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Fung FW, Parikh DS, Donnelly M, Jacobwitz M, Topjian AA, Xiao R, Abend NS. EEG Monitoring in Critically Ill Children: Establishing High-Yield Subgroups. J Clin Neurophysiol 2024; 41:305-311. [PMID: 36893385 PMCID: PMC10492893 DOI: 10.1097/wnp.0000000000000995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023] Open
Abstract
PURPOSE Continuous EEG monitoring (CEEG) is increasingly used to identify electrographic seizures (ES) in critically ill children, but it is resource intense. We aimed to assess how patient stratification by known ES risk factors would impact CEEG utilization. METHODS This was a prospective observational study of critically ill children with encephalopathy who underwent CEEG. We calculated the average CEEG duration required to identify a patient with ES for the full cohort and subgroups stratified by known ES risk factors. RESULTS ES occurred in 345 of 1,399 patients (25%). For the full cohort, an average of 90 hours of CEEG would be required to identify 90% of patients with ES. If subgroups of patients were stratified by age, clinically evident seizures before CEEG initiation, and early EEG risk factors, then 20 to 1,046 hours of CEEG would be required to identify a patient with ES. Patients with clinically evident seizures before CEEG initiation and EEG risk factors present in the initial hour of CEEG required only 20 (<1 year) or 22 (≥1 year) hours of CEEG to identify a patient with ES. Conversely, patients with no clinically evident seizures before CEEG initiation and no EEG risk factors in the initial hour of CEEG required 405 (<1 year) or 1,046 (≥1 year) hours of CEEG to identify a patient with ES. Patients with clinically evident seizures before CEEG initiation or EEG risk factors in the initial hour of CEEG required 29 to 120 hours of CEEG to identify a patient with ES. CONCLUSIONS Stratifying patients by clinical and EEG risk factors could identify high- and low-yield subgroups for CEEG by considering ES incidence, the duration of CEEG required to identify ES, and subgroup size. This approach may be critical for optimizing CEEG resource allocation.
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Affiliation(s)
- France W Fung
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, U.S.A
- Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, U.S.A
| | - Darshana S Parikh
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, U.S.A
| | - Maureen Donnelly
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, U.S.A
| | - Marin Jacobwitz
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, U.S.A
| | - Alexis A Topjian
- Department of Anesthesia and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphi||a, Pennsylvania, U.S.A
- Department of Anesthesia and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, U.S.A.; and
| | - Rui Xiao
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, U.S.A
| | - Nicholas S Abend
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, U.S.A
- Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, U.S.A
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, U.S.A
- Department of Anesthesia and Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, U.S.A.; and
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, U.S.A
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Fung FW, Parikh DS, Walsh K, Fitzgerald MP, Massey SL, Topjian AA, Abend NS. Late-Onset Findings During Extended EEG Monitoring Are Rare in Critically Ill Children. J Clin Neurophysiol 2024:00004691-990000000-00131. [PMID: 38687298 DOI: 10.1097/wnp.0000000000001083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2024] Open
Abstract
PURPOSE Electrographic seizures (ES) are common in critically ill children undergoing continuous EEG (CEEG) monitoring, and previous studies have aimed to target limited CEEG resources to children at highest risk of ES. However, previous studies have relied on observational data in which the duration of CEEG was clinically determined. Thus, the incidence of late occurring ES is unknown. The authors aimed to assess the incidence of ES for 24 hours after discontinuation of clinically indicated CEEG. METHODS This was a single-center prospective study of nonconsecutive children with acute encephalopathy in the pediatric intensive care unit who underwent 24 hours of extended research EEG after the end of clinical CEEG. The authors assessed whether there were new findings that affected clinical management during the extended research EEG, including new-onset ES. RESULTS Sixty-three subjects underwent extended research EEG. The median duration of the extended research EEG was 24.3 hours (interquartile range 24.0-25.3). Three subjects (5%) had an EEG change during the extended research EEG that resulted in a change in clinical management, including an increase in ES frequency, differential diagnosis of an event, and new interictal epileptiform discharges. No subjects had new-onset ES during the extended research EEG. CONCLUSIONS No subjects experienced new-onset ES during the 24-hour extended research EEG period. This finding supports observational data that patients with late-onset ES are rare and suggests that ES prediction models derived from observational data are likely not substantially underrepresenting the incidence of late-onset ES after discontinuation of clinically indicated CEEG.
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Affiliation(s)
- France W Fung
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, PA
- Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Darshana S Parikh
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, PA
| | - Kathleen Walsh
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, PA
| | - Mark P Fitzgerald
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, PA
- Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Shavonne L Massey
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, PA
- Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Alexis A Topjian
- Department of Anesthesia and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, PA; and
- Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Nicholas S Abend
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, PA
- Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
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Coleman K, Fung FW, Topjian A, Abend NS, Xiao R. Optimizing EEG monitoring in critically ill children at risk for electroencephalographic seizures. Seizure 2024; 117:244-252. [PMID: 38522169 DOI: 10.1016/j.seizure.2024.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 03/06/2024] [Accepted: 03/19/2024] [Indexed: 03/26/2024] Open
Abstract
OBJECTIVE Strategies are needed to optimally deploy continuous EEG monitoring (CEEG) for electroencephalographic seizure (ES) identification and management due to resource limitations. We aimed to construct an efficient multi-stage prediction model guiding CEEG utilization to identify ES in critically ill children using clinical and EEG covariates. METHODS The largest prospective single-center cohort of 1399 consecutive children undergoing CEEG was analyzed. A four-stage model was developed and trained to predict whether a subject required additional CEEG at the conclusion of each stage given their risk of ES. Logistic regression, elastic net, random forest, and CatBoost served as candidate methods for each stage and were evaluated using cross validation. An optimal multi-stage model consisting of the top-performing stage-specific models was constructed. RESULTS When evaluated on a test set, the optimal multi-stage model achieved a cumulative specificity of 0.197 and cumulative F1 score of 0.326 while maintaining a high minimum cumulative sensitivity of 0.938. Overall, 11 % of test subjects with ES were removed from the model due to a predicted low risk of ES (falsely negative subjects). CEEG utilization would be reduced by 32 % and 47 % compared to performing 24 and 48 h of CEEG in all test subjects, respectively. We developed a web application called EEGLE (EEG Length Estimator) that enables straightforward implementation of the model. CONCLUSIONS Application of the optimal multi-stage ES prediction model could either reduce CEEG utilization for patients at lower risk of ES or promote CEEG resource reallocation to patients at higher risk for ES.
