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Vaughan T, Hammoud MS, Pande A, Chu L, Cummins K, McCloskey O, Parfyonov M, Doh CY, Edwards A, Sharew B, Greason C, Abushanab E, Gupta A, Marino B, Najm HK, Karamlou T. Can perioperative electroencephalogram and adverse hemodynamic events predict neurodevelopmental outcomes in infants with congenital heart disease? J Thorac Cardiovasc Surg 2024; 168:342-352.e7. [PMID: 37951534 DOI: 10.1016/j.jtcvs.2023.10.063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 09/26/2023] [Accepted: 10/30/2023] [Indexed: 11/14/2023]
Abstract
OBJECTIVE The study objective was to characterize preoperative and postoperative continuous electroencephalogram metrics and hemodynamic adverse events as predictors of neurodevelopment in congenital heart disease infants undergoing cardiac surgery. METHODS From 2010 to 2021, 320 infants underwent congenital heart disease surgery at our institution, of whom 217 had perioperative continuous electroencephalogram monitoring and were included in our study. Neurodevelopment was assessed in 76 patients by the Bayley Scales of Infant and Toddler Development, 3rd edition, consisting of cognitive, communication, and motor scaled scores. Patient and procedural factors, including hemodynamic adverse events, were included by means of the likelihood of covariate selection in our predictive model. Median (25th, 75th percentile) follow-up was 1.03 (0.09, 3.44) years with 3 (1, 6) Bayley Scales of Infant and Toddler Development, 3rd Edition evaluations per patient. RESULTS Median age at index surgery was 7 (4, 23) days, and 81 (37%) were female. Epileptiform discharges, encephalopathy, and abnormality (lethargy and coma) were more prevalent on postoperative continuous electroencephalograms, compared with preoperative continuous electroencephalograms (P < .005). In 76 patients with Bayley Scales of Infant and Toddler Development, 3rd edition evaluations, patients with diffuse abnormality (P = .009), waveform discontinuity (P = .007), and lack of continuity (P = .037) on preoperative continuous electroencephalogram had lower cognitive scores. Patients with synchrony (P < .005) on preoperative and waveform continuity (P = .009) on postoperative continuous electroencephalogram had higher fine motor scores. Patients with postoperative adverse events had lower cognitive (P < .005) and gross motor scores (P < .005). CONCLUSIONS Phenotypic patterns of perioperative continuous electroencephalogram metrics are associated with late-term neurologic injury in infants with congenital heart disease requiring surgery. Continuous electroencephalogram metrics can be integrated with hemodynamic adverse events in a predictive algorithm for neurologic impairment.
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Affiliation(s)
- Tiffany Vaughan
- Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Miza Salim Hammoud
- Division of Pediatric and Congenital Cardiac Surgery, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio
| | - Amol Pande
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio
| | - Lee Chu
- Division of Pediatric and Congenital Cardiac Surgery, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio
| | - Kaleigh Cummins
- Division of Pediatric and Congenital Cardiac Surgery, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio
| | - Olivia McCloskey
- Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Maksim Parfyonov
- Department of Pediatric Neurology, Cleveland Clinic Children's, Cleveland, Ohio
| | - Chang Yoon Doh
- Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Alyssa Edwards
- Case Western Reserve University School of Medicine, Cleveland, Ohio
| | | | - Christie Greason
- Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Elham Abushanab
- Department of Pediatric Neurology, Cleveland Clinic Children's, Cleveland, Ohio
| | - Ajay Gupta
- Department of Pediatric Neurology, Cleveland Clinic Children's, Cleveland, Ohio
| | - Bradley Marino
- Department of Pediatric Cardiology, Cleveland Clinic Children's, Cleveland, Ohio
| | - Hani K Najm
- Division of Pediatric and Congenital Cardiac Surgery, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio
| | - Tara Karamlou
- Division of Pediatric and Congenital Cardiac Surgery, Heart, Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio.
