Keller Steven P, Chang Brian Y, Tan Qing, Zhang Zhengyang, El Katerji Ahmad, Edelman Elazer R
Institute for Medical Engineering and Science, Massachusetts Institutes of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA.
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
Ann Biomed Eng. 2020 Sep;48(9):2333-2342. doi: 10.1007/s10439-020-02510-3. Epub 2020 Apr 13.
Clinical adoption of mechanical circulatory support for shock is rapidly expanding. Achieving optimal therapeutic benefit requires metrics of state to guide titration and weaning of support. Using the transvalvular positioning of a percutaneous ventricular assist device (pVAD), device:heart interactions are leveraged to determine cardiac output (CO) and systemic vascular resistance (SVR) near-continuously without disrupting therapeutic function. An automated algorithm rapidly alternates between device support levels to dynamically modulate physiological response. Employing a two-element lumped parameter model of the vasculature, SVR and CO are quantified directly from measurements obtained by the pVAD without external calibration or invasive catheters. The approach was validated in an acute porcine model across a range of cardiac (CO = 3-10.6 L/min) and vascular (SVR = 501-1897 dyn s/cm) states. Cardiac output calculations closely correlated (r = 0.82) to measurements obtained by the pulmonary artery catheter-based thermodilution method with a mean bias of 0.109 L/min and limits of agreement from - 1.67 to 1.89 L/min. SVR was also closely correlated (r = 0.86) to traditional catheter-based measurements with a mean bias of 62.1 dyn s/cm and limits of agreement from - 260 to 384 dyn s/cm. Use of diagnostics integrated into therapeutic device function enables the potential for optimizing support to improve outcomes for cardiogenic shock.
用于休克治疗的机械循环支持在临床上的应用正在迅速扩展。要实现最佳治疗效果,需要有状态指标来指导支持治疗的滴定和撤机。利用经皮心室辅助装置(pVAD)的跨瓣定位,借助装置与心脏的相互作用来近乎连续地确定心输出量(CO)和全身血管阻力(SVR),同时不干扰治疗功能。一种自动算法在装置支持水平之间快速切换,以动态调节生理反应。采用血管系统的双元件集总参数模型,可直接根据pVAD获得的测量值对SVR和CO进行量化,无需外部校准或侵入性导管。该方法在急性猪模型中针对一系列心脏(CO = 3 - 10.6 L/min)和血管(SVR = 501 - 1897 dyn s/cm)状态进行了验证。心输出量计算结果与基于肺动脉导管热稀释法获得的测量值密切相关(r = 0.82),平均偏差为0.109 L/min,一致性界限为 -1.67至1.89 L/min。SVR与传统的基于导管的测量值也密切相关(r = 0.86),平均偏差为62.1 dyn s/cm,一致性界限为 -260至384 dyn s/cm。将诊断功能集成到治疗设备功能中,有可能优化支持治疗,从而改善心源性休克的治疗结果。