Arterial stiffness and prediction of cardiovascular risk

Cardiovascular disease remains one of the main contributors to morbidity and mortality in the developed world. Primary prevention of an unselected population has proven to be effective [1]. However, it is also obvious that this approach is not economically viable given the high cost per year of life saved multiplied by the number of possible beneficiaries [2]. This economical reality would only change if either treatment became more efficacious or less expensive [3]. In fact, as these primary prevention studies also demonstrated that risk and benefit is restricted to certain subpopulations, research has concentrated on identifying those subpopulations with higher risk, larger treatment benefits, reduced eligibility and, consequently, dramatically reduced cost to society. Known contributors to risk can be broadly defined as originating from five areas: (i) demographic factors – age [4], gender [4]; (ii) genetic determination – family history [5]; (iii) disease promoters – hypercholesterolaemia [4], hypertension [4], diabetes [4], smoking [4], obesity [6]; (iv) symptomatic disease – myocardial or cerebral ischaemia [7] and (v) asymptomatic disease – left ventricular hypertrophy [4], carotid artery stenosis [8], large artery stiffness [9–11]. Large epidemiological, longitudinal studies have clarified their individual contribution and the factors determined have been incorporated into risk prediction algorithms for asymptomatic individuals [4]. One example is the risk level suggested by the joint task force of European and other societies on coronary prevention [12], as employed by Nürnberger et al. [13] in the present issue of the journal, which was recently validated against an independent population [14]. As this predicts probability of future symptomatic disease based on a disease-free population, it becomes meaningless once disease has become symptomatic. Hence, it should not be applied to symptomatic populations as performed by Nürnberger et al. [13] (consider their Figure 1, which also includes patients with cardiovascular disease). Risk for further morbidity and mortality increases dramatically once subjects are symptomatic [7]. In consequence, these patients benefit most from (now secondary) prevention. A number of interventions have recently been shown to be effective, and these enjoyed a prompt uptake [15]. Currently available algorithms for the prediction of future events are based on observations that pre-date these changes to medical practice and may no longer accurately predict risk in subjects on treatment. This applies to the EPOZ score used in [13], whereas the SMART score used in [13] has not been prospectively validated in its prediction of risk. Current recommendations for secondary prevention do not employ risk scoring, but treat the presence of disease in a dichotomous fashion [12]. The contribution of asymptomatic disease has been studied less. As opposed to a simple demographic factor, such as age or gender, this involves the evaluation of the individual, with a potentially laborious method to detect such asymptomatic disease. However, it is hoped that the evaluation of asymptomatic individuals may help define subpopulations with lower and higher risk of future events. The latter may in turn be eligible for primary prevention at a cost more acceptable to the community. The assessment of arterial stiffness is an attractive candidate for a number or reasons. Arterial stiffness is associated with severity of coronary artery disease [16], severity of carotid artery disease [17], predicts future morbidity and mortality [9–11] and can be assessed automatically and non-invasively [18]. A number of methods are available, and a number of devices are now commercially available. This has the advantage that methods are easily accessible to anyone without special knowledge or association with a researcher specializing in arterial mechanics. In fact, commercial availability promotes applied research, such as that undertaken by Nürnberger et al. [13]. At the same time, the potential exists for scientists turned inventors/salesmen to introduce a commercial conflict of interest to the peer review process, even more than might ordinarily be expected from normal scientific argument or differences between basic/mechanistic and applied scientists. In particular, objective comparisons of the various methods in their predictive power are lacking, and these are unlikely to be forthcoming. Pulse wave contour analysis is one of several methods to assess arterial stiffness. It involves measuring (either invasively or non-invasively) a central arterial pressure wave. A sample of such a measured pressure waveform is given in Figure 1. The contraction of the left ventricle increases left ventricular pressure until the aortic valve opens. After aortic valve opening, left ventricular contraction continues and pressure keeps increasing until reaching a peak. This is followed later in the cardiac cycle by ventricular relaxation, expansion, aortic valve closure and diastole. The latter events are irrelevant for the present consideration.Fig. 1: The waveform in the centre is a carotid waveform obtained by applanation tonometry scaled to brachial artery mean and diastolic pressure (Dinamap). Diastolic pressure, 75 mmHg; systolic pressure, 142 mmHg; pulse pressure, 66 mmHg. Below is the measured wave decomposed into its forward and backward component (not to scale), based on ascending aortic flow measured with a 3.5-MHz continuous wave Doppler transducer in the suprasternal notch. Above is the fourth derivative of the pressure waveform, which can be used to mathematically define the augmentation point. With this method, the augmentation point is defined as the first zero crossing from positive to negative of the fourth derivative and this occurs 55 ms after the onset of systole. Pressure at this point is 101 mmHg. Hence, the augmentation index is (142 – 101)/66 = 62%.The increase in pressure at the aorti