Pharmacokinetics of propofol in severely obese surgical patients.

BACKGROUND: Existing PK models of propofol include sparse data from very obese patients. The aim of this study was to develop a PK model based on standardised surgical conditions and spanning from normal-weight up to, and including, a high number of very obese patients. METHODS: Adult patients scheduled for laparoscopic cholecystectomy or bariatric surgery were studied. Anaesthesia was induced with propofol 2 mg/kg adjusted body weight over 2 min followed by 6 mg/kg/h adjusted body weight over 30 min. For the remainder of the operation anaesthesia was maintained with sevoflurane. Remifentanil was dosed according to clinical need. Eight arterial samples were drawn in a randomised block sampling regimen over a span of 24 h. Time-concentration data were analysed by population PK modelling using non-linear mixed-effects modelling. RESULTS: Four hundred and seventy four serum propofol concentrations were collected from 69 patients aged 19-60 years with a BMI 21.6-67.3 kg/m2. Twenty one patients had a BMI above 50 kg/m2. A 3-compartment PK model was produced wherein three different body weight descriptors and sex were included as covariates in the final model. Total body weight was found to be a covariate for clearance and Q3; lean body weight for V1, V2 and Q2; predicted normal weight for V3 and sex for V1. The fixed allometric exponent of 0.75 applied to all clearance parameters improved the performance of the model. Accuracy and precision were 1.4% and 21.7% respectively in post-hoc performance evaluation. CONCLUSION: We have developed a new PK model of propofol that is suitable for all adult weight classes. Specifically, it is based on data from an unprecedented number of individuals with very high BMI.

External validation of the modified Marsh and Schnider models for medium-chain triglyceride propofol in target-controlled infusion anesthesia.

BACKGROUND: Propofol formulated with medium- and long-chain triglycerides (MCT/LCT propofol) has rapidly replaced propofol formulated with long-chain triglycerides (LCT propofol). Despite this shift, the modified Marsh and Schnider pharmacokinetic models developed using LCT propofol are still widely used for target-controlled infusion (TCI) of propofol. This study aimed to validate the external applicability of these models by evaluating their predictive performance during TCI of MCT/LCT propofol in general anesthesia. METHODS: Adult patients (n = 48) undergoing elective surgery received MCT/LCT propofol via a TCI system using either the modified Marsh or Schnider models. Blood samples were collected at various target propofol concentrations and at specific time points, including the loss of consciousness and the recovery of consciousness (13 samples per patient). The actual plasma concentration of propofol was determined using high-performance liquid chromatography. The predictive performance of each pharmacokinetic model was assessed by calculating four parameters: inaccuracy, bias, divergence, and wobble. RESULTS: Both the modified Marsh and Schnider models demonstrated predictive performances within clinically acceptable ranges for MCT/LCT propofol. The inaccuracy values were 24.4% for the modified Marsh model and 26.9% for the Schnider model. Both models showed an overall positive bias, 16.4% for the modified Marsh model and 16.6% for the Schnider model. The predictive performance of MCT/LCT propofol was comparable to that of LCT propofol, suggesting formulation changes might exert only a minor impact on the reliability of the TCI system during general anesthesia. Additionally, both models exhibited higher bias and inaccuracy at target concentrations ranging from 3.5 ~ 5 ug/ml than at concentrations between 2 ~ 3 ug/ml. CONCLUSIONS: The modified Marsh and Schnider models, initially developed for LCT propofol, remain clinically acceptable for TCI with MCT/LCT propofol. TRIAL REGISTRATION: This study was registered at the Clinical Research Information Service of the Korean National Institute of Health ( https://cris.nih.go.kr ; registration number: KCT0002191; 06/01/2017).

Nongenetic and genetic predictors of haemodynamic instability induced by propofol and opioids: A retrospective clinical study.