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Fung FW, Carpenter JL, Chapman KE, Gallentine W, Giza CC, Goldstein JL, Hahn CD, Loddenkemper T, Matsumoto JH, Press CA, Riviello JJ, Abend NS. Survey of Pediatric ICU EEG Monitoring-Reassessment After a Decade. J Clin Neurophysiol 2024; 41:458-472. [PMID: 36930237 PMCID: PMC10504411 DOI: 10.1097/wnp.0000000000001006] [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: 03/18/2023] Open
Abstract
PURPOSE In 2011, the authors conducted a survey regarding continuous EEG (CEEG) utilization in critically ill children. In the interim decade, the literature has expanded, and guidelines and consensus statements have addressed CEEG utilization. Thus, the authors aimed to characterize current practice related to CEEG utilization in critically ill children. METHODS The authors conducted an online survey of pediatric neurologists from 50 US and 12 Canadian institutions in 2022. RESULTS The authors assessed responses from 48 of 62 (77%) surveyed institutions. Reported CEEG indications were consistent with consensus statement recommendations and included altered mental status after a seizure or status epilepticus, altered mental status of unknown etiology, or altered mental status with an acute primary neurological condition. Since the prior survey, there was a 3- to 4-fold increase in the number of patients undergoing CEEG per month and greater use of written pathways for ICU CEEG. However, variability in resources and workflow persisted, particularly regarding technologist availability, frequency of CEEG screening, communication approaches, and electrographic seizure management approaches. CONCLUSIONS Among the surveyed institutions, which included primarily large academic centers, CEEG use in pediatric intensive care units has increased with some practice standardization, but variability in resources and workflow were persistent.
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Affiliation(s)
- France W Fung
- Departments of Pediatrics and Neurology, Children's Hospital of Philadelphia and University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, U.S.A
| | - Jessica L Carpenter
- Departments of Pediatrics and Neurology, University of Maryland School of Medicine, Baltimore, Maryland, U.S.A
| | - Kevin E Chapman
- Division of Neurology, Phoenix Children's Hospital and University of Arizona School of Medicine Phoenix, Arizona, U.S.A
| | - William Gallentine
- Division of Neurology, Stanford University and Lucile Packard Children's Hospital, Palo Alto, California, U.S.A
| | - 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, California, U.S.A
| | - Joshua L Goldstein
- Division of Neurology, Children's Memorial Hospital and Northwestern University Feinberg School of Medicine, Chicago, Illinois, U.S.A
| | - Cecil D Hahn
- Division of Neurology, The Hospital for Sick Children and University of Toronto, Toronto, U.S.A
| | - Tobias Loddenkemper
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, U.S.A.; and
| | - 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, California, U.S.A
| | - Craig A Press
- Departments of Pediatrics and Neurology, Children's Hospital of Philadelphia and University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, U.S.A
| | - James J Riviello
- Division of Neurology and Developmental Neuroscience, Department of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, Texas, U.S.A
| | - Nicholas S Abend
- Departments of Pediatrics and Neurology, Children's Hospital of Philadelphia and University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, U.S.A
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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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Fung FW, Parikh DS, Donnelly M, Xiao R, Topjian AA, Abend NS. Electrographic Seizure Characteristics and Electrographic Status Epilepticus Prediction. J Clin Neurophysiol 2024:00004691-990000000-00117. [PMID: 38194638 PMCID: PMC11231061 DOI: 10.1097/wnp.0000000000001068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2024] Open
Abstract
PURPOSE We aimed to characterize electrographic seizures (ES) and electrographic status epilepticus (ESE) and determine whether a model predicting ESE exclusively could effectively guide continuous EEG monitoring (CEEG) utilization in critically ill children. METHODS This was a prospective observational study of consecutive critically ill children with encephalopathy who underwent CEEG. We used descriptive statistics to characterize ES and ESE, and we developed a model for ESE prediction. RESULTS ES occurred in 25% of 1,399 subjects. Among subjects with ES, 23% had ESE, including 37% with continuous seizures lasting >30 minutes and 63% with recurrent seizures totaling 30 minutes within a 1-hour epoch. The median onset of ES and ESE occurred 1.8 and 0.18 hours after CEEG initiation, respectively. The optimal model for ESE prediction yielded an area under the receiver operating characteristic curves of 0.81. A cutoff selected to emphasize sensitivity (91%) yielded specificity of 56%. Given the 6% ESE incidence, positive predictive value was 11% and negative predictive value was 99%. If the model were applied to our cohort, then 53% of patients would not undergo CEEG and 8% of patients experiencing ESE would not be identified. CONCLUSIONS ESE was common, but most patients with ESE had recurrent brief seizures rather than long individual seizures. A model predicting ESE might only slightly improve CEEG utilization over models aiming to identify patients at risk for ES but would fail to identify some patients with ESE. Models identifying ES might be more advantageous for preventing ES from evolving into ESE.
