Using Electroencephalography (EEG) to Guide Propofol and Sevoflurane Dosing in Pediatric Anesthesia

A study comparing brain wave patterns of fentanyl and ketamine in adult patients undergoing minimally invasive surgery

This study aimed to investigate and compare the neurophysiological impacts of two widely used anesthetic agents, Fentanyl and Ketamine, on EEG power spectra during different stages of anesthesia in adult patients undergoing minimally invasive surgery. EEG data were collected from patients undergoing anesthesia with either Fentanyl or Ketamine. The data were analyzed for relative power spectrum and fast-to-slow wave power ratios, alongside Spectral Edge Frequency 95% (SEF95), at 3 key stages: pre-anesthesia, during stable anesthesia, and post-anesthesia. EEG Relative Power Spectrum: Initially, both groups exhibited similar EEG spectral profiles, establishing a uniform baseline (P > .05). Upon anesthesia induction, the Fentanyl group showed a substantial increase in delta band power (P < .05), suggesting deeper anesthesia, while the Ketamine group maintained higher alpha and beta band activity (P < .05), indicative of a lighter sedative effect. Fast and Slow Wave Power Ratios: The Fentanyl group exhibited a marked reduction in the fast-to-slow wave power ratio during anesthesia (P < .05), persisting post-anesthesia (P < .05) and indicating a lingering effect on brain activity. Conversely, the Ketamine group demonstrated a more stable ratio (P > .05), conducive to settings requiring rapid cognitive recovery. Spectral Edge Frequency 95% (SEF95): Analysis showed a significant decrease in SEF95 values for the Fentanyl group during anesthesia (P < .05), reflecting a shift towards lower frequency power. The Ketamine group experienced a less pronounced decrease (P > .05), maintaining a higher SEF95 value that suggested a lighter level of sedation. The study highlighted the distinct impacts of Fentanyl and Ketamine on EEG power spectra, with Fentanyl inducing deeper anesthesia as evidenced by shifts towards lower frequency activity and a significant decrease in SEF95 values. In contrast, Ketamine's preservation of higher frequency activity and more stable SEF95 values suggests a lighter, more dissociative anesthetic state. These findings emphasize the importance of EEG monitoring in anesthesia for tailoring anesthetic protocols to individual patient needs and optimizing postoperative outcomes.

Variational Mode Decomposition Analysis of Electroencephalograms during General Anesthesia: Using the Grey Wolf Optimizer to Determine Hyperparameters

Frequency analysis via electroencephalography (EEG) during general anesthesia is used to develop techniques for measuring anesthesia depth. Variational mode decomposition (VMD) enables mathematical optimization methods to decompose EEG signals into natural number intrinsic mode functions with distinct narrow bands. However, the analysis requires the a priori determination of hyperparameters, including the decomposition number (K) and the penalty factor (PF). In the VMD analysis of EEGs derived from a noninterventional and noninvasive retrospective observational study, we adapted the grey wolf optimizer (GWO) to determine the K and PF hyperparameters of the VMD. As a metric for optimization, we calculated the envelope function of the IMF decomposed via the VMD method and used its envelope entropy as the fitness function. The K and PF values varied in each epoch, with one epoch being the analytical unit of EEG; however, the fitness values showed convergence at an early stage in the GWO algorithm. The K value was set to 2 to capture the α wave enhancement observed during the maintenance phase of general anesthesia in intrinsic mode function 2 (IMF-2). This study suggests that using the GWO to optimize VMD hyperparameters enables the construction of a robust analytical model for examining the EEG frequency characteristics involved in the effects of general anesthesia.

Electroencephalographic Indices for Clinical Endpoints during Propofol Anesthesia in Infants: An Early-phase Propofol Biomarker-finding Study

BACKGROUND

Unlike expired sevoflurane concentration, propofol lacks a biomarker for its brain effect site concentration, leading to dosing imprecision particularly in infants. Electroencephalography monitoring can serve as a biomarker for propofol effect site concentration, yet proprietary electroencephalography indices are not validated in infants. The authors evaluated spectral edge frequency (SEF95) as a propofol anesthesia biomarker in infants. It was hypothesized that the SEF95 targets will vary for different clinical stimuli and an inverse relationship existed between SEF95 and propofol plasma concentration.

