Ocasio W C, Rigney D R, Clark K P, Mark R G
Harvard-M.I.T. Division of Health Sciences and Technology, Boston, MA.
Comput Methods Programs Biomed. 1993 Apr;39(3-4):169-94. doi: 10.1016/0169-2607(93)90020-l.
We describe the theory and computer implementation of a newly-derived mathematical model for analyzing the shape of blood pressure waveforms. Input to the program consists of an ECG signal, plus a single continuous channel of peripheral blood pressure, which is often obtained invasively from an indwelling catheter during intensive-care monitoring or non-invasively from a tonometer. Output from the program includes a set of parameter estimates, made for every heart beat. Parameters of the model can be interpreted in terms of the capacitance of large arteries, the capacitance of peripheral arteries, the inertance of blood flow, the peripheral resistance, and arterial pressure due to basal vascular tone. Aortic flow due to contraction of the left ventricle is represented by a forcing function in the form of a descending ramp, the area under which represents the stroke volume. Differential equations describing the model are solved by the method of Laplace transforms, permitting rapid parameter estimation by the Levenberg-Marquardt algorithm. Parameter estimates and their confidence intervals are given in six examples, which are chosen to represent a variety of pressure waveforms that are observed during intensive-care monitoring. The examples demonstrate that some of the parameters may fluctuate markedly from beat to beat. Our program will find application in projects that are intended to correlate the details of the blood pressure waveform with other physiological variables, pathological conditions, and the effects of interventions.
我们描述了一种新推导的用于分析血压波形形状的数学模型的理论及计算机实现。该程序的输入包括一个心电图信号，以及一个外周血压的单一连续通道，外周血压通常在重症监护监测期间通过留置导管侵入性获取，或通过眼压计非侵入性获取。该程序的输出包括针对每个心跳得出的一组参数估计值。该模型的参数可以从大动脉的电容、外周动脉的电容、血流的惯性、外周阻力以及基础血管张力引起的动脉压力等方面进行解释。左心室收缩引起的主动脉血流由一个下降斜坡形式的强迫函数表示，其下的面积代表每搏输出量。描述该模型的微分方程通过拉普拉斯变换方法求解，从而允许使用列文伯格 - 马夸尔特算法进行快速参数估计。在六个示例中给出了参数估计值及其置信区间，这些示例被选来代表在重症监护监测期间观察到的各种压力波形。这些示例表明，一些参数可能在逐搏之间有显著波动。我们的程序将在旨在将血压波形细节与其他生理变量、病理状况以及干预效果相关联的项目中得到应用。
