Undergoing Propofol Anesthesia Research Articles

Propofol Versus Remimazolam on Cognitive Function, Hemodynamics, and Oxygenation During One-Lung Ventilation in Older Patients Undergoing Pulmonary Lobectomy: A Randomized Controlled Trial

To investigate the effects of remimazolam on postoperative cognitive function, intraoperative hemodynamics, and oxygenation in older patients undergoing lobectomy. A prospective, double-blind, randomized, controlled study. A university hospital. Eighty-four older patients with lung cancer who underwent lobectomy, aged ≥65 years. Patients were divided randomly into the remimazolam (group R) and propofol (group P) groups. Group R underwent remimazolam anesthesia induction and maintenance, whereas group P underwent propofol anesthesia induction and maintenance. Cognitive function was assessed with neuropsychological tests 1 day before surgery and 7 days after surgery. The Clock Drawing Test, Verbal Fluency Test (VFT), Digit Symbol Switching Test (DSST), and Auditory Verbal Learning Test-Huashan (AVLT-H) assessed visuospatial ability, language function, attention, and memory, respectively. The systolic blood pressure (SBP), heart rate, mean arterial pressure (MAP), and cardiac index were recorded 5 minutes before induction of anesthesia (T0), 2 minutes after sedation (T1), 5 minutes after intubation with two-lung ventilation (T2), 30 minutes after one-lung ventilation (OLV) (T3), 60 minutes after OLV (T4), and at the end of surgery (T5), and the incidences of hypotension and bradycardia were recorded. The PaO2, oxygenation index (OI), and intrapulmonary shunt (Qs/Qt) were assessed at T0, T2, T3, T4, and T5. The levels of S-100β and interleukin 6 were measured by enzyme-linked immunosorbent assay at T0, T5, 24 hours after surgery (T6), and on day 7 after surgery (T7). The VFT, DSST, immediate recall AVLT-H, and short-delayed recall AVLT-H scores were significantly higher in group R than in group P on day 7 after surgery (p < 0.05). The SBP and MAP at T2 to T5 were significantly higher in group R than in group P, the incidence of hypotension was significantly lower in group R (9.5%) than in group P (35.7%) (p=0.004), and remimazolam significantly reduced the dose of phenylephrine used (p < 0.05). The PaO2 and OI at T4 were significantly higher in group R than in group P, and Qs/Qt was significantly lower in group R than in group P. The levels of S-100β at T5 were significantly lower in group R than in group P (p < 0.05). The results showed that remimazolam (versus propofol) may lessen the degree of short-term postoperative cognitive dysfunction measured by standard neuropsychological tests, better optimize intraoperative hemodynamics, and lead to improved oxygenation during OLV.

Microsynt: Exploring the syntax of EEG microstates

Microstates represent electroencephalographic (EEG) activity as a sequence of switching, transient, metastable states. Growing evidence suggests the useful information on brain states is to be found in the higher-order temporal structure of these sequences. Instead of focusing on transition probabilities, here we propose “Microsynt”, a method designed to highlight higher-order interactions that form a preliminary step towards understanding the syntax of microstate sequences of any length and complexity. Microsynt extracts an optimal vocabulary of “words” based on the length and complexity of the full sequence of microstates. Words are then sorted into classes of entropy and their representativeness within each class is statistically compared with surrogate and theoretical vocabularies. We applied the method on EEG data previously collected from healthy subjects undergoing propofol anesthesia, and compared their “fully awake” (BASE) and “fully unconscious” (DEEP) conditions. Results show that microstate sequences, even at rest, are not random but tend to behave in a more predictable way, favoring simpler sub-sequences, or “words”. Contrary to high-entropy words, lowest-entropy binary microstate loops are prominent and favored on average 10 times more than what is theoretically expected. Progressing from BASE to DEEP, the representation of low-entropy words increases while that of high-entropy words decreases. During the awake state, sequences of microstates tend to be attracted towards “A – B – C” microstate hubs, and most prominently A – B binary loops. Conversely, with full unconsciousness, sequences of microstates are attracted towards “C – D – E” hubs, and most prominently C – E binary loops, confirming the putative relation of microstates A and B to externally-oriented cognitive processes and microstate C and E to internally-generated mental activity. Microsynt can form a syntactic signature of microstate sequences that can be used to reliably differentiate two or more conditions.

