Effects of Ketamine Infusion on Breathing and Encephalography in Spontaneously Breathing ICU Patients.

BACKGROUND: Preclinical studies suggest that ketamine stimulates breathing. We investigated whether adding a ketamine infusion at low and high doses to propofol sedation improves inspiratory flow and enhances sedation in spontaneously breathing critically ill patients. METHODS: In this prospective interventional study, twelve intubated, spontaneously breathing patients received ketamine infusions at 5 mcg/kg/min, followed by 10 mcg/kg/min for 1 h each. Airway flow, pressure, and esophageal pressure were recorded during a spontaneous breathing trial (SBT) at baseline, and during the SBT conducted at the end of each ketamine infusion regimen. SBT consisted of one-minute breathing with zero end-expiratory pressure and no pressure support. Changes in inspiratory flow at the pre-specified time points were assessed as the primary outcome. Ketamine-induced change in beta-gamma electroencephalogram power was the key secondary endpoint. We also analyzed changes in other ventilatory parameters respiratory timing, and resistive and elastic inspiratory work of breathing. RESULTS: Ketamine infusion of 5 and 10 mcg/kg/min increased inspiratory flow (median, IQR) from 0.36 (0.29-0.46) L/s at baseline to 0.47 (0.32-0.57) L/s and 0.44 (0.33-0.58) L/s, respectively (p = .013). Resistive work of breathing decreased from 0.4 (0.1-0.6) J/l at baseline to 0.2 (0.1-0.3) J/l after ketamine 10 mcg/kg/min (p = .042), while elastic work of breathing remained unchanged. Electroencephalogram beta-gamma power (19-44 Hz) increased compared to baseline (p < .01). CONCLUSIONS: In intubated, spontaneously breathing patients receiving a constant rate of propofol, ketamine increased inspiratory flow, reduced inspiratory work of breathing, and was associated with an "activated" electroencephalographic pattern. These characteristics might facilitate weaning from mechanical ventilation.

A hidden Markov model reliably characterizes ketamine-induced spectral dynamics in macaque local field potentials and human electroencephalograms.

Ketamine is an NMDA receptor antagonist commonly used to maintain general anesthesia. At anesthetic doses, ketamine causes high power gamma (25-50 Hz) oscillations alternating with slow-delta (0.1-4 Hz) oscillations. These dynamics are readily observed in local field potentials (LFPs) of non-human primates (NHPs) and electroencephalogram (EEG) recordings from human subjects. However, a detailed statistical analysis of these dynamics has not been reported. We characterize ketamine's neural dynamics using a hidden Markov model (HMM). The HMM observations are sequences of spectral power in seven canonical frequency bands between 0 to 50 Hz, where power is averaged within each band and scaled between 0 and 1. We model the observations as realizations of multivariate beta probability distributions that depend on a discrete-valued latent state process whose state transitions obey Markov dynamics. Using an expectation-maximization algorithm, we fit this beta-HMM to LFP recordings from 2 NHPs, and separately, to EEG recordings from 9 human subjects who received anesthetic doses of ketamine. Our beta-HMM framework provides a useful tool for experimental data analysis. Together, the estimated beta-HMM parameters and optimal state trajectory revealed an alternating pattern of states characterized primarily by gamma and slow-delta activities. The mean duration of the gamma activity was 2.2s([1.7,2.8]s) and 1.2s([0.9,1.5]s) for the two NHPs, and 2.5s([1.7,3.6]s) for the human subjects. The mean duration of the slow-delta activity was 1.6s([1.2,2.0]s) and 1.0s([0.8,1.2]s) for the two NHPs, and 1.8s([1.3,2.4]s) for the human subjects. Our characterizations of the alternating gamma slow-delta activities revealed five sub-states that show regular sequential transitions. These quantitative insights can inform the development of rhythm-generating neuronal circuit models that give mechanistic insights into this phenomenon and how ketamine produces altered states of arousal.

A polysomnography study examining the association between sleep and postoperative delirium in older hospitalized cardiac surgical patients.