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Affiliation(s)
- Kyle Coleman
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, United States
| | - France W Fung
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, United States; Department of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, United States
| | - Alexis Topjian
- Department of Anesthesia and Critical Care, University of Pennsylvania Perelman School of Medicine, United States
| | - Nicholas S Abend
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, United States; Department of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, United States; Department of Anesthesia and Critical Care, University of Pennsylvania Perelman School of Medicine, United States; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, United States
| | - Rui Xiao
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, United States; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, United States.
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Fung FW, Fan J, Parikh DS, Vala L, Donnelly M, Jacobwitz M, Topjian AA, Xiao R, Abend NS. Validation of a Model for Targeted EEG Monitoring Duration in Critically Ill Children. J Clin Neurophysiol 2023; 40:589-599. [PMID: 35512186 PMCID: PMC9582115 DOI: 10.1097/wnp.0000000000000940] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
PURPOSE Continuous EEG monitoring (CEEG) to identify electrographic seizures (ES) in critically ill children is resource intense. Targeted strategies could enhance implementation feasibility. We aimed to validate previously published findings regarding the optimal CEEG duration to identify ES in critically ill children. METHODS This was a prospective observational study of 1,399 consecutive critically ill children with encephalopathy. We validated the findings of a multistate survival model generated in a published cohort ( N = 719) in a new validation cohort ( N = 680). The model aimed to determine the CEEG duration at which there was <15%, <10%, <5%, or <2% risk of experiencing ES if CEEG were continued longer. The model included baseline clinical risk factors and emergent EEG risk factors. RESULTS A model aiming to determine the CEEG duration at which a patient had <10% risk of ES if CEEG were continued longer showed similar performance in the generation and validation cohorts. Patients without emergent EEG risk factors would undergo 7 hours of CEEG in both cohorts, whereas patients with emergent EEG risk factors would undergo 44 and 36 hours of CEEG in the generation and validation cohorts, respectively. The <10% risk of ES model would yield a 28% or 64% reduction in CEEG hours compared with guidelines recommending CEEG for 24 or 48 hours, respectively. CONCLUSIONS This model enables implementation of a data-driven strategy that targets CEEG duration based on readily available clinical and EEG variables. This approach could identify most critically ill children experiencing ES while optimizing CEEG use.
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Affiliation(s)
- France W Fung
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
- Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Jiaxin Fan
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Darshana S Parikh
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Lisa Vala
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Maureen Donnelly
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Marin Jacobwitz
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Alexis A Topjian
- Department of Anesthesia and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; and
- Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Rui Xiao
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Nicholas S Abend
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
- Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
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deCampo D, Husari KS, Bembea MM, Habela CW, Ritzl EK. Continuous Electroencephalography (EEG) Protocol Improves Seizure Detection in Children on Extracorporeal Membrane Oxygenation. J Child Neurol 2023; 38:581-589. [PMID: 37624689 PMCID: PMC11060699 DOI: 10.1177/08830738231190145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/27/2023]
Abstract
BACKGROUND / OBJECTIVE Seizures are a complication for pediatric patients requiring extracorporeal membrane oxygenation (ECMO). There are no standardized guidelines regarding continuous electroencephalography (EEG) monitoring to detect seizures in these patients, and the impact of protocolized monitoring has not been evaluated. Here we examined the effects of continuous EEG protocol implementation in our pediatric ECMO population. METHODS Retrospective chart reviews were conducted on 57 patients who underwent extracorporeal membrane oxygenation and concurrent continuous EEG out of 165 patients supported on extracorporeal membrane oxygenation. Timing of continuous EEG initiation and seizures detected by continuous EEG was determined for 5 years prior to and 15 months after protocol implementation. RESULTS Protocol implementation was associated with increased ECMO-supported patients who were concurrently monitored by continuous EEG. Time from ECMO cannulation to continuous EEG initiation was shorter (median 7 hours after versus 16.2 hours before; P < .001). Patients who had ongoing seizures at the start of continuous EEG recording decreased from 64% preprotocol to 0% postprotocol (P < .001), and there was an associated earlier time to break in status epilepticus postprotocol. Seizures were detected past 48 hours after cannulation in 50% of patients in the postprotocol group. CONCLUSIONS Protocol implementation resulted in earlier continuous EEG initiation and more EEGs initiated before seizure onset with evidence of altered seizure dynamics. Although current recommendations suggest that continuous EEG duration of 24-48 hours results in seizure detection for >90% of critically ill adults, longer monitoring may be needed to reliably detect seizures in children supported with ECMO, particularly if monitoring is initiated earlier in the post-cannulation period.
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Affiliation(s)
- Danielle deCampo
- Departments of Neurology, Johns Hopkins Hospital, Baltimore, MD
- Department of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA
| | | | - Melania M. Bembea
- Department of Anesthesiology and Critical Care, Johns Hopkins Hospital, Baltimore, MD
| | | | - Eva K. Ritzl
- Departments of Neurology, Johns Hopkins Hospital, Baltimore, MD
- Department of Anesthesiology and Critical Care, Johns Hopkins Hospital, Baltimore, MD
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A Commentary on Electrographic Seizure Management and Clinical Outcomes in Critically Ill Children. CHILDREN (BASEL, SWITZERLAND) 2023; 10:children10020258. [PMID: 36832387 PMCID: PMC9954965 DOI: 10.3390/children10020258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 01/17/2023] [Accepted: 01/29/2023] [Indexed: 02/03/2023]
Abstract
Continuous EEG (cEEG) monitoring is the gold standard for detecting electrographic seizures in critically ill children and the current consensus-based guidelines recommend urgent cEEG to detect electrographic seizures that would otherwise be undetected. The detection of seizures usually leads to the use of antiseizure medications, even though current evidence that treatment leads to important improvements in outcomes is limited, raising the question of whether the current strategies need re-evaluation. There is emerging evidence indicating that the presence of electrographic seizures is not associated with unfavorable neurological outcome, and thus treatment is unlikely to alter the outcomes in these children. However, a high seizure burden and electrographic status epilepticus is associated with unfavorable outcome and the treatment of status epilepticus is currently warranted. Ultimately, outcomes are more likely a function of etiology than of a direct effect of the seizures themselves. We suggest re-examining our current consensus toward aggressive treatment to abolish all electrographic seizures and recommend a tailored approach where therapeutic interventions are indicated when seizure burden breaches above a critical threshold that may be associated with adverse outcomes. Future studies should explicitly evaluate whether there is a positive impact of treating electrographic seizures or electrographic status epilepticus in order to justify continuing current approaches.
