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Abstract
Propofol’s pharmacokinetics have been extensively studied using human blood samples and applied to target-controlled infusion systems; however, information on its concentration in the brain remains scarce. Therefore, this study aimed to simultaneously measure propofol plasma and brain concentrations in patients who underwent awake craniotomy and establish new pharmacokinetic model. Fifty-seven patients with brain tumors or brain lesions who underwent awake craniotomy were sequentially assigned to model-building and validating groups. Plasma and brain (lobectomy or uncapping margins) samples were collected at five time-points. The concentration of propofol was measured using high-performance liquid chromatography. Population pharmacokinetic analysis was conducted through a nonlinear mixed-effects modeling program using a first-order conditional estimation method with interactions. Propofol’s brain concentrations were higher than its plasma concentrations. The measured brain concentrations were higher than the effect site concentrations using the previous models. Extended models were constructed based on measured concentrations by incorporating the brain/plasma partition coefficient (Kp value). Extended models showed good predictive accuracy for brain concentrations in the validating group. The Kp value functioned as a factor explaining retention in the brain. Our new pharmacokinetic models and Kp value can predict propofol’s brain and plasma concentrations, contributing to safer and more stable anesthesia.
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Details
1 Kyoto University Hospital, Department of Clinical Pharmacology and Therapeutics, Kyoto, Japan (GRID:grid.411217.0) (ISNI:0000 0004 0531 2775)
2 Kyoto University Hospital, Department of Clinical Pharmacology and Therapeutics, Kyoto, Japan (GRID:grid.411217.0) (ISNI:0000 0004 0531 2775); Kyoto University, Graduate School of Pharmaceutical Sciences, Kyoto, Japan (GRID:grid.258799.8) (ISNI:0000 0004 0372 2033)
3 Kyoto University Graduate School of Medicine, Department of Neurosurgery, Kyoto, Japan (GRID:grid.258799.8) (ISNI:0000 0004 0372 2033); Kyoto University Graduate School of Medicine, Department of Artificial Intelligence in Healthcare and Medicine, Kyoto, Japan (GRID:grid.258799.8) (ISNI:0000 0004 0372 2033)
4 Kyoto University Hospital, Department of Anesthesia, Kyoto, Japan (GRID:grid.411217.0) (ISNI:0000 0004 0531 2775)
5 Kyoto University Graduate School of Medicine, Department of Neurosurgery, Kyoto, Japan (GRID:grid.258799.8) (ISNI:0000 0004 0372 2033)
6 Kyoto University Hospital, Cancer Center, Kyoto, Japan (GRID:grid.411217.0) (ISNI:0000 0004 0531 2775)