Can intraoperative electroencephalogram finally prevent emergence delirium in children?

We read with great interest the randomized clinical trial by Miyasaka et al. (1) evaluating electroencephalogram (EEG)-guided titration of sevoflurane and its effect on pediatric anesthesia emergence delirium (PAED), defined as a PAED scale score ≥10. The authors analyzed over 170 children aged between 1 and 6 years who underwent various types of surgeries under general anesthesia. They reported a 14% reduction in PAED incidence when Sevoflurane was adjusted based on EEG data compared to a fixed 1.0 Mean Alveolar Concentration (MAC) regimen. Additionally, children in the experimental group woke up 21 minutes earlier and were discharged from the Post-Anesthesia Care Unit (PACU) 16 minutes earlier than the control group. This work supports the evolving field of personalized anesthetic titration strategies, which include monitoring neuromuscular blocking, nociception, and consciousness via processed EEG [i.e., Bispectral Index (BIS) and Patient State Index (PSI)] (2).

The intraoperative EEG used during anesthesia analyzes electrical activity from the frontal cortex via electrodes applied to the patient’s forehead. The frequency bands recorded are conventionally classified in delta (0.1–4 Hz), theta (5–8 Hz), alpha (9–13 Hz), beta (14–30 Hz), and gamma (30–80 Hz) (3). The early machines only displayed cortical signals processed using proprietary algorithms to quantify consciousness on a 100-point scale, known as processed EEG, with 0 indicating cortical burst suppression and 100 indicating full awakening (4,5).

The use of intraoperative EEG monitoring has gained prominence with the adoption of intravenous anesthesia, which has made it imperative to ensure that patients under general anesthesia, especially when neuromuscular blockers are employed, remain entirely unconscious (2). In fact, contrary to inhalational anesthetics, the pharmacokinetic of intravenous agents such as propofol is difficult to predict. Although automated infusion systems based on complex pharmacokinetic models have been developed, the algorithms were derived from small adult cohorts (6). In pediatric patients, individual variability within age groups renders these models highly inaccurate, with reported error margins of up to 200% (7,8). Consequently, propofol infusion in children is often guided by clinical indicators, such as hemodynamic responses or patient movement, which frequently leads to overdosing (7,9). In contrast, EEG-derived metrics demonstrate a strong correlation with propofol blood concentrations, thereby supporting their use for intravenous anesthetic titration (7,10). Intraoperative EEG monitoring has also found significant application when inhalational anesthetics are used (7). Although the inhaled end-expiratory concentration serves as a reliable indicator of anesthetic depth and can prevent awareness (11), it may also lead to anesthetic overdose, causing brain burst suppression and hemodynamic instability (12).

In both adults and children, intraoperative EEG has been recommended to prevent intraoperative awareness, hemodynamic instability, and postoperative delirium (13-16), three goals that have been advocated as indicators of high-quality care in pediatric practice (17).

Intraoperative awareness in pediatrics has been reported as high as 1 in 51 (18), compared to 1 in 600 in the adult population (19), and can result in significant distress and even post-traumatic stress disorder (20). In adults, numerous studies have demonstrated that processed EEG monitoring may reduce the risk of intraoperative awareness (21), anesthetic requirements, and hemodynamic instability, while facilitating recovery from anesthesia (22). In children, evidence of reduced anesthetic requirements and faster recovery times has also been reported in a handful of investigations (5). Instead, the efficacy of processed EEG has remained a subject of debate for several years. This uncertainty primarily arose from the fact that the EEG algorithms were developed using adult data and did not account for the significant developmental alterations in cortical activity that occur in children during early childhood (5,10,23). During the first 3 years of life, cortical size, thickness, and myelination increase significantly, while network connectivity continues to develop until puberty (24). From an EEG perspective, this is reflected in significant changes in waveforms, with alpha- and beta-band oscillations typically absent at birth and gradually emerging during infancy (10,24,25). Therefore, studies involving children <3 years of age failed to find a benefit of using processed-EEG during general anesthesia (26,27). Furthermore, general anesthetics modify cortical activity in various ways, such that a patient may be unconscious despite high processed EEG values, as observed with the use of ketamine (2), a medication widely used in pediatric anesthesia. In recent years, the new generation of EEG monitors not only displays processed EEG data but also the raw waveforms, spectral edge frequency (SEF), and the density spectral array (DSA). The SEF represents the EEG frequency below a specific percentage (e.g., 95%), whereas the DSA displays color-coded power of each frequency over time. The introduction of DSA revealed that the anesthetic state is characterized by prominent power in the delta and alpha bands, but each anesthetic agent produces distinct features (28). Consequently, there was a renewed interest in EEG-guided anesthesia and its potential benefits in children.