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Joshi C. Electroencephalographic Seizure or Electroencephalographic Status Epilepticus in the ICU? Is it Time to Focus Just on Electroencephalographic Status Epilepticus? Epilepsy Curr 2021; 21:421-423. [PMID: 34924847 PMCID: PMC8652328 DOI: 10.1177/15357597211040941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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Fung FW, Parikh DS, Massey SL, Fitzgerald MP, Vala L, Donnelly M, Jacobwitz M, Kessler SK, Topjian AA, Abend NS. Periodic and rhythmic patterns in critically ill children: Incidence, interrater agreement, and seizures. Epilepsia 2021; 62:2955-2967. [PMID: 34642942 DOI: 10.1111/epi.17068] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 08/27/2021] [Accepted: 09/01/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVES We aimed to determine the incidence of periodic and rhythmic patterns (PRP), assess the interrater agreement between electroencephalographers scoring PRP using standardized terminology, and analyze associations between PRP and electrographic seizures (ES) in critically ill children. METHODS This was a prospective observational study of consecutive critically ill children undergoing continuous electroencephalographic monitoring (CEEG). PRP were identified by one electroencephalographer, and then two pediatric electroencephalographers independently scored the first 1-h epoch that contained PRP using standardized terminology. We determined the incidence of PRPs, evaluated interrater agreement between electroencephalographers scoring PRP, and evaluated associations between PRP and ES. RESULTS One thousand three hundred ninety-nine patients underwent CEEG. ES occurred in 345 (25%) subjects. PRP, ES + PRP, and ictal-interictal continuum (IIC) patterns occurred in 142 (10%), 81 (6%), and 93 (7%) subjects, respectively. The most common PRP were generalized periodic discharges (GPD; 43, 30%), lateralized periodic discharges (LPD; 34, 24%), generalized rhythmic delta activity (GRDA; 34, 24%), bilateral independent periodic discharges (BIPD; 14, 10%), and lateralized rhythmic delta activity (LRDA; 11, 8%). ES risk varied by PRP type (p < .01). ES occurrence was associated with GPD (odds ratio [OR] = 6.35, p < .01), LPD (OR = 10.45, p < .01), BIPD (OR = 6.77, p < .01), and LRDA (OR = 6.58, p < .01). Some modifying features increased the risk of ES for each of those PRP. GRDA was not significantly associated with ES (OR = 1.34, p = .44). Each of the IIC patterns was associated with ES (OR = 6.83-8.81, p < .01). ES and PRP occurred within 6 h (before or after) in 45 (56%) subjects. SIGNIFICANCE PRP occurred in 10% of critically ill children who underwent CEEG. The most common patterns were GPD, LPD, GRDA, BIPD, and LRDA. The GPD, LPD, BIPD, LRDA, and IIC patterns were associated with ES. GRDA was not associated with ES.
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Affiliation(s)
- France W Fung
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Darshana S Parikh
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Shavonne L Massey
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Mark P Fitzgerald
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Lisa Vala
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Maureen Donnelly
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Marin Jacobwitz
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Sudha K Kessler
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Alexis A Topjian
- Department of Anesthesia and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Nicholas S Abend
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.,Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.,Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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Fung FW, Wang Z, Parikh DS, Jacobwitz M, Vala L, Donnelly M, Topjian AA, Xiao R, Abend NS. Electrographic Seizures and Outcome in Critically Ill Children. Neurology 2021; 96:e2749-e2760. [PMID: 33893203 PMCID: PMC8205469 DOI: 10.1212/wnl.0000000000012032] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Accepted: 03/04/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To determine the association between electroencephalographic seizure (ES) and electroencephalographic status epilepticus (ESE) exposure and unfavorable neurobehavioral outcomes in critically ill children with acute encephalopathy. METHODS This was a prospective cohort study of acutely encephalopathic critically ill children undergoing continuous EEG monitoring (CEEG). ES exposure was assessed as (1) no ES/ESE, (2) ES, or (3) ESE. Outcomes assessed at discharge included the Glasgow Outcome Scale-Extended Pediatric Version (GOS-E-Peds), Pediatric Cerebral Performance Category (PCPC), and mortality. Unfavorable outcome was defined as a reduction in GOS-E-Peds or PCPC score from preadmission to discharge. Stepwise selection was used to generate multivariate logistic regression models that assessed associations between ES exposure and outcomes while adjusting for multiple other variables. RESULTS Among 719 consecutive critically ill patients, there was no evidence of ES in 535 patients (74.4%), ES occurred in 140 patients (19.5%), and ESE in 44 patients (6.1%). The final multivariable logistic regression analyses included ES exposure, age dichotomized at 1 year, acute encephalopathy category, initial EEG background category, comatose at CEEG initiation, and Pediatric Index of Mortality 2 score. There was an association between ESE and unfavorable GOS-E-Peds (odds ratio 2.21, 95% confidence interval 1.07-4.54) and PCPC (odds ratio 2.17, 95% confidence interval 1.05-4.51) but not mortality. There was no association between ES and unfavorable outcome or mortality. CONCLUSIONS Among acutely encephalopathic critically ill children, there was an association between ESE and unfavorable neurobehavioral outcomes, but no association between ESE and mortality. ES exposure was not associated with unfavorable neurobehavioral outcomes or mortality.