AIM: Propofol and opioids are commonly used in anaesthesia, but are highly susceptible to haemodynamic instability, thereby threatening the patient's surgical safety and prognosis. The purpose of this study was to investigate the predictors of haemodynamic instability and establish its predictive model. METHODS: A total of 150 Chinese patients undergoing thyroid or breast surgery participated in the study, with target-controlled infusion concentrations of propofol, opioids dosage, heart rate (HR), mean arterial pressure (MAP) and Narcotrend Index recorded at key points throughout the procedure. The Agena MassARRAY system was used to genotype candidate single nucleotide polymorphisms related to pharmacodynamics and pharmacokinetics of propofol and opioids. RESULTS: Among nongenetic factors, baseline HR (R = -.579, P < .001) and baseline MAP (R = -.725, P < .001) had a significant effect on the haemodynamic instability. Among genetic factors, the CT/CC genotype of GABRB1 rs4694846 (95% confidence interval [CI]: -11.309 to -3.155), AA/AG of OPRM1 rs1799971 (95%CI: 0.773 to 10.290), AA of CES2 rs8192925 (95%CI: 1.842 to 9.090) were associated with higher HR instability; the AA/GG genotype of NR1I2 rs6438550 (95%CI: 0.351 to 7.761), AA of BDNF rs2049046 (95%CI: -9.039 to -0.640) and GG of GABBR2 rs1167768 (95%CI: -10.146 to -1.740) were associated with higher MAP instability. The predictive models of HR and MAP fluctuations were developed, accounting for 45.0 and 59.2% of variations, respectively. CONCLUSION: We found that cardiovascular fundamentals and genetic variants of GABRB1, GABBR2, OPRM1, BDNF, CES2 and NR1I2 are associated with cardiovascular susceptibility, which can provide a reference for haemodynamic management in clinical anaesthesia.

Effect of CYB2B6 (c.516G>T), CYP2C9 (c.1075A>C) and UGT1A9 (c.98T>C) polymorphisms on propofol pharmacokinetics in patients submitted to colonoscopy: a cohort study.

BACKGROUND: The aim of this study was to investigate the effect of CYB2B6 (c.516G>T, rs3745274), CYP2C9 (c.1075A>C, rs1057910) and UGT1A9 (c.98T>C, rs72551330) polymorphisms on the pharmacokinetics of single-drug propofol in adult patients undergoing intravenous sedation. METHODS: In this prospective clinical study, a total of 124 patients undergoing anaesthesia with propofol, as a single drug, were evaluated when undergoing colonoscopy procedure. Clinical variables were obtained from the patient's anamnesis prior to performing the anaesthetic procedure, in the moment of the patient's loss of consciousness, during the colonoscopy exam (recorded every 5 min) and in the awakening time. RESULTS: Polymorphic genotypes for the rs3745274 and rs1057910 polymorphisms were associated with bispectral index, target-controlled infusion (TCI)/effector concentration of propofol and TCI/plasma concentration of propofol values. Based on multivariate analysis, it was observed that weight, age, surgery time, systolic blood pressure and the rs1057910 polymorphism corresponded to predictive values for the dose of propofol used. Weight (B = 4.807±0.897), age (B = 1.834±0.834) and duration of surgery (B = 8.164±1.624) corresponded to factors associated with increased propofol dose, while systolic blood pressure (B = -1.892±0.679) and the genotypes (AA vs CA) of the single nucleotide polymorphism (SNP) rs1057910 CYPP2C9 gene (B = -74.161±26.820) decreased the total dose of propofol used. CONCLUSION: We concluded that the rs1057910 and rs3745274 polymorphisms affect the metabolism of propofol in patients exclusively submitted to this drug. Thus, the knowledge of the polymorphic genotypes of the CYPP2C9 and CYB2B6 genes may be predictive of different metabolising phenotypes, suggesting expected behaviours of BIS parameter in the anaesthetic procedure, which contributes to safer monitoring by anaesthesiologists during the clinical intervention.

Population pharmacokinetic and pharmacodynamic model of propofol externally validated in Korean elderly subjects.

The Eleveld propofol pharmacokinetic (PK) model, which was developed based on a broad range of populations, showed greater bias (- 27%) in elderly subjects in a previous validation study conducted by Vellinga and colleagues. We aimed to develop and externally validate a new PK-pharmacodynamic (PK-PD) model of propofol for elderly subjects. A population PK-PD model was constructed using propofol plasma concentrations and bispectral index (BIS) values that were obtained from 31 subjects aged 65 years older in previously published phase I studies. The predictive performance of the newly-developed PK-PD model (Choi model) was assessed in a separate Korean elderly population and compared with that of the Eleveld model. A three-compartment mammillary model using an allometric expression and a sigmoid Emax model well-described the time courses of propofol concentrations and BIS values. The V1, V2, V3, Cl, Q1, Q2, E0, Emax, Ce50, γ, and ke0 of a 60-kg subject were 8.36, 58.0, 650 L, 1.26, 0.917, 0.669 L/min, 92.1, 18.7, 2.21 µg/mL, 2.89, and 0.138 /min, respectively. In the Choi model and Eleveld model, pooled biases (95% CI) of the propofol concentration were 7.78 ( 3.09-12.49) and 16.70 (9.46-23.93) and pooled inaccuracies were 22.84 (18.87-26.81) and 24.85 (18.07-31.63), respectively. The Choi PK model was less biased than the Eleveld PK model in Korean elderly subjects (age range: 65.0-79.0 yr; weight range: 45.0-75.3 kg). Our results suggest that the Choi PK model, particularly, is applicable to target-controlled infusion in non-obese Korean elderly subjects.

