Department of Health and Human Physiology, The University of Iowa, Iowa City, IA 52242, USA.
Am J Physiol Heart Circ Physiol. 2013 Jul 1;305(1):H135-42. doi: 10.1152/ajpheart.00916.2012. Epub 2013 Apr 26.
We hypothesized that demographic/anthropometric parameters can be used to estimate effective reflecting distance (EfRD), required to derive aortic pulse wave velocity (APWV), a prognostic marker of cardiovascular risk, from peripheral waveforms and that such estimates can discriminate differences in APWV and EfRD with aging and habitual endurance exercise in healthy adults. Ascending aortic pressure waveforms were derived from peripheral waveforms (brachial artery pressure, n = 25; and finger volume pulse, n = 15) via a transfer function and then used to determine the time delay between forward- and backward-traveling waves (Δtf-b). True EfRDs were computed as directly measured carotid-femoral pulse wave velocity (CFPWV) × 1/2Δtf-b and then used in regression analysis to establish an equation for EfRD based on demographic/anthropometric data (EfRD = 0.173·age + 0.661·BMI + 34.548 cm, where BMI is body mass index). We found good agreement between true and estimated APWV (Pearson's R² = 0.43; intraclass correlation = 0.64; both P < 0.05) and EfRD (R² = 0.24; intraclass correlation = 0.40; both P < 0.05). In young sedentary (22 ± 2 years, n = 6), older sedentary (62 ± 1 years, n = 24), and older endurance-trained (61 ± 2 years, n = 14) subjects, EfRD (from demographic/anthropometric parameters), APWV, and 1/2Δtf-b (from brachial artery pressure waveforms) were 52.0 ± 0.5, 61.8 ± 0.4, and 60.6 ± 0.5 cm; 6.4 ± 0.3, 9.6 ± 0.2, and 8.1 ± 0.2 m/s; and 82 ± 3, 65 ± 1 and 76 ± 2 ms (all P < 0.05), respectively. Our results demonstrate that APWV derived from peripheral waveforms using age and BMI to estimate EfRD correlates with CFPWV in healthy adults. This method can reliably detect the distal shift of the reflecting site with age and the increase in APWV with sedentary aging that is attenuated with habitual endurance exercise.
我们假设,人口统计学/人体测量学参数可用于估计有效反射距离(EfRD),以便从外周波形中得出主动脉脉搏波速度(APWV),APWV 是心血管风险的预后标志物,并且这些估计可以区分健康成年人中因年龄增长和习惯性耐力运动导致的 APWV 和 EfRD 的差异。通过传递函数从外周波形(肱动脉压,n = 25;和手指容积脉搏,n = 15)中得出升主动脉压力波形,然后用于确定前向和后向波之间的时间延迟(Δtf-b)。通过直接测量颈股脉搏波速度(CFPWV)×1/2Δtf-b 计算真实 EfRD,并将其用于回归分析,根据人口统计学/人体测量学数据建立 EfRD 方程(EfRD = 0.173·年龄 + 0.661·BMI + 34.548 cm,其中 BMI 是体重指数)。我们发现真实 APWV 和估计 APWV(Pearson 的 R² = 0.43;组内相关系数 = 0.64;两者 P < 0.05)以及 EfRD(R² = 0.24;组内相关系数 = 0.40;两者 P < 0.05)之间具有良好的一致性。在年轻久坐(22 ± 2 岁,n = 6)、年长久坐(62 ± 1 岁,n = 24)和年长耐力训练(61 ± 2 岁,n = 14)的受试者中,EfRD(来自人口统计学/人体测量学参数)、APWV 和 1/2Δtf-b(来自肱动脉压力波形)分别为 52.0 ± 0.5、61.8 ± 0.4 和 60.6 ± 0.5 cm;6.4 ± 0.3、9.6 ± 0.2 和 8.1 ± 0.2 m/s;82 ± 3、65 ± 1 和 76 ± 2 ms(均 P < 0.05)。我们的结果表明,使用年龄和 BMI 从外周波形中得出的 APWV 来估计 EfRD 与健康成年人的 CFPWV 相关。该方法可可靠地检测到随着年龄的增长反射点的远端移位,以及久坐不动的衰老导致的 APWV 增加,而习惯性耐力运动可减轻这种增加。