Time-trend analysis of the center frequency of the intrinsic mode function from the Hilbert–Huang transform of electroencephalography during general anesthesia: a retrospective observational study

BackgroundAnesthesiologists are required to maintain an optimal depth of anesthesia during general anesthesia, and several electroencephalogram (EEG) processing methods have been developed and approved for clinical use to evaluate anesthesia depth. Recently, the Hilbert–Huang transform (HHT) was introduced to analyze nonlinear and nonstationary data. In this study, we assessed whether the changes in EEG characteristics during general anesthesia that are analyzed by the HHT are useful for monitoring the depth of anesthesia.MethodsThis retrospective observational study enrolled patients who underwent propofol anesthesia. Raw EEG signals were obtained from a monitor through a previously developed software application. We developed an HHT analyzer to decompose the EEG signal into six intrinsic mode functions (IMFs) and estimated the instantaneous frequencies (HHT_IF) for each IMF. Changes over time in the raw EEG waves and parameters such as HHT_IF, BIS, spectral edge frequency 95 (SEF95), and electromyogram parameter (EMGlow) were assessed, and a Gaussian process regression model was created to assess the association between BIS and HHT_IF.ResultsWe analyzed EEG signals from 30 patients. The beta oscillation frequency range (13–25 Hz) was detected in IMF1 and IMF2 during the awake state, then after loss of consciousness, the frequency decreased and alpha oscillation (8–12 Hz) was detected in IMF2. At the emergence phase, the frequency increased and beta oscillations were detected in IMF1, IMF2, and IMF3. BIS and EMGlow changed significantly during the induction and emergence phases, whereas SEF95 showed a wide variability and no significant changes during the induction phase. The root mean square error between the observed BIS values and the values predicted by a Gaussian process regression model ranged from 4.69 to 9.68.ConclusionsWe applied the HHT to EEG analyses during propofol anesthesia. The instantaneous frequency in IMF1 and IMF2 identified changes in EEG characteristics during induction and emergence from general anesthesia. Moreover, the HHT_IF in IMF2 showed strong associations with BIS and was suitable for depicting the alpha oscillation. Our study suggests that the HHT is useful for monitoring the depth of anesthesia.

Recall of extubation after remimazolam anesthesia with flumazenil antagonism during emergence: a retrospective clinical study.

This study was performed to examine and compare the incidence of extubation recall in surgical patients who underwent remimazolam anesthesia with flumazenil antagonism during emergence and in those who underwent propofol anesthesia. One hundred sixty-three patients who underwent surgery using general endotracheal or supraglottic airway anesthesia with propofol (n = 97) or remimazolam (n = 66) were retrospectively analyzed. Remimazolam was antagonized by flumazenil after discontinuation of remimazolam at the end of surgery. The endotracheal tube or supraglottic airway was removed after surgery was complete, and consciousness and adequate spontaneous breathing were confirmed. The incidence of extubation recall was compared between the remimazolam and propofol anesthesia groups using propensity score matching. Extubation recall was observed in 28 patients (17%). After propensity score matching, the incidence of extubation recall did not significantly differ between the remimazolam and propofol anesthesia groups (15.6% vs. 18.8%; p = 1.000). The incidence of extubation recall after remimazolam anesthesia with flumazenil antagonism during emergence did not significantly differ from that after propofol anesthesia.

Association of dexmedetomidine with recovery room and hospital discharge times: A retrospective cohort analysis

