Pulse Wave Velocity and Digital Volume Pulse as Indirect Estimators of Blood Pressure: Pilot Study on Healthy Volunteers
Pulse Wave Velocity and Digital Volume Pulse as Indirect Estimators of Blood Pressure: Pilot Study on Healthy Volunteers
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DOI：
10.1007/s10558-009-9080-5
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发表时间：
2009-09-01
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影响因子：
--
通讯作者：
Facila, Lorenzo
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作者：
Padilla, Juan M.;Berjano, Enrique J.;Facila, Lorenzo
该研究的目的是评估脉搏波速度(PWV)和数字容积脉搏(DVP)作为估计收缩压(SBP)和舒张压(DPB)的潜在用途。进行了单一和多重相关性研究，包括生物测量参数和危险因素。分别从脉冲轨迹PWV和脉冲轨迹PCA(脉冲轮廓分析)获得臂踝PWV(BaPWV)和DVP信号。计算了DVP(通过光体积描记获得)、允许刚性(SI)和反射指数(RI)。对47名健康志愿者的第一项研究表明，SBP和DPB都与baPWV和SI显著相关。多元回归模型的基础脉搏血流量和腰臀比(腰臀比)允许分别用r=0.838和r=0.673来模拟收缩压和舒张压。SI结果还考虑了腰臀比并模拟了收缩压和舒张压，分别为r=0.852和r=0.663。RI与SBP、DBP均无相关性。为了避免使用超声技术来测量PWV，我们开发了一种定制的系统，通过光体积描记来测量PWV，并对照脉搏轨迹进行了验证。使用相同的设备，我们对10名健康志愿者进行了第二次先导性研究。考虑R波至食指之间的心指PWV、腰臀比和心率的最佳SBP多元回归模型r=0.997。在DBP模型中，只有腰臀比有显著意义。我们的发现表明，hfPWV光体积图信号可以可靠地估计近似SBP，例如，可以用来监测心脏康复运动期间的心脏患者。
The purpose of the study was to asses the potential use of pulse wave velocity (PWV) and digital volume pulse (DVP) as estimators of systolic (SBP) and diastolic (DPB) blood pressure. Single and multiple correlation studies were conducted, including biometric parameters and risk factors. Brachial-ankle PWV (baPWV) and DVP signals were obtained from a Pulse Trace PWV and Pulse Trace PCA (pulse contour analysis), respectively. The DVP (obtained by photoplethysmography), allowed stiffness (SI) and reflection indexes (RI) to be derived. The first study on 47 healthy volunteers showed that both SBP and DPB correlated significantly both with baPWV and SI. Multiple regression models of the baPWV and the waist-to-hip ratio (WHR) allowed SBP and DBP to be modeled with r = 0.838 and r = 0.673, respectively. SI results also employed WHR and modeled SBP and DBP with r = 0.852 and r = 0.663, respectively. RI did not correlate either with SBP or DBP. In order to avoid the use of ultrasound techniques to measure PWV, we then developed a custom-built system to measure PWV by photoplethysmography and validated it against the Pulse Trace. With the same equipment we conducted a second pilot study with ten healthy volunteers. The best SBP multiple regression model for SBP achieved r = 0.997 by considering the heart-finger PWV (hfPWV measured between R-wave and index finger), WHR and heart rate. Only WHR was significant in the DBP model. Our findings suggest that the hfPWV photoplethysmography signal could be a reliable estimator of approximate SBP and could be used, for example, to monitor cardiac patients during physical exercise sessions in cardiac rehabilitation.