Abstract

Introduction

Electroencephalogram (EEG) discontinuity can occur at high concentrations of anesthetic drugs reflecting a pattern of suppression or transient attenuation of electrocortical activity. This EEG pattern occurs frequently during general anesthesia in adults as well as in children^1,2, and is defined by the presence of EEG amplitudes less than 25 microvolts that persist for longer than 2 seconds³. Discontinuous EEG patterns during general anesthesia have been reported to occur with a prevalence as high as 52–63%^1,2 and may be an indicator of unnecessarily deep anesthesia. While EEG discontinuities can be present in normal preterm infants during sleep-wake cycling, a pattern labeled tracé alternant³, in full-term infants suppression to less than 15 microvolts for longer than 2 seconds (tracé discontinu) is non-physiologic and abnormal³. A recent study found that increased duration of isoelectric events on the EEG, a more extreme degree of suppression to less than 2 microvolts, is associated with worse long-term neurologic outcomes in neonates undergoing cardiac surgery⁴, but the clinical significance of EEG discontinuities during pediatric anesthesia for non-cardiac surgery is not yet known.

In this paper, we performed an analysis of prospectively collected EEG data to identify periods of EEG discontinuity and estimate its incidence during the period of anesthesia induction. Inhalational induction is a dynamic period consisting typically of rapid wash-in of volatile anesthesia with possible later co-administration of intravenous agents. This period may be uniquely susceptible to the development of EEG discontinuity due to the important clinical need to rapidly obtain a deep level of sedation/hypnosis to avoid unwanted airway hyperreflexia (e.g., laryngospasm)⁵. We hypothesized that EEG discontinuity would occur during anesthesia induction at a rate as high as 50–60%^1–2. Sevoflurane, propofol, and other gamma-aminobutyric acidergic (GABAergic) anesthetics produce stereotyped slow (0.1 to 1 Hz) activity and frontal alpha (8 to 12 Hz) oscillations in the EEG during unconsciousness which can be quantified using power spectral analysis^6–11. The amount of energy or power in the EEG signal within these frequency bands may be calculated from the power spectrum (e.g., alpha band power)^6–11. Frontal alpha band activity appears to be generated by prefrontal cortical and thalamic circuits¹². It is absent in neonates and begins developing at approximately 6 months of age, suggesting it may be a neurophysiologic biomarker of brain development^13–19. In adults, the size of the anesthesia-induced frontal alpha activity decreases with age, is correlated with cognitive function^18,19, and is inversely associated with the likelihood of anesthesia-induced discontinuities²⁰. Therefore, our secondary hypothesis was that there would be an association between early sevoflurane-induced alpha power during anesthetic induction and development of EEG discontinuity.

Methods

This is a prospective observational study approved by the Institutional Review Board (IRB) of Albert Einstein College of Medicine in which we collected EEG data and coded a priori for a variety of EEG features during anesthesia. In a prior report, we described epileptiform changes²¹. In this present manuscript, we describe our analyses of EEG discontinuity. Written informed consent was obtained from a legal surrogate, the parents or legal guardians for all subjects. This manuscript adheres to the applicable STROBE statement guidelines. We described details of cohort recruitment and characteristics in our previous report²¹.

Quantitative EEG analyses

Custom EEG analysis scripts were written using MATLAB (version R2017a, MathWorks, Natick, MA), employing functions in the Chronux and Fieldtrip toolboxes²³. We compared the EEG spectral features of patients who developed discontinuity (Figure 1) to those who did not at baseline prior to anesthesia administration (Supplemental Figure 1) as well as during the period of anesthesia induction. We excluded the first three minutes of anesthetic induction from EEG analysis to avoid potential artifacts due to patient movement or clinical interactions such as airway management or positioning. Thereafter, power spectral features were analysed on a minute-by-minute basis, requiring for each minute-long epoch at least 30 seconds of data that were free of both artifacts and suppression events. EEG data were band-pass filtered from 0.1 to 40 Hz. We also examined power spectral features in the period of transition before, during, and after EEG discontinuity (Supplemental Figure 2).

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Figure 1.