METHODS

This prospective study enrolled infants (3 to 12 months) to determine the SEF95 ranges for three clinical endpoints of anesthesia (consciousness-pacifier placement, pain-electrical nerve stimulation, and intubation-laryngoscopy) and correlation between SEF95 and propofol plasma concentration at steady state. Dixon's up-down method was used to determine target SEF95 for each clinical endpoint. Centered isotonic regression determined the dose-response function of SEF95 where 50% and 90% of infants (ED50 and ED90) did not respond to the clinical endpoint. Linear mixed-effect model determined the association of propofol plasma concentration and SEF95.

RESULTS

Of 49 enrolled infants, 44 evaluable (90%) showed distinct SEF95 for endpoints: pacifier (ED50, 21.4 Hz; ED90, 19.3 Hz), electrical stimulation (ED50, 12.6 Hz; ED90, 10.4 Hz), and laryngoscopy (ED50, 8.5 Hz; ED90, 5.2 Hz). From propofol 0.5 to 6 μg/ml, a 1-Hz SEF95 increase was linearly correlated to a 0.24 (95% CI, 0.19 to 0.29; P < 0.001) μg/ml decrease in plasma propofol concentration (marginal R2 = 0.55).

CONCLUSIONS

SEF95 can be a biomarker for propofol anesthesia depth in infants, potentially improving dosing accuracy and utilization of propofol anesthesia in this population.

EDITOR’S PERSPECTIVE

Quantitative electroencephalogram in term neonates under different sleep states

Electroencephalogram (EEG) can be used to assess depth of consciousness, but interpreting EEG can be challenging, especially in neonates whose EEG undergo rapid changes during the perinatal course. EEG can be processed into quantitative EEG (QEEG), but limited data exist on the range of QEEG for normal term neonates during wakefulness and sleep, baseline information that would be useful to determine changes during sedation or anesthesia. We aimed to determine the range of QEEG in neonates during awake, active sleep and quiet sleep states, and identified the ones best at discriminating between the three states. Normal neonatal EEG from 37 to 46 weeks were analyzed and classified as awake, quiet sleep, or active sleep. After processing and artifact removal, total power, power ratio, coherence, entropy, and spectral edge frequency (SEF) 50 and 90 were calculated. Descriptive statistics were used to summarize the QEEG in each of the three states. Receiver operating characteristic (ROC) curves were used to assess discriminatory ability of QEEG. 30 neonates were analyzed. QEEG were different between awake vs asleep states, but similar between active vs quiet sleep states. Entropy beta, delta2 power %, coherence delta2, and SEF50 were best at discriminating awake vs active sleep. Entropy beta had the highest AUC-ROC ≥ 0.84. Entropy beta, entropy delta1, theta power %, and SEF50 were best at discriminating awake vs quiet sleep. All had AUC-ROC ≥ 0.78. In active sleep vs quiet sleep, theta power % had highest AUC-ROC > 0.69, lower than the other comparisons. We determined the QEEG range in healthy neonates in different states of consciousness. Entropy beta and SEF50 were best at discriminating between awake and sleep states. QEEG were not as good at discriminating between quiet and active sleep. In the future, QEEG with high discriminatory power can be combined to further improve ability to differentiate between states of consciousness.