A significant potential application of intraoperative EEG is the prevention of postoperative delirium, a phenomenon that affects both adults (29) and children, although its pathophysiology may differ and remains poorly understood (30-32). In children, the incidence of PAED [also known as emergence delirium (ED)] is around 32% of children emerging from anesthesia, but can be as high as 80% (33). The PAED can have significant consequences, including patient injury, heightened parental anxiety, greater PACU nursing needs (34,35), and long-lasting behavioral changes (36).

In adults, postoperative delirium has been associated with intraoperative burst suppression (29), which can be prevented by the use if intraoperative EEG (12). In pediatric patients, intraoperative burst suppression or isoelectric EEG has been documented in more than 60% of cases (9). However, the presence of intraoperative burst suppression has not been clearly associated with specific behaviors on emergence, including PAED (9). In children, PAED appear to be associated with increased functional connectivity within the frontal lobe network during emergence (32). While children without PAED typically transition through sleep-like EEG patterns, characterized by theta activity associated with drowsiness or slower delta activity, before awakening, children with PAED emerge from an “indeterminate state” without transitioning to sleep-like patterns (32,37). Epileptiform discharges, particularly interictal spike events, have also been associated with PAED (37). Collectively, increased frontal connectivity, arousal from an indeterminate state, and interictal spike activity suggest that PAED may be associated with heightened cerebral excitability (37).

Prevention of PAED encompasses various pharmacological and non-pharmacological approaches (30,33). A more multidisciplinary approach with nurses in the postoperative monitoring of children, identifying early signs of PAED and taking timely action to mitigate its impact and ensure optimal health outcomes, is also essential (35). While PAED’s etiology is poorly understood (30), certain risk factors have been identified, including young age, behavior before and during the anesthesia induction, and the use of volatile anesthesia (33). Epileptiform EEG patterns have been shown to be associated with PAED when high doses of Sevoflurane are used (38). In particular, recovery from Sevoflurane anesthesia appears to alter cortical functional connectivity and, consequently, PAED (32). Thus, a decrease in inhaled anesthetic exposure may influence volatile washout and excitatory emergence in pediatric patients (39,40), and decrease the incidence of PAED. Indeed, recent investigations have hypothesized that intraoperative EEG monitoring may prevent the onset of PAED, primarily by reducing intraoperative exposure to general anesthetics (14-16).

Finally, an excessive exposure to general anesthetics raises concerns regarding their potential neurotoxic impact (41) on vulnerable patients, such as children (42,43), although recent data remain inconclusive (44). In this context, Miyasaka et al.’s result (1) on decreased exposure to Sevoflurane may have implications that extend beyond the prevention of PAED.

Thus, the work by Miyasaka et al. (1) makes a significant contribution to understanding the potential applications of intraoperative EEG and the prevention of PAED. However, it is important to consider these findings in light of their methodological limitations, including the potential confounding influence of pain on the assessment of PAED, limited reporting of rescue medications and intraoperative physiological variables, and potentially significant differences between study groups.

Severe pain affects over 40% of children following surgery (45). In children under the age of 3 or those with neurodevelopmental disabilities, pain assessment is particularly challenging due to the absence of verbal communication or report bias (46,47). Several scales have been developed to assess pain in nonverbal children, such as the Face, Legs, Activity, Cry, Consolability (FLACC) scale, the COMFORT behavior scale, and the Children’s Hospital of Eastern Ontario Pain Scale (CHEOPS) (48,49).

Pain has been recognized as a significant confounding factor in interpreting PAED (30). In fact, the 5-point PAED scale includes items that may indicate pain, such as restlessness and inconsolability, which are also present in pain scales (e.g., the FLACC and CHEOPS), making it difficult to distinguish between the two phenomena (50,51). The relationship between pain and PAED, whether pain is mistaken for PAED or it precipitates PAED, remains unclear. Nevertheless, up to 15% of children may experience both PAED and pain (51), and children exhibiting PAED are more likely to have postoperative pain (52). Poor pain management has also been shown to increase the incidence of PAED (40).