Comparison of alpha power in infants with electroencephalogram (EEG) discontinuity (n=18) and without EEG discontinuity (n=34) during anesthesia induction. (A-C) Topographic distribution over the head of the group-mean power spectrum in the alpha band (8 to 12 Hz) between subjects who did not develop discontinuity in their EEG (A) compared to those who did (B). The power difference between the two groups is presented in (C) with statistically significant differences represented by “X” observed in temporal, parietal, and occipital leads. Non-significant differences are represented by “O”. (D-F) Comparison of average power spectra in infants with EEG discontinuity (red, n=18) and without EEG discontinuity (blue, n= 34) during anesthesia induction with their respective 95% CIs estimated using the bootstrap method in the (D) Fz electrode, (E) Pz electrode and (F) T3 electrode. The horizontal black line parallel to the X axis in (E) and (F) represents the frequency segment in which the 95% CIs do not cross zero and therefore the difference between the groups is considered to be statistically significant.

Power spectra were computed for each patient using the multitaper method implemented in the Chronux toolbox²³. The parameters were as follows: window length T = 5 s with no overlap, time-bandwidth product TW = 3, number of tapers K = 5, and spectral resolution of W = 1.2 Hz. Group-averaged spectra were computed by taking the mean power across subjects at each frequency for discontinuity compared to no discontinuity groups across the entire epoch at every electrode separately. We calculated 95% confidence intervals (CIs) for each spectral estimate and differences between power spectra using a bootstrap procedure²³. To account for the spectral resolution of the power spectral estimates, for frequencies f > 2W, we deemed differences in spectra to be significant only if their CIs did not include zero within at least one spectral resolution (2W = 1.2 Hz).

For each electrode, alpha power was estimated by computing the average power from 8 to 12 Hz. Delta power was estimated by computing the average power from 1 to 4 Hz. We then averaged across subjects to obtain the group-level average power with 95% CIs. To characterize the topographic distribution of the power spectrum in the alpha band, we used the topoplot function implemented in the Fieldtrip toolbox²⁴.

Statistical Analysis

Data were reported as means and standard deviations or medians and interquartile ranges for continuous variables and frequencies and percentages for categorical variables. Differences in clinical characteristics between those with and without EEG discontinuity were compared using Wilcoxon rank-sum tests for continuous variables and chi-square or Fisher’s exact tests for categorical variables. A two-sided p value of less than 0.05 was considered statistically significant (Table 1). We counted the number of EEG discontinuity events and described their characteristics after sevoflurane and propofol (Table 2).

Table 1.

Clinical and Electroencephalogram (EEG) Spectral Characteristics of Cohort

	Overall	No EEG Discontinuity (n = 34)	EEG Discontinuity (n = 20)	P value*
Age (months)	7.6 (4.9, 9.8)	7.3 (4.9, 9.8)	7.6 (5.0, 9.9)	0.94
Weight (kg)	8.9 (6.7, 10.4)	8.7 (6.8, 10.2)	9.4 (6.0, 10.5)	0.61
Male sex	41 (75.9)	28 (82.4)	13 (65.0)	0.15
Full term	52 (96.3)	33 (97.1)	19 (95)	0.99
Alpha Power at Pz (dB)	10.6 (8.0, 11.8)	11.2 (8.7, 12.9)	8.3 (7.8, 10.1)#	0.004
Epileptiform EEG	4 (7.4)	1 (2.9)	3 (15.0)	0.14
Maximum etSEV (%)	6.1 (5.5, 6.6)	6.1 (5.5, 6.5)	6.1 (5.5, 6.6)	0.14
Minimum etCO2 (mmHg)	15.5 (10.0, 20.5)	16.5 (11.0, 21.5)	14.5 (9.5, 19.5)	0.31
Maximum etCO2 (mmHg)	36.5 (32.0, 41.0)	35.5 (30.0, 39.5)	39.5 (33.0, 44.5)	0.10
Propofol administration				<0.001
Propofol given	21 (38.9)	4 (11.8)	17 (85.0)
Propofol not given	33 (61.1)	30 (88.2)	3 (15.0)
Propofol dose (mg/kg)	0 (0, 2.6)	0 (0, 0)	2.7 (2.0, 3.3)	<0.001
Fentanyl administration				0.36
Fentanyl given	28 (51.9)	16 (47.1)	12 (60.0)
Fentanyl not given	26 (48.1)	18 (52.9)	8 (40.0)
Fentanyl dose (mcg/kg)	0.5 (0, 1.1])	0 (0, 0.9)	1.0 (0, 1.6)	0.12
Airway				<0.001
Mask	16 (29.6)	15 (44.1)	1 (0.1)
Laryngeal mask airway	11 (20.4)	9 (26.5)	2 (0.1)
Endotracheal tube	27 (50.0)	10 (29.4)	17 (0.9)

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^*No EEG discontinuity group compared to EEG discontinuity group.

