Jessica J. Chemali

Active Emergence from Propofol General Anesthesia is Induced by Methylphenidate

Background: A recent study showed that methylphenidate induces emergence from isoflurane general anesthesia. Isoflurane and propofol are general anesthetics that may have distinct molecular mechanisms of action. The objective of this study was to test the hypothesis that methylphenidate actively induces emergence from propofol general anesthesia. Methods: Using adult rats, the effect of methylphenidate on time to emergence after a single bolus of propofol was determined. The ability of methylphenidate to restore righting during a continuous target-controlled infusion (TCI) of propofol was also tested. In a separate group of rats, a TCI of propofol was established and spectral analysis was performed on electroencephalogram recordings taken before and after methylphenidate administration. Results: Methylphenidate decreased median time to emergence after a single dose of propofol from 735 s (95% CI: 598–897 s, n = 6) to 448 s (95% CI: 371–495 s, n = 6). The difference was statistically significant (P = 0.0051). During continuous propofol anesthesia with a median final target plasma concentration of 4.0 &mgr;g/ml (95% CI: 3.2–4.6, n = 6), none of the rats exhibited purposeful movements after injection of normal saline. After methylphenidate, however, all six rats promptly exhibited arousal and had restoration of righting with a median time of 82 s (95% CI: 30–166 s). Spectral analysis of electroencephalogram data demonstrated a shift in peak power from &dgr; (less than 4 Hz) to &thgr; (4–8 Hz) and &bgr; (12–30 Hz) after administration of methylphenidate, indicating arousal in 4/4 rats. Conclusions: Methylphenidate decreases time to emergence after a single dose of propofol, and induces emergence during continuous propofol anesthesia in rats. Further study is warranted to test the hypothesis that methylphenidate induces emergence from propofol general anesthesia in humans.

Activation of D1 dopamine receptors induces emergence from isoflurane general anesthesia.

Background:A recent study showed that methylphenidate induces emergence from isoflurane anesthesia. Methylphenidate inhibits dopamine and norepinephrine reuptake transporters. The objective of this study was to test the hypothesis that selective dopamine receptor activation induces emergence from isoflurane anesthesia. Methods:In adult rats, we tested the effects of chloro-APB (D1 agonist) and quinpirole (D2 agonist) on time to emergence from isoflurane general anesthesia. We then performed a dose–response study to test for chloro-APB–induced restoration of righting during continuous isoflurane anesthesia. SCH-23390 (D1 antagonist) was used to confirm that the effects induced by chloro-APB are specifically mediated by D1 receptors. In a separate group of animals, spectral analysis was performed on surface electroencephalogram recordings to assess neurophysiologic changes induced by chloro-APB and quinpirole during isoflurane general anesthesia. Results:Chloro-APB decreased median time to emergence from 330 to 50 s. The median difference in time to emergence between the saline control group (n = 6) and the chloro-APB group (n = 6) was 222 s (95% CI: 77–534 s, Mann–Whitney test). This difference was statistically significant (P = 0.0082). During continuous isoflurane anesthesia, chloro-APB dose-dependently restored righting (n = 6) and decreased electroencephalogram &dgr; power (n = 4). These effects were inhibited by pretreatment with SCH-23390. Quinpirole did not restore righting (n = 6) and had no significant effect on the electroencephalogram (n = 4) during continuous isoflurane anesthesia. Conclusions:Activation of D1 receptors by chloro-APB decreases time to emergence from isoflurane anesthesia and produces behavioral and neurophysiologic evidence of arousal during continuous isoflurane anesthesia. These findings suggest that selective activation of a D1 receptor–mediated arousal mechanism is sufficient to induce emergence from isoflurane general anesthesia.

