The effect of cardiac output on the pharmacokinetics and pharmacodynamics of propofol during closed-loop induction of anesthesia

Abstract

Background and objectiveIntraoperative 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). MethodsWe 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 (WAVCNS) is used as clinical end-point of propofol hypnotic effect. ResultsThe 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. WAVCNS < 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 WAVCNS. ConclusionsSignificant 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.