AbstractBackgroundDexmedetomidine is a useful anesthetic adjunct, increasingly popular during pediatric surgery and procedural sedation. Its half‐life of 2–3 hours might prolong recovery and discharge times when compared with an un‐supplemented propofol anesthetic. This may create an additional burden in a busy post‐anesthetic care unit (PACU).AimTo investigate whether intraoperative adjuvant dexmedetomidine delays PACU discharge in patients undergoing propofol anesthesia for day surgery or procedural investigations with minimal anticipated post‐procedural pain.MethodsWe conducted a retrospective review of outpatient procedures performed during a six‐month period including pediatric patients, ASA physical status I‐III, who underwent intravenous anesthesia with propofol and remifentanil for magnetic resonance imaging (MRI), strabismus repair, upper gastrointestinal endoscopy, or combined upper/lower gastrointestinal endoscopy. Patients receiving a sedative premedication, long‐acting opioids, or volatile anesthetics for maintenance of anesthesia, were excluded. Duration of PACU stay was compared for patients who did or did not receive intraoperative dexmedetomidine in the four procedure groups.ResultsCharts were reviewed for 359 patients; 130 (36%) received dexmedetomidine. Median differences in duration of PACU stay for dexmedetomidine versus non‐dexmedetomidine cases were: 5 minutes (95%CI 0 to 10, p=0.037) for MRI; 5 minutes (95%CI −3 to 15, p=0.258) for strabismus surgery; 7 minutes (95%CI 3 to 10, p&lt;0.001) for upper endoscopy; and 5 minutes (95%CI 1 to 12, p=0.021) for combined upper/lower endoscopy. Linear regression (F=61.1, adjusted R2=0.40) indicated a significant relationship between dexmedetomidine dose (estimate 14.6 minutes per μg/kg, 95%CI 8.2 to 21.1, p&lt;0.001) and duration of PACU stay.ConclusionWe found evidence for a small association of intraoperative dexmedetomidine with duration of recovery from propofol anesthesia for a set of common outpatient procedures, with a potential dose relationship equivalent to approximately 15 minutes delay per μg/kg dexmedetomidine administered. Future research into the benefits of dexmedetomidine in pediatric anesthesia should further evaluate this relationship.

Validation of a new approach for distinguishing anesthetized from awake state in patients using directed transfer function applied to raw EEG

We test whether a measure based on the directed transfer function (DTF) calculated from short segments of electroencephalography (EEG) time-series can be used to monitor the state of the patients also during sevoflurane anesthesia as it can for patients undergoing propofol anesthesia. We collected and analyzed 25-channel EEG from 7 patients (3 females, ages 41–56 years) undergoing surgical anesthesia with sevoflurane, and quantified the sensor space directed connectivity for every 1-s epoch using DTF. The resulting connectivity parameters were compared to corresponding parameters from our previous study (n = 8, patients anesthetized with propofol and remifentanil, but otherwise using a similar protocol). Statistical comparisons between and within studies were done using permutation statistics, a data driven algorithm based on the DTF-parameters was employed to classify the epochs as coming from awake or anesthetized state. According to results of the permutation tests, DTF-parameter topographies were significantly different between the awake and anesthesia state at the group level. However, the topographies were not significantly different when comparing results computed from sevoflurane and propofol data, neither in the awake nor in anesthetized state. Optimizing the algorithm for simultaneously having high sensitivity and specificity in classification yielded an accuracy of 95.1% (SE = 0.96%), with sensitivity of 98.4% (SE = 0.80%) and specificity of 94.8% (SE = 0.10%). These findings indicate that the DTF changes in a similar manner when humans undergo general anesthesia caused by two distinct anesthetic agents with different molecular mechanisms of action.

Effect of hypoxemia factor on hippocampal long-term potentiation in newborn rats undergoing propofol anesthesia