Electrical Stimulation of the Ventral Tegmental Area Induces Reanimation from General Anesthesia

Background:Methylphenidate or a D1 dopamine receptor agonist induces reanimation (active emergence) from general anesthesia. The authors tested whether electrical stimulation of dopaminergic nuclei also induces reanimation from general anesthesia. Methods:In adult rats, a bipolar insulated stainless steel electrode was placed in the ventral tegmental area (VTA, n = 5) or substantia nigra (n = 5). After a minimum 7-day recovery period, the isoflurane dose sufficient to maintain loss of righting was established. Electrical stimulation was initiated and increased in intensity every 3 min to a maximum of 120 µA. If stimulation restored the righting reflex, an additional experiment was performed at least 3 days later during continuous propofol anesthesia. Histological analysis was conducted to identify the location of the electrode tip. In separate experiments, stimulation was performed in the prone position during general anesthesia with isoflurane or propofol, and the electroencephalogram was recorded. Results:To maintain loss of righting, the dose of isoflurane was 0.9% ± 0.1 vol%, and the target plasma dose of propofol was 4.4 ± 1.1 µg/ml (mean ± SD). In all rats with VTA electrodes, electrical stimulation induced a graded arousal response including righting that increased with current intensity. VTA stimulation induced a shift in electroencephalogram peak power from &dgr; (<4 Hz) to &thgr; (4–8 Hz). In all rats with substantia nigra electrodes, stimulation did not elicit an arousal response or significant electroencephalogram changes. Conclusions:Electrical stimulation of the VTA, but not the substantia nigra, induces reanimation during general anesthesia with isoflurane or propofol. These results are consistent with the hypothesis that dopamine release by VTA neurons, but not substantia nigra neurons, induces reanimation from general anesthesia.

Real-time Closed-loop Control in a Rodent Model of Medically Induced Coma Using Burst Suppression

Background:A medically induced coma is an anesthetic state of profound brain inactivation created to treat status epilepticus and to provide cerebral protection after traumatic brain injuries. The authors hypothesized that a closed-loop anesthetic delivery system could automatically and precisely control the electroencephalogram state of burst suppression and efficiently maintain a medically induced coma. Methods:In six rats, the authors implemented a closed-loop anesthetic delivery system for propofol consisting of: a computer-controlled pump infusion, a two-compartment pharmacokinetics model defining propofol’s electroencephalogram effects, the burst-suppression probability algorithm to compute in real time from the electroencephalogram the brain’s burst-suppression state, an online parameter-estimation procedure and a proportional-integral controller. In the control experiment each rat was randomly assigned to one of the six burst-suppression probability target trajectories constructed by permuting the burst-suppression probability levels of 0.4, 0.65, and 0.9 with linear transitions between levels. Results:In each animal the controller maintained approximately 60 min of tight, real-time control of burst suppression by tracking each burst-suppression probability target level for 15 min and two between-level transitions for 5–10 min. The posterior probability that the closed-loop anesthetic delivery system was reliable across all levels was 0.94 (95% CI, 0.77–1.00; n = 18) and that the system was accurate across all levels was 1.00 (95% CI, 0.84–1.00; n = 18). Conclusion:The findings of this study establish the feasibility of using a closed-loop anesthetic delivery systems to achieve in real time reliable and accurate control of burst suppression in rodents and suggest a paradigm to precisely control medically induced coma in patients.

A Brain-Machine Interface for Control of Medically-Induced Coma

Medically-induced coma is a drug-induced state of profound brain inactivation and unconsciousness used to treat refractory intracranial hypertension and to manage treatment-resistant epilepsy. The state of coma is achieved by continually monitoring the patients brain activity with an electroencephalogram (EEG) and manually titrating the anesthetic infusion rate to maintain a specified level of burst suppression, an EEG marker of profound brain inactivation in which bursts of electrical activity alternate with periods of quiescence or suppression. The medical coma is often required for several days. A more rational approach would be to implement a brain-machine interface (BMI) that monitors the EEG and adjusts the anesthetic infusion rate in real time to maintain the specified target level of burst suppression. We used a stochastic control framework to develop a BMI to control medically-induced coma in a rodent model. The BMI controlled an EEG-guided closed-loop infusion of the anesthetic propofol to maintain precisely specified dynamic target levels of burst suppression. We used as the control signal the burst suppression probability (BSP), the brains instantaneous probability of being in the suppressed state. We characterized the EEG response to propofol using a two-dimensional linear compartment model and estimated the model parameters specific to each animal prior to initiating control. We derived a recursive Bayesian binary filter algorithm to compute the BSP from the EEG and controllers using a linear-quadratic-regulator and a model-predictive control strategy. Both controllers used the estimated BSP as feedback. The BMI accurately controlled burst suppression in individual rodents across dynamic target trajectories, and enabled prompt transitions between target levels while avoiding both undershoot and overshoot. The median performance error for the BMI was 3.6%, the median bias was -1.4% and the overall posterior probability of reliable control was 1 (95% Bayesian credibility interval of [0.87, 1.0]). A BMI can maintain reliable and accurate real-time control of medically-induced coma in a rodent model suggesting this strategy could be applied in patient care.

