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EEG monitoring duration to identify electroencephalographic seizures in critically ill children
France W Fung1, Jiaxin Fan2, Lisa Vala2
1From the Department of Anesthesia and Critical Care Medicine (D.S.P., A.A.T.), Department of Pediatrics, Division of Neurology (F.W.F., M.J., D.S.P., N.S.A.), and Department of Neurodiagnostics (L.V., M.D., N.S.A.), Children's Hospital of Philadelphia; and Departments of Neurology (N.S.A., F.W.F.), Pediatrics (N.S.A., F.W.F.), Anesthesia and Critical Care (A.A.T., N.S.A.), and Biostatistics, Epidemiology and Informatics (J.F., R.X., N.S.A.), University of Pennsylvania Perelman School of Medicine, Philadelphia. fungf@email.chop.edu.
Insights
Optimal continuous EEG monitoring (CEEG) duration for electrographic seizure (ES) detection in critically ill children varies by age and risk factors. Personalized CEEG strategies can optimize resource use and improve neuroprotection.
Area of Science:
- Pediatric Neurology
- Critical Care Medicine
- Neurophysiology
Background:
- Continuous EEG monitoring (CEEG) is crucial for identifying electrographic seizures (ES) in critically ill children with encephalopathy.
- Determining the optimal duration of CEEG is essential for efficient resource allocation and timely neuroprotective interventions.
Purpose of the Study:
- To establish the optimal duration of CEEG for electrographic seizure (ES) identification in critically ill pediatric patients.
- To develop a risk-stratified approach for CEEG monitoring duration based on patient-specific factors.
Main Methods:
- Prospective observational cohort study of 719 critically ill children with encephalopathy.
- Multistate survival model analyzing baseline (age, prior seizures) and emergent CEEG risk factors (epileptiform discharges, ictal-interictal continuum).
- Determination of CEEG durations associated with <5% and <2% risk of ES for different subgroups.
Main Results:
- Electrographic seizures (ES) occurred in 26% of patients (184/719).
- Optimal CEEG durations to achieve <5% ES risk ranged from 6 hours to 2.5 days, varying by age and presence of prior seizures or EEG risk factors.
- Similar trends observed for achieving <2% ES risk, with some subgroups requiring longer monitoring.
Conclusions:
- A predictive model incorporating clinical and EEG risk factors can personalize CEEG duration.
- Tailored CEEG strategies can optimize the use of limited monitoring resources.
- Widespread implementation of CEEG-guided management may enhance neuroprotection in critically ill children.
Objectives:
To determine the optimal duration of continuous EEG monitoring (CEEG) for electrographic seizure (ES) identification in critically ill children.
Methods:
We performed a prospective observational cohort study of 719 consecutive critically ill children with encephalopathy. We evaluated baseline clinical risk factors (age and prior clinically evident seizures) and emergent CEEG risk factors (epileptiform discharges and ictal-interictal continuum patterns) using a multistate survival model. For each subgroup, we determined the CEEG duration for which the risk of ES was <5% and <2%.
Results:
ES occurred in 184 children (26%). Patients achieved <5% risk of ES after (1) 6 hours if ≥1 year without prior seizures or EEG risk factors; (2) 1 day if <1 year without prior seizures or EEG risks; (3) 1 day if ≥1 year with either prior seizures or EEG risks; (4) 2 days if ≥1 year with prior seizures and EEG risks; (5) 2 days if <1 year without prior seizures but with EEG risks; and (6) 2.5 days if <1 year with prior seizures regardless of the presence of EEG risks. Patients achieved <2% risk of ES at the same durations except patients without prior seizures or EEG risk factors would require longer CEEG (1.5 days if <1 year of age, 1 day if ≥1 year of age).
Conclusions:
A model derived from 2 baseline clinical risk factors and emergent EEG risk factors would allow clinicians to implement personalized strategies that optimally target limited CEEG resources. This would enable more widespread use of CEEG-guided management as a potential neuroprotective strategy.
Clinicaltrialsgov Identifier:
NCT03419260.
