声学定量和脉冲波多普勒测定心输出量的对比研究

应用声学定量(Acoustic Quantification;AQ)和脉冲波多普勒(Pulsed Wave;PW)同时测定32例心输出量,发现二者高度相关(r=0.97-0.99)。前者能以曲线的形式,实时地显示整个心动周期的左室容积及射血分数,更直观、方便、快捷。     

Hemodynamic Impact of the C‐Pulse Cardiac Support Device: A One‐Dimensional Arterial Model Study

The C‐Pulse is a novel extra‐aortic counter‐pulsation device to unload the heart in patients with heart failure. Its impact on overall hemodynamics, however, is not fully understood. In this study, the function of the C‐Pulse heart assist system is implemented in a one‐dimensional (1‐D) model of the arterial tree, and central and peripheral pressure and flow waveforms with the C‐Pulse turned on and off were simulated. The results were studied using wave intensity analysis and compared with in vivo data measured non‐invasively in three patients with heart failure and with invasive data measured in a large animal (pig). In all cases the activation of the C‐Pulse was discernible by the presence of a diastolic augmentation in the pressure and flow waveforms. Activation of the device initiates a forward traveling compression wave, whereas a forward traveling expansion wave is associated to the device relaxation, with waves exerting an action in the coronary and the carotid vascular beds. We also found that the stiffness of the arterial tree is an important determinant of action of the device. In settings with reduced arterial compliance, the same level of aortic compression demands higher values of external pressure, leading to stronger hemodynamic effects and enhanced perfusion. We conclude that the 1‐D model may be used as an efficient tool for predicting the hemodynamic impact of the C‐Pulse system in the entire arterial tree, complementing in vivo observations.     

基于脉搏波信号和血管弹性腔模型的动脉血压连续测量方法

目的为满足健康监护中的连续测量血压的要求,研究并实现一种基于脉搏波信号和血管弹性腔模型的动脉血压拟合计算方法。方法利用自制的穿戴式人体生理参数监测系统收集测试对象的脉搏波信号、心电信号以及血压数据。根据心电信号与脉搏波信号的时间关系,推导出收缩压和脉搏波传导时间的回归分析方程,而舒张压的测量,则是通过脉搏波的波形系数分析以及血管单弹性腔模型的参数计算完成。结果试验结果表明,该方法血压测量结果的平均偏差和标准偏差为(0.51±0.74)kPa([384±5.54)mmHg],达到了美国医疗仪器促进协会建议的(0.665±1.064)kPa([5±8)mmHg]标准。结论结合脉搏波信号和弹性腔模型可以估算人体血压值,为连续血压测量提供了新的实现方法。     

Wave intensity analysis and the development of the reservoir–wave approach

The parameters of wave intensity analysis are calculated from incremental changes in pressure and velocity. While it is clear that forward- and backward-traveling waves induce incremental changes in pressure, not all incremental changes in pressure are due to waves; changes in pressure may also be due to changes in the volume of a compliant structure. When the left ventricular ejects blood rapidly into the aorta, aortic pressure increases, in part, because of the increase in aortic volume: aortic inflow is momentarily greater than aortic outflow. Therefore, to properly quantify the effects of forward or backward waves on arterial pressure and velocity (flow), the component of the incremental change in arterial pressure that is due only to this increase in arterial volume—and not, fundamentally, due to waves—first must be excluded. This component is the pressure generated by the filling and emptying of the reservoir, Otto Frank’s Windkessel.     

经胆道镜治疗胆道难取性残留结石

目的：对碎石结合胆道镜取石治疗胆管难取性结石的有效性和安全性作出初步评估。方法：采用碎石后经胆道镜取石的方法治疗１５０例胆道难取性残留结石。其中活检钳碎石５５例,压电冲击波碎石１７例,液电冲击波碎石３８例,碎石篮碎石４０例。对取石失败者联合应用十二指肠镜括约肌切开或乳头气囊导管扩张术（ＥＳＴ／ＥＰＴ）。结果：活检钳碎石、压电冲击波、民冲击波和取石篮碎石取石成功率分别为９０．９％、９４．１％、９４．     

瞬时波强技术在新领域的研究进展

瞬时波强是一项评估心血管系统的总体功能新技术。文中首先简介瞬时波强的概念、原理、参数意义,其后对此项技术在高血压、内分泌、儿科及妇科疾病等新领域中的研究进展进行综述。     

Relationship between Renying pulse augmentation index and Cunkou pulse condition in different blood pressure groups

Objective

To explore the relationship between Renying pulse (carotid) augmentation index (AI) and Cunkou pulse condition in different blood pressure groups, and the clinical significance of Renying and Cunkou pulse parameters to reflect vascular function.