A Closed-Loop Anesthetic Delivery System for Real-Time Control of Burst Suppression

OBJECTIVE There is growing interest in using closed-loop anesthetic delivery (CLAD) systems to automate control of brain states (sedation, unconsciousness and antinociception) in patients receiving anesthesia care. The accuracy and reliability of these systems can be improved by using as control signals electroencephalogram (EEG) markers for which the neurophysiological links to the anesthetic-induced brain states are well established. Burst suppression, in which bursts of electrical activity alternate with periods of quiescence or suppression, is a well-known, readily discernible EEG marker of profound brain inactivation and unconsciousness. This pattern is commonly maintained when anesthetics are administered to produce a medically-induced coma for cerebral protection in patients suffering from brain injuries or to arrest brain activity in patients having uncontrollable seizures. Although the coma may be required for several hours or days, drug infusion rates are managed inefficiently by manual adjustment. Our objective is to design a CLAD system for burst suppression control to automate management of medically-induced coma. APPROACH We establish a CLAD system to control burst suppression consisting of: a two-dimensional linear system model relating the anesthetic brain level to the EEG dynamics; a new control signal, the burst suppression probability (BSP) defining the instantaneous probability of suppression; the BSP filter, a state-space algorithm to estimate the BSP from EEG recordings; a proportional-integral controller; and a system identification procedure to estimate the model and controller parameters. MAIN RESULTS We demonstrate reliable performance of our system in simulation studies of burst suppression control using both propofol and etomidate in rodent experiments based on Vijn and Sneyd, and in human experiments based on the Schnider pharmacokinetic model for propofol. Using propofol, we further demonstrate that our control system reliably tracks changing target levels of burst suppression in simulated human subjects across different epidemiological profiles. SIGNIFICANCE Our results give new insights into CLAD system design and suggest a control-theory framework to automate second-to-second control of burst suppression for management of medically-induced coma.

Ageing delays emergence from general anaesthesia in rats by increasing anaesthetic sensitivity in the brain

BACKGROUND Little is known about ageing-related changes in the brain that affect emergence from general anaesthesia. We used young adult and aged Fischer 344 rats to test the hypothesis that ageing delays emergence from general anaesthesia by increasing anaesthetic sensitivity in the brain. METHODS Time to emergence was determined for isoflurane (1.5 vol% for 45 min) and propofol (8 mg kg(-1) i.v.). The dose of isoflurane required to maintain loss of righting (LOR) was established in young adult and aged rats. The efficacy of methylphenidate to reverse LOR from general anaesthesia was tested. Separate young adult and aged rats with implanted electroencephalogram (EEG) electrodes were used to test whether ageing increases sensitivity to anaesthetic-induced burst suppression. RESULTS Mean time to emergence from isoflurane anaesthesia was 47 s [95% CI 33, 60; young adult) compared with 243 s (95% CI 185, 308; aged). For propofol, mean time to emergence was 13.1 min (95% CI 11.9, 14.0; young adult) compared with 23.1 min (95% CI 18.8, 27.9; aged). These differences were statistically significant. When methylphenidate was administered after propofol, the mean time to emergence decreased to 6.6 min (95% CI 5.9, 7.1; young adult) and 10.2 min (95% CI 7.9, 12.3; aged). These reductions were statistically significant. Methylphenidate restored righting in all rats during continuous isoflurane anaesthesia. Aged rats had lower EEG power and were more sensitive to anaesthetic-induced burst suppression. CONCLUSIONS Ageing delays emergence from general anaesthesia. This is due, at least in part, to increased anaesthetic sensitivity in the brain. Further studies are warranted to establish the underlying causes.