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Affiliation(s)
- France W Fung
- From the Departments of Neurology (F.F.W., N.S.A.), Pediatrics (F.F.W., N.S.A.), Biostatistics, Epidemiology and Informatics (Z.W., R.X.), and Anesthesia & Critical Care (A.A.T., N.S.A.) and Center for Clinical Epidemiology and Biostatistics (R.X., N.S.A.), Perelman School of Medicine at the University of Pennsylvania; and Departments of Pediatrics (Division of Neurology) (F.F.W., D.S.P., M.J., N.S.A.), Neurodiagnostics (L.V., M.D., N.S.A.), and Anesthesia and Critical Care Medicine (A.A.T.), Children's Hospital of Philadelphia, PA.
| | - Zi Wang
- From the Departments of Neurology (F.F.W., N.S.A.), Pediatrics (F.F.W., N.S.A.), Biostatistics, Epidemiology and Informatics (Z.W., R.X.), and Anesthesia & Critical Care (A.A.T., N.S.A.) and Center for Clinical Epidemiology and Biostatistics (R.X., N.S.A.), Perelman School of Medicine at the University of Pennsylvania; and Departments of Pediatrics (Division of Neurology) (F.F.W., D.S.P., M.J., N.S.A.), Neurodiagnostics (L.V., M.D., N.S.A.), and Anesthesia and Critical Care Medicine (A.A.T.), Children's Hospital of Philadelphia, PA
| | - Darshana S Parikh
- From the Departments of Neurology (F.F.W., N.S.A.), Pediatrics (F.F.W., N.S.A.), Biostatistics, Epidemiology and Informatics (Z.W., R.X.), and Anesthesia & Critical Care (A.A.T., N.S.A.) and Center for Clinical Epidemiology and Biostatistics (R.X., N.S.A.), Perelman School of Medicine at the University of Pennsylvania; and Departments of Pediatrics (Division of Neurology) (F.F.W., D.S.P., M.J., N.S.A.), Neurodiagnostics (L.V., M.D., N.S.A.), and Anesthesia and Critical Care Medicine (A.A.T.), Children's Hospital of Philadelphia, PA
| | - Marin Jacobwitz
- From the Departments of Neurology (F.F.W., N.S.A.), Pediatrics (F.F.W., N.S.A.), Biostatistics, Epidemiology and Informatics (Z.W., R.X.), and Anesthesia & Critical Care (A.A.T., N.S.A.) and Center for Clinical Epidemiology and Biostatistics (R.X., N.S.A.), Perelman School of Medicine at the University of Pennsylvania; and Departments of Pediatrics (Division of Neurology) (F.F.W., D.S.P., M.J., N.S.A.), Neurodiagnostics (L.V., M.D., N.S.A.), and Anesthesia and Critical Care Medicine (A.A.T.), Children's Hospital of Philadelphia, PA
| | - Lisa Vala
- From the Departments of Neurology (F.F.W., N.S.A.), Pediatrics (F.F.W., N.S.A.), Biostatistics, Epidemiology and Informatics (Z.W., R.X.), and Anesthesia & Critical Care (A.A.T., N.S.A.) and Center for Clinical Epidemiology and Biostatistics (R.X., N.S.A.), Perelman School of Medicine at the University of Pennsylvania; and Departments of Pediatrics (Division of Neurology) (F.F.W., D.S.P., M.J., N.S.A.), Neurodiagnostics (L.V., M.D., N.S.A.), and Anesthesia and Critical Care Medicine (A.A.T.), Children's Hospital of Philadelphia, PA
| | - Maureen Donnelly
- From the Departments of Neurology (F.F.W., N.S.A.), Pediatrics (F.F.W., N.S.A.), Biostatistics, Epidemiology and Informatics (Z.W., R.X.), and Anesthesia & Critical Care (A.A.T., N.S.A.) and Center for Clinical Epidemiology and Biostatistics (R.X., N.S.A.), Perelman School of Medicine at the University of Pennsylvania; and Departments of Pediatrics (Division of Neurology) (F.F.W., D.S.P., M.J., N.S.A.), Neurodiagnostics (L.V., M.D., N.S.A.), and Anesthesia and Critical Care Medicine (A.A.T.), Children's Hospital of Philadelphia, PA
| | - Alexis A Topjian
- From the Departments of Neurology (F.F.W., N.S.A.), Pediatrics (F.F.W., N.S.A.), Biostatistics, Epidemiology and Informatics (Z.W., R.X.), and Anesthesia & Critical Care (A.A.T., N.S.A.) and Center for Clinical Epidemiology and Biostatistics (R.X., N.S.A.), Perelman School of Medicine at the University of Pennsylvania; and Departments of Pediatrics (Division of Neurology) (F.F.W., D.S.P., M.J., N.S.A.), Neurodiagnostics (L.V., M.D., N.S.A.), and Anesthesia and Critical Care Medicine (A.A.T.), Children's Hospital of Philadelphia, PA
| | - Rui Xiao
- From the Departments of Neurology (F.F.W., N.S.A.), Pediatrics (F.F.W., N.S.A.), Biostatistics, Epidemiology and Informatics (Z.W., R.X.), and Anesthesia & Critical Care (A.A.T., N.S.A.) and Center for Clinical Epidemiology and Biostatistics (R.X., N.S.A.), Perelman School of Medicine at the University of Pennsylvania; and Departments of Pediatrics (Division of Neurology) (F.F.W., D.S.P., M.J., N.S.A.), Neurodiagnostics (L.V., M.D., N.S.A.), and Anesthesia and Critical Care Medicine (A.A.T.), Children's Hospital of Philadelphia, PA
| | - Nicholas S Abend
- From the Departments of Neurology (F.F.W., N.S.A.), Pediatrics (F.F.W., N.S.A.), Biostatistics, Epidemiology and Informatics (Z.W., R.X.), and Anesthesia & Critical Care (A.A.T., N.S.A.) and Center for Clinical Epidemiology and Biostatistics (R.X., N.S.A.), Perelman School of Medicine at the University of Pennsylvania; and Departments of Pediatrics (Division of Neurology) (F.F.W., D.S.P., M.J., N.S.A.), Neurodiagnostics (L.V., M.D., N.S.A.), and Anesthesia and Critical Care Medicine (A.A.T.), Children's Hospital of Philadelphia, PA
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Machine learning models to predict electroencephalographic seizures in critically ill children. Seizure 2021; 87:61-68. [PMID: 33714840 DOI: 10.1016/j.seizure.2021.03.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 12/23/2020] [Accepted: 03/02/2021] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE To determine whether machine learning techniques would enhance our ability to incorporate key variables into a parsimonious model with optimized prediction performance for electroencephalographic seizure (ES) prediction in critically ill children. METHODS We analyzed data from a prospective observational cohort study of 719 consecutive critically ill children with encephalopathy who underwent clinically-indicated continuous EEG monitoring (CEEG). We implemented and compared three state-of-the-art machine learning methods for ES prediction: (1) random forest; (2) Least Absolute Shrinkage and Selection Operator (LASSO); and (3) Deep Learning Important FeaTures (DeepLIFT). We developed a ranking algorithm based on the relative importance of each variable derived from the machine learning methods. RESULTS Based on our ranking algorithm, the top five variables for ES prediction were: (1) epileptiform discharges in the initial 30 minutes, (2) clinical seizures prior to CEEG initiation, (3) sex, (4) age dichotomized at 1 year, and (5) epileptic encephalopathy. Compared to the stepwise selection-based approach in logistic regression, the top variables selected by our ranking algorithm were more informative as models utilizing the top variables achieved better prediction performance evaluated by prediction accuracy, AUROC and F1 score. Adding additional variables did not improve and sometimes worsened model performance. CONCLUSION The ranking algorithm was helpful in deriving a parsimonious model for ES prediction with optimal performance. However, application of state-of-the-art machine learning models did not substantially improve model performance compared to prior logistic regression models. Thus, to further improve the ES prediction, we may need to collect more samples and variables that provide additional information.
