Quantification of the variability in response to propofol administration in children

Closed-loop control of anesthesia is expected to decrease drug dosage and wake up time while increasing patient safety and decreasing the work load of the anesthesiologist. The potential of closed-loop control in anesthesia has been demon- strated in several clinical studies. One of the challenges in the development of a closed-loop system that can be widely accepted by clinicians and regulatory authorities is the effect of inter- patient variability in drug sensitivity. This system uncertainty may lead to unacceptable performance, or even instability of the closed-loop system for some individuals. The development of reliable models of the effect of anesthetic drugs and charac- terization of the uncertainty is therefore an important step in the development of a closed-loop system. Model identification from clinical data is challenging due to limited excitation and the lack of validation data. In this paper, approximate models are therefore validated for controller design by evaluating the predictive accuracy of the closed-loop behavior. A set of 47 validated models that describe the inter-patient variability in the response to propofol in children is presented. This model set can be used for robust linear controller design provided that the experimental conditions are similar to the conditions during data collection

Early phase pharmacokinetics but not pharmacodynamics are influenced by propofol infusion rate

Background: Conventional compartmental pharmacokinetic models wrongly assume instantaneous drug mixing in the central compartment, resulting in a flawed prediction of drug disposition for the first minutes, and the flaw affects pharmacodynamic modeling. This study examined the influence of the administration rate and other covariates on early phase kinetics and dynamics of propofol by using the enlarged structural pharmacokinetic model. Methods: Fifty patients were randomly assigned to one of five groups to receive 1.2 mg/kg propofol given with the rate of 10 to 160 mg . kg(-1) . h(-1). Arterial blood samples were taken frequently, especially during the first minute. The authors compared four basic pharmacokinetic models by using presystemic compartments and the time shift of dosing, LAG time. They also examined a sigmoidal maximum possible drug effect pharmacodynamic model. Patient characteristics and dose rate were obtained to test the model structure. Results: Our final pharmacokinetic model includes two conventional compartments enlarged with a LAG time and six presystemic compartments and includes following covariates: dose rate for transit rate constant, age for LAG time, and weight for central distribution volume. However, the equilibration rate constant between central and effect compartments was not influenced by infusion rate. Conclusions: This study found that a combined pharmacokinetic-dynamic model consisting of a two-compartmental model with a LAG time and presystemic compartments and a sigmoidal maximum possible drug effect model accurately described the early phase pharmacology of propofol during infusion rate between 10 and 160 mg . kg(-1) . h(-1). The infusion rate has an influence on kinetics, but not dynamics. Age was a covariate for LAG time

Design and clinical evaluation of robust PID control of propofol anesthesia in children

This paper describes the design of a robust PID controller for propofol infusion in children and presents the results of clinical evaluation of this closed-loop system during endoscopic investigations in children age 6y-17y. The controller design is based on a set of models that describes the inter- patient variability in the response to propofol infusion in the study population. The PID controller is tuned to achieve sufficient robustness margins for the identified uncertainty. 108 children were enrolled in the study, anesthesia was closed-loop controlled in 102 of these cases. Clinical evaluation of the system shows that closed-loop control of both induction and maintenance of anesthesia in children based on the WAVCNS index as a measure of clinical effect is feasible. A robustly tuned PID controller can accommodate the inter-patient variability in children and spontaneous breathing can be maintained in most subjects

Optimizing robust PID control of propofol anesthesia for children; design and clinical evaluation

Objective: The goal of this study was to optimize robust PID control for propofol anesthesia in children aged 5-10 years to improve performance, particularly to decrease the time of induction of anesthesia while maintaining robustness.Methods: We analyzed results of a previous study conducted by our group to identify opportunities for system improvement. Allometric scaling was introduced to reduce the interpatient variability and a new robust PID controller was designed using an optimization based method. We evaluated this optimized design in a clinical study involving 16 new cases.Results: The optimized controller design achieved the performance predicted in simulation studies in the design stage. Time of induction of anesthesia was median [Q1, Q3] 3.7 [2.3, 4.1] minutes and the achieved global score was 13.4 [9.9, 16.8]. Conclusion: Allometric scaling reduces the interpatient variability in this age group, and allows for improved closed-loop performance. The uncertainty described by the model set, the predicted closedloop responses and the predicted robustness margins are realistic. The system meets the design objectives of improved speed of induction of anesthesia while maintaining robustness, improving clinically relevant system behavior.Significance: Control system optimization and ongoing system improvement are essential to the development of a clinically relevant commercial device. This paper demonstrates the validity of our approach, including system modeling, controller optimization and pre-clinical testing in simulation

Do Complexity Measures of Frontal EEG Distinguish Loss of Consciousness in Geriatric Patients Under Anesthesia?