Objective To evaluate the effect of hypoxemia factor on hippocampal long-term potentiation(LTP)in newborn rats undergoing propofol anesthesia. Methods Forty-two pathogen-free healthy Sprague-Dawley rats(21 males, 21 females), aged 7 days, weighing 14-18 g, were divided into 3 groups(n=14 each)using a random number table: propofol plus air group(group PA), propofol plus pure oxygen group(group PO)and intralipid plus pure oxygen group(group IO). Propofol 50 mg/kg was injected intraperitoneally once a day for 7 consecutive days in PA and PO groups. Intralipid 5.0 ml/kg was injected intraperitoneally once a day for 7 consecutive days in IO group. The rats were exposed to air or pure oxygen for 6 h after the end of each injection. The arterial oxygen saturation and respiratory rate were determined after administration. The rats were returned to the cage after recovery of righting reflex. Six rats in each group were selected for preparation of hippocampal slices at 24 h after the last injection on 7th day, and the electric stimulation-induced field excitatory post synaptic potential(fEPSP)and success rate of LTP induction were recorded. Morris water maze test was performed in the other rats at 2 weeks after administration to assess the cognitive function. Results Compared with group IO, the respiratory rate, amplitude of fEPSP and success rate of LTP induction were significantly decreased, and the escape latency was prolonged in group PO(P<0.05). Compared with group PO, the arterial oxygen saturation, amplitude of fEPSP and success rate of LTP induction were significantly decreased, the escape latency was prolonged, and the number of crossing the original platform was decreased in group PA(P<0.05). Conclusion Hypoxemia factor increases propofol-induced neurotoxicity in the central nervous system of newborn rats. Key words: Oxygen; Propofol; Hippocampus; Long-term potentiation; Cognition

Neural mass model-based tracking of anesthetic brain states

Neural mass model-based tracking of brain states from electroencephalographic signals holds the promise of simultaneously tracking brain states while inferring underlying physiological changes in various neuroscientific and clinical applications. Here, neural mass model-based tracking of brain states using the unscented Kalman filter applied to estimate parameters of the Jansen–Rit cortical population model is evaluated through the application of propofol-based anesthetic state monitoring. In particular, 15 subjects underwent propofol anesthesia induction from awake to anesthetised while behavioral responsiveness was monitored and frontal electroencephalographic signals were recorded. The unscented Kalman filter Jansen–Rit model approach applied to frontal electroencephalography achieved reasonable testing performance for classification of the anesthetic brain state (sensitivity: 0.51; chance sensitivity: 0.17; nearest neighbor sensitivity 0.75) when compared to approaches based on linear (autoregressive moving average) modeling (sensitivity 0.58; nearest neighbor sensitivity: 0.91) and a high performing standard depth of anesthesia monitoring measure, Higuchi Fractal Dimension (sensitivity: 0.50; nearest neighbor sensitivity: 0.88). Moreover, it was found that the unscented Kalman filter based parameter estimates of the inhibitory postsynaptic potential amplitude varied in the physiologically expected direction with increases in propofol concentration, while the estimates of the inhibitory postsynaptic potential rate constant did not. These results combined with analysis of monotonicity of parameter estimates, error analysis of parameter estimates, and observability analysis of the Jansen–Rit model, along with considerations of extensions of the Jansen–Rit model, suggests that the Jansen–Rit model combined with unscented Kalman filtering provides a valuable reference point for future real-time brain state tracking studies. This is especially true for studies of more complex, but still computationally efficient, neural models of anesthesia that can more accurately track the anesthetic brain state, while simultaneously inferring underlying physiological changes that can potentially provide useful clinical information.

Effect of sleep deprivation on cognitive function in rats undergoing propofol anesthesia

Objective To evaluate the effect of sleep deprivation on cognitive function in the rats undergoing propofol anesthesia. Methods Sixty healthy male Sprague Dawley rats, aged 14-18 weeks, weighing 200-250 g, were randomly assigned into 3 groups(n=20 each)using a random number table: control group(group C), propofol anesthesia group(group P), and sleep deprivation+ propofol anesthesia group(group SDP). Propofol was given as a bolus of 15 mg/kg followed by an infusion of 40 mg·kg-1·h-1 for 2 h in group P. After the rats were subjected to rapid eye movement sleep deprivation for 24 h, the rats received propofol anesthesia in group SDP.Before sleep deprivation, after sleep deprivation, and at 1, 3 and 7 days after anesthesia, Morris water maze test was used to assess the learning and memory function, and the escape latency and frequency of crossing the original platform were recorded.Ten rats randomly selected from each group at 1 and 7 days after anesthesia were sacrificed, and brains were removed to observe the morphology of nerve cells in the hippocampal CA1 region(by Nissl's staining)and to detect the expression of phosphorylated Tau at Thr231(Tau-pThr231)in the hippocampal CA1 region(by immunohistochemisty). Results Compared with group C, the escape latency was significantly prolonged, the frequency of crossing the original platform was decreased, the expression of Tau-pThr231in the hippocampal CA1 region was up-regulated at 1 day after anesthesia in P and SDP groups(P 0.05). The pathological changes were aggravated at 1 day after anesthesia in group SDP compared with group P, and there was no significant difference at 3 and 7 days after anesthesia between group SDP and group P. Conclusion Sleep deprivation can aggravate the transient cognitive dysfunction after propofol anesthesia, and the mechanism is related to promotion of Tau phosphorylation in the rats. Key words: Sleep deprivation; Propofol; Cognition disorders