Intraoperative pediatric electroencephalography monitoring: an updated review

Intraoperative electroencephalography (EEG) monitoring under pediatric anesthesia has begun to attract increasing interest, driven by the availability of pediatric-specific EEG monitors and the realization that traditional dosing methods based on patient movement or changes in hemodynamic response often lead to imprecise dosing, especially in younger infants who may experience adverse events (e.g., hypotension) due to excess anesthesia. EEG directly measures the effects of anesthetics on the brain, which is the target end-organ responsible for inducing loss of consciousness. Over the past ten years, research on anesthesia and computational neuroscience has improved our understanding of intraoperative pediatric EEG monitoring and expanded the utility of EEG in clinical practice. We now have better insights into neurodevelopmental changes in the developing pediatric brain, functional connectivity, the use of non-proprietary EEG parameters to guide anesthetic dosing, epileptiform EEG changes during induction, EEG changes from spinal/regional anesthesia, EEG discontinuity, and the use of EEG to improve clinical outcomes. This review article summarizes the recent literature on EEG monitoring in perioperative pediatric anesthesia, highlighting several of the topics mentioned above.

Implementation of an electroencephalogram-guided propofol anesthesia practice in a large academic pediatric hospital: A quality improvement project

BACKGROUND

Propofol-based total intravenous anesthesia is gaining popularity in pediatric anesthesia. Electroencephalogram can be used to guide propofol dosing to the individual patient to mitigate against overdosing and adverse events. However, electroencephalogram interpretation and propofol pharmacokinetics are not sufficiently taught in training programs to confidently deploy electroencephalogram-guided total intravenous anesthesia.

AIMS

We conducted a quality improvement project with the smart aim of increasing the percentage of electroencephalogram-guided total intravenous anesthesia cases in our main operating room from 0% to 80% over 18 months. Balancing measures were number of total intravenous anesthesia cases, emergence times, and perioperative emergency activations.

METHODS

The project key drivers were education, equipment, and electronic health record modifications. Plan-Do-Study-Act cycles included: (1) providing journal articles, didactic lectures, intraoperative training, and teaching documents; (2) scheduling electroencephalogram-guided total intravenous anesthesia teachers to train faculty, staff, and fellows for specific cases and to assess case-based knowledge; (3) adding age-based propofol dosing tables and electroencephalogram parameters to the electronic health record (EPIC co, Verona, WI); (4) procuring electroencephalogram monitors (Sedline, Masimo Inc). Electroencephalogram-guided total intravenous anesthesia cases and balancing measures were identified from the electronic health record. The smart aim was evaluated by statistical process control chart.

RESULTS

After the four Plan-Do-Study-Act cycles, electroencephalogram-guided total intravenous anesthesia increased from 5% to 75% and was sustained at 72% 9 months after project completion. Total intravenous anesthesia cases/mo and number of perioperative emergency activations did not change significantly from start to end of the project, while emergence time for electroencephalogram-guided total intravenous anesthesia was greater statistically but not clinically (total intravenous anesthesia without electroencephalogram [16 ± 10 min], total intravenous anesthesia with electroencephalogram [18 ± 9 min], sevoflurane [17 ± 9 min] p < .001).

CONCLUSION

Quality improvement methods may be deployed to adopt electroencephalogram-guided total intravenous anesthesia in a large academic pediatric anesthesia practice. Keys to success include education, in operating room case training, scheduling teachers with learners, electronic health record modifications, and electroencephalogram devices and supplies.

A Narrative Review Illustrating the Clinical Utility of Electroencephalogram-Guided Anesthesia Care in Children

