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Aim: The sickle cell trait (SCT) is the heterozygous and benign form of the homozygous SC disease (SCD). Although SCT exhibits hemorheological disturbances and increased oxidative stress, its exact role in the development of cardiovascular disease in SCT remains to be determined. The present study sought to determine the arterial stiffness, an independent marker of sub-clinical atherosclerosis, between SCT and trained SCD. Materials and methods: Twelve SCT (43±11yrs, 6 males) were compared to 14 trained younger SCD (29±9yrs, 2 males) and 26 controls with normal hemoglobin (36±11rs, 13 males). Aortic (AoStiff-Physioflow) and peripheral arterial stiffness (pOpmetre-Axelife-France) assessed by foot-to-toe pulse wave velocity (ft-PWV), blood pressure (BP) and Framingham-Laurier cardiovascular risk score (CVR in %) were measured in each group. Results: SCT exhibited stiffer arteries (Aostiff: 5.8±0.71 m/s, ft-PWV: 10.9±6.2 m/s) than controls (Aostiff = 4.8±0.5 m/s, ft-PWV: 7.7±2.6 m/s) and SCD (Aostiff = 4.9±0.6 m/s, p=0.001, ft-PWV: 6.1±0.9 m/s p=0.003). SCT were older (p=0.001) than controls and SCD. The systolic and mean AP were lower in SCD than controls and SCT. In the whole group, the CVR score was the major contributor to PerStiff (r2=0.402, p

Analysis of the contour of the peripheral pulse to assess arterial properties was first described in the nineteenth century. The reference technique to estimate central blood pressure (CBP), non-invasively, is by analyzing the radial pressure pulse acquired using a tonometer and then to establish a transfer function relating the radial pressure to the CBP. An alternative technique utilizes a volume pulse. This may conveniently be acquired optically from a finger. This technique deserves further consideration because of its simplicity and ease of use. The objective is to establish a transfer function estimating the central blood pressure (CBP), calibrated with a brachial pressure cuff and using the parameters obtained with the contour analysis of the photoplethysmographic pulse measured at the finger with the pOpmetre® system. We positioned the photodiode sensor on the finger, insuring that the sensor's lens is in contact with the finger. Brachial blood pressure measurements was performed with a standard cuff. The central blood pressure values measured with Sphygmocor used as the reference values. Multiple regression analysis was done to establish the transfer functions. Sixty-nine subjects were included: 24 healthy subjects and 45 patients with essential hypertension aged 33 ± 8 years and 59 ± 17 years respectively. The correlation between the estimated central systolic pressure (CSP) and the reference one, was good and significant (r2 = 0.91; P

Background Arterial pulse wave velocity and pulse waveform analysis have become an established component of cardiovascular research. As validation and assessment of devices is not always trivial in an in vivo setting, arterial network computer models may be useful for that purpose. It is, however, mandatory that the model includes sufficient detail, especially when analysing peripheral waveforms. Purpose To extend the existing 1D arterial network model (103 segments) of Reymond et al. to a more detailed model (143 segments) including the foot and hand circulation (radial and tibial arteries). The goal is to (i) extend the existing 1D arterial network model (103 segments) of Reymond et al. to a more detailed model (143 segments) including the foot and hand circulation (Radial and Tibial arteries); (ii) use the extending model as testing tool for pOpmetre® (finger–toe pulse wave velocity). Method The arterial tree dimensions and properties were taken from the literature and completed with data from patient scans. The model solves the one-dimensional form of the Navier-Stokes equations over each arterial segment. A non-linear viscoelastic constitutive law for the arterial wall was considered. Result Comparison of simulations with & without detailed hand and foot circulation demonstrate important differences in waveform morphology in the distal beds. The completed model predicts pressure and flow waves in the hand and foot arteries which are in good qualitative agreement with the published in-vivo measurements. The agreement is especially good for the shape and wave details of the flow wave, where all features are reproduced in a rather faithful manner. The correlation between ftPWV and aPWV was good and significant (R2 = 0.95). The Bland and Altman analysis, mean difference was 0.4 m/s, classifying the ftPWV as good agreement with reference method. Conclusion The extended model yields realistic pressure and flow waveforms in arteries of the hand and the foot.

Objective: Pulse Wave Velocity (PWV) can be measured between different sites. Here we used two different aspects to assess the PWV; the standard method Carotid-Femoral (CF) Sphygmocor (AtCorMedical – Australia) and the pOpmetre ® (Axelife SAS – France) which uses the Finger to Toe (FT) signals. The aim of this study was to evaluate the agreement between FT-PWV and CF-PWV and to test the robustness of pOpmetre ® build-in algorithm. Design and method: CF and FT PWV was measured in 150 subjects. MatLab was used to calculate FT-PWV from pOpmetre ® waveforms using four methods: maximum of second derivative (used by pOpmetre ®), intersecting tangents, 10% threshold and the cross correlation method. Results: Using built in algorithms, the comparisons of the PWVs and transit times showed a good agreement between the two methods. FT-PWV correlated with CF-PWV (r2=0.51; p