Jurmann M J, Rosenberg G, Snyder A J, Weiss W, Donachy J H, Pierce W S
Department of Surgery, College of Medicine, Pennsylvania State University, Hershey 17033.
ASAIO Trans. 1989 Jul-Sep;35(3):745-7. doi: 10.1097/00002480-198907000-00187.
To identify factors responsible for energy consumption, a retrospective investigation of the in-vivo performance of the 100 ml electric motor-driven left ventricular assist device (ELVAD), and the e-motor 100 ml total artificial heart, was undertaken. Multivariate regression analysis of the device parameters demonstrated that device flow, and estimated outlet pressure, were the most significant independent variables for predicting changes in motor power. Weighted least-square curvefit, using the product of these two variables, showed that changes in energy consumption can be well predicted for the ventricular assist device (r2 = 0.732). However, by applying the same model to the total artificial heart (ETAH), less favorable results were achieved (r2 = 0.422). In this model, device flow seemed to be more important in predicting energy consumption for the ETAH compared to the ELVAD. Therefore, changing the model by using flow to the third order significantly improved the fit (r2 = 0.6706) for the ETAH, and could compensate in part for the greater variability of the values and increased number of outliers in this group.
为确定能量消耗的相关因素，对100毫升电动左心室辅助装置（ELVAD）和100毫升电动全人工心脏的体内性能进行了回顾性研究。对装置参数进行多元回归分析表明，装置流量和估计出口压力是预测电机功率变化的最显著独立变量。使用这两个变量的乘积进行加权最小二乘曲线拟合表明，心室辅助装置的能量消耗变化能够得到很好的预测（r2 = 0.732）。然而，将相同模型应用于全人工心脏（ETAH）时，结果不太理想（r2 = 0.422）。在该模型中，与ELVAD相比，装置流量在预测ETAH的能量消耗方面似乎更为重要。因此，通过将流量提升至三阶来改变模型，显著改善了ETAH的拟合度（r2 = 0.6706），并且可以部分补偿该组中数值的较大变异性和异常值数量的增加。
