PSE-Lab, Process Systems Engineering Laboratory, Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano, Piazza Leonardo da Vinci 32, Milano 20133, Italy.
Department of Electrical & Computer Engineering, The University of British Columbia, Vancouver, British Columbia, Canada.
Comput Methods Programs Biomed. 2020 Aug;192:105406. doi: 10.1016/j.cmpb.2020.105406. Epub 2020 Feb 19.
Intraoperative hemodynamic stability is essential to safety and post-operative well-being of patients and should be optimized in closed-loop control of anesthesia. Cardiovascular changes inducing variations in pharmacokinetics may require dose modification. Rigorous investigational tools can strengthen current knowledge of the anesthesiologists and support clinical practice. We quantify the cardiovascular response of high-risk patients to closed-loop anesthesia and propose a new application of physiologically-based pharmacokinetic-pharmacodynamic (PBPK-PD) simulations to examine the effect of hemodynamic changes on the depth of hypnosis (DoH).
We evaluate clinical hemodynamic changes in response to anesthesia induction in high-risk patients from a study on closed-loop anesthesia. We develop and validate a PBPK-PD model to simulate the effect of changes in cardiac output (CO) on plasma levels and DoH. The wavelet-based anesthetic value for central nervous system monitoring index (WAV) is used as clinical end-point of propofol hypnotic effect.
The median (interquartile range, IQR) changes in CO and arterial pressure (AP), 3 min after induction of anesthesia, are 22.43 (14.82-36.0) % and 26.60 (22.39-35.33) % respectively. The decrease in heart rate (HR) is less marked, i.e. 8.82 (4.94-12.68) %. The cardiovascular response is comparable or less enhanced than in manual propofol induction studies. PBPK simulations show that the marked decrease in CO coincides with high predicted plasma levels and deep levels of hypnosis, i.e. WAV < 40. PD model identification is improved using the PBPK model rather than a standard three-compartment PK model. PD simulations reveal that a 30% drop in CO can cause a 30% change in WAV.
Significant CO drops produce increased predicted plasma concentrations corresponding to deeper anesthesia, which is potentially dangerous for elderly patients. PBPK-PD model simulations allow studying and quantifying these effects to improve clinical practice.
术中血流动力学的稳定性对患者的安全和术后舒适度至关重要，应在麻醉的闭环控制中进行优化。诱导心血管变化可能会引起药代动力学的变化，需要进行剂量调整。严格的研究工具可以增强麻醉医师的现有知识，并支持临床实践。我们量化了高危患者对闭环麻醉的心血管反应，并提出了生理相关药代动力学-药效动力学（PBPK-PD）模拟的新应用，以检查血流动力学变化对催眠深度（DoH）的影响。
我们评估了来自闭环麻醉研究中高危患者对麻醉诱导的临床血流动力学变化。我们开发并验证了一个 PBPK-PD 模型，以模拟心输出量（CO）变化对血浆水平和 DoH 的影响。基于小波的中枢神经系统监测指标的麻醉值（WAV）用作丙泊酚催眠作用的临床终点。
麻醉诱导后 3 分钟时，CO 和动脉压（AP）的中位数（四分位距，IQR）变化分别为 22.43（14.82-36.0）%和 26.60（22.39-35.33）%。心率（HR）的下降幅度较小，即 8.82（4.94-12.68）%。心血管反应与手动丙泊酚诱导研究相当或增强程度较小。PBPK 模拟表明，CO 的显著下降与高预测血浆水平和深度催眠一致，即 WAV<40。使用 PBPK 模型而不是标准三腔 PK 模型进行 PD 模型识别可提高 PD 模型的识别能力。PD 模拟显示，CO 下降 30%可导致 WAV 变化 30%。
显著的 CO 下降会导致预测的血浆浓度增加，从而导致麻醉深度增加，这对老年患者可能是危险的。PBPK-PD 模型模拟允许研究和量化这些影响，以改善临床实践。