Remifentanil requirement for i-gel insertion is reduced in male patients with Parkinson's disease undergoing deep brain stimulator implantation: an up-and-down sequential allocation trial.

BACKGROUND: Laryngeal mask airways have been widely used in clinical practice. The aim of this study was to investigate whether the remifentanil requirement for facilitation of i-gel insertion in Parkinson's disease (PD) patients undergoing deep brain stimulation (DBS) surgery was different from that in non-PD (NPD) patients undergoing intracranial surgery. STUDY DESIGN: An up-and-down sequential allocation trial. METHODS: Male patients aged between 40 and 64 years old were enrolled. The first patient in each group (PD and NPD) group received an effect-site concentration (Ce) of remifentanil (Minto pharmacokinetic model) of 4.0 ng.ml-1 during a target-controlled infusion (TCI) of 3.5 µg.ml-1 propofol (Marsh pharmacokinetic model). The next dose of remifentanil was determined by the response of the previous patient. The Ce of remifentanil required for i-gel insertion in 50% of patients (EC50) was estimated by the modified Dixon's up-and-down method and by probit analysis. RESULTS: The PD group included 24 patients and the NPD group included 23. The EC50 of remifentanil for i-gel insertion during a TCI of 3.5 µg.ml-1 propofol estimated by the modified Dixon's up-and-down method in PD patients (2.38 ± 0.65 ng.ml-1) was significantly lower than in NPD patients (3.21 ± 0.49 ng.ml-1) (P = 0.03). From the probit analysis, the EC50 and EC95 (effective Ce in 95% of patients) of remifentanil were 1.95 (95% CI 1.52-2.36) ng.ml-1 and 3.12 (95% CI 2.53-5.84) ng.ml-1 in PD patients and 2.85 (95% CI 2.26-3.41) ng.ml-1 and 4.57 (95% CI 3.72-8.54) ng.ml-1 in NPD patients, respectively. CONCLUSIONS: The remifentanil requirement for successful i-gel insertion is reduced in male PD patients undergoing DBS implantation during propofol TCI induction. Clinicians should closely monitor the remifentanil requirement in patients with PD. TRIAL REGISTRATION: Registered at http://www.chictr.org.cn ( ChiCTR1900021760 ).

Asymmetric neural dynamics characterize loss and recovery of consciousness.

Anesthetics are known to disrupt neural interactions in cortical and subcortical brain circuits. While the effect of anesthetic drugs on consciousness is reversible, the neural mechanism mediating induction and recovery may be different. Insight into these distinct mechanisms can be gained from a systematic comparison of neural dynamics during slow induction of and emergence from anesthesia. To this end, we used functional magnetic resonance imaging (fMRI) data obtained in healthy volunteers before, during, and after the administration of propofol at incrementally adjusted target concentrations. We analyzed functional connectivity of corticocortical and subcorticocortical networks and the temporal autocorrelation of fMRI signal as an index of neural processing timescales. We found that en route to unconsciousness, temporal autocorrelation across the entire brain gradually increased, whereas functional connectivity gradually decreased. In contrast, regaining consciousness was associated with an abrupt restoration of cortical but not subcortical temporal autocorrelation and an abrupt boost of subcorticocortical functional connectivity. Pharmacokinetic effects could not account for the difference in neural dynamics between induction and emergence. We conclude that the induction and recovery phases of anesthesia follow asymmetric neural dynamics. A rapid increase in the speed of cortical neural processing and subcorticocortical neural interactions may be a mechanism that reboots consciousness.

Arginase II polymorphisms modify the hypotensive responses to propofol by affecting nitric oxide bioavailability.