^#Excluding two subjects who already developed EEG discontinuity before the initial sampling epoch.

EEG: electroencephalogram

kg: kilogram

Pz: midline parietal channel on the electroencephalogram, International 10–20 System

dB: decibel

et_SEV: end tidal sevoflurane

et_CO2: end-tidal carbon dioxide

mmHg: millimeters of mercury

mg/kg: milligrams per kilogram

mcg/kg: micrograms per kilogram

Table 2.

Characteristics of Electroencephalogram (EEG) discontinuity events

	Overall	Sevoflurane alone	Propofol bolus
Number of discontinuity events	25	9	16
EtSEV when first discontinuity begins (%)	4.2 (2.9, 5.0)	4.2 (3.8, 6.5)	4.4 (2.9, 5)
Duration of EEG discontinuity (seconds)	139 (14.5, 310)	7 (2.5, 52)	190 (115, 384)
Burst suppression pattern*	7	2 (22.2)	5 (31.3)
Time from start of anesthesia induction to onset of EEG discontinuity (seconds)#	-	328.5 (200, 550)	-
Time from intravenous injection to appearance of EEG discontinuity	-	-	15.5 (6, 26)

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^*A burst suppression pattern was observed more often when EEG discontinuity occurred after propofol (5, 31.3%) compared to during sevoflurane alone (2, 22.2%).

^#In all but three patients, the earliest onset of EEG discontinuity was more than 6 minutes after the start of induction of anesthesia; the onsets of the earliest discontinuities in the other three patients were 2 min and 15 sec, 3 min and 17 sec, and 3 min and 48 sec, respectively, after the start of sevoflurane induction.

EEG: electroencephalogram

Et_SEV: end tidal sevoflurane

To assess whether differences in sevoflurane-induced EEG spectral features could be related to differences in sevoflurane dosing, we compared the minute-by-minute end-tidal sevoflurane levels, alpha power and delta power in the EEG discontinuity and no discontinuity groups, respectively, using two-way repeated measures analysis of variance (ANOVA) (Figure 2). We comprehensively explored all clinical covariates using univariable logistic regression with a threshold p value <0.1 for variable selection in a purposeful, multivariable logistic regression model building process (Supplemental Table 1). The objective of our models was to explore the independent association of early sevoflurane-induced alpha power during anesthesia induction and later development of EEG discontinuity and potential confounders of this association. As propofol is known to cause EEG discontinuity²⁵, we adjusted for propofol and assessed other intravenous anesthetic administration as possible confounders. We defined an airway management variable (three-level categorical variable with reference = face mask only, 1 = laryngeal mask airway, and 2 = endotracheal tube). We used likelihood ratio tests to select variables for inclusion in multivariable models with a threshold level of p <0.05. We explored possible interaction effects by age¹⁷ and sex. Age was thought to be an important potential confounder because the appearance of frontal alpha power seems to occur between 4 to 8 months of age¹⁷ and was forced into the final model. We selected the model with the lowest Akaike Information Criterion (AIC) value as the final model. We limited multivariable models to a maximum of 4 covariates to avoid model instability (Table 3). All statistical analyses were performed using Stata 17.0 (StataCorp, College Station, TX).

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Figure 2.

Comparison of minute-by-minute end-tidal sevoflurane, alpha and delta power between infants with and without discontinuity during anesthesia induction. (A) Average end-tidal sevoflurane concentrations. No differences were observed between the groups; however, we observed a significant reduction in end-tidal sevoflurane through time (^##temporal effect, p <0.0001). (B) Average alpha power in the Pz electrode. Subjects experiencing discontinuity exhibit lower alpha power throughout anesthesia induction compared to subjects in the no discontinuity group (***group effect, p <0.0001). Alpha power remains stable in both groups through time (temporal effect, p = 0.12). (C) Average delta power in the Pz electrode. No differences in delta power were observed between groups, but average delta power decreased through time (^##temporal effect, p <0.0001). All results are expressed as means and standard deviations and compared using a repeated measures two-way analysis of variance (ANOVA). Blue circles and red boxes represent the no discontinuity and discontinuity groups, respectively.

Pz: midline parietal channel on the electroencephalogram, International 10–20 System

Table 3.