A Pharmacokinetics-Neural Mass Model (PK-NMM) for the Simulation of EEG Activity during Propofol Anesthesia.

Modeling the effects of anesthetic drugs on brain activity is very helpful in understanding anesthesia mechanisms. The aim of this study was to set up a combined model to relate actual drug levels to EEG dynamics and behavioral states during propofol-induced anesthesia. We proposed a new combined theoretical model based on a pharmacokinetics (PK) model and a neural mass model (NMM), which we termed PK-NMM—with the aim of simulating electroencephalogram (EEG) activity during propofol-induced general anesthesia. The PK model was used to derive propofol effect-site drug concentrations (C eff) based on the actual drug infusion regimen. The NMM model took C eff as the control parameter to produce simulated EEG-like (sEEG) data. For comparison, we used real prefrontal EEG (rEEG) data of nine volunteers undergoing propofol anesthesia from a previous experiment. To see how well the sEEG could describe the dynamic changes of neural activity during anesthesia, the rEEG data and the sEEG data were compared with respect to: power-frequency plots; nonlinear exponent (permutation entropy (PE)); and bispectral SynchFastSlow (SFS) parameters. We found that the PK-NMM model was able to reproduce anesthesia EEG-like signals based on the estimated drug concentration and patients’ condition. The frequency spectrum indicated that the frequency power peak of the sEEG moved towards the low frequency band as anesthesia deepened. Different anesthetic states could be differentiated by the PE index. The correlation coefficient of PE was 0.80±0.13 (mean±standard deviation) between rEEG and sEEG for all subjects. Additionally, SFS could track the depth of anesthesia and the SFS of rEEG and sEEG were highly correlated with a correlation coefficient of 0.77±0.13. The PK-NMM model could simulate EEG activity and might be a useful tool for understanding the action of propofol on brain activity.

Epidural levobupivacaine alone or combined with different morphine doses in bitches under continuous propofol infusion

The aim of this study was to assess the cardiopulmonary, analgesic, adverse effects, serum concentration of cortisol and plasma levels of levobupivacaine and morphine in bitches undergoing propofol anesthesia and epidural analgesia with levobupivacaine alone or combined with morphine. This was a randomized 'blinded' prospective clinical study using 32 adult bitches weighing 9.8±4.1kg that were admitted for elective ovariohysterectomy. Twenty minutes after administration of acepromazine and midazolam, anesthesia was induced with propofol (4mg kg-1) and maintained by a continuous rate infusion (CRI). Each animal was randomly assigned to one of four epidural groups: GL = levobupivacaine alone (0.33mg kg-1); GLM0.1 = levobupivacaine and morphine (0.1mg kg-1); GLM0.15 = levobupivacaine and morphine (0.15mg kg-1); and GLM0.2 = levobupivacaine and morphine (0.2mg kg-1). Variables obtained during anesthesia were heart rate, respiratory rate, systolic, mean and diastolic arterial blood pressures, oxyhemoglobin saturation, inspired oxygen fraction, end-tidal carbon dioxide tension, blood gases, serum cortisol, and plasma levels of levobupivacaine and morphine. The onset and duration times of the blockade were recorded. Arterial pressures were significantly increased in all groups at the times of ovarian pedicle clamping. There was a decrease in pH, together with an increase in both PaO2and PaCO2 over time. Serum cortisol levels were increased in TESu compared to TB, T30 and TR. Limb spasticity, muscle tremors, opisthotonos and diarrhea were observed in some animals during propofol infusion and ceased with the end of CRI. Reactions happened at different moments and lasted for different periods of time in each individual. Epidural with levobupivacaine alone or combined with morphine allowed for ovariohysterectomy to be performed under low propofol infusion rates, with minimal changes in cardiovascular variables and in serum cortisol levels. Adverse effects were observed in very few animals in each group.