The major therapeutic end points of general anesthesia include hypnosis, amnesia, and immobility. There is a complex relationship between general anesthesia, responsiveness, hemodynamic stability, and reaction to noxious stimuli. This complexity is compounded in pediatric anesthesia, where clinicians manage children from a wide range of ages, developmental stages, and body sizes, with their concomitant differences in physiology and pharmacology. This renders anesthetic requirements difficult to predict based solely on a child's age, body weight, and vital signs. Electroencephalogram (EEG) monitoring provides a window into children's brain states and may be useful in guiding clinical anesthesia management. However, many clinicians are unfamiliar with EEG monitoring in children. Young children's EEGs differ substantially from those of older children and adults, and there is a lack of evidence-based guidance on how and when to use the EEG for anesthesia care in children. This narrative review begins by summarizing what is known about EEG monitoring in pediatric anesthesia care. A key knowledge gap in the literature relates to a lack of practical information illustrating the utility of the EEG in clinical management. To address this gap, this narrative review illustrates how the EEG spectrogram can be used to visualize, in real time, brain responses to anesthetic drugs in relation to hemodynamic stability, surgical stimulation, and other interventions such as cardiopulmonary bypass. This review discusses anesthetic management principles in a variety of clinical scenarios, including infants, children with altered conscious levels, children with atypical neurodevelopment, children with hemodynamic instability, children undergoing total intravenous anesthesia, and those undergoing cardiopulmonary bypass. Each scenario is accompanied by practical illustrations of how the EEG can be visualized to help titrate anesthetic dosage to avoid undersedation or oversedation when patients experience hypotension or other physiological challenges, when surgical stimulation increases, and when a child's anesthetic requirements are otherwise less predictable. Overall, this review illustrates how well-established clinical management principles in children can be significantly complemented by the addition of EEG monitoring, thus enabling personalized anesthesia care to enhance patient safety and experience.

Association of volatile anesthesia exposure and depth with emergence agitation and delirium in children: Prospective observational cohort study

Background

Sevoflurane anesthesia is widely used in pediatric ambulatory surgery. However, emergency agitation (EA) and emergency delirium (ED), as major complications following sevoflurane anesthesia in children, pose risks to surgery and prognosis. Identifying the high risk of EA/ED, especially anesthesia exposure and the depth of anesthesia, may allow preemptive treatment.

Methods

A total of 137 patients were prospectively enrolled in this single-center observational cohort study to assess the incidence of EA or ED. Multivariable logistic regression analyses were used to test the association between volatile anesthesia exposure and depth with EA or ED. The Richmond Agitation and Sedation Scale (RASS), Pediatric Anesthesia Emergence Delirium Scale (PAED) and Face, Legs, Activity, Cry, and Consolability (FLACC) behavioural pain scale was used to assess the severity of EA or ED severity and pain. Bispectral index (BIS) to monitor the depth of anesthesia, as well as Time_LOW-BIS/Time_ANES %, EtSevo (%) and EtSevo-time AUC were included in the multivariate logistic regression model as independent variables to analyze their association with EA or ED.

Results

The overall prevalence of EA and ED was 73/137 (53.3%) and 75/137 (54.7%) respectively, where 48/137 (35.0%), 19/137 (13.9%), and 6/137 (4.4%) had mild, moderate, and severe EA. When the recovery period was lengthened, the prevalence of ED and extent of FLACC decreased and finally normalized within 30 min in recovered period. Multivariable logistic regression demonstrated that intraoperative agitation [2.84 (1.08, 7.47) p = 0.034], peak FLACC [2.56 (1.70, 3.85) p < 0.001] and adverse event (respiratory complications) [0.03 (0.00, 0.29) p = 0.003] were independently associated with higher odds of EA. Taking EtSevo-time AUC ≤ 2,000 as a reference, the incidence of EA were [15.84 (2.15, 116.98) p = 0.002] times and 16.59 (2.42, 113.83) p = 0.009] times for EtSevo-time AUC 2,500-3,000 and EtSevo-time AUC > 3,000, respectively. Peak FLACC [3.46 (2.13, 5.62) p < 0.001] and intraoperative agitation [5.61 (1.99, 15.86) p = 0.001] were independently associated with higher odds of developing ED. EtSevo (%), intraoperative BIS value and the percentage of the duration of anesthesia at different depths of anesthesia (BIS ≤ 40, BIS ≤ 30, BIS ≤ 20) were not associated with EA and ED.

Conclusions

For pediatrics undergoing ambulatory surgery where sevoflurane anesthesia was administered, EA was associated with surgical time, peak FLACC, respiratory complications, and "EtSevo-time AUC" with a dose-response relationship; ED was associated with peak FLACC and intraoperative agitation.