While geriatric patients have a high likelihood of requiring anesthesia, they carry an increased risk for adverse cognitive outcomes from its use. Previous work suggests this could be mitigated by better intraoperative monitoring using indexes defined by several processed electroencephalogram (EEG) measures. Unfortunately, inconsistencies between patients and anesthetic agents in current analysis techniques have limited the adoption of EEG as standard of care. In attempts to identify new analyses that discriminate clinically-relevant anesthesia timepoints, we tested 1/f frequency scaling as well as measures of complexity from nonlinear dynamics. Specifically, we tested whether analyses that characterize time-delayed embeddings, correlation dimension (CD), phase-space geometric analysis, and multiscale entropy (MSE) capture loss-of-consciousness changes in EEG activity. We performed these analyses on EEG activity collected from a traditionally hard-to-monitor patient population: geriatric patients on beta-adrenergic blockade who were anesthetized using a combination of fentanyl and propofol. We compared these analyses to traditional frequency-derived measures to test how well they discriminated EEG states before and after loss of response to verbal stimuli. We found spectral changes similar to those reported previously during loss of response. We also found significant changes in 1/f frequency scaling. Additionally, we found that our phase-space geometric characterization of time-delayed embeddings showed significant differences before and after loss of response, as did measures of MSE. Our results suggest that our new spectral and complexity measures are capable of capturing subtle differences in EEG activity with anesthesia administration-differences which future work may reveal to improve geriatric patient monitoring

Modeling of the Sedative and Airway Obstruction Effects of Propofol in Patients with Parkinson Disease undergoing Stereotactic Surgery

BACKGROUND: Functional stereotactic surgery requires careful titration of sedation since patients with Parkinson disease need to be rapidly awakened for testing. This study reports a population pharmacodynamic model of propofol sedation and airway obstruction in the Parkinson disease population. METHODS: Twenty-one patients with advanced Parkinson disease undergoing functional stereotactic surgery were included in the study and received propofol target-controlled infusion to achieve an initial steady state concentration of 1 microg/ml. Sedation was measured using the Ramsay Sedation Scale. Airway obstruction was measured using a four-category score. Blood samples were drawn for propofol measurement. Individual pharmacokinetic profiles were constructed nonparametrically using linear interpolation. Time course of sedation and respiratory effects were described with population pharmacodynamic models using NONMEM. The probability (P) of a given level of sedation or airway obstruction was related to the estimated effect-site concentration of propofol (Ce) using a logistic regression model. RESULTS: The concentrations predicted by the target-controlled infusion system generally exceeded the measured concentrations. The estimates of C(50) for Ramsay scores 3, 4, and 5 were 0.1, 1.02, and 2.28 microg/ml, respectively. For airway obstruction scores 2 and 3, the estimates of C(50) were 0.32 and 2.98 microg/ml, respectively. Estimates of k(e0) were 0.24 and 0.5 1/min for the sedation and respiratory effects, respectively. CONCLUSIONS: The pharmacokinetic behavior of propofol in patients with Parkinson disease differs with respect to the population from which the model used by the target-controlled infusion device was developed. Based on the results from the final models, a typical steady state plasma propofol concentration of 0.35 microg/ml eliciting a sedation score of 3 with only minimal, if any, airway obstruction has been defined as the therapeutic target

Instantaneous monitoring of heart beat dynamics during anesthesia and sedation

Anesthesia-induced altered arousal depends on drugs having their effect in specific brain regions. These effects are also reflected in autonomic nervous system (ANS) outflow dynamics. To this extent, instantaneous monitoring of ANS outflow, based on neurophysiological and computational modeling, may provide a more accurate assessment of the action of anesthetic agents on the cardiovascular system. This will aid anesthesia care providers in maintaining homeostatic equilibrium and help to minimize drug administration while maintaining antinociceptive effects. In previous studies, we established a point process paradigm for analyzing heartbeat dynamics and have successfully applied these methods to a wide range of cardiovascular data and protocols. We recently devised a novel instantaneous nonlinear assessment of ANS outflow, also suitable and effective for real-time monitoring of the fast hemodynamic and autonomic effects during induction and emergence from anesthesia. Our goal is to demonstrate that our framework is suitable for instantaneous monitoring of the ANS response during administration of a broad range of anesthetic drugs. Specifically, we compare the hemodynamic and autonomic effects in study participants undergoing propofol (PROP) and dexmedetomidine (DMED) administration. Our methods provide an instantaneous characterization of autonomic state at different stages of sedation and anesthesia by tracking autonomic dynamics at very high time-resolution. Our results suggest that refined methods for analyzing linear and nonlinear heartbeat dynamics during administration of specific anesthetic drugs are able to overcome nonstationary limitations as well as reducing inter-subject variability, thus providing a potential real-time monitoring approach for patients receiving anesthesia