France W Fung1, Jiaxin Fan2, Lisa Vala2, Marin Jacobwitz2, Darshana S Parikh2, Maureen Donnelly2, Alexis A Topjian2, Rui Xiao2, Nicholas S Abend2. 1. From 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. 2. From 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.
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.
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.
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