Comparing an Automatic PWV Analyser to Pulse Pressure in Hemodialysis

Chronic hemodialysis patients should have arterial stiffness evaluated monthly using Pulse Pressure as suggested by KDOQI guidelines [1]. This recommendation pursues a dual goal since it outlines the importance of monitoring vascular stiffness in hemodialysis patients [2-4] and, at the same time, emphasizes the fact that Pulse Pressure provides valuable information on tissue perfusion characteristics [5]. Arterial stiffening in dialysis patients is the result of aging, non-specific and End Stage Renal Disease (ESRD) related risk factors, such as medial calcification, volume overload, uraemia-related endothelial dysfunction, increased extracellular matrix and intimal fibroelastic thickening [6]. Arterial stiffness of the aorta and its major branches can be evaluated by measuring Pulse Wave Velocity (PWV) - e.g. carotid-femoral Pulse Wave Velocity ("gold standard") [7] - or, alternatively, it can be estimated by Pulse Wave Analysis (PWA) at a peripheral site, usually the brachial artery [8-11]. In the first case, a doppler ultrasound detector is used together with a software tool for data analysis. The second approach requires the use of a sphygmomanometer, such as the Mobil-O-Graph, capable of analysing the pulse wave morphology and of calculating PWV [9-14]. The first methodology is complex, operator-dependent and not routinely applicable, whereas the second one is potentially usable in clinical practice [9].

The increase in PWV related to the above-mentioned risk factors also accelerates with age [7].

Both PWV and PP correlate to mortality in the dialysis population [15-17]: for each PWV increase of 1 m/s Blacher et al. found an all-cause mortality-adjusted OR of 1.39 (95% CI, 1.19 to 1.62) [16] while for each 10 mmHg increase in PP, Tozawa et al. found an increase in all-cause mortality relative risk of 8% [17].

Risk factors such as age, hypertension, previous history of heart diseases and diabetes influence the evolution of Pulse Wave Velocity before dialysis initiation whereas their impact during the course of dialysis has not yet been demonstrated [18]. In this regard, a study published in 2013 by Utescu et al. indicated that the only risk factor significantly associated with PWV progression was the level of an advanced glycation end-product known as pentosidine [18]. The results of this study confirmed that specific uraemia-related risk factors can be identified and possibly quantified.

In the above-mentioned study, the rate of PWV progression (+0.84 m/s per year) was surprisingly high, especially when projected over time as a function of the average life span of ESRD patients on dialysis. Another critical data point outlined in the study was the discrepancy in the annual rate of change in carotid-femoral compared to carotid-radial Pulse Wave Velocity, which was +0.84 m/s per year and -0.66 m/s per year, respectively. The authors of the study postulate that this discrepancy may be due to anatomical differences between central (elastic) and peripheral (muscular) arteries and that the latter could deploy an adaptive response to central aortic stiffening. Although interesting, these data raise some concerns about the promising possibility of using the brachial artery as a site for PWV estimation, even if based on a non-operator dependent method.

Furthermore, another limitation identified in the literature currently available on prospective longitudinal studies analysing the PWV behaviour on dialysis patients, is the lack of a control group made up of patients with similar characteristics and co-morbidities but without kidney failure [2,16,18].

In the light of this, we decided to test a Mobil-O-Graph, a simple device estimating PWV (MogPWV) through a modified sphygmomanometer on the brachial artery and to analyse the baseline and follow-up MogPWV values in a cohort of dialysis patients and in a control group with the same risk factors but without kidney failure.

The aim of the study was answering the following 4 questions, which also reflect both the primary and the secondary endpoints of the trial: 1. Does PWV estimated by Mobil-O-Graph on the brachial artery, be more sensitive for vascular aging and better discriminate the dialysis population from the control group than pulse pressure? (primary endpoint); 2. Is MogPWV progression faster during dialysis than in the pre-dialysis setting? (secondary endpoint); 3. Are there specific risk factors that correlate to MogPWV progression? (secondary endpoint); 4. Does mortality correlate to MogPWV? (secondary endpoint).