Hospitalized older patients who undergo elective cardiac surgery with cardiopulmonary bypass are prone to postoperative delirium. Self-reported shorter sleep and longer sleep have been associated with impaired cognition. Few data exist to guide us on whether shorter or longer sleep is associated with postoperative delirium in this hospitalized cohort. This was a prospective, single-site, observational study of hospitalized patients (>60 years) scheduled to undergo elective major cardiac surgery with cardiopulmonary bypass (n = 16). We collected and analysed overnight polysomnography data using the Somté PSG device and assessed for delirium twice a day until postoperative day 3 using the long version of the confusion assessment method and a structured chart review. We also assessed subjective sleep quality using the Pittsburg Sleep Quality Index. The delirium median preoperative hospital stay of 9 [Q1, Q3: 7, 11] days was similar to the non-delirium preoperative hospital stay of 7 [4, 9] days (p = .154). The incidence of delirium was 45.5% (10/22) in the entire study cohort and 50% (8/16) in the final cohort with clean polysomnography data. The preoperative delirium median total sleep time of 323.8 [Q1, Q3: 280.3, 382.1] min was longer than the non-delirium median total sleep time of 254.3 [210.9, 278.1] min (p = .046). This was accounted for by a longer delirium median non-rapid eye movement (REM) stage 2 sleep duration of 282.3 [229.8, 328.8] min compared to the non-delirium median non-REM stage 2 sleep duration of 202.5 [174.4, 208.9] min (p = .012). Markov chain modelling confirmed these findings. There were no differences in measures of sleep quality assessed by the Pittsburg Sleep Quality Index. Polysomnography measures of sleep obtained the night preceding surgery in hospitalized older patients scheduled for elective major cardiac surgery with cardiopulmonary bypass are suggestive of an association between longer sleep duration and postoperative delirium.

A Pharmacokinetic and Pharmacodynamic Study of Oral Dexmedetomidine.

BACKGROUND: Dexmedetomidine is only approved for use in humans as an intravenous medication. An oral formulation may broaden the use and benefits of dexmedetomidine to numerous care settings. The authors hypothesized that oral dexmedetomidine (300 mcg to 700 mcg) would result in plasma concentrations consistent with sedation while maintaining hemodynamic stability. METHODS: The authors performed a single-site, open-label, phase I dose-escalation study of a solid oral dosage formulation of dexmedetomidine in healthy volunteers (n = 5, 300 mcg; followed by n = 5, 500 mcg; followed by n = 5, 700 mcg). The primary study outcome was hemodynamic stability defined as lack of hypertension, hypotension, or bradycardia. The authors assessed this outcome by analyzing raw hemodynamic data. Plasma dexmedetomidine concentrations were determined by liquid chromatograph-tandem mass spectrometry. Nonlinear mixed effect models were used for pharmacokinetic and pharmacodynamic analyses. RESULTS: Oral dexmedetomidine was associated with plasma concentration-dependent decreases in heart rate and mean arterial pressure. All but one subject in the 500-mcg group met our criteria for hemodynamic stability. The plasma concentration profile was adequately described by a 2-compartment, weight allometric, first-order absorption, first-order elimination pharmacokinetic model. The standardized estimated parameters for an individual of 70 kg was V1 = 35.6 [95% CI, 23.8 to 52.8] l; V2 = 54.7 [34.2 to 81.7] l; CL = 0.56 [0.49 to 0.64] l/min; and F = 7.2 [4.7 to 14.4]%. Linear models with effect sites adequately described the decreases in mean arterial pressure and heart rate associated with oral dexmedetomidine administration. However, only the 700-mcg group reached plasma concentrations that have previously been associated with sedation (>0.2 ng/ml). CONCLUSIONS: Oral administration of dexmedetomidine in doses between 300 and 700 mcg was associated with decreases in heart rate and mean arterial pressure. Despite low oral absorption, the 700-mcg dose scheme reached clinically relevant concentrations for possible use as a sleep-enhancing medication.