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Affiliation(s)
- France W Fung
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, U.S.A
- Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, U.S.A
| | - Darshana S Parikh
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, U.S.A
| | - Maureen Donnelly
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, U.S.A
| | - Rui Xiao
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, U.S.A
| | - Alexis A Topjian
- Department of Anesthesia and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, U.S.A.; and
- Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, U.S.A
| | - Nicholas S Abend
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, U.S.A
- Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, U.S.A
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, U.S.A
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, U.S.A
- Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, U.S.A
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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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Sheikh Z, Selioutski O, Taraschenko O, Gilmore EJ, Westover MB, Cohen AB. Systematic Evaluation of Research Priorities in Critical Care Electroencephalography. J Clin Neurophysiol 2023; 40:426-433. [PMID: 35066530 PMCID: PMC9296700 DOI: 10.1097/wnp.0000000000000916] [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: 11/25/2022] Open
Abstract
PURPOSE The Critical Care EEG Monitoring Research Consortium (CCEMRC) is an international research group focusing on critical care EEG and epilepsy. As CCEMRC grew to include 50+ institutions over the past decade, members met to establish research priorities. METHODS The authors used an analytical hierarchy process-based research prioritization method, adapted from an approach previously applied to a Department of Defense health-related research program. Forty-six CCEMRC members identified and scored a set of eight clinical problems (CPs) and 15 research topic areas (RTAs) at an annual CCEMRC meeting. Members scored CPs on three criteria using a five-point ordinal scale: Incidence, Impact, and Gap Size; and RTAs on four additional criteria: Niche, Feasibility, Scientific Importance, and Medical Importance, each of which was assigned a weight. The first three RTA criteria were scored using a five-point scale, and CPs were mapped to RTAs using a four-point scale. The Medical Importance score was a weighted average of its mapping scores and the CP score. Finally, a Priority score was calculated for each RTA as a product of the four RTA criteria scores. RESULTS The CPs with the highest scores were "Altered mental status" and "Long-term neurologic disability after hospital discharge." The RTAs with the highest priority scores were "Development of risk prediction tools," "Multicenter observational studies," and "Outcome prediction." CONCLUSIONS Research prioritization helped CCEMRC evaluate its current research trajectory, identify high-priority near-term research pursuits, and create a roadmap for future research plans aligned with its mission. This approach may be helpful to other academic consortia and research programs.
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Affiliation(s)
- Zubeda Sheikh
- Department of Neurology, West Virginia University School of Medicine, Morgantown, West Virginia, U.S.A
| | - Olga Selioutski
- Epilepsy Division, Department of Neurology, University of Rochester School of Medicine and Dentistry, Rochester, New York, U.S.A
| | - Olga Taraschenko
- Comprehensive Epilepsy Center, Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska, U.S.A
| | - Emily J Gilmore
- Division of Neurocritical Care, Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, U.S.A
| | - M Brandon Westover
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, U.S.A
- Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Adam B Cohen
- The Johns Hopkins University Applied Physics Lab, National Health Mission Area, Laurel, Maryland, U.S.A.; and
- Department of Neurology, The Johns Hopkins Hospital, Baltimore, Maryland, U.S.A
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Waak M, Laing J, Nagarajan L, Lawn N, Harvey AS. Continuous electroencephalography in the intensