EEG monitoring duration to identify electroencephalographic seizures in critically ill children

France W Fung, Jiaxin Fan, Lisa Vala, Marin Jacobwitz, Darshana S Parikh, Maureen Donnelly, Alexis A Topjian, Rui Xiao, Nicholas S Abend, France W Fung, Jiaxin Fan, Lisa Vala, Marin Jacobwitz, Darshana S Parikh, Maureen Donnelly, Alexis A Topjian, Rui Xiao, Nicholas S Abend

Abstract

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.

© 2020 American Academy of Neurology.

Figures

Figure 1. Summary of the model states…
Figure 1. Summary of the model states (entry state, EEG risk state, and ES state) and transitions
Each participant could remain in the entry state, transition from the entry state to the electrographic seizures (ES) state, or transition from the entry state to the EEG risk state. Subjects in the EEG risk state could remain in the EEG risk state or transition to the ES state.
Figure 2. Swimmer plots and multistate survival…
Figure 2. Swimmer plots and multistate survival analysis results for the full cohort and each clinical risk state
Top row: swimmer plot showing the duration of continuous EEG monitoring (line length along x-axis) and state (entry = green; EEG risk = yellow; electrographic seizures [ES] = red) for each participant (y-axis). Middle row: proportion of participants in each state (entry, ES risk, ES) over time. Some participants remain in the same state over time (same color); some participants develop EEG risk factors but never experience ES (green to yellow transition); some participants experience ES without having experienced EEG risk factors (green to red transition); and some participants experience EEG risk factors and then ES (green to yellow to red transitions). Bottom row: remaining risk of transitioning to the ES state for patients in the entry (green) and EEG risk (yellow) states. Shaded areas represent the 95% confidence intervals. For the full cohort and each of the 4 clinical risk states, the risk of transitioning to the ES state remains higher over time for participants with EEG risk factors than those in the entry state.

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Source: PubMed

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