Dissociative and Analgesic Properties of Ketamine Are Independent.

BACKGROUND: Ketamine is a dissociative anesthetic with analgesic properties. Ketamine's analgesic properties have been suggested to result from its dissociative properties. To the authors' knowledge, this postulate is unsubstantiated. The authors hypothesize that the dissociative and analgesic properties of ketamine are independent. METHODS: The authors conducted a single-site, open-label study of ketamine anesthesia (2 mg/kg) in 15 healthy subjects. Midazolam was administered at a prespecified time point to attenuate dissociation. The authors longitudinally assessed precalibrated cuff pain intensity and quality using Patient-Reported Outcomes Measurement Information System questionnaires, and dissociation, using the Clinician Administered Dissociative States Scale. Mixed effects models were used to assess whether dissociation accounted for the effect of ketamine on pain intensity and quality. RESULTS: The dissociation model demonstrated an inverted U-shaped quadratic relationship between time and dissociation scores. Additive to this effect, midazolam reduced the dissociation adjusted means by 10.3 points (95% CI, 3.4 to 17.1; P = 0.005). The pain intensity model also demonstrated a U-shaped quadratic relationship between time and pain intensity. When the pain intensity model was reanalyzed with dissociation scores as an additional covariate, the dissociation term was not retained in the model, and the other effects were preserved in direction and strength. This result was conserved for nociceptive and neuropathic pain quality. CONCLUSIONS: Ketamine's analgesic properties are not exclusively caused by dissociation. Thus, ketamine may be used as a probe to advance our knowledge of dissociation independent neural circuits that encode pain.

Oral Dexmedetomidine Promotes Non-rapid Eye Movement Stage 2 Sleep in Humans.

BACKGROUND: The administration of dexmedetomidine is limited to highly monitored care settings because it is only available for use in humans as intravenous medication. An oral formulation of dexmedetomidine may broaden its use to all care settings. The authors investigated the effect of a capsule-based solid oral dosage formulation of dexmedetomidine on sleep polysomnography. METHODS: The authors performed a single-site, placebo-controlled, randomized, crossover, double-blind phase II study of a solid oral dosage formulation of dexmedetomidine (700 mcg; n = 15). The primary outcome was polysomnography sleep quality. Secondary outcomes included performance on the motor sequence task and psychomotor vigilance task administered to each subject at night and in the morning to assess motor memory consolidation and psychomotor function, respectively. Sleep questionnaires were also administered. RESULTS: Oral dexmedetomidine increased the duration of non-rapid eye movement (non-REM) stage 2 sleep by 63 (95% CI, 19 to 107) min (P = 0.010) and decreased the duration of rapid eye movement (REM) sleep by 42 (5 to 78) min (P = 0.031). Overnight motor sequence task performance improved after placebo sleep (7.9%; P = 0.003) but not after oral dexmedetomidine-induced sleep (-0.8%; P = 0.900). In exploratory analyses, we found a positive correlation between spindle density during non-REM stage 2 sleep and improvement in the overnight test performance (Spearman rho = 0.57; P = 0.028; n = 15) for placebo but not oral dexmedetomidine (Spearman rho = 0.04; P = 0.899; n = 15). Group differences in overnight motor sequence task performance, psychomotor vigilance task metrics, and sleep questionnaires did not meet the threshold for statistical significance. CONCLUSIONS: These results demonstrate that the nighttime administration of a solid oral dosage formulation of dexmedetomidine is associated with increased non-REM 2 sleep and decreased REM sleep. Spindle density during dexmedetomidine sleep was not associated with overnight improvement in the motor sequence task.

Electroencephalogram Burst-suppression during Cardiopulmonary Bypass in Elderly Patients Mediates Postoperative Delirium.