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Fung FW, Fan J, Vala L, Jacobwitz M, Parikh DS, Donnelly M, Topjian AA, Xiao R, Abend NS. EEG monitoring duration to identify electroencephalographic seizures in critically ill children. Neurology 2020; 95:e1599-e1608. [PMID: 32690798 DOI: 10.1212/wnl.0000000000010421] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Accepted: 04/10/2020] [Indexed: 11/15/2022] Open
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.
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Affiliation(s)
- France W Fung
- 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.
| | - Jiaxin Fan
- 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
| | - Lisa Vala
- 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
| | - Marin Jacobwitz
- 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
| | - Darshana S Parikh
- 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
| | - Maureen Donnelly
- 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
| | - Alexis A Topjian
- 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
| | - Rui Xiao
- 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
| | - Nicholas S Abend
- 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
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Fung FW, Jacobwitz M, Vala L, Parikh D, Donnelly M, Xiao R, Topjian AA, Abend NS. Electroencephalographic seizures in critically ill children: Management and adverse events. Epilepsia 2019; 60:2095-2104. [PMID: 31538340 DOI: 10.1111/epi.16341] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2019] [Revised: 08/27/2019] [Accepted: 08/27/2019] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Guidelines recommend that encephalopathic critically ill children undergo continuous electroencephalographic (CEEG) monitoring for electrographic seizure (ES) identification and management. However, limited data exist on antiseizure medication (ASM) safety for ES treatment in critically ill children. METHODS We performed a single-center prospective observational study of encephalopathic critically ill children undergoing CEEG. Clinical and EEG features and ASM utilization patterns were evaluated. We determined the incidence, types, and risk factors for adverse events associated with ASM administration. RESULTS A total of 472 consecutive critically ill children undergoing CEEG were enrolled. ES occurred in 131 children (28%). Clinicians administered ASM to 108 children with ES (82%). ES terminated after the initial ASM in 38% of patients who received one ASM, after the second ASM in 35% of patients who received two ASMs, after the third ASM in 50% of patients who received three ASMs, and after the fourth ASM in 53% of patients who received four ASMs. Thirty patients (28%) received anesthetic infusions for ES management. Adverse events occurred in 18 patients (17%). Adverse effects were expected and resolved in all patients, and they were generally serious (in 15 patients) and definitely related (in 12 patients). Adverse events were rare in patients with acute symptomatic seizures requiring only one to two ASMs for treatment, but were more common in children with epilepsy, ictal-interictal continuum EEG patterns, or patients requiring more extensive ASM management. SIGNIFICANCE ES ceased after one ASM in only 38% of critically ill children but ceased after two ASMs in 73% of critically ill children. Thus, ES management was often accomplished with readily available medications, but optimization of multistep ES management strategies might be beneficial. Adverse events were rare and manageable in children with acute symptomatic seizures requiring only one to two ASMs for treatment. Future studies are needed to determine whether management of acute symptomatic ES improves neurobehavioral outcomes.
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Affiliation(s)
- France W Fung
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia,, Philadelphia, PA, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Marin Jacobwitz
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia,, Philadelphia, PA, USA
| | - Lisa Vala
- Department of Neurodiagnostics, Children's Hospital of Philadelphia,, Philadelphia, PA, USA
| | - Darshana Parikh
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia,, Philadelphia, PA, USA.,Department of Anesthesia and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Maureen Donnelly
- Department of Neurodiagnostics, Children's Hospital of Philadelphia,, Philadelphia, PA, USA
| | - Rui Xiao
- Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Alexis A Topjian
- Department of Anesthesia and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.,Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nicholas S Abend
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia,, Philadelphia, PA, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Neurodiagnostics, Children's Hospital of Philadelphia,, Philadelphia, PA, USA.,Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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Dineen J, Maus DC, Muzyka I, See RB, Cahill DP, Carter BS, Curry WT, Jones PS, Nahed BV, Peterfreund RA, Simon MV. Factors that modify the risk of intraoperative seizures triggered by electrical stimulation during supratentorial functional mapping. Clin Neurophysiol 2019; 130:1058-1065. [DOI: 10.1016/j.clinph.2019.03.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 02/05/2019] [Accepted: 03/13/2019] [Indexed: 12/19/2022]
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Welsh SS, Lin N, Topjian AA, Abend NS. Safety of intravenous lacosamide in critically ill children. Seizure 2017; 52:76-80. [PMID: 29017081 PMCID: PMC5685892 DOI: 10.1016/j.seizure.2017.09.019] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Revised: 07/07/2017] [Accepted: 09/28/2017] [Indexed: 01/17/2023] Open
Abstract
PURPOSE Acute seizures are common in critically ill children. These patients would benefit from intravenous anti-seizure medications with few adverse effects. We reviewed the usage and effects of intravenous lacosamide in critically ill children with seizures or status epilepticus. METHODS This retrospective series included consecutive patients who received at least one dose of intravenous lacosamide from April 2011 to February 2016 in the pediatric intensive care unit of a quaternary care children's hospital, including patients with new lacosamide initiation and continuation of outpatient oral lacosamide. Dosing and prescribing practices were reviewed. Adverse effects were defined by predefined criteria, and most were evaluated during the full admission. RESULTS We identified 51 intensive care unit admissions (47 unique patients) with intravenous lacosamide administration. Lacosamide was utilized as a third or fourth-line anti-seizure medication for acute seizures or status epilepticus in the lacosamide-naïve cohort. One patient experienced bradycardia and one patient experienced a rash that were considered potentially related to lacosamide. No other adverse effects were identified, including no evidence of PR interval prolongation. CONCLUSIONS Lacosamide was well tolerated in critically ill children. Further study is warranted to evaluate the effectiveness of earlier lacosamide use for pediatric status epilepticus and acute seizures.