PURPOSE: Propofol anesthesia is usually accompanied by hypotensive responses, which are at least in part mediated by nitric oxide (NO). Arginase I (ARG1) and arginase II (ARG2) compete with NO synthases for their common substrate L-arginine, therefore influencing the NO formation. We examined here whether ARG1 and ARG2 genotypes and haplotypes affect the changes in blood pressure and NO bioavailability in response to propofol. METHODS: Venous blood samples were collected from 167 patients at baseline and after 10 min of anesthesia with propofol. Genotypes were determined by polymerase chain reaction. Nitrite concentrations were measured by using an ozone-based chemiluminescence assay, while NOx (nitrites + nitrates) levels were determined by using the Griess reaction. RESULTS: We found that patients carrying the AG + GG genotypes for the rs3742879 polymorphism in ARG2 gene and the ARG2 GC haplotype show lower increases in nitrite levels and lower decreases in blood pressure after propofol anesthesia. On the other hand, subjects carrying the variant genotypes for the rs10483801 polymorphism in ARG2 gene show more intense decreases in blood pressure (CA genotype) and/or higher increases in nitrite levels (CA and AA genotypes) in response to propofol. CONCLUSION: Our results suggest that ARG2 variants affect the hypotensive responses to propofol, possibly by modifying NO bioavailability. TRIAL REGISTRATION: NCT02442232.

Prospective clinical validation of the Eleveld propofol pharmacokinetic-pharmacodynamic model in general anaesthesia.

BACKGROUND: Target-controlled infusion (TCI) systems incorporating pharmacokinetic (PK) or PK-pharmacodynamic (PK-PD) models can be used to facilitate drug administration. Existing models were developed using data from select populations, the use of which is, strictly speaking, limited to these populations. Recently a propofol PK-PD model was developed for a broad population range. The aim of the study was to prospectively validate this model in children, adults, older subjects, and obese adults undergoing general anaesthesia. METHODS: The 25 subjects included in each of four groups were stratified by age and weight. Subjects received propofol through TCI with the Eleveld model, titrated to a bispectral index (BIS) of 40-60. Arterial blood samples were collected at 5, 10, 20, 30, 40, and 60 min after the start of propofol infusion, and every 30 min thereafter, to a maximum of 10 samples. BIS was recorded continuously. Predictive performance was assessed using the Varvel criteria. RESULTS: For PK, the Eleveld model showed a bias < ±20% in children, adults, and obese adults, but a greater bias (-27%) in older subjects. Precision was <30% in all groups. For PD, the bias and wobble were <5 BIS units and the precision was close to 10 BIS units in all groups. Anaesthetists were able to achieve intraoperative BIS values of 40-60 using effect-site target concentrations about 85-140% of the age-adjusted Ce50. CONCLUSIONS: The Eleveld propofol PK-PD model showed predictive precision <30% for arterial plasma concentrations and BIS predictions with a low (population) bias when used in TCI in clinical anaesthesia practice.

Correlation of exhaled propofol with Narcotrend index and calculated propofol plasma levels in children undergoing surgery under total intravenous anesthesia - an observational study.

BACKGROUND: Exhaled propofol concentrations correlate with propofol concentrations in adult human blood and the brain tissue of rats, as well as with electroencephalography (EEG) based indices of anesthetic depth. The pharmacokinetics of propofol are however different in children compared to adults. The value of exhaled propofol measurements in pediatric anesthesia has not yet been investigated. Breathing system filters and breathing circuits can also interfere with the measurements. In this study, we investigated correlations between exhaled propofol (exP) concentrations and the Narkotrend Index (NI) as well as calculated propofol plasma concentrations. METHODS: A multi-capillary-column (MCC) combined with ion mobility spectrometry (IMS) was used to determine exP. Optimal positioning of breathing system filters (near-patient or patient-distant) and sample line (proximal or distal to filter) were investigated. Measurements were taken during induction (I), maintenance (M) and emergence (E) of children under total intravenous anesthesia (TIVA). Correlations between ExP concentrations and NI and predicted plasma propofol concentrations (using pediatric pharmacokinetic models Kataria and Paedfusor) were assessed using Pearson correlation and regression analysis. RESULTS: Near-patient positioning of breathing system filters led to continuously rising exP values when exP was measured proximal to the filters, and lower concentrations when exP was measured distal to the filters. The breathing system filters were therefore subsequently attached between the breathing system tubes and the inspiratory and expiratory limbs of the anesthetic machine. ExP concentrations significantly correlated with NI and propofol concentrations predicted by pharmacokinetic models during induction and maintenance of anesthesia. During emergence, exP significantly correlated with predicted propofol concentrations, but not with NI. CONCLUSION: In this study, we demonstrated that exP correlates with calculated propofol concentrations and NI during induction and maintenance in pediatric patients. However, the correlations are highly variable and there are substantial obstacles: Without patient proximal placement of filters, the breathing circuit tubing must be changed after each patient, and furthermore, during ventilation, a considerable additional loss of heat and moisture can occur. Adhesion of propofol to plastic parts (endotracheal tube, breathing circle) may especially be problematic during emergence. TRIAL REGISTRATION: The study was registered in the German registry of clinical studies (DRKS-ID:  DRKS00015795 ).