BACKGROUND: Intraoperative burst-suppression is associated with postoperative delirium. Whether this association is causal remains unclear. Therefore, the authors investigated whether burst-suppression during cardiopulmonary bypass (CPB) mediates the effects of known delirium risk factors on postoperative delirium. METHODS: This was a retrospective cohort observational substudy of the Minimizing ICU [intensive care unit] Neurological Dysfunction with Dexmedetomidine-induced Sleep (MINDDS) trial. The authors analyzed data from patients more than 60 yr old undergoing cardiac surgery (n = 159). Univariate and multivariable regression analyses were performed to assess for associations and enable causal inference. Delirium risk factors were evaluated using the abbreviated Montreal Cognitive Assessment and Patient-Reported Outcomes Measurement Information System questionnaires for applied cognition, physical function, global health, sleep, and pain. The authors also analyzed electroencephalogram data (n = 141). RESULTS: The incidence of delirium in patients with CPB burst-suppression was 25% (15 of 60) compared with 6% (5 of 81) in patients without CPB burst-suppression. In univariate analyses, age (odds ratio, 1.08 [95% CI, 1.03 to 1.14]; P = 0.002), lowest CPB temperature (odds ratio, 0.79 [0.66 to 0.94]; P = 0.010), alpha power (odds ratio, 0.65 [0.54 to 0.80]; P < 0.001), and physical function (odds ratio, 0.95 [0.91 to 0.98]; P = 0.007) were associated with CPB burst-suppression. In separate univariate analyses, age (odds ratio, 1.09 [1.02 to 1.16]; P = 0.009), abbreviated Montreal Cognitive Assessment (odds ratio, 0.80 [0.66 to 0.97]; P = 0.024), alpha power (odds ratio, 0.75 [0.59 to 0.96]; P = 0.025), and CPB burst-suppression (odds ratio, 3.79 [1.5 to 9.6]; P = 0.005) were associated with delirium. However, only physical function (odds ratio, 0.96 [0.91 to 0.99]; P = 0.044), lowest CPB temperature (odds ratio, 0.73 [0.58 to 0.88]; P = 0.003), and electroencephalogram alpha power (odds ratio, 0.61 [0.47 to 0.76]; P < 0.001) were retained as predictors in the burst-suppression multivariable model. Burst-suppression (odds ratio, 4.1 [1.5 to 13.7]; P = 0.012) and age (odds ratio, 1.07 [0.99 to 1.15]; P = 0.090) were retained as predictors in the delirium multivariable model. Delirium was associated with decreased electroencephalogram power from 6.8 to 24.4 Hertz. CONCLUSIONS: The inference from the present study is that CPB burst-suppression mediates the effects of physical function, lowest CPB temperature, and electroencephalogram alpha power on delirium.

Ketamine induces EEG oscillations that may aid anesthetic state but not dissociation monitoring.

OBJECTIVE: Ketamine is an anesthetic drug associated with dissociation. Decreased electroencephalogram alpha (8-13 Hz) and low-beta (13-20 Hz) oscillation power have been associated with ketamine-induced dissociation. We aimed to characterize surface electroencephalogram signatures that may serve as biomarkers for dissociation. METHODS: We analyzed data from a single-site, open-label, high-density surface electroencephalogram study of ketamine anesthesia (2 mg/kg, n = 15). We assessed dissociation longitudinally using the Clinician Administered Dissociation States Scale (CADSS) and administered midazolam to attenuate dissociation and enable causal inference. We analyzed electroencephalogram power and global coherence with multitaper spectral methods. Mixed effects models were used to assess whether power and global coherence signatures of ketamine could be developed into dissociation-specific biomarkers. RESULTS: Compared to baseline, ketamine unresponsiveness was associated with increased frontal power between 0.5 to 9.3 Hz, 12.2 to 16.6 Hz, and 24.4 to 50 Hz. As subjects transitioned into a responsive but dissociated state (mean CADSS ± SD, 22.1 ± 17), there was a decrease in power between 0.5 to 10.3 Hz and 11.7 to 50 Hz. Midazolam reduced dissociation scores (14.3 ± 11.6), decreased power between 4.4 to 11.7 Hz and increased power between 14.2 to 50 Hz. Our mixed-effects model demonstrated a quadratic relationship between time and CADSS scores. When models (frontal power, occipital power, global coherence) were reanalyzed with midazolam and electroencephalogram features as covariates, only midazolam was retained. CONCLUSIONS: Ketamine is associated with structured electroencephalogram power and global coherence signatures that may enable principled anesthetic state but not dissociation monitoring. SIGNIFICANCE: A neurophysiological biomarker for dissociation may lead to a better understanding of neuropsychiatric disorders.