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Affiliation(s)
- Sarah S Welsh
- Division of Critical Care Medicine, Children's Hospital of Philadelphia, Department of Anesthesia and Critical Care Medicine, The University of Pennsylvania, United States
| | - Nan Lin
- Division of Neurology, Children's Hospital of Philadelphia, Departments of Neurology and Pediatrics, The University of Pennsylvania, United States
| | - Alexis A Topjian
- Division of Critical Care Medicine, Children's Hospital of Philadelphia, Department of Anesthesia and Critical Care Medicine, The University of Pennsylvania, United States
| | - Nicholas S Abend
- Division of Neurology, Children's Hospital of Philadelphia, Departments of Neurology and Pediatrics, The University of Pennsylvania, United States.
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Could EEG Monitoring in Critically Ill Children Be a Cost-effective Neuroprotective Strategy? J Clin Neurophysiol 2016; 32:486-94. [PMID: 26057408 DOI: 10.1097/wnp.0000000000000198] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
PURPOSE Electrographic status epilepticus (ESE) in critically ill children is associated with unfavorable functional outcomes, but identifying candidates for ESE management requires resource-intense EEG monitoring. A cost-effectiveness analysis was performed to estimate how much ESE identification and management would need to improve patient outcomes to make EEG monitoring strategies a good value. METHODS A decision tree was created to examine the relationships among variables important to deciding whether to perform EEG monitoring. Variable costs were estimated from their component parts, outcomes were estimated in quality-adjusted life-years, and incremental cost-effectiveness ratios were calculated to compare the relative values using four alternative EEG monitoring strategies that varied by monitoring duration. RESULTS Forty-eight hours of EEG monitoring would be worth its cost if ESE identification and management improved patient outcomes by ≥7%. If ESE identification and management improved patient outcomes by 3% to 6%, then 24 or 48 hours of EEG monitoring would be worth the cost depending on how much decision makers were willing to pay per quality-adjusted life-year gained. If ESE identification and management improved outcomes by as little as 3%, then 24 hours of EEG monitoring would be worth the cost. CONCLUSIONS EEG monitoring has the potential to be cost-effective if ESE identification and management improves patient outcomes by as little as 3%.
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How much does it cost to identify a critically ill child experiencing electrographic seizures? J Clin Neurophysiol 2016; 32:257-64. [PMID: 25626776 DOI: 10.1097/wnp.0000000000000170] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVES Electrographic seizures in critically ill children may be identified by continuous EEG monitoring. We evaluated the cost effectiveness of 4 electrographic seizure identification strategies (no EEG monitoring and EEG monitoring for 1 hour, 24 hours, or 48 hours). METHODS We created a decision tree to model the relationships among variables from a societal perspective. To provide input for the model, we estimated variable costs directly related to EEG monitoring from their component parts, and we reviewed the literature to estimate the probabilities of outcomes. We calculated incremental cost-effectiveness ratios to identify the trade-off between cost and effectiveness at different willingness-to-pay values. RESULTS Our analysis found that the preferred strategy was EEG monitoring for 1 hour, 24 hours, and 48 hours if the decision maker was willing to pay <$1,666, $1,666-$22,648, and >$22,648 per critically ill child identified with electrographic seizures, respectively. The 48-hour strategy only identified 4% more children with electrographic seizures at substantially higher cost. Sensitivity analyses found that all 3 strategies were acceptable at lower willingness-to-pay values when children with higher electrographic seizure risk were monitored. CONCLUSIONS The results of this study support monitoring of critically ill children for 24 hours because the cost to identify a critically ill child with electrographic seizures is modest. Further study is needed to predict better which children may benefit from 48 hours of EEG monitoring because the costs are much higher.
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Greiner MV, Greiner HM, Caré MM, Owens D, Shapiro R, Holland K. Adding Insult to Injury: Nonconvulsive Seizures in Abusive Head Trauma. J Child Neurol 2015; 30:1778-84. [PMID: 25900138 DOI: 10.1177/0883073815580285] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Accepted: 02/16/2015] [Indexed: 11/17/2022]
Abstract
The primary objectives of this study were to determine the prevalence of nonconvulsive seizures and nonconvulsive status epilepticus in patients with abusive head trauma who underwent electroencephalography (EEG) monitoring and to describe predictive factors for this population. Children with a diagnosis of abusive head trauma were studied retrospectively to determine the rate of EEG monitoring, the rate of nonconvulsive seizures and nonconvulsive status epilepticus, and the associated neuroimaging findings. Over 11 years, 73 of 199 (36.8%) children with abusive head trauma had electroencephalography monitoring performed. Of these, 20 (27.4%) had nonconvulsive seizures and 3 (4.1%) had nonconvulsive status epilepticus. The presence of subarachnoid hemorrhage and cortical T2 / fluid-attenuated inversion recovery signal abnormalities were both significantly associated with the presence of nonconvulsive seizures / nonconvulsive status epilepticus. Nonconvulsive seizures are relatively common in abusive head trauma and may go unrecognized. Specific neuroimaging characteristics increase the likelihood of nonconvulsive seizures on EEG.