These data underscore the importance of assessing and reporting both pain and PAED in research. In Miyasaka et al.’s (1) work, no postoperative pain assessment was reported, nor were the analgesics administered after surgery. Reporting a comparable level of postoperative pain would have likely excluded pain as a confounding variable in the PAED assessment and strengthened the study’s results. Moreover, the authors stated that the study was limited to procedures amenable to regional anesthesia, but they did not assess the effectiveness of the regional or central blocks (e.g., hemodynamic responses at the surgical incision). Previous investigations have reported that up to 30% of ilioinguinal and 6% of caudal blocks are ineffective (53,54). Given the considerable variation in anesthesia duration (up to 112 minutes longer in the control group), the type and timing of the block provide valuable information, as they may influence postoperative pain and, consequently, the PAED assessment. Reporting intraoperative data (e.g., hemodynamics) would also provide valuable information on the appropriateness of the anesthetic regimen. Signs of nociception (e.g., hypertension and tachycardia) or episodes of hypotension without nociception would have likely prompted the anesthesiologist to adjust the sevoflurane administration in the control group.

Furthermore, intraoperative nociception may increase beta-band activity (55), which might explain the higher processed EEG in the study group compared with the control group (PSI 66 vs. 42, respectively). It is worth noting that a higher percentage of children in the control group required endotracheal intubation (31% vs. 23%). Endotracheal tubes are associated with greater airway stimulation and postoperative discomfort than supraglottic devices (56,57), which may affect the quality of recovery and, in turn, the incidence of PAED (40). Thus, the absence of intraoperative data leads to a cautious interpretation of the results.

Several medications, such as dexmedetomidine, opioids, benzodiazepine, and propofol boluses, are known to reduce PAED (33,58,59). Similarly, preoperative anxiety and the type of surgery are known risk factors for PAED. The authors did not report whether any of these preoperative variables were taken into account, nor whether any medication was administered in the PACU, making it challenging to assess homogeneity between the two groups. It must also be noted that PAED was evaluated from PACU admission, regardless of whether the patient was awake, although the PAED scale was designed to assess PAED after the patient had awakened (50). This bias may have influenced the study results, as a PAED score of 10 can potentially be reached by an asleep child that is moving in the bed (i.e., the child doesn’t make eye contact with the caregiver =4; the child’s actions are not purposeful =2; the child is not aware of his/her surroundings =4). Indeed, the authors found no significant difference when the PAED score was set to 12. A PAED score ≥12 would more likely identifies PAED in “awake” children and was found to have higher sensitivity and specificity (60).

Finally, Miyasaka et al.’s results raised the question of whether we typically expose children to an unnecessarily high dose of Sevoflurane. In the control group, Sevoflurane was maintained at a MAC of 1.0, a target used in several investigations as a marker of adequate depth of anesthesia (61). However, such concentration is likely unnecessary when regional anesthesia is employed. Conversely, the intervention group was kept in the high-beta band (median SEF >20), a range compatible with an awake state (10). The authors reported no episodes of intraoperative awareness, although their study was likely underpowered to detect such events. Nevertheless, these data also underscore that consciousness is not a binary state (2), and the relationship between consciousness and awareness may not be as simple as previously thought.

Despite these significant limitations, we commend Miyasaka et al. (1) for providing important information on the use of EEG to guide precision anesthetic titration in pediatrics. Their work should encourage anesthesiologists to employ encephalographic monitoring rather than rely on fixed anesthetic dosing. As the field continues to move toward individualized anesthetic care, studies that incorporate comprehensive pain-behavior discrimination and robust physiologic controls will be crucial for determining whether EEG guidance truly alters the incidence of PAED or primarily serves as an efficient means to reduce anesthetic exposure and to utilize health care resources more consciously.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Translational Pediatrics. The article has undergone external peer review.