Do epoch lengths of hypnotic depth indicators affect estimated of blood-brain equilibration rate constants of propofol?

This study aimed to investigate the effect of epoch length of hypnotic depth indicators on the blood-brain equilibration rate constant (ke0) estimates of propofol. Propofol was administered by zero-order infusion (1.5, 3.0, 6, and 12 mg·kg-1·h-1) for one hour in 63 healthy volunteers. The ke0 of propofol was estimated using an effect-compartment model linking pharmacokinetics and pharmacodynamics, in which response variables were electroencephalographic approximate entropy (ApEn) or bispectral index (BIS) (n = 32 each for propofol infusion rates of 6 and 12 mg·kg-1·h-1). Epoch lengths of ApEn were 2, 10, 30, and 60 seconds (s). The correlations between plasma propofol concentrations (Cp) and BIS and ApEn 2, 10, 30, and 60 s were determined, as was the Ce associated with 50% probability of unconsciousness (Ce50,LOC). The pharmacokinetics of propofol were well described by a three-compartment model. The correlation coefficient between Cp and ApEn 2, 10, 30, and 60 s were -0.64, -0.54, -0.39, and -0.26, respectively, whereas correlation coefficient between Cp and BIS was -0.74. The blood-brain equilibration half-life based on the ke0 estimates for ApEn at 2, 10, 30, 60 s and BIS were 4.31, 3.96, 5.78. 6.54, 5.09 min, respectively, whereas the Ce50,LOC for ApEn at 2, 10, 30, 60 s and BIS were 1.55, 1.47, 1.28, 1.04, and 1.55 µg·ml-1, respectively. Since ke0, which determines the onset of drug action, varies according to the epoch length, it is necessary to consider the epoch length together when estimating ke0.

Pharmacokinetics and effects on clinical and physiological parameters following a single bolus dose of propofol in common marmosets (Callithrix jacchus).

The objectives of this study were (a) to establish a population pharmacokinetic model and (b) to investigate the clinical and physiological effects of a single bolus dose of propofol in common marmosets. In Study 1, pharmacokinetic analysis was performed in six marmosets under sevoflurane anaesthesia. 8 mg/kg of propofol was administrated at a rate of 4 mg kg-1  min-1 . Blood samples were collected 2, 5, 15, 30, 60, 90, 120 or 180 min after starting propofol administration. Plasma concentration was measured, and population pharmacokinetic modelling was performed. A two-compartment model was selected as the final model. The population pharmacokinetic parameters were as follows: V1  = 1.14 L, V2  = 77.6 L, CL1  = 0.00182 L/min, CL2  = 0.0461 L/min. In Study 2, clinical and physiological parameters were assessed and recorded every 2 min after 12 mg/kg of propofol was administrated at a rate of 4 mg kg-1  min-1 . Immobilization was sustained for 5 min following propofol administration without apparent bradycardia. While combination of propofol and sevoflurane caused apnoea in Study 1, apnoea was not observed following single administration of propofol in Study 2. These data provide bases for further investigation on intravenous anaesthesia using propofol in common marmosets.

Circadian Clock Component Rev-erbα Regulates Diurnal Rhythm of UDP-Glucuronosyltransferase 1a9 and Drug Glucuronidation in Mice.

UDP-glucuronosyltransferases (UGTs) are a family of phase II enzymes that play an important role in metabolism and elimination of numerous endo- and xenobiotics. Here, we aimed to characterize diurnal rhythm of Ugt1a9 in mouse liver and to determine the molecular mechanisms underlying the rhythmicity. Hepatic Ugt1a9 mRNA and protein displayed robust diurnal rhythms in wild-type mice with peak levels at zeitgeber time (ZT) 6. Rhythmicity in Ugt1a9 expression was confirmed using synchronized Hepa-1c1c7 cells. We observed time-varying glucuronidation (ZT6 > ZT18) of propofol, a specific Ugt1a9 substrate, consistent with the diurnal pattern of Ugt1a9 protein. Loss of Rev-erbα (a circadian clock component) downregulated the Ugt1a9 expression and blunted its rhythm in mouse liver. Accordingly, propofol glucuronidation was reduced and its dosing time dependency was lost in Rev-erbα -/- mice. Dec2 (a transcription factor) was screened to be the potential intermediate that mediated Rev-erbα regulation of Ugt1a9. We confirmed Rev-erbα as a negative regulator of Dec2 in mice and in Hepa-1c1c7 cells. Based on promoter analysis and luciferase reporter assays, it was found that Dec2 trans-repressed Ugt1a9 via direct binding to an E-box-like motif in the gene promoter. Additionally, regulation of Ugt1a9 by Rev-erbα was Dec2-dependent. In conclusion, Rev-erbα generates and regulates rhythmic Ugt1a9 through periodical inhibition of Dec2, a transcriptional repressor of Ugt1a9. Our study may have implications for understanding of circadian clock-controlled drug metabolism and of metabolism-based chronotherapeutics. SIGNIFICANCE STATEMENT: Hepatic Ugt1a9 displays diurnal rhythmicities in expression and glucuronidation activity in mice. It is uncovered that Rev-erbα generates and regulates rhythmic Ugt1a9 through periodical inhibition of Dec2, a transcriptional repressor of Ugt1a9. The findings may have implications for understanding of circadian clock-controlled drug metabolism and of metabolism-based chronotherapeutics.