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Affiliation(s)
- Mary V Greiner
- Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Hansel M Greiner
- Department of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Marguerite M Caré
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Deanna Owens
- Department of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Robert Shapiro
- Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Katherine Holland
- Department of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
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Abend NS, Wagenman KL, Blake TP, Schultheis MT, Radcliffe J, Berg RA, Topjian AA, Dlugos DJ. Electrographic status epilepticus and neurobehavioral outcomes in critically ill children. Epilepsy Behav 2015; 49:238-44. [PMID: 25908325 PMCID: PMC4536172 DOI: 10.1016/j.yebeh.2015.03.013] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Revised: 03/10/2015] [Accepted: 03/11/2015] [Indexed: 01/04/2023]
Abstract
PURPOSE Electrographic seizures (ESs) and electrographic status epilepticus (ESE) are common in children with acute neurologic conditions in pediatric intensive care units (PICUs), and ESE is associated with worse functional and quality-of-life outcomes. As an exploratory study, we aimed to determine if ESE was associated with worse outcomes using more detailed neurobehavioral measures. METHODS Three hundred children with an acute neurologic condition and altered mental status underwent clinically indicated EEG monitoring and were enrolled in a prospective observational study. We obtained follow-up data from subjects who were neurodevelopmentally normal prior to PICU admission. We evaluated for associations between ESE and adaptive behavior (Adaptive Behavior Assessment System-II, ABAS-II), behavioral and emotional problems (Child Behavior Checklist, CBCL), and executive function (Behavior Rating Inventory of Executive Function, BRIEF) using linear regression analyses. A p-value of <0.05 was considered significant. RESULTS One hundred thirty-seven of 300 subjects were neurodevelopmentally normal prior to PICU admission. We obtained follow-up data from 36 subjects for the CBCL, 32 subjects for the ABAS-II, and 20 subjects for the BRIEF. The median duration from admission to follow-up was 2.6 years (IQR: 1.2-3.8). There were no differences in the acute care variables (age, sex, mental status category, intubation status, paralysis status, acute neurologic diagnosis category, seizure category, EEG background category, or short-term outcome) between subjects with and without follow-up data for any of the outcome measures. On univariate analysis, significant differences were not identified for CBCL total problem (ES coefficient: -4.1, p = 0.48; ESE coefficient: 8.9, p = 0.13) or BRIEF global executive function (ES coefficient: 2.1, p = 0.78; ESE coefficient: 14.1, p = 0.06) scores, although there were trends toward worse scores in subjects with ESE. On univariate analysis, ESs were not associated with worse scores (coefficient: -21.5, p = 0.051), while ESE (coefficient: -29.7, p = 0.013) was associated with worse ABAS-II adaptive behavioral global composite scores. On multivariate analysis, when compared to subjects with no seizures, both ESs (coefficient: -28, p=0.014) and ESE (coefficient: -36, p = 0.003) were associated with worse adaptive behavioral global composite scores. DISCUSSION Among previously neurodevelopmentally normal children with acute neurologic disorders, ESs and ESE were associated with worse adaptive behavior and trends toward worse behavioral-emotional and executive function problems. This was a small exploratory study, and the impact of ESs and ESE on these neurobehavioral measures may be clarified by subsequent larger studies. This article is part of a Special Issue entitled "Status Epilepticus".
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Affiliation(s)
- Nicholas S Abend
- Division of Neurology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Katherine L Wagenman
- Division of Neurology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Taylor P Blake
- Psychology Department, Drexel University, Philadelphia, PA, USA
| | | | - Jerilynn Radcliffe
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Robert A Berg
- Department of Anesthesia and Critical Care Medicine, The Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alexis A Topjian
- Department of Anesthesia and Critical Care Medicine, The Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dennis J Dlugos
- Division of Neurology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Nakazawa M, Akasaka M, Hasegawa T, Suzuki T, Shima T, Takanashi JI, Yamamoto A, Ishidou Y, Kikuchi K, Niijima S, Shimizu T, Okumura A. Efficacy and safety of fosphenytoin for acute encephalopathy in children. Brain Dev 2015; 37:418-22. [PMID: 25008803 DOI: 10.1016/j.braindev.2014.06.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Revised: 06/20/2014] [Accepted: 06/20/2014] [Indexed: 11/18/2022]
Abstract
PURPOSE To evaluate the efficacy and safety of fosphenytoin (fPHT) for the treatment of seizures in children with acute encephalopathy. METHODS Using responses from physicians on the Annual Zao Conference on Pediatric Neurology mailing list we chose patients who met the following criteria: clinical diagnosis of acute encephalopathy and use of intravenous fPHT for the treatment of seizures. We divided the patients into two groups: acute encephalopathy with biphasic seizures and late reduced diffusion (AESD) and other encephalopathies. The efficacy of fPHT was considered effective when a cessation of seizures was achieved. RESULTS Data of 38 children were obtained (median age, 27 months). Eighteen children were categorized into the AESD group and 20 into the other encephalopathies group. fPHT was administered in 48 clinical events. The median loading dose of fPHT was 22.5 mg/kg and was effective in 34 of 48 (71%) events. The rate of events in which fPHT was effective did not differ according to the presence or absence of prior antiepileptic treatment, subtype of acute encephalopathy, or the type of seizures. One patient experienced apnea and oral dyskinesia as adverse effects of fPHT, whereas arrhythmia, hypotension, obvious reduction of consciousness, local irritation, phlebitis and purple grove syndrome were not observed in any patient. CONCLUSION fPHT is effective and well tolerated among children with acute encephalopathy.
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Affiliation(s)
- Mika Nakazawa
- Department of Pediatrics, Juntendo University Faculty of Medicine, Japan; Department of Pediatrics, Juntendo University Nerima Hospital, Japan.
| | - Manami Akasaka
- Department of Pediatrics, Iwate Medical University Faculty of Medicine, Japan
| | | | - Tomonori Suzuki
- Department of Pediatrics, Kawaguchi Municipal Medical Center, Japan
| | - Taiki Shima
- Department of Pediatrics, Juntendo University Faculty of Medicine, Japan; Department of Neuropediatrics, Nagano Children's Hospital, Japan
| | | | - Atsuko Yamamoto
- Department of Pediatrics, Tsuchiura Kyodo General Hospital, Japan
| | - Yuuki Ishidou
- Department of Pediatrics, St. Mary's Hospital, Japan
| | - Kenjiro Kikuchi
- Division of Neurology, Saitama Children's Medical Center, Japan
| | - Shinichi Niijima
- Department of Pediatrics, Juntendo University Nerima Hospital, Japan
| | - Toshiaki Shimizu
- Department of Pediatrics, Juntendo University Faculty of Medicine, Japan
| | - Akihisa Okumura
- Department of Pediatrics, Juntendo University Faculty of Medicine, Japan; Department of Pediatrics, Aichi Medical University, Japan
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Sánchez Fernández I, Abend NS, Arndt DH, Carpenter JL, Chapman KE, Cornett KM, Dlugos DJ, Gallentine WB, Giza CC, Goldstein JL, Hahn CD, Lerner JT, Matsumoto JH, McBain K, Nash KB, Payne E, Sánchez SM, Williams K, Loddenkemper T. Electrographic seizures after convulsive status epilepticus in children and young adults: a retrospective multicenter study. J Pediatr 2014; 164:339-46.e1-2. [PMID: 24161223 PMCID: PMC3946834 DOI: 10.1016/j.jpeds.2013.09.032] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2013] [Revised: 08/22/2013] [Accepted: 09/13/2013] [Indexed: 11/17/2022]
Abstract
OBJECTIVE To describe the prevalence, characteristics, and predictors of electrographic seizures after convulsive status epilepticus (CSE). STUDY DESIGN This was a multicenter retrospective study in which we describe clinical and electroencephalographic (EEG) features of children (1 month to 21 years) with CSE who underwent continuous EEG monitoring. RESULTS Ninety-eight children (53 males) with CSE (median age of 5 years) underwent subsequent continuous EEG monitoring after CSE. Electrographic seizures (with or without clinical correlate) were identified in 32 subjects (33%). Eleven subjects (34.4%) had electrographic-only seizures, 17 subjects (53.1%) had electroclinical seizures, and 4 subjects (12.5%) had an unknown clinical correlate. Of the 32 subjects with electrographic seizures, 15 subjects (46.9%) had electrographic status epilepticus. Factors associated with the occurrence of electrographic seizures after CSE were a previous diagnosis of epilepsy (P = .029) and the presence of interictal epileptiform discharges (P < .0005). The median (p25-p75) duration of stay in the pediatric intensive care unit was longer for children with electrographic seizures than for children without electrographic seizures (9.5 [3-22.5] vs 2 [2-5] days, Wilcoxon test, Z = 3.916, P = .0001). Four children (4.1%) died before leaving the hospital, and we could not identify a relationship between death and the presence or absence of electrographic seizures. CONCLUSIONS After CSE, one-third of children who underwent EEG monitoring experienced electrographic seizures, and among these, one-third experienced entirely electrographic-only seizures. A previous diagnosis of epilepsy and the presence of interictal epileptiform discharges were risk factors for electrographic seizures.