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-1-953/prf

Funding: A.T. holds a Junior 2 Research Scholar Award (2024-2028) from the Fonds de recherche de Québec.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-1-953/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Miyasaka KW, Suzuki Y, Brown EN, et al. EEG-Guided Titration of Sevoflurane and Pediatric Anesthesia Emergence Delirium: A Randomized Clinical Trial. JAMA Pediatr 2025;179:704-12. [Crossref] [PubMed]
2. Laferrière-Langlois P, Morisson L, Jeffries S, et al. Depth of Anesthesia and Nociception Monitoring: Current State and Vision For 2050. Anesth Analg 2024;138:295-307. [Crossref] [PubMed]
3. Kane N, Acharya J, Benickzy S, et al. A revised glossary of terms most commonly used by clinical electroencephalographers and updated proposal for the report format of the EEG findings. Revision 2017. Clin Neurophysiol Pract 2017;2:170-85.
4. Messieha ZS, Ananda RC, Hoffman WE, et al. Bispectral index system (BIS) monitoring reduces time to extubation and discharge in children requiring oral presedation and general anesthesia for outpatient dental rehabilitation. Pediatr Dent 2005;27:500-4.
5. de Oliveira DAC, Dos Santos Monteiro J, de Macêdo NR, et al. Bispectral index-guided anesthesia in children: A systematic review and meta-analysis. Anaesth Crit Care Pain Med 2025;44:101607. [Crossref] [PubMed]
6. Absalom AR, Mani V, De Smet T, et al. Pharmacokinetic models for propofol--defining and illuminating the devil in the detail. Br J Anaesth 2009;103:26-37. [Crossref] [PubMed]
7. Yuan I, Xu T, Kurth CD. Using Electroencephalography (EEG) to Guide Propofol and Sevoflurane Dosing in Pediatric Anesthesia. Anesthesiol Clin 2020;38:709-25. [Crossref] [PubMed]
8. McFarlan CS, Anderson BJ, Short TG. The use of propofol infusions in paediatric anaesthesia: a practical guide. Paediatr Anaesth 1999;9:209-16.
9. Yuan I, Landis WP, Topjian AA, et al. Prevalence of Isoelectric Electroencephalography Events in Infants and Young Children Undergoing General Anesthesia. Anesth Analg 2020;130:462-71. [Crossref] [PubMed]
10. Xu T, Kurth CD, Yuan I, et al. An approach to using pharmacokinetics and electroencephalography for propofol anesthesia for surgery in infants. Paediatr Anaesth 2020;30:1299-307. [Crossref] [PubMed]
11. Messina AG, Wang M, Ward MJ, et al. Anaesthetic interventions for prevention of awareness during surgery. Cochrane Database Syst Rev 2016;10:CD007272. [Crossref] [PubMed]
12. Jarry S, Halley I, Calderone A, et al. Impact of Processed Electroencephalography in Cardiac Surgery: A Retrospective Analysis. J Cardiothorac Vasc Anesth 2022;36:3517-25. [Crossref] [PubMed]
13. Templeton TW, Alex G, Eloy JD, et al. BIS Guided Titration of Sevoflurane in Pediatric Patients Undergoing Elective Surgery: A Randomized Controlled Trial. Paediatr Anaesth 2025;35:277-86. [Crossref] [PubMed]
14. Frederick HJ, Wofford K, de Lisle Dear G, et al. A Randomized Controlled Trial to Determine the Effect of Depth of Anesthesia on Emergence Agitation in Children. Anesth Analg 2016;122:1141-6. [Crossref] [PubMed]
15. Long MHY, Lim EHL, Balanza GA, et al. Sevoflurane requirements during electroencephalogram (EEG)-guided vs standard anesthesia Care in Children: A randomized controlled trial. J Clin Anesth 2022;81:110913. [Crossref] [PubMed]
16. Han Y, Miao M, Li P, et al. EEG-Parameter-Guided Anesthesia for Prevention of Emergence Delirium in Children. Brain Sci 2022;12:1195. [Crossref] [PubMed]
17. Weiss M, Vutskits L, Hansen TG, et al. Safe Anesthesia For Every Tot - The SAFETOTS initiative. Curr Opin Anaesthesiol 2015;28:302-7. [Crossref] [PubMed]
18. Sury MR. Accidental awareness during anesthesia in children. Paediatr Anaesth 2016;26:468-74. [Crossref] [PubMed]
19. Sebel PS, Bowdle TA, Ghoneim MM, et al. The incidence of awareness during anesthesia: a multicenter United States study. Anesth Analg 2004;99:833-9. [Crossref] [PubMed]
