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Int J Cardiol. 2014 Jan 15;171(1):31-6. doi: 10.1016/j.ijcard.2013.11.039. Epub 2013 Nov 23.

Reservoir and excess pressures predict cardiovascular events in high-risk patients.

Author information

1
Health & Environment Department, AIT Austrian Institute of Technology, Vienna, Austria; International Centre for Circulatory Health, National Heart & Lung Institute, Imperial College London, United Kingdom. Electronic address: bernhard.hametner@ait.ac.at.
2
Health & Environment Department, AIT Austrian Institute of Technology, Vienna, Austria; Department of Analysis and Scientific Computing, Vienna University of Technology, Vienna, Austria.
3
UCL Institute of Cardiovascular Science, University College London, United Kingdom.
4
Department of Bioengineering, Imperial College London, United Kingdom.
5
Cardiology Department, Klinikum Wels-Grieskirchen, Wels, Austria.

Abstract

BACKGROUND:

Analysis of the arterial pressure curve plays an increasing role in cardiovascular risk stratification. Measures of wave reflection and aortic stiffness have been identified as independent predictors of risk. Their determination is usually based on wave propagation models of the circulation. Another modeling approach relies on modified Windkessel models, where pressure curves can be divided into reservoir and excess pressure. Little is known of their prognostic value.

METHODS AND RESULTS:

The aim of this study is to evaluate the predictive value of parameters gained from reservoir theory applied to aortic pressure curves in a cohort of high-risk patients. Furthermore the relation of these parameters to those from wave separation analysis is investigated. Central pressure curves from 674 patients with preserved ejection fraction, measured by radial tonometry and a validated transfer function, were analyzed. A high correlation between the amplitudes of backward traveling pressure waves and reservoir pressures was found (R=0.97). Various parameters calculated from the reservoir and excess pressure waveforms predicted cardiovascular events in univariate Cox proportional hazards modeling. In a multivariate model including several other risk factors such as brachial blood pressure, the amplitude of reservoir pressure remained a significant predictor (HR=1.37 per SD, p=0.016).

CONCLUSIONS:

Based on very different models, parameters from reservoir theory and wave separation analysis are closely related and can predict cardiovascular events to a similar extent. Although Windkessel models cannot describe all of the physiological properties of the arterial system, they can be useful to analyze its behavior and to predict cardiovascular events.

KEYWORDS:

Arterial reservoir; Arterial stiffness; Pulse wave analysis; Wave reflections; Wave separation analysis

PMID:
24315153
DOI:
10.1016/j.ijcard.2013.11.039
[Indexed for MEDLINE]
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