Multivariable logistic regression models of the association between alpha power and Electroencephalogram (EEG) discontinuity

	Odds Ratio	P value	95% confidence interval
Model 1
Alpha power at Pz (dB)	0.71	0.04*	(0.51 – 0.98)
Propofol dose (mg/kg)	3.77	<0.001*	(1.81 – 7.87)
Model 2
Age (months)	1.10	0.36	(0.90 – 1.35)
Alpha power at Pz (dB)	0.70	0.03*	(0.51 – 0.97)
Propofol dose (mg/kg)	3.95	<0.001*	(1.85 – 8.42)
Model 3
Age (months)	1.17	0.21	(0.92 – 1.48)
Alpha power at Pz (dB)	0.64	0.03*	(0.43 – 0.96)
Propofol dose (mg/kg)	4.47	0.001*	(1.82 – 11.00)
Fentanyl (mcg/kg)	4.07	0.04*	(1.08 – 15.34)
Model 4
Age (months)	1.04	0.78	(0.81 – 1.31)
Alpha power at Pz (dB)	0.51	0.02*	(0.30 – 0.89)
Propofol dose (mg/kg)	4.72	0.002*	(1.78 – 12.56)
Maximum end tidal CO2 (mmHg)	1.29	0.045*	(1.01 – 1.66)

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^*Statistically significant at p <0.05 level.

EEG: electroencephalogram

Pz: midline parietal channel on the electroencephalogram, International 10–20 System

dB: decibel

mg/kg: milligram per kilogram

mcg/kg: microgram per kilogram

CO₂: carbon dioxide

mmHg: millimeters of mercury

Results

We obtained interpretable data in 54 of 68 (79.4%) subjects with a median (interquartile range) age of 7.6 (4.9, 9.8) months (Table 1). The neurologist readers (AL, EY) deemed 14 of 68 EEG recordings uninterpretable and these were excluded from analysis (Supplemental Figure 3). Two subjects who developed EEG discontinuity prior to the initial sampling epoch in which the spectral power was computed were excluded from the analysis. Three subjects had missing data for their end tidal gases (5.6%) because the physiological gas data were not transferred to the electronic medical record. These data values were kept as null without additional special handling. The final analytical sample was 52 subjects. EEG discontinuities were observed in 20 (37.0%) subjects with a total of 25 discrete events (concordance rate = 92.59%, Kappa = 0.84, 95% CI [0.69 – 0.99], p <0.0001) (Table 2). There were no detected differences in age, weight, sex, presence of epileptiform EEG (7.4%)²¹, maximum end-tidal sevoflurane, maximum and minimum end-tidal carbon dioxide (etCO₂), or fentanyl administration between discontinuity groups.

Prior to anesthesia, we examined the baseline EEG power spectra of infant subjects who went on to develop EEG discontinuity during anesthesia induction (n=18) compared to those who did not (n=29). We excluded 7 subjects in this analysis because of data artifact. We found no differences in the average spectra between the groups at any frequency from 1 to 40 Hz (Supplemental Figure 1).

Under the effect of inhaled sevoflurane alone, before any intravenous agents were administered, we compared the EEG power spectra between subjects who developed discontinuity (n = 18) and those who did not (n = 34). We excluded two subjects from this analysis because they had already developed discontinuity within the first three minutes after induction, prior to the first sampling epoch. We found significant differences in sevoflurane-induced alpha power between groups at multiple electrodes in the posterior and temporal head regions (8 of 19 leads [42.1%], Figure 1C). In frontal regions, there were visible differences in the topographic plot (i.e., the group average alpha power, Figure 1A, ​,1B),1B), however these differences did not reach statistical significance (Figure 1C, ​,1D).1D). Alpha power at the midline parietal channel (Pz), selected as the representative lead, was statistically significantly lower in the discontinuity group, 8.3 IQR (7.8, 10.1) dBs, compared to the no discontinuity group, 11.2 IQR (8.7, 12.9) dBs (p = 0.004) (Table 1, Figure 1E). A sensitivity analysis incorporating the two subjects who were excluded found a significant alpha power difference consistent with these results (data not shown). The repeated measures ANOVA of minute-by-minute end-tidal sevoflurane concentrations showed no difference between groups (p = 0.4, Figure 2A). During this same timeframe, we observed a significantly lower Pz alpha power between groups on a minute-by-minute basis (p <0.0001; Figure 2B) whereas delta power showed no difference (P = 0.6, Figure 2C). Thus, the main difference between groups during this time period was posterior alpha power.

