min Cheng1, Shao-Yuan Chuang2, Jiun-Jr Wang3
1Department of Medical Education, Taipei Veterans General Hospital, Taipei, Taiwan; Cardiovascular Research Center, National Yang-Ming University, Taipei, Taiwan; Faculty of Medicine, National Yang-Ming University, Taipei, Taiwan; Department of Public Health, National Yang-Ming University, Taipei, Taiwan.
Background:
Numerous mechanical biomarkers derived from pulse wave analysis (PWA) have been proposed to predict cardiovascular outcomes. However, whether these biomarkers carry independent prognostic value and clinical utility beyond traditional cardiovascular risk factors hasn't been systematically evaluated. We aimed to investigate the additive utility of PWA-derived biomarkers in two independent population-based cohorts.
Methods:
PWA on central arterial pressure waveforms obtained from subjects without a prior history of cardiovascular diseases of two studies was conducted based on the wave transmission and reservoir-wave theory: firstly in the Kinmen study (1272 individuals, a median follow-up of 19.8years); and then in the Cardiovascular Disease Risk Factors Two-Township Study (2221 individuals, median follow-up of 10years). The incremental value of the biomarkers was evaluated by net reclassification index (NRI).
Results:
In multivariate Cox analyses accounting for age, gender, body mass index, systolic blood pressure, fasting glucose, high-density- and low-density-lipoprotein cholesterol, and smoking, only systolic (SC) and diastolic rate constant (DC) of reservoir pressure could independently and consistently predict cardiovascular mortality in both cohorts and the combined cohort (SC: hazard ratio 1.18 [95% confidence interval 1.08-1.28, p<0.001; DC: 1.18 [1.09-1.28], p<0.001]. Risk prediction estimates in traditional risk prediction models were significantly more accurate when incorporating peak of reservoir pressure (NRI=0.049, p=0.0361), SC (NRI=0.043, p=0.0236) and DC (NRI=0.054, p=0.047).
Conclusions:
Of all PWA-derived biomarkers, SC and DC were consistently identified as valuable parameters for incremental cardiovascular risk prediction in two large prospective cohorts.
