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出血期间心输出量和血容量的个体特异性模型估计

Subject-specific model estimation of cardiac output and blood volume during hemorrhage.

作者信息

Neal Maxwell Lewis, Bassingthwaighte James B

机构信息

Department of Medical Education and Biomedical Informatics, University of Washington, Seattle, WA 98195, USA.

出版信息

Cardiovasc Eng. 2007 Sep;7(3):97-120. doi: 10.1007/s10558-007-9035-7.

Abstract

We have developed a novel method for estimating subject-specific hemodynamics during hemorrhage. First, a mathematical model representing a closed-loop circulation and baroreceptor feedback system was parameterized to match the baseline physiology of individual experimental subjects by fitting model results to 1 min of pre-injury data. This automated parameterization process matched pre-injury measurements within 1.4 +/- 1.3% SD. Tuned parameters were then used in similar open-loop models to simulate dynamics post-injury. Cardiac output (CO) estimates were obtained continuously using post-injury measurements of arterial blood pressure (ABP) and heart rate (HR) as inputs to the first open-loop model. Secondarily, total blood volume (TBV) estimates were obtained by summing the blood volumes in all the circulatory segments of a second open-loop model that used measured CO as an additional input. We validated the estimation method by comparing model CO results to flowprobe measurements in 14 pigs. Overall, CO estimates had a Bland-Altman bias of -0.30 l/min with upper and lower limits of agreement 0.80 and -1.40 l/min. The negative bias is likely due to overestimation of the peripheral resistance response to hemorrhage. There was no reference measurement of TBV; however, the estimates appeared reasonable and clearly predicted survival versus death during the post-hemorrhage period. Both open-loop models ran in real time on a computer with a 2.4 GHz processor, and their clinical applicability in emergency care scenarios is discussed.

摘要

我们开发了一种用于估计出血期间个体特异性血流动力学的新方法。首先,通过将模型结果与1分钟的损伤前数据拟合,对代表闭环循环和压力感受器反馈系统的数学模型进行参数化,以匹配个体实验对象的基线生理学。这种自动参数化过程使损伤前测量值在1.4±1.3%标准差范围内匹配。然后,将调整后的参数用于类似的开环模型,以模拟损伤后的动态变化。使用损伤后测量的动脉血压(ABP)和心率(HR)作为第一个开环模型的输入,连续获得心输出量(CO)估计值。其次,通过将第二个开环模型所有循环段中的血容量相加来获得总血容量(TBV)估计值,该模型使用测量的CO作为额外输入。我们通过将模型CO结果与14头猪的流量探头测量值进行比较,验证了该估计方法。总体而言,CO估计值的Bland-Altman偏差为-0.30升/分钟,一致性上限和下限分别为0.80和-1.40升/分钟。负偏差可能是由于对出血外周阻力反应的高估。没有TBV的参考测量值;然而,这些估计值似乎合理,并且清楚地预测了出血后时期的存活与死亡情况。两个开环模型都在配备2.4 GHz处理器的计算机上实时运行,并讨论了它们在急诊护理场景中的临床适用性。

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