Methods

Eighty-six patients with essential hypertension (EH) and 52 individuals with normal blood pressure (control group) between September 2010 and January 2012 were included in this study. Renying pulse AI was examined by a new diagnostic tool (ALOKA ProSound Alpha 10) — wave intensity (WI) that is calculated as the product of the derivatives of the simultaneously recorded blood pressure changes (dP/dt) and blood-flow-velocity changes (dU/dt), while Cunkou pulse condition was detected by DDMX-100 Pulse Apparatus in both EH and control groups. A multifactorial correlation analysis was performed for data analysis.

Results

After adjusting for potential confounding variables, in the EH group, AI was positively correlated with t₅, w_2/t (r_t5=0.225, P<0.05; r_w2/t=0.230, P< 0.05) and negatively correlated with h₅, h₅/h₁ and w₂ (r_h5= − 0.393, P<0.01; r_h5/h1= − 0.444, P<0.01; r_w2= − 0.389, P<0.01). In the control group, AI was positively correlated with t₃, t₄, t₅ and w₁ (r_t3=0.595, P<0.01; r_t4= 0.292, P<0.05; r_t5=0.318, P<0.05; r_w1=0.541, P<0.01) and negatively correlated with h₁, h₂, h₃, Ad and A (r_h1= − 0.368, P<0.05; r_h2= − 0.330, P<0.05; r_h3= − 0.327, P< 0.05; r_Ad= − 0.322, P<0.05; r_A= − 0.410, P<0.01). In the total sample group (EH plus control group, n= 138), AI was positively correlated with t, t₅, w₁ and w_2/t (r_t=0.257, P<0.01; r_t5=0.266, P<0.01; r_w1=0.184, P< 0.05; r_w2/t=0.210, P<0.05) and negatively correlated with h₅, h₅/h₁, w₂ and Ad (r_h5= − 0.230, P<0.01; r_h5/h1= − 0.218, P<0.05; r_w2= − 0.267, P<0.01; r_Ad= - 0.246, P<0.01). Multiple linear regression analysis was carried out to model the relationship (F=7.887, P< 0.001).

Conclusion

Renying pulse AI can effectively predict arterial stiffness in synchrony with the manifestations of Cunkou pulse in elderly patients with hypertension. Cunkou pulse apparatus is a valuable tool for evaluating AI in clinical practice. The close correlations reported above reflect the holistic concept of Traditional Chinese Medicine.     

Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences

BackgroundCoronary Wave Intensity Analysis (cWIA) is a technique capable of separating the effects of proximal arterial haemodynamics from cardiac mechanics. Studies have identified WIA-derived indices that are closely correlated with several disease processes and predictive of functional recovery following myocardial infarction. The cWIA clinical application has, however, been limited by technical challenges including a lack of standardization across different studies and the derived indices' sensitivity to the processing parameters. Specifically, a critical step in WIA is the noise removal for evaluation of derivatives of the acquired signals, typically performed by applying a Savitzky–Golay filter, to reduce the high frequency acquisition noise.MethodsThe impact of the filter parameter selection on cWIA output, and on the derived clinical metrics (integral areas and peaks of the major waves), is first analysed. The sensitivity analysis is performed either by using the filter as a differentiator to calculate the signals' time derivative or by applying the filter to smooth the ensemble-averaged waveforms.Furthermore, the power-spectrum of the ensemble-averaged waveforms contains little high-frequency components, which motivated us to propose an alternative approach to compute the time derivatives of the acquired waveforms using a central finite difference scheme.Results and ConclusionThe cWIA output and consequently the derived clinical metrics are significantly affected by the filter parameters, irrespective of its use as a smoothing filter or a differentiator. The proposed approach is parameter-free and, when applied to the 10 in-vivo human datasets and the 50 in-vivo animal datasets, enhances the cWIA robustness by significantly reducing the outcome variability (by 60%).