Implementation of an electroencephalogram-guided propofol anesthesia education program in an academic pediatric anesthesia practice

BACKGROUND

Propofol total intravenous anesthesia (TIVA) is increasingly popular in pediatric anesthesia, but education on its use is variable and over-dosage adverse events are not uncommon. Recent work suggests that electroencephalogram (EEG) parameters can guide propofol dosing in the pediatric population. This education quality improvement project aimed to implement a standardized EEG TIVA training program over 12 months in a large pediatric anesthesia division.

METHODS

The division consisted of 63 faculty, 11 clinical fellows, 32 residents, and 28 nurse anesthetists at the Children's Hospital of Philadelphia. The program was assessed for effectiveness (a significant improvement in EEG knowledge scores), scalability (training 50% of fellows and staff), and sustainability (recurring EEG lectures for 80% of rotating residents and 100% of new fellows and staff). The key drivers included educational content development (lectures, articles, and hand-outs), training a cohort of EEG TIVA trainers, intraoperative teaching (teaching points and dosing tables), decision support tools (algorithms and anesthesia electronic record pop-ups), and knowledge tests (written exam and verbal quiz during cases).

RESULTS

Over 12 months, 78.5% of the division (62/79) completed EEG training and test scores improved (mean score 38% before training vs 59% after training, p < .001). Didactic lectures were given to 100% of the fellows, 100% (11/11) of new staff, and 80% (4/5 blocks) of rotating residents.

CONCLUSION

This quality improvement education project successfully trained pediatric anesthesia faculty, staff, residents, and fellows in EEG-guided TIVA. The training program was effective, scalable, and sustainable over time for newly hired faculty staff and rotating fellows and residents.

EEG-Parameter-Guided Anesthesia for Prevention of Emergence Delirium in Children

Background: Emergence delirium (ED) usually occurs in children after surgery with an incidence of 10−80%. Though ED is mostly self-limited, its potential injuries cannot be ignored. Whether electroencephalography (EEG)-parameter-guided anesthesia could reduce the incidence of ED in pediatric surgery has not been fully discussed to date. Methods: Fifty-four boys aged 2−12 years undergoing elective hypospadias surgery under sevoflurane anesthesia were selected. In the EEG-parameter-guided group (E group), sevoflurane was used for anesthesia induction and was maintained by titrating the spectral edge frequency (SEF) to 10−15 and combining the monitoring of density spectral array (DSA) power spectra and raw EEG. While in the control group (C group), anesthesiologists were blinded to the SedLine screen (including SEF, DSA, and raw EEG) and adjusted the intraoperative drug usage according to their experience. Patients with a Pediatric Anesthesia Emergence Delirium (PAED) score > 10 were diagnosed with ED, while patients with a PAED score > 2 were diagnosed with emergence agitation (EA). Results: Finally, a total of 37 patients were included in this trial. The incidence of ED in the E group was lower than in the C group (5.6% vs. 36.8%; p = 0.04), while the incidence of EA was similar in the two groups (61% vs. 78.9%; p = 0.48). Intraoperative parameters including remifentanil dosage and the decrease in mean arterial pressure (MAP) were not different between the two groups (p > 0.05), but the mean end-tidal sevoflurane concentration (EtSevo) was lower in the E group than in the C group (p > 0.05). Moreover, during PACU stay, the extubation time and discharge time of the groups were similar, while the PAED scores within 5 min from extubation and the Face, Legs, Activity, Cry, and Consolability (FLACC) scores within 30 min from extubation were lower in the E group than in the C group. Conclusion: EEG-parameter-guided anesthesia management reduced the incidence of ED in children. Studies with larger sample sizes are needed to obtain more convincing results.

Timely completion of spinal fusion: A multidisciplinary quality improvement initiative to improve operating room efficiency

BACKGROUND

Failure to complete surgery within the scheduled timeframe impairs operating room efficiency leading to patient dissatisfaction and unplanned labor costs. We sought to improve timely completion (within 30 min of scheduled time) of first-case spine fusion surgery (for idiopathic scoliosis) from a baseline of 25%-80% over 12 months. We also targeted timely completion of perioperative stages within predetermined target completion times.

