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Continuous Video Electroencephalography (EEG) for Event Characterization in Critically Ill Children
Melissa L DiBacco1,2, Kelly Cavan1,2, Arnold J Sansevere1,2,3
1Division of Epilepsy and Neurophysiology, 1862Boston Children's Hospital, Boston, MA, USA.
Insights
In critically ill children, autonomic events alone are unlikely to indicate electroclinical seizures. Analyzing paroxysmal event details helps determine which patients benefit most from continuous video electroencephalography (EEG) monitoring.
Area of Science:
- Critical care medicine
- Pediatric neurology
- Clinical neurophysiology
Background:
- Continuous video electroencephalography (EEG) is crucial for diagnosing seizures in critically ill children.
- Characterizing paroxysmal events is essential for accurate diagnosis and management.
Purpose of the Study:
- To identify features of paroxysmal events and EEG abnormalities associated with electroclinical seizures in critically ill children.
- To characterize clinical events using continuous video EEG.
Main Methods:
- A prospective study included 100 critically ill children (non-neonates) undergoing continuous video EEG.
- Paroxysmal events were documented and classified (motor, ocular, orobuccal, autonomic, other).
- Events with multiple components were classified as motor-plus or nonmotor-plus.
Main Results:
- Electroclinical seizures were captured in 30% of patients.
- Autonomic events were the most common (32%), but isolated autonomic events were not associated with electroclinical seizures (OR 0.3).
- Asymmetry (OR 2.7) and epileptiform discharges (OR 12.5) were significantly associated with electroclinical seizures.
Conclusions:
- Isolated autonomic events in critically ill children are unlikely to represent electroclinical seizures.
- Detailed characterization of paroxysmal events aids in selecting patients who will benefit from continuous video EEG, optimizing resource allocation.
Objective:
To determine features of paroxysmal events and background electroencephalographic (EEG) abnormalities associated with electroclinical seizures in critically ill children who undergo continuous video EEG to characterize clinical events.
Methods:
This is a prospective study of critically ill children from July 2016 to October 2018. Non-neonates with continuous video EEG indication to characterize a clinical event were included. Patients with continuous video EEG to assess for subclinical seizures due to unexplained encephalopathy and those whose event of concern were not captured on continuous video EEG were excluded. The event to be characterized was taken from documented descriptions of health care providers and classified as motor, ocular, orobuccal, autonomic, and other. In patients with more than 1 component to their paroxysmal event, the events were classified as motor plus and nonmotor plus.
Results:
One hundred patients met inclusion and exclusion criteria, with electroclinical seizures captured in 30% (30/100). The most common event to be characterized was an autonomic event in 32% (32/100). Asymmetry and epileptiform discharges were associated with electroclinical seizures (odds ratio [OR] 2.7, 95% confidence interval [CI] 1.1-6.5, P = .03; and OR 12.5, 95% CI 4.4-35.6, P < .0001). Autonomic events alone, particularly unexplained vital sign changes, were not associated with electroclinical seizures (OR 0.3, 95% CI 0.11-0.93, P = .03).
Conclusions:
Isolated autonomic events are unlikely to be electroclinical seizures. Details of the paroxysmal events in question can help decide which patient will benefit most from continuous video EEG based on institutional resources.
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