EEG slow-wave coherence changes in propofol-induced general anesthesia: experiment and theory.

The electroencephalogram (EEG) patterns recorded during general anesthetic-induced coma are closely similar to those seen during slow-wave sleep, the deepest stage of natural sleep; both states show patterns dominated by large amplitude slow waves. Slow oscillations are believed to be important for memory consolidation during natural sleep. Tracking the emergence of slow-wave oscillations during transition to unconsciousness may help us to identify drug-induced alterations of the underlying brain state, and provide insight into the mechanisms of general anesthesia. Although cellular-based mechanisms have been proposed, the origin of the slow oscillation has not yet been unambiguously established. A recent theoretical study by Steyn-Ross et al. (2013) proposes that the slow oscillation is a network, rather than cellular phenomenon. Modeling anesthesia as a moderate reduction in gap-junction interneuronal coupling, they predict an unconscious state signposted by emergent low-frequency oscillations with chaotic dynamics in space and time. They suggest that anesthetic slow-waves arise from a competitive interaction between symmetry-breaking instabilities in space (Turing) and time (Hopf), modulated by gap-junction coupling strength. A significant prediction of their model is that EEG phase coherence will decrease as the cortex transits from Turing–Hopf balance (wake) to Hopf-dominated chaotic slow-waves (unconsciousness). Here, we investigate changes in phase coherence during induction of general anesthesia. After examining 128-channel EEG traces recorded from five volunteers undergoing propofol anesthesia, we report a significant drop in sub-delta band (0.05–1.5 Hz) slow-wave coherence between frontal, occipital, and frontal–occipital electrode pairs, with the most pronounced wake-vs.-unconscious coherence changes occurring at the frontal cortex.

Lower incidence of emergence agitation in children after propofol anesthesia compared with sevoflurane: a meta-analysis of randomized controlled trials

Emergence agitation (EA) from general anesthesia has been reported as an adverse effect of sevoflurane in children. We describe a meta-analysis of randomized controlled trials that compared the incidence of EA between children who underwent sevoflurane anesthesia and those who underwent propofol anesthesia. A literature search was conducted to identify clinical trials that met our inclusion criteria. Prospective randomized trials comparing sevoflurane and propofol anesthesia in children less than 15 years of age were included in the meta-analysis. Data from each trial were combined using the random effects model to calculate pooled odds ratios (ORs) and their corresponding 95 % confidence intervals (CIs). The heterogeneity of data was assessed by Cochran's Q and I (2) tests. Sensitivity analysis was conducted for study quality, patient age, and type of surgical procedure. The meta-analysis included 14 studies, in which 560 patients received sevoflurane and 548 received propofol. The pooled OR for EA was 0.25 with a 95 % CI of 0.16-0.39 (P = 0.000), which indicates that propofol anesthesia resulted in a lower incidence of EA. The heterogeneity of data was not statistically supported (P = 0.191). All sensitivity analyses strengthened the evidence for the lower incidence of EA with propofol. Our meta-analysis demonstrated that EA in children is less likely to occur after propofol anesthesia compared with sevoflurane anesthesia.

Spectral Pattern Analysis of Propofol Induced Spindle Oscillations in the Presence of Auditory Stimulations

