BACKGROUND: The Eleveld pharmacokinetic/pharmacodynamic (PKPD) model for propofol encounters predictive difficulties in certain clinical scenarios. This might be a consequence of the linear model framework used in the development of compartmental models. We aimed to evaluate whether Eleveld’s predicted effects correlate with the actual neurophysiological responses in patients before and after a brief burst suppression period that could be considered a pharmacological perturbation. METHODS: We conducted a nonrandomized dose–response study. Twenty-three healthy young patients scheduled for surgery under general anesthesia were included in the study. Following slow and titrated induction and tracheal intubation, we initiated a pharmacological perturbation by administrating a 15 mg·kg −1 ·h − 1 propofol infusion until a 1% burst suppression rate was achieved. We then returned to the propofol concentration predicted by the Eleveld model needed to achieve unresponsiveness. We compared the actual bispectral index (BIS) with the predicted BIS by the Eleveld PKPD model throughout the study protocol. We also analyzed the electroencephalographic signal to compare the power spectrum and the delta-alpha phase-amplitude modulation before and after the perturbation. RESULTS: Before perturbation, there was no significant difference between the mean ± standard deviation (SD) observed and the predicted BIS (64.5 ± 10.7 vs 61.3 ± 8.7, respectively, paired t test P = .3). However, after pharmacological perturbation, actual BIS was consistently lower than the predicted BIS (38.2 ± 7.5 vs 55.5 ± 7.5, paired t test; P < .001). Accordingly, despite propofol effect-site concentration returned to the level before perturbation, alpha power remained lower and phase-amplitude modulation strength was significantly higher after the perturbation (0.16 ± 0.04 vs 0.21 ± 0.06; P = .01). CONCLUSIONS: These findings suggest that current models are inadequate in explaining the dose-effect relationship of propofol’s anesthetic properties. Specifically, linear models are unable to capture the nonlinear dynamics of brain activity and their response to disturbances, such as a brief period of burst suppression.
Sepúlveda et al. (Mon,) studied this question.