The Performance of an Artificial Neural Network Model in Predicting the Early Distribution Kinetics of Propofol in Morbidly Obese and Lean Subjects.

BACKGROUND: Induction of anesthesia is a phase characterized by rapid changes in both drug concentration and drug effect. Conventional mammillary compartmental models are limited in their ability to accurately describe the early drug distribution kinetics. Recirculatory models have been used to account for intravascular mixing after drug administration. However, these models themselves may be prone to misspecification. Artificial neural networks offer an advantage in that they are flexible and not limited to a specific structure and, therefore, may be superior in modeling complex nonlinear systems. They have been used successfully in the past to model steady-state or near steady-state kinetics, but never have they been used to model induction-phase kinetics using a high-resolution pharmacokinetic dataset. This study is the first to use an artificial neural network to model early- and late-phase kinetics of a drug. METHODS: Twenty morbidly obese and 10 lean subjects were each administered propofol for induction of anesthesia at a rate of 100 mg/kg/h based on lean body weight and total body weight for obese and lean subjects, respectively. High-resolution plasma samples were collected during the induction phase of anesthesia, with the last sample taken at 16 hours after propofol administration for a total of 47 samples per subject. Traditional mammillary compartment models, recirculatory models, and a gated recurrent unit neural network were constructed to model the propofol pharmacokinetics. Model performance was compared. RESULTS: A 4-compartment model, a recirculatory model, and a gated recurrent unit neural network were assessed. The final recirculatory model (mean prediction error: 0.348; mean square error: 23.92) and gated recurrent unit neural network that incorporated ensemble learning (mean prediction error: 0.161; mean square error: 20.83) had similar performance. Each of these models overpredicted propofol concentrations during the induction and elimination phases. Both models had superior performance compared to the 4-compartment model (mean prediction error: 0.108; mean square error: 31.61), which suffered from overprediction bias during the first 5 minutes followed by under-prediction bias after 5 minutes. CONCLUSIONS: A recirculatory model and gated recurrent unit artificial neural network that incorporated ensemble learning both had similar performance and were both superior to a compartmental model in describing our high-resolution pharmacokinetic data of propofol. The potential of neural networks in pharmacokinetic modeling is encouraging but may be limited by the amount of training data available for these models.

Prevalence of Isoelectric Electroencephalography Events in Infants and Young Children Undergoing General Anesthesia.

BACKGROUND: In infants and young children, anesthetic dosing is based on population pharmacokinetics and patient hemodynamics not on patient-specific brain activity. Electroencephalography (EEG) provides insight into brain activity during anesthesia. The primary goal of this prospective observational pilot study was to assess the prevalence of isoelectric EEG events-a sign of deep anesthesia-in infants and young children undergoing general anesthesia using sevoflurane or propofol infusion for maintenance. METHODS: Children 0-37 months of age requiring general anesthesia for surgery excluding cardiac, intracranial, and emergency cases were enrolled by age: 0-3, 4-6, 7-12, 13-18, and 19-37 months. Anesthesia was maintained with sevoflurane or propofol infusion. EEG was recorded from induction to extubation. Isoelectric EEG events (amplitude <20 µV, lasting ≥2 seconds) were characterized by occurrence, number, duration, and percent of isoelectric EEG time over anesthetic time. Associations with patient demographics, anesthetic, and surgical factors were determined. RESULTS: Isoelectric events were observed in 63% (32/51) (95% confidence interval [CI], 49-76) of patients. The median (interquartile range [IQR]) number of isoelectric events per patient was 3 (0-31), cumulative isoelectric time per patient was 12 seconds (0-142 seconds), isoelectric time per event was 3 seconds (0-4 seconds), and percent of total isoelectric over anesthetic time was 0.1% (0%-2.2%). The greatest proportion of isoelectric events occurred between induction and incision. Isoelectric events were associated with higher American Society of Anesthesiologists (ASA) physical status, propofol bolus, endotracheal tube use, and lower arterial pressure during surgical phase. CONCLUSIONS: Isoelectric EEG events were common in infants and young children undergoing sevoflurane or propofol anesthesia. Although the clinical significance of these events remains uncertain, they suggest that dosing based on population pharmacokinetics and patient hemodynamics is often associated with unnecessary deep anesthesia during surgical procedures.

