Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand.
GIGA-Cardiovascular Sciences, University of Liège, Liège, Belgium.
Ann Biomed Eng. 2018 Jan;46(1):171-185. doi: 10.1007/s10439-017-1947-9. Epub 2017 Oct 25.
This paper develops a method for the minimally invasive, beat-by-beat estimation of the left ventricular pressure-volume loop. This method estimates the left ventricular pressure and volume waveforms that make up the pressure-volume loop using clinically available inputs supported by a short, baseline echocardiography reading. Validation was performed across 142,169 heartbeats of data from 11 Piétrain pigs subject to two distinct protocols encompassing sepsis, dobutamine administration and clinical interventions. The method effectively located pressure-volume loops, with low overall median errors in end-diastolic volume of 8.6%, end-systolic volume of 17.3%, systolic pressure of 19.4% and diastolic pressure of 6.5%. The method further demonstrated a low overall mean error of 23.2% predicting resulting stroke work, and high correlation coefficients along with a high percentage of trend compass 'in band' performance tracking changes in stroke work as patient condition varied. This set of results forms a body of evidence for the potential clinical utility of the method. While further validation in humans is required, the method has the potential to aid in clinical decision making across a range of clinical interventions and disease state disturbances by providing real-time, beat-to-beat, patient specific information at the intensive care unit bedside without requiring additional invasive instrumentation.
本文提出了一种微创、逐搏估计左心室压力-容积环的方法。该方法使用临床可用的输入,结合短基线超声心动图读数,估计构成压力-容积环的左心室压力和容积波形。在经过两个不同方案的验证后,该方案在 11 头 Piétrain 猪的 142169 次心跳数据中得到了验证,这些数据包括脓毒症、多巴酚丁胺给药和临床干预。该方法有效地定位了压力-容积环,舒张末期容积、收缩末期容积、收缩压和舒张压的总体中位数误差分别为 8.6%、17.3%、19.4%和 6.5%。该方法进一步证明了预测心搏量功的总体平均误差低至 23.2%,并具有较高的相关系数,以及高百分比的趋势罗盘“在带内”性能,可跟踪患者病情变化时的心搏量功变化。这组结果为该方法的潜在临床应用提供了证据。虽然还需要在人体中进一步验证,但该方法有可能通过在重症监护病房床边提供实时、逐搏、患者特异性信息,而无需额外的侵入性仪器,从而在一系列临床干预和疾病状态干扰中辅助临床决策。