Dissociative and analgesic properties of ketamine are independent and unaltered by sevoflurane general anesthesia.

INTRODUCTION: Ketamine, an anesthetic adjunct, is routinely administered as part of a balanced general anesthetic technique. We recently showed that the acute analgesic and dissociation properties of ketamine are separable to suggest that distinct neural circuits underlie these states. OBJECTIVE: We aimed to study whether this finding is robust to the substantial neural circuit alterations associated with general anesthesia. METHODS: We conducted a single-site, open-label, randomized controlled, cross-over study of sevoflurane and sevoflurane-plus-ketamine (SK) general anesthesia in healthy subjects (n = 12). Before and after general anesthesia, we assessed precalibrated cuff pain intensity and nociceptive pain quality as well as dissociation using the Clinician-Administered Dissociative States Scale (CADSS). For statistical inference, we ran a variation of backward elimination repeated-measures analysis of covariance. Models with CADSS as a covariate term were used to assess whether dissociation mediated the effect of ketamine on pain intensity and quality. RESULTS: Sevoflurane-plus-ketamine general anesthesia was associated with a significant (P = 0.0002) pain intensity decline of 3 (SE, 0.44). There was an order effect for dissociation such that SK was associated with a significant (P = 0.0043) CADSS increase of 17.8 (3.2) when the SK treatment came first. When the pain intensity model was reanalyzed with CADSS as an additional covariate, the effect of CADSS was not significant. These results were also conserved for pain quality. CONCLUSIONS: Our findings suggest that the analgesic and dissociation properties of ketamine remain separable despite general anesthesia. Thus, ketamine may be used as a probe to advance our knowledge of dissociation independent pain circuits.

Frequency dependent functional brain reorganization in anesthesia is specific to drug concentration.

The differential effects of general anesthesia on brain activity in terms of drug selection, concentration and combination remain to be elucidated. Using fMRI, it has been shown that increasing doses of sevoflurane is associated with progressive breakdown in brain functional connectivity, while EEG studies have shown that higher activity in the delta band is associated with unconsciousness. Despite these promising results, the band- specific neural substrates of brain changes which occur during sevoflurane anesthesia have not yet been investigated. To this end, we employ high-density EEG-based brain connectivity estimates and graph theoretical analysis in a protocol of progressive sevoflurane administration (conditions: baseline, 1.1%, 2.1%, 2.8%, recovery), both at a global (whole-brain) and at a local (sensor-specific) level in 12 healthy subjects (7 males, mean age 25 ± 4.7 years). We show a statistically significant dependence of global strength, clustering coefficient and efficiency on sevoflurane concentration in the slow delta, beta 1 and beta 2 bands. Interestingly, high and low-frequency bands behaved in an opposite manner as a function of condition. We also found significant band*condition interactive effects in clustering coefficient, efficiency and strength both on local and global scales.

Improved tracking of sevoflurane anesthetic states with drug-specific machine learning models.