Comparison of predicted and real propofol and remifentanil concentrations in plasma and brain tissue during target-controlled infusion: a prospective observational study.

Target-controlled infusion systems are increasingly used to administer intravenous anaesthetic drugs to achieve a user-specified plasma or effect-site target concentration. While several studies have investigated the ability of the underlying pharmacokinetic-dynamic models to predict plasma concentrations, there are no data on their performance in predicting drug concentrations in the human brain. We assessed the predictive performance of the Marsh propofol model and Minto remifentanil model for plasma and brain tissue concentrations. Plasma samples were obtained during neurosurgery from 38 patients, and brain tissue samples from nine patients. Propofol and remifentanil concentrations were measured using gas chromatography mass spectrometry and liquid chromatography tandem mass spectrometry. Data were analysed from the nine patients in whom both plasma and brain samples were simultaneously obtained. For the Minto model (five patients), the median performance error was 72% for plasma and -14% for brain tissue concentration predictions. The model tended to underestimate plasma remifentanil concentrations, and to overestimate brain tissue remifentanil concentrations. For the Marsh model (five patients), the median prediction errors for plasma and brain tissue concentrations were 12% and 81%, respectively. However, when the data from all blood propofol assays (36 patients) were analysed, the median prediction error was 11%, with overprediction in 15 (42%) patients and underprediction in 21 (58%). These findings confirm earlier reports demonstrating inaccuracy for commonly used pharmacokinetic-dynamic models for plasma concentrations and extend these findings to the prediction of effect-site concentrations.

The influence of cardiac output on propofol and fentanyl pharmacokinetics and pharmacodynamics in patients undergoing abdominal aortic surgery.

Cardiac output (CO) is expected to affect elimination and distribution of highly extracted and perfusion rate-limited drugs. This work was undertaken to quantify the effect of CO measured by the pulse pressure method on pharmacokinetics and pharmacodynamics of propofol and fentanyl administrated during total intravenous anesthesia (TIVA). The data were obtained from 22 ASA III patients undergoing abdominal aortic surgery. Propofol was administered via target-controlled infusion system (Diprifusor) and fentanyl was administered at a dose of 2-3 µg/kg each time analgesia appeared to be inadequate. Hemodynamic measurements as well as bispectral index were monitored and recorded throughout the surgery. Data analysis was performed by using a non-linear mixed-effect population modeling (NONMEM 7.4 software). Three compartment models that incorporated blood flows as parameters were used to describe propofol and fentanyl pharmacokinetics. The delay of the anesthetic effect, with respect to plasma concentrations, was described using a biophase (effect) compartment. The bispectral index was linked to the propofol and fentanyl effect site concentrations through a synergistic Emax model. An empirical linear model was used to describe CO changes observed during the surgery. Cardiac output was identified as an important predictor of propofol and fentanyl pharmacokinetics. Consequently, it affected the depth of anesthesia and the recovery time after propofol-fentanyl TIVA infusion cessation. The model predicted (not observed) CO values correlated best with measured responses. Patients' age was identified as a covariate affecting the rate of CO changes during the anesthesia leading to age-related difference in individual patient's responses to both drugs.

Age progression from vicenarians (20-29 year) to nonagenarians (90-99 year) among a population pharmacokinetic/pharmacodynamic (PopPk-PD) covariate analysis of propofol-bispectral index (BIS) electroencephalography.