20. Lopez U, Habre W, Van der Linden M, et al. Intra-operative awareness in children and post-traumatic stress disorder. Anaesthesia 2008;63:474-81. [Crossref] [PubMed]
21. Lewis SR, Pritchard MW, Fawcett LJ, et al. Bispectral index for improving intraoperative awareness and early postoperative recovery in adults. Cochrane Database Syst Rev 2019;9:CD003843. [Crossref] [PubMed]
22. Monk TG. Processed EEG and patient outcome. Best Pract Res Clin Anaesthesiol 2006;20:221-8. [Crossref] [PubMed]
23. Sury M. Brain monitoring in children. Anesthesiol Clin 2014;32:115-32. [Crossref] [PubMed]
24. Cornelissen L, Kim SE, Lee JM, et al. Electroencephalographic markers of brain development during sevoflurane anaesthesia in children up to 3 years old. Br J Anaesth 2018;120:1274-86. [Crossref] [PubMed]
25. Cornelissen L, Kim SE, Purdon PL, et al. Age-dependent electroencephalogram (EEG) patterns during sevoflurane general anesthesia in infants. Elife 2015;4:e06513. [Crossref] [PubMed]
26. Sullivan CA, Egbuta C, Park RS, et al. The Use of Bispectral Index Monitoring Does Not Change Intraoperative Exposure to Volatile Anesthetics in Children. J Clin Med 2020;9:2437. [Crossref] [PubMed]
27. Faulk DJ, Twite MD, Zuk J, et al. Hypnotic depth and the incidence of emergence agitation and negative postoperative behavioral changes. Paediatr Anaesth 2010;20:72-81. [Crossref] [PubMed]
28. Purdon PL, Sampson A, Pavone KJ, et al. Clinical Electroencephalography for Anesthesiologists: Part I: Background and Basic Signatures. Anesthesiology 2015;123:937-60. [Crossref] [PubMed]
29. Fritz BA, Kalarickal PL, Maybrier HR, et al. Intraoperative Electroencephalogram Suppression Predicts Postoperative Delirium. Anesth Analg 2016;122:234-42. [Crossref] [PubMed]
30. Mason KP. Paediatric emergence delirium: a comprehensive review and interpretation of the literature. Br J Anaesth 2017;118:335-43. [Crossref] [PubMed]
31. Gjini K, Casey C, Kunkel D, et al. Delirium is associated with loss of feedback cortical connectivity. Alzheimers Dement 2024;20:511-24. [Crossref] [PubMed]
32. Martin JC, Liley DT, Harvey AS, et al. Alterations in the functional connectivity of frontal lobe networks preceding emergence delirium in children. Anesthesiology 2014;121:740-52. [Crossref] [PubMed]
33. Aoyama K, Furuta M, Ameye L, et al. Risk factors for pediatric emergence delirium: a systematic review. Can J Anaesth 2025;72:384-96. [Crossref] [PubMed]
34. Aamri IA, Bertolizio G. The importance of maintaining normal perioperative physiological parameters in children during anaesthesia. Signa Vitae 2021;17:42-8.
35. Moyo P, Francis K, Kornhaber R, et al. Peri-Operative Nurses' Experiences of Recognizing and Responding to Post-Anesthetic Pediatric Emergence Delirium: A Narrative Review. SAGE Open Nurs 2025;11:23779608251389303. [Crossref] [PubMed]
36. Kim J, Byun SH, Kim JW, et al. Behavioral changes after hospital discharge in preschool children experiencing emergence delirium after general anesthesia: A prospective observational study. Paediatr Anaesth 2021;31:1056-64. [Crossref] [PubMed]
37. Koch S, Rupp L, Prager C, et al. Emergence delirium in children is related to epileptiform discharges during anaesthesia induction: An observational study. Eur J Anaesthesiol 2018;35:929-36. [Crossref] [PubMed]
38. Kreuzer I, Osthaus WA, Schultz A, et al. Influence of the sevoflurane concentration on the occurrence of epileptiform EEG patterns. PLoS One 2014;9:e89191. [Crossref] [PubMed]
39. Choi EK, Park S, Park KB, et al. Postoperative emergence agitation and intraoperative sevoflurane sedation under caudal block in children: a randomized comparison of two sevoflurane doses. Anesth Pain Med (Seoul) 2019;14:434-40. [Crossref] [PubMed]
40. Davies L, Qi TS, Ng A. Emergence delirium: an overview with an emphasis on the use of electroencephalography in its management. Anesth Pain Med (Seoul) 2024;19:S87-95. [Crossref] [PubMed]