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Affiliation(s)
- Iván Sánchez Fernández
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA; Department of Child Neurology, Hospital Sant Joan de Déu, Universidad de Barcelona, Barcelona, Spain
| | - Nicholas S Abend
- Departments of Neurology and Pediatrics, The Children's Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA.
| | - Daniel H Arndt
- Department of Pediatrics, Oakland University William Beaumont School of Medicine, Royal Oak, MI; Department of Neurology, Oakland University William Beaumont School of Medicine, Royal Oak, MI
| | | | - Kevin E Chapman
- Division of Neurology, Children's Hospital Colorado and University of Colorado School of Medicine, Aurora, CO
| | - Karen M Cornett
- Division of Pediatric Neurology, Duke University Hospital and Duke University School of Medicine, Durham, NC
| | - Dennis J Dlugos
- Departments of Neurology and Pediatrics, The Children's Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - William B Gallentine
- Division of Pediatric Neurology, Duke University Hospital and Duke University School of Medicine, Durham, NC
| | - Christopher C Giza
- Division of Neurology, Department of Pediatrics Mattel Children's Hospital and UCLA Brain Injury Research Center, Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Joshua L Goldstein
- Division of Neurology, Children's Memorial Hospital and Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Cecil D Hahn
- Division of Neurology, The Hospital for Sick Children and University of Toronto, Toronto, ON
| | - Jason T Lerner
- Division of Neurology, Department of Pediatrics Mattel Children's Hospital and UCLA Brain Injury Research Center, Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Joyce H Matsumoto
- Division of Neurology, Department of Pediatrics Mattel Children's Hospital and UCLA Brain Injury Research Center, Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Kristin McBain
- Division of Neurology, The Hospital for Sick Children and University of Toronto, Toronto, ON
| | - Kendall B Nash
- Department of Neurology, University of California San Francisco, San Francisco, CA
| | - Eric Payne
- Division of Neurology, The Hospital for Sick Children and University of Toronto, Toronto, ON
| | - Sarah M Sánchez
- Departments of Neurology and Pediatrics, The Children's Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Korwyn Williams
- Department of Pediatrics, University of Arizona College of Medicine and Barrow's Neurological Institute at Phoenix Children's Hospital, Phoenix, AZ
| | - Tobias Loddenkemper
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA
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21
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Wagenman KL, Blake TP, Sanchez SM, Schultheis MT, Radcliffe J, Berg RA, Dlugos DJ, Topjian AA, Abend NS. Electrographic status epilepticus and long-term outcome in critically ill children. Neurology 2014; 82:396-404. [PMID: 24384638 DOI: 10.1212/wnl.0000000000000082] [Citation(s) in RCA: 111] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE Electrographic seizures (ES) and electrographic status epilepticus (ESE) are common in children in the pediatric intensive care unit (PICU) with acute neurologic conditions. We aimed to determine whether ES or ESE was associated with worse long-term outcomes. METHODS Three hundred children with an acute neurologic condition and encephalopathy underwent clinically indicated EEG monitoring and were enrolled in a prospective observational study. We aimed to obtain follow-up data from 137 subjects who were neurodevelopmentally normal before PICU admission. RESULTS Follow-up data were collected for 60 of 137 subjects (44%) at a median of 2.7 years. Subjects with and without follow-up data were similar in clinical characteristics during the PICU admission. Among subjects with follow-up data, ES occurred in 12 subjects (20%) and ESE occurred in 14 subjects (23%). Multivariable analysis indicated that ESE was associated with an increased risk of unfavorable Glasgow Outcome Scale (Extended Pediatric Version) category (odds ratio 6.36, p = 0.01) and lower Pediatric Quality of Life Inventory scores (23 points lower, p = 0.001). Among subjects without prior epilepsy diagnoses ESE was associated with an increased risk of subsequently diagnosed epilepsy (odds ratio 13.3, p = 0.002). ES were not associated with worse outcomes. CONCLUSIONS Among children with acute neurologic disorders who were reported to be neurodevelopmentally normal before PICU admission, ESE but not ES was associated with an increased risk of unfavorable global outcome, lower health-related quality of life scores, and an increased risk of subsequently diagnosed epilepsy even after adjusting for neurologic disorder category, EEG background category, and age.
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Affiliation(s)
- Katherine L Wagenman
- From the Department of Anesthesia and Critical Care Medicine (R.A.B., A.A.T.), The Children's Hospital of Philadelphia and Perelman School of Medicine at the University of Pennsylvania, Philadelphia; Division of Neurology (K.L.W., S.M.S., D.J.D., N.S.A.), The Children's Hospital of Philadelphia; Departments of Neurology and Pediatrics (D.J.D., N.S.A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia; Psychology Department (T.P.B., M.T.S.), Drexel University, Philadelphia, PA; and Department of Pediatrics (J.R.), Perelman School of Medicine at the University of Pennsylvania, The Children's Hospital of Philadelphia, PA
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