A state-space model of the burst suppression ratio

Burst suppression is an electroencephalogram pattern observed in states of severely reduced brain activity, such as general anesthesia, hypothermia and anoxic brain injuries. The burst suppression ratio (BSR), defined as the fraction of EEG spent in suppression per epoch, is the standard quantitative measure used to characterize burst suppression. We present a state space model to compute a dynamic estimate of the BSR as the instantaneous probability of suppression. We estimate the model using an approximate EM algorithm and illustrate its application in the analysis of rodent burst suppression recordings under general anesthesia. Our approach removes the need to artificially average the ratio over long epochs and allows us to make formal statistical comparisons of burst activity at different time points. Our state-space model suggests a more principled way to analyze this key EEG feature that may offer more informative assessments of its associated brain state.

Physostigmine and Methylphenidate Induce Distinct Arousal States During Isoflurane General Anesthesia in Rats.

BACKGROUND:Although emergence from general anesthesia is clinically treated as a passive process driven by the pharmacokinetics of drug clearance, agents that hasten recovery from general anesthesia may be useful for treating delayed emergence, emergence delirium, and postoperative cognitive dysfunction. Activation of central monoaminergic neurotransmission with methylphenidate has been shown to induce reanimation (active emergence) from general anesthesia. Cholinergic neurons in the brainstem and basal forebrain are also known to promote arousal. The objective of this study was to test the hypothesis that physostigmine, a centrally acting cholinesterase inhibitor, induces reanimation from isoflurane anesthesia in adult rats. METHODS:The dose-dependent effects of physostigmine on time to emergence from a standardized isoflurane general anesthetic were tested. It was then determined whether physostigmine restores righting during continuous isoflurane anesthesia. In a separate group of rats with implanted extradural electrodes, physostigmine was administered during continuous inhalation of 1.0% isoflurane, and the electroencephalogram changes were recorded. Finally, 2.0% isoflurane was used to induce burst suppression, and the effects of physostigmine and methylphenidate on burst suppression probability (BSP) were tested. RESULTS:Physostigmine delayed time to emergence from isoflurane anesthesia at doses ≥0.2 mg/kg (n = 9). During continuous isoflurane anesthesia (0.9% ± 0.1%), physostigmine did not restore righting (n = 9). Blocking the peripheral side effects of physostigmine with the coadministration of glycopyrrolate (a muscarinic antagonist that does not cross the blood–brain barrier) produced similar results (n = 9 each). However, during inhalation of 1.0% isoflurane, physostigmine shifted peak electroencephalogram power from &dgr; (<4 Hz) to &thgr; (4–8 Hz) in 6 of 6 rats. During continuous 2.0% isoflurane anesthesia, physostigmine induced large, statistically significant decreases in BSP in 6 of 6 rats, whereas methylphenidate did not. CONCLUSIONS:Unlike methylphenidate, physostigmine does not accelerate time to emergence from isoflurane anesthesia and does not restore righting during continuous isoflurane anesthesia. However, physostigmine consistently decreases BSP during deep isoflurane anesthesia, whereas methylphenidate does not. These findings suggest that activation of cholinergic neurotransmission during isoflurane anesthesia produces arousal states that are distinct from those induced by monoaminergic activation.

A brain-machine interface for control of burst suppression in medical coma

Burst suppression is an electroencephalogram (EEG) marker of profound brain inactivation and unconsciousness and consists of bursts of electrical activity alternating with periods of isoelectricity called suppression. Burst suppression is the EEG pattern targeted in medical coma, a drug-induced brain state used to help recovery after brain injuries and to treat epilepsy that is refractory to conventional drug therapies. The state of coma is maintained manually by administering an intravenous infusion of an anesthetic, such as propofol, to target a pattern of burst suppression on the EEG. The coma often needs to be maintained for several hours or days, and hence an automated system would offer significant benefit for tight control. Here we present a brain-machine interface (BMI) for automatic control of burst suppression in medical coma that selects the real-time drug infusion rate based on EEG observations and can precisely control the burst suppression level in real time in rodents. We quantify the burst suppression level using the burst suppression probability (BSP), the brains instantaneous probability of being in the suppressed state, and represent the effect of the anesthetic propofol on the BSP using a two-dimensional linear compartment model that we fit in experiments. We compute the BSP in real time from the EEG segmented into a binary time-series by deriving a two-dimensional state-space algorithm. We then derive a stochastic controller using both a linear-quadratic-regulator strategy and a model predictive control strategy. The BMI can promptly change the level of burst suppression without overshoot or undershoot and maintains precise control of time-varying target levels of burst suppression in individual rodents in real time.