41. Jevtovic-Todorovic V. Exposure of Developing Brain to General Anesthesia: What Is the Animal Evidence? Anesthesiology 2018;128:832-9. [Crossref] [PubMed]
42. Colletti G, Di Bartolomeo M, Negrello S, et al. Multiple General Anesthesia in Children: A Systematic Review of Its Effect on Neurodevelopment. J Pers Med 2023;13:867. [Crossref] [PubMed]
43. Scholes MA, Jensen EL, Polaner DM, et al. Multiple surgeries in pediatric otolaryngology patients and associated anesthesia risks. Int J Pediatr Otorhinolaryngol 2018;113:115-8. [Crossref] [PubMed]
44. Vutskits L, Culley DJ. GAS, PANDA, and MASK: No Evidence of Clinical Anesthetic Neurotoxicity! Anesthesiology 2019;131:762-4. [Crossref] [PubMed]
45. Boselli E, Bouvet L, Bégou G, et al. Prediction of immediate postoperative pain using the analgesia/nociception index: a prospective observational study. Br J Anaesth 2014;112:715-21. [Crossref] [PubMed]
46. Fanurik D, Koh JL, Harrison RD, et al. Pain assessment in children with cognitive impairment. An exploration of self-report skills. Clin Nurs Res 1998;7:103-19; discussion 120-4.
47. Stanford EA, Chambers CT, Craig KD. The role of developmental factors in predicting young children's use of a self-report scale for pain. Pain 2006;120:16-23. [Crossref] [PubMed]
48. Blount RL, Loiselle KA. Behavioural assessment of pediatric pain. Pain Res Manag 2009;14:47-52. [Crossref] [PubMed]
49. Andersen RD, Langius-Eklöf A, Nakstad B, et al. The measurement properties of pediatric observational pain scales: A systematic review of reviews. Int J Nurs Stud 2017;73:93-101. [Crossref] [PubMed]
50. Sikich N, Lerman J. Development and psychometric evaluation of the pediatric anesthesia emergence delirium scale. Anesthesiology 2004;100:1138-45. [Crossref] [PubMed]
51. Somaini M, Engelhardt T, Ingelmo P. Emergence from General Anaesthesia: Can We Discriminate between Emergence Delirium and Postoperative Pain? J Pers Med 2023;13:435. [Crossref] [PubMed]
52. Abdallah BM, Elshoeibi AM, ElTantawi N, et al. Comparison of postoperative pain in children after maintenance anaesthesia with propofol or sevoflurane: a systematic review and meta-analysis. Br J Anaesth 2024;133:93-102. [Crossref] [PubMed]
53. Seyedhejazi M, Daemi OR, Taheri R, et al. Success rate of two different methods of ilioinguinal-iliohypogastric nerve block in children inguinal surgery. Afr J Paediatr Surg 2013;10:255-8. [Crossref] [PubMed]
54. Dalens B, Hasnaoui A. Caudal anesthesia in pediatric surgery: success rate and adverse effects in 750 consecutive patients. Anesth Analg 1989;68:83-9.
55. García PS, Kreuzer M, Hight D, et al. Effects of noxious stimulation on the electroencephalogram during general anaesthesia: a narrative review and approach to analgesic titration. Br J Anaesth 2021;126:445-57. [Crossref] [PubMed]
56. Park EJ, Hwang BY, Kwon JY, et al. Effect of Airway Devices on Emergence Delirium in Pediatric Strabismus Surgery. Med Sci Monit 2025;31:e948351. [Crossref] [PubMed]
57. Chen Y, Li Q, Pan S, et al. Impact of laryngeal mask airway versus endotracheal intubation on emergence delirium in children undergoing same-day endoscopic-assisted coblation adenoidectomy: a randomized, single-center clinical trial. Minerva Anestesiol 2025;91:1154-62. [Crossref] [PubMed]
58. Liang ZJ, Liang JM, Nong XL, et al. Effect of intravenous different drugs on the prevention of restlessness during recovery period of pediatric laparoscopic surgery: a randomized control trial. J Anesth 2025;39:15-22. [Crossref] [PubMed]
59. Klabusayová E, Musilová T, Fabián D, et al. Incidence of Emergence Delirium in the Pediatric PACU: Prospective Observational Trial. Children (Basel) 2022;9:1591. [Crossref] [PubMed]
60. Bajwa SA, Costi D, Cyna AM. A comparison of emergence delirium scales following general anesthesia in children. Paediatr Anaesth 2010;20:704-11. [Crossref] [PubMed]
61. Lerman J, Sikich N, Kleinman S, et al. The pharmacology of sevoflurane in infants and children. Anesthesiology 1994;80:814-24. [Crossref] [PubMed]