BACKGROUND: Pharmacokinetic/pharmacodynamic (PK/PD) modeling has made an enormous contribution to intravenous anesthesia. Because of their altered physiological, pharmacological and pathological aspects, titrating general anesthesia in the elderly is a challenging task. METHODS: Eighty patients were consecutively enrolled divided by decades from vicenarians (20-29 year) to nonagenarians (90-99 year) into eight groups. Using target controlled infusion (TCI) and electroencephalographic (EEG)-derived bispectral index (BIS) we set propofol plasma concentration (Cp) to gradually reach 3.5 µg mL-1 over 3.5-min. In each patient, we constructed a PK/PD model and conducted a population PK/PD (PopPK-PD) covariate analysis. RESULTS: Age was significant covariate for baseline BIS effect (E0), inhibitory propofol concentration at 50% BIS decline (IC50) and maximum BIS decline (Emax). First-order rate constant Ke0 of 0.47 min-1 in vicenarians (20-29 year) gradually increased with age-progression to 1.85 min-1 in nonagenarians (90-99 year). Simulation modelling showed that clinically recommended Cp of 3.5 µg mL-1 for 20-29 year BIS 50 should be reduced to 3.0 for 30-49 year, 2.5 for 50-69 year and 2.0 for 80-89 year. CONCLUSION: We quantified and graded EEG-BIS age-progression among different age groups divided by decades. We demonstrated deeper BIS values with decades' age progression. Our data has important implications for propofol dosing. The practical information for physicians in their daily clinical practice is using propofol Cp of 3.5 µg mL-1 might not yield BIS value of 50 in elderly patients. Our simulations showed that the recommended regimen of Cp 3.5 µg mL-1 for 20-29 year should be gradually decreased to 2.0 µg mL-1 for 80-89 year. CLINICAL TRIAL REGISTRY NUMBERS: European Community Clinical Trials Database EudraCT (http://eudract.emea.eu) initial trial registration number: 2011-002847-81, and subsequently registered at www.clinicaltrials.gov; trial registration number: NCT02585284. Xijing Hospital of Fourth Military Medical University ethics committee approval number 20110707-4.

External Validation of a Pharmacokinetic Model of Propofol for Target-Controlled Infusion in Children under Two Years Old.

BACKGROUND: Previously, a linked pharmacokinetic-pharmacodynamic model (the Kim model) of propofol with concurrent infusion of remifentanil was developed for children aged 2-12 years. There are few options for pharmacokinetic-pharmacodynamic model of propofol for children under two years old. We performed an external validation of the Kim model for children under two years old to evaluate whether the model is applicable to this age group. METHODS: Twenty-four children were enrolled. After routine anesthetic induction, a continuous infusion of 2% propofol and remifentanil was commenced using the Kim model. The target effect-site concentration of propofol was set as 2, 3, 4, and 5 µg/mL, followed by arterial blood sampling after 10 min of each equilibrium. Population estimates of four parameters-pooled bias, inaccuracy, divergence, and wobble-were used to evaluate the performance of the Kim model. RESULTS: A total of 95 plasma concentrations were used for evaluation of the Kim model. The population estimate (95% confidence interval) of bias was -0.96% (-8.45%, 6.54%) and that of inaccuracy was 21.0% (15.0%-27.0%) for the plasma concentration of propofol. CONCLUSION: The pooled bias and inaccuracy of the pharmacokinetic predictions are clinically acceptable. Therefore, our external validation of the Kim model indicated that the model can be applicable to target-controlled infusion of propofol in children younger than 2 years, with the recommended use of actual bispectral index monitoring in clinical settings that remifentanil is present. TRIAL REGISTRATION: Clinical Research Information Service Identifier: KCT0001752.

The role of pharmacokinetics and pharmacodynamics in clinical anaesthesia practice.

PURPOSE OF REVIEW: Growing concerns about the environmental effects of volatile anaesthetics are likely to lead to increased use of intravenous anaesthetic drugs. Pharmacokinetic/pharmacodynamic (PKPD) models can increase the accuracy of intravenous drug titration, especially in populations that differ from the 'average.' However, with a growing number of PKPD models, and other technology available to date, it can be hard to see the wood for the trees. This review attempts to guide the reader through the PKPD jungle. RECENT FINDINGS: General purpose PKPD models for propofol and remifentanil designed to apply to a broader population, including children, the elderly and the obese, reduce the need for population-specific models. PKPD models for drugs such as dexmedetomidine and antimicrobial agents may be useful for procedural sedation or in the ICU. Technological advances such as Bayesian model adjustment based on point-of-care plasma concentration measurements, closed-loop drug delivery and artificial intelligence may improve the ease of use of the anaesthetic drugs and increase the accuracy of titration. SUMMARY: Newer and more complex modelling techniques and technological advancements can help to deliver anaesthetic drugs, sedatives and other drugs in a more stable and thereby safer way.