Gurovich Alvaro N, Beck Darren T, Braith Randy W
Center for Exercise Science, Department of Applied Physiology and Kinesiology, College of Health and Human Performance, University of Florida, PO Box 118206, Gainesville, FL 32611, USA.
Exp Biol Med (Maywood). 2009 Nov;234(11):1339-44. doi: 10.3181/0902-RM-88. Epub 2009 Aug 5.
Arterial Stiffness (AS) is a primary cardiovascular risk factor. AS increases myocardial oxygen demand and LV work and decreases coronary perfusion. Pulse Wave Velocity (PWV) is considered the gold standard for assessing AS. However, PWV testing is time consuming and impractical in the clinical setting. The purpose of this study was to determine if Pulse Wave Analysis (PWA) parameters obtained with applanation tonometry can be used to predict PWV. Radial artery PWA testing and aortic PWV measurements were performed on 77 apparently healthy subjects. A correlation matrix between all the studied variables and a stepwise multiple regression were performed. The best regression equation was obtained with central PWV as the dependent variable and Age, Height, Weight, Brachial Systolic and Diastolic Blood pressures, normalized and non-normalized Augmentation Index, Cardiac Cycle time, Ejection Duration, reflected wave round trip travel time, and time to peak pressure as independent variables. Finally, a Bland-Altman test was performed to determine the agreement between measured and predicted PWV. No significant correlations between PWV and PWA parameters were found. The resulting stepwise regression equation was PWV = 1.76 + 0.044Age + 0.023SBP (R = 0.544, Adj-R(2) = 0.28, P < 0.001). No agreement between measured and predicted PWV was observed using the Bland-Altman test. Although the regression equation is significant, the adjusted coefficient of determination shows that the model could explain just 28% of PWV variability. These findings suggest that PWA should not be used as a surrogate measure for assessing aortic PWV and stiffness.
动脉僵硬度(AS)是主要的心血管危险因素。AS增加心肌需氧量和左心室做功,并减少冠状动脉灌注。脉搏波速度(PWV)被认为是评估AS的金标准。然而,PWV检测在临床环境中既耗时又不实用。本研究的目的是确定通过压平式眼压测量法获得的脉搏波分析(PWA)参数是否可用于预测PWV。对77名看似健康的受试者进行了桡动脉PWA检测和主动脉PWV测量。对所有研究变量进行了相关矩阵分析和逐步多元回归分析。以中心PWV作为因变量,年龄、身高、体重、肱动脉收缩压和舒张压、标准化和非标准化增强指数、心动周期时间、射血持续时间、反射波往返传播时间以及压力峰值时间作为自变量,得到了最佳回归方程。最后,进行了Bland-Altman检验以确定测量的PWV与预测的PWV之间的一致性。未发现PWV与PWA参数之间存在显著相关性。所得的逐步回归方程为PWV = 1.76 + 0.044×年龄 + 0.023×收缩压(R = 0.544,调整后R² = 0.28,P < 0.001)。使用Bland-Altman检验未观察到测量的PWV与预测的PWV之间的一致性。尽管回归方程具有显著性,但调整后的决定系数表明该模型仅能解释PWV变异性的28%。这些发现表明,PWA不应被用作评估主动脉PWV和僵硬度的替代指标。