Utility of Neonatal Pain, Agitation and Sedation Scale and Amplitude Integrated Electroencephalogram to Differentiate the Different Levels of Sedation in Neonatal Intensive Care Units

Ibrahim, Mariam; El Raggal, Nehal; Dawoud, Mohamed; Mohamed, Bassem; Mohammed, Maha

doi:10.21608/ejhm.2022.271909

Utility of Neonatal Pain, Agitation and Sedation Scale and Amplitude Integrated Electroencephalogram to Differentiate the Different Levels of Sedation in Neonatal Intensive Care Units

Document Type : Original Article

Authors

pediatrics department ain shams university

10.21608/ejhm.2022.271909

Abstract

Background: Neonates admitted in any Neonatal Intensive Care Unit (NICU) are constantly subjected to several stressful and painful conditions and require pain and sedation management. Ineffective sedation has severe consequences. Excessive sedation can prolong the duration of mechanical ventilation. On the other hand, inadequate sedation may lead to asynchronization with the ventilator and inability of adequate ventilation. The objective of the current study is to evaluate the use of Neonatal Pain, Agitation and Sedation Scale (N-PASS) parameters and double channel amplitude integrated electroencephalography (aEEG) to differentiate between light and deep sedation in neonatal patients.
Patients and methods: A total of 30 full term neonates mechanically ventilated with congenital pneumonia were recruited for the current study. Neonates of the study were divided into 2 groups according to the dose of sedative received into Lightly sedated group and Deeply sedated. All studied neonates were subjected toN-PASS and aEEG monitoring before starting sedation and after 2 hours of sedation. Results: Parameters of Burdjalov score (Continuity, Cycling, bandwidth span) and its total score showed a statistically significant decrease after sedation with median in the in non-sedated patients than deeply sedated patients (12 (11 - 12) vs. 8 (8 - 9), respectively (p < 0.001).There was also a difference which was statistically significant between deeply sedated patients than lightly sedated patients [8 (7 - 8) vs. 9 (9 - 9), respectively (p < 0.00)]. When applying ROC analysis, aEEG total (Burdjalov) score at a cut-off value of ≤8 was predictive of deep sedation with 100% sensitivity and specificity. Conclusion: aEEG can be used to differentiate between states of awake and sedation, and can also be used to differentiate the different sedation levels.

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