OBJECTIVE: The ability to monitor anesthetic states using automated approaches is expected to reduce inaccurate drug dosing and side-effects. Commercially available anesthetic state monitors perform poorly when ketamine is administered as an anesthetic-analgesic adjunct. Poor performance is likely because the models underlying these monitors are not optimized for the electroencephalogram (EEG) oscillations that are unique to the co-administration of ketamine. APPROACH: In this work, we designed two k-nearest neighbors algorithms for anesthetic state prediction. MAIN RESULTS: The first algorithm was trained only on sevoflurane EEG data, making it sevoflurane-specific. This algorithm enabled discrimination of the sevoflurane general anesthesia (GA) state from sedated and awake states (true positive rate = 0.87, [95% CI, 0.76, 0.97]). However, it did not enable discrimination of the sevoflurane-plus-ketamine GA state from sedated and awake states (true positive rate = 0.43, [0.19, 0.67]). In our second algorithm, we implemented a cross drug training paradigm by including both sevoflurane and sevoflurane-plus-ketamine EEG data in our training set. This algorithm enabled discrimination of the sevoflurane-plus-ketamine GA state from sedated and awake states (true positive rate = 0.91, [0.84, 0.98]). SIGNIFICANCE: Instead of a one-algorithm-fits-all-drugs approach to anesthetic state monitoring, our results suggest that drug-specific models are necessary to improve the performance of automated anesthetic state monitors.

Delta oscillations phase limit neural activity during sevoflurane anesthesia.

Understanding anesthetic mechanisms with the goal of producing anesthetic states with limited systemic side effects is a major objective of neuroscience research in anesthesiology. Coherent frontal alpha oscillations have been postulated as a mechanism of sevoflurane general anesthesia. This postulate remains unproven. Therefore, we performed a single-site, randomized, cross-over, high-density electroencephalogram study of sevoflurane and sevoflurane-plus-ketamine general anesthesia in 12 healthy subjects. Data were analyzed with multitaper spectral, global coherence, cross-frequency coupling, and phase-dependent methods. Our results suggest that coherent alpha oscillations are not fundamental for maintaining sevoflurane general anesthesia. Taken together, our results suggest that subanesthetic and general anesthetic sevoflurane brain states emerge from impaired information processing instantiated by a delta-higher frequency phase-amplitude coupling syntax. These results provide fundamental new insights into the neural circuit mechanisms of sevoflurane anesthesia and suggest that anesthetic states may be produced by extracranial perturbations that cause delta-higher frequency phase-amplitude interactions.

Automatic Detection of General Anesthetic-States using ECG-Derived Autonomic Nervous System Features.

Electroencephalogram (EEG)-based prediction systems are used to target anesthetic-states in patients undergoing procedures with general anesthesia (GA). These systems are not widely employed in resource-limited settings because they are cost-prohibitive. Although anesthetic-drugs induce highly-structured, oscillatory neural dynamics that make EEG-based systems a principled approach for anesthetic-state monitoring, anesthetic-drugs also significantly modulate the autonomic nervous system (ANS). Because ANS dynamics can be inferred from electrocardiogram (ECG) features such as heart rate variability, it may be possible to develop an ECG-based system to infer anesthetic-states as a low-cost and practical alternative to EEG-based anesthetic-state prediction systems. In this work, we demonstrate that an ECG-based system using ANS features can be used to discriminate between non-GA and GA states in sevoflurane, with a GA F1 score of 0.834, [95% CI, 0.776, 0.892], and in sevoflurane-plus-ketamine, with a GA F1 score of 0.880 [0.815, 0.954]. With further refinement, ECG-based anesthetic-state systems could be developed as a fully automated system for anesthetic-state monitoring in resource-limited settings.

Drug-Specific Models Improve the Performance of an EEG-based Automated Brain-State Prediction System.

Maintaining anesthetic states using automated brain-state prediction systems is expected to reduce drug overdosage and associated side-effects. However, commercially available brain-state monitoring systems perform poorly on drug-class combinations. We assume that current automated brain-state prediction systems perform poorly because they do not account for brain-state dynamics that are unique to drug-class combinations. In this work, we develop a k-nearest neighbors model to test whether improvements to automated brain-state prediction of drug-class combinations are feasible. We utilize electroencephalogram data collected from human subjects who received general anesthesia with sevoflurane and general anesthesia with the drug-class combination of sevoflurane-plus-ketamine. We demonstrate improved performance predicting anesthesia-induced brain-states using drug-specific models.