迈向肺动脉导管自动化：一项犬类验证研究。
Towards automating the pulmonary artery catheter: a canine validation study.
作者信息
Xu Da, Olivier N Bari, Mukkamala Ramakrishna
机构信息
Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA.
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:994-7. doi: 10.1109/IEMBS.2007.4352461.
We have recently introduced a unique technique to automatically estimate both cardiac output (CO) and left atrial pressure (LAP) by pulmonary artery pressure (PAP) waveform analysis. In this contribution, we review the technique and present its evaluation with respect to gold standard, but highly invasive, reference aortic flow probe CO and direct LAP catheter measurements from two dogs during various pharmacological interventions. We report that the technique achieved an overall CO error of 15.3% and an overall LAP error of 17.1% over a wide hemodynamic range. For comparison, the overall LAP error of classic end-diastolic PAP estimates was about three times as large. With further successful testing, the technique may ultimately be employed so as to effectively automate the pulmonary artery catheter.
我们最近引入了一种独特的技术，通过肺动脉压力（PAP）波形分析自动估算心输出量（CO）和左心房压力（LAP）。在本论文中，我们回顾了该技术，并展示了其相对于金标准（但具有高度侵入性）的评估，即参考主动脉流量探头测量的CO以及在两只狗进行各种药理学干预期间通过直接LAP导管测量的数据。我们报告称，在广泛的血流动力学范围内，该技术实现的CO总体误差为15.3%，LAP总体误差为17.1%。相比之下，经典舒张末期PAP估算的LAP总体误差大约是其三倍。经过进一步的成功测试，该技术最终可能会被用于有效实现肺动脉导管的自动化。
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