METHODS

The project was conducted in three overlapping phases over 16 months. A simplified process map outlining five sequential perioperative stages, preintervention baselines (N = 24) and time targets were defined. A multidisciplinary team conducted a series of tests of change addressing the aims. The key drivers included effective scheduling, team communications, family engagement, data collection veracity, standardized pathways, and situational awareness. Data collected by an independent data collector and from electronic medical records were analyzed using control charts and statistical process control methods.

RESULTS

Post-intervention, timely case completion increased from 25% to 68% (N = 49) (95% CI 15.1-62.7), (p = 0.003) and was sustained (N = 14). Implementation of prediction model for case-scheduling decreased difference between scheduled and actual case end-time (33 vs. 53 min [baseline]) and variance [lower/upper control limits ([-26, 51] vs. [-109, 216] min [baseline]). Average start time delay decreased from 6 to 2 min and on-time surgical starts improved from 50% to 70% (95% CI 3.2-41.6%). Timely completion increased for anesthesia induction (60% to 85%), surgical procedure (26% to 48%) and emergence from anesthesia (44% to 80%) but not for intraoperative patient preparation (30% to 25%) perioperative stages. Families reported satisfaction with preoperative processes (N = 14), and no untoward intraoperative safety events occurred.

CONCLUSIONS

Application of QI methodology reduced time variation of several tasks and improved timely completion of spine surgery. Beyond the study period, sustained team behavior, adaptive changes, and vigilant monitoring are imperative for continued success.

Isoelectric Electroencephalography in Infants and Toddlers During Anesthesia for Surgery-an International Observational Study

BACKGROUND

Intraoperative isoelectric electroencephalography (EEG) has been associated with hypotension and postoperative delirium in adults. This international prospective observational study sought to determine the prevalence of isoelectric EEG in young children during anesthesia. We hypothesized that the prevalence of isoelectric events would be common worldwide and associated with certain anesthetic practices and intraoperative hypotension.

METHODS.

Fifteen hospitals enrolled patients age ≤ 36 months for surgery using sevoflurane or propofol anesthetic. Frontal 4-channel EEG was recorded for isoelectric events. Demographics, anesthetic, emergence behavior, and Pediatric Quality of Life (PedsQL) variables were analyzed for association with isoelectric events.

RESULTS.

Isoelectric events occurred in 32% (206/648) of patients, varied significantly among sites (9-88%), and were most prevalent during pre-incision (117/628, 19%) and surgical maintenance (117/643, 18%). Isoelectric events were more likely with [odds ratio-OR (95% confidence interval-CI)] infants < 3 months [4.4 (2.57-7.4) p<0.001], endotracheal tube use [1.78 (1.16-2.73) p=0.008], propofol bolus for airway placement after sevoflurane induction [2.92 (1.78-4.8) p<0.001], and less likely with use of muscle relaxant for intubation [0.67 (0.46-0.99) p=0.046]. Expired sevoflurane was higher in patients with isoelectric events [mean difference (95% CI)] during pre-incision [0.2% (0.1, 0.4) p=0.005] and surgical maintenance [0.2% (0.1, 0.3) p=0.002]. Isoelectric events were associated with moderate (8/12, 67%) and severe hypotension (11/18, 61%) during pre-incision [OR: 4.6 (1.30-16.1) p=0.018; 3.54 (1.27, 9.9) p=0.015] and surgical maintenance [OR: 3.64 (1.71-7.8) p=0.001; 7.1 (1.78- 28.1) p=0.005], and lower PedsQL scores [median of differences (95% CI)] at baseline in patients 0-12 [-3.5 (-6.2, -0.7) p=0.008] and 25-36 months [-6.3 (-10.4, -2.1) p=0.003] and 30-day follow-up in 0-12 months [-2.8 (-4.9, 0) p=0.036]. Isoelectric events were not associated with emergence behavior or anesthetic (sevoflurane vs propofol).

CONCLUSIONS.

Isoelectric events were common worldwide in young children during anesthesia and associated with age, specific anesthetic practices, and intraoperative hypotension.