This study’s primary objective is to analyze human EEG spindle oscillations during propofol-induced anesthesia and to address possible activation sources. Such an analysis also has a secondary role of investigating the short- term spectral patterns and their functional role.Artifact-free epochs of spindle activations were selected from the electroencephalograms of patients undergoing propofol anesthesia. Power spectral analysis and source localization using standardized low-resolution-brain-electromagnetic-tomography (sLORETA) were performed. Additionally, spectrograms were obtained by means of using the Complex Morlet-based algorithm. In order to highlight the functional properties, auditory stimulations were conducted during the propofol administration. The loss of consciousness was reached at a level of 0.8-1.2 µg/mL, which also provided distinct spindle oscillations in the continuous EEG. The un-evoked (spontaneous) and evoked (auditory) conditions were examined across non-medicated and medicated conditions (propofol). The propofol administration resulted in appearance of 12-14 Hz spindle activity mostly localized in BA6, BA9, BA10, BA21, BA24 and BA37 areas. The presence of auditory stimulations slightly shifted these maximum activities to different locations. Between the medicated and non-medicated conditions, there was a significant reduction of spindle activity, which was pinpointed to BA7 (precuneus area). The findings indicate that spindle oscillations may have a dual nature. That is, spindle oscillations may be activity dependent and disruptive for large-scale information processing networks in the brain. Hence, the study of spindle oscillation may provide a basis for understanding the short-term spectral patterns of human EEG.

Time–frequency properties of electroencephalogram during induction of anesthesia

A method for detailed description of the time–frequency characteristics of electroencephalogram during induction of anesthesia is proposed. The method, based on averaging of time-normalized smoothed pseudo-Wigner–Ville distributions, is applied to data recorded from nine patients undergoing propofol anesthesia. An extensive representation of the frequency progression pattern related to the induction of anesthesia is given and the time–frequency characteristics that are consistent/not consistent between patients are determined. It is also illustrated how four different clinical end-points, generally used in the assessment of the depth of anesthesia, can be related to different phases of the frequency progression pattern. The method presented has importance in providing information about the neurophysiological phenomenon during induction of anesthesia and can therefore be used in the development of new monitoring algorithms.

Linear and nonlinear analysis of heart rate variability during propofol anesthesia for short-duration procedures in children.

To determine whether heart rate variability metrics provide an accurate method of monitoring depth of anesthesia, assessing the response to painful stimuli, and assessing neuroautonomic regulation of cardiac activity in children receiving propofol anesthesia for short-duration procedures. Prospective, case series. Sixteen-bed pediatric intensive care unit, oncology unit, and endoscopy suite in a tertiary care children's hospital and ophthalmology examination rooms in an associated eye institute. Thirty-three pediatric patients undergoing propofol anesthesia for short procedures. None. Heart rate variability metrics studied included mean, SD, low- and high-frequency power, detrended fluctuation analysis (represented by correlation coefficient, alpha), and approximate entropy. Compared with the initial anesthetized state, we found increased heart rate SD (3.17 +/- 1.31 vs. 7.05 +/- 0.26 bpm, p <.0001), heart rate low-frequency power (3.69 +/- 0.36 vs. 4.48 +/- 0.41 bpm(2)/Hz, p <.0001), heart rate low-/high-frequency ratio (1.47 +/- 0.26 vs. 1.26 +/- 0.24, p =.001), and heart rate alpha (1.12 +/- 0.24 vs. 1.35 +/- 0.21, p <.0001) during painful procedure. Mean heart rate (105.8 +/- 13.4 vs. 101.5 +/- 12.4 bpm, p =.005) and heart rate approximate entropy decreased with painful procedure (0.75 +/- 0.19 vs. 0.53 + 0.16, p <.001), whereas there was no significant change in heart rate high-frequency power (3.04 +/- 0.63 vs. 3.16 +/- 0.71 bpm(2)/Hz, p =.26). We conclude that power spectral analysis of heart rate variability may be an accurate and clinically useful measure of depth of propofol anesthesia. We speculate that high-frequency heart rate power during propofol anesthesia correlates with depth of anesthesia, whereas low-frequency power allows for assessment of the patient's sympathetic response to pain.

プロポフォールの体内動態と臨床薬理効果

Propofol is a comparatively new intravenous anesthetic drug. We measured the concentration of propofol in the plasma of both the arterial blood and the venous blood using highperformance liquid chromatography (HPLC) in 12 patients who underwent propofol anesthesia. The pharmacokinetic behavior of propofol concentration in the venous blood was similar to that in the arterial blood. Both concentrations reflected the pharmacological effects based on the changes in several monitoring values (blood pressure, the pulse, Sjo 2, SEP). The monitoring of intravenous anesthetic drugs are done using arterial blood. Using this method we can therefore easily monitor propofol which is recently being used for sedation by collecting venous blood samples.