We characterized intravenous anesthetic administration. Overall, 21 subjects (38.9%) received propofol. A greater proportion of patients in the discontinuity group received propofol (17 of 20 subjects, 85.0%) but not all propofol administration led to discontinuity (4 of 34 subjects who received propofol did not develop EEG discontinuity, 11.8%, p <0.001) (Table 1). The majority of discontinuity events occurred after propofol administration (16 of 25 events, 64.0%) but a substantial proportion of discontinuity events occurred after sevoflurane alone (9 of 25, 36.0%) (Table 2). Median propofol dose was higher in patients exhibiting EEG discontinuity (2.7 IQR [2.0, 3.3] mg/kg) compared to those with no discontinuity (0 IQR [0, 0] mg/kg), p <0.001 (Table 1).

In logistic regression models (Table 3, Supplemental Table 1), maximum end-tidal sevoflurane was not found to be associated with EEG discontinuity. Sevoflurane-induced alpha power at Pz was significantly associated with EEG discontinuity, as was propofol administration. Biological sex was found to contribute to model instability and was not included in the model. There were no significant two-way interactions of age with propofol or alpha power, nor of sex with propofol and alpha power, suggesting that the association of propofol and alpha power on probability of developing EEG discontinuity did not vary with age and sex. The final association model consisted of age, alpha power, propofol dose, and maximum etCO₂ (Model 4, Table 3). Increasing posterior alpha power (in dBs) was associated with decreasing odds of EEG discontinuity (adjusted OR [aOR] = 0.51, [95% CI: 0.30 – 0.89; p=0.02]).

In exploratory analyses, the median emergence time among subjects who did not develop EEG discontinuity was 8.5 IQR (4.5, 23) minutes compared to a median emergence time of 15 IQR (8, 32) minutes among subjects who developed EEG discontinuity. This difference approached, but did not reach, statistical significance (p = 0.07). Agitation or crying was not noted to be statistically significantly different between infants developing EEG discontinuity (2/10, 10%) compared to those who did not (9/34, 26.5%), p = 0.18.

Discussion

This study demonstrates a 37% incidence of EEG discontinuity during pediatric anesthesia induction, consistent with prior reports examining the period of maintenance of anesthesia^1–2. Infants who develop discontinuity events exhibit significantly lower initial alpha power in temporal, parietal, and occipital regions of the brain (Figure 1C–F) under sevoflurane in the absence of any other drugs, despite equivalent end-tidal sevoflurane levels (Figure 2A). There were no significant differences between groups in alpha power, or power in any other frequency band, during the baseline period prior to any anesthesia administration (Supplemental Figure 1), suggesting that the relationship of decreased alpha power to development of EEG discontinuity reflects a different neurophysiologic process in the developing brain in response to anesthesia. This decreased posterior alpha power persisted throughout the period of EEG recording during anesthesia (Figure 2B). Sevoflurane-induced alpha power was significantly associated with EEG discontinuity even after multivariable adjustment for known confounders such as intravenous propofol administration (Table 3). This analysis shows that, all else being equal, EEG discontinuity is more likely when the patient has a low alpha power at induction, i.e., that low alpha power is a marker of susceptibility or vulnerability to suppression, whether by propofol bolus or high sevoflurane concentration. Our findings suggest that identifiable neurophysiologic markers such as alpha power are associated with later development of EEG discontinuity.

Our findings are consistent with previous work investigating the relationship between intraoperative EEG features and burst suppression, a specific pattern of EEG discontinuity^1,2. In older adults, low frontal alpha power predicts burst suppression during anesthesia independent of chronological age^19,26. While the most well-known alpha activity elicited by anesthesia is frontal, our study shows that posterior alpha activity may also carry important information. Previous work by Agrawal found that discontinuity episodes were preceded by EEG spectra with a significantly lower spectral edge²⁵, consistent with our results (Supplemental Figure 2). The mechanism underlying the association between alpha power and discontinuity or burst suppression is unclear. Shao, Kahali, et al. proposed that astrocytes could mediate the link between alpha oscillations and discontinuity events, as they support both neuronal synchronization required for oscillatory dynamics as well as neuronal metabolism whose compromise leads to suppression events²⁰. They also point out that cholinergic and noradrenergic neuromodulators can influence the activity of these astrocytes, which may explain both the age and drug dose-dependence of burst suppression under anesthesia^27,28. Pertinent to the results reported here, we note that neuromodulatory systems are rapidly changing in the first year of life and may have significant between-patient variation²⁹.

The clinical implications of anesthesia-induced discontinuity in infants are not fully understood. Isoelectric EEG, a more extreme degree of voltage suppression, has been associated with poor long-term neurological outcomes in neonates undergoing cardiac surgery⁴. In adults, low frontal alpha power is associated with burst suppression during anesthesia^21,27, which may be associated with postoperative neurocognitive disorder^20,30,31. The causal relationship between burst suppression or anesthetic depth and post-operative neurocognitive outcomes, however, is at present unclear. A recent study show that EEG-guided anesthesia that regulates or reduces anesthetic depth can reduce post-operative delirium³². On the other hand, other studies have not demonstrated a relationship between postoperative cognitive outcomes and depth of intraoperative anesthetic management employing behavioral³³ or EEG guidance³⁴. In infants and children, the clinical implications of EEG discontinuity are unknown at this time. Exploratory analyses of our dataset suggested a trend towards longer emergence times and decreased emergence excitation among infants who experienced EEG discontinuity, but additional studies are necessary. Further work is planned to investigate whether EEG discontinuity during pediatric anesthesia is a prognostic factor of clinical outcomes.

We accounted for propofol administration, which always occurred after sevoflurane administration was initiated and was typically correlated with the need for advanced airway management (e.g., endotracheal intubation) in this sample. 36% (9 of 25) of the discontinuity events occurred under the effect of sevoflurane alone without propofol (Table 2). In addition, in the subset of patients who did not develop any discontinuity, 4 of 34 (11.8%) received propofol; conversely, in the subset of patients who did develop discontinuity, 3 of 20 (15%) did not receive propofol (Table 1). Even after adjustment for the confounding effect of propofol administration, the association of alpha power with discontinuity remained significant (Table 3). Adjustment for propofol led to loss of significance of the airway variable; propofol was also thought to be a proximal event explaining airway management. Therefore, propofol was retained and airway was dropped from the model for both clinical and statistical reasons. Fentanyl blocks nociception and has a direct sedative effect through inhibitory effects on brainstem cholinergic circuits³⁵; in combination with propofol and sevoflurane, fentanyl’s influence on arousal may promote EEG discontinuity (Model 3, Table 3). The association of maximum etCO₂ might reflect the fact that significantly increased etCO₂ diminishes the size of the EEG signal in premature and full-term infants³⁶ (Model 4, Table 3). Future studies with a larger cohort will help further characterize the influence of fentanyl and other opioids, their interaction with sedative-hypnotic drugs, and the role of physiological variables such as etCO₂.

This prospective observational study was not specifically powered to investigate discontinuity effects. The small sample size, which resulted in model instability when additional variables were added into the model, precluded us from accounting for all potentially relevant covariates. We also cannot rule out residual confounding. Although our sample size was moderate as was the level of statistical significance for alpha power (p = 0.02, Model 4), associations were consistently observed across multiple model formulations with no substantial change in either the effect size or the significance level of the alpha power covariate (Table 3). Inhalational induction is a dynamic period that can be difficult to observe with EEG due to its relative brevity spanning several minutes and the possibility of data artifact during airway management. However, we were able to obtain epochs of interpretable EEG data in all study subjects followed by minute-by-minute, repeated analyses. Sevoflurane in oxygen was the sole inhaled anesthetic agent used to initiate anesthesia induction in all subjects with subsequent management otherwise left to the discretion of the responsible anesthesiologist. This may have introduced some variation that could have been mitigated with a more standardized protocol. Nonetheless, the association of decreased posterior alpha power with discontinuity consistently observed during routine clinical practice suggests it may be useful in predicting which patients have a greater chance of developing discontinuity.

The brain develops rapidly during the first year of life^37–39 and anesthesia-induced brain rhythms vary systematically during this process of maturation^13–15,17. In particular, anesthesia-induced alpha waves are absent in early infancy and develop between 4 to 10 months of age, a putative consequence of increasing GABAergic inhibitory tone within thalamocortical circuits¹⁷. At the same time, individual children may also develop at different rates during infancy⁴⁰ and may have different anesthetic requirements. Our study appears to connect these two ideas by showing how individual patients’ sevoflurane-induced alpha power might be associated with their anesthetic requirements, as measured by their tendency to experience discontinuity. Future studies will expand on these findings with a larger sample size, explore potential mechanisms, and identify any associations with postoperative outcomes.

Supplementary Material

Acknowledgements

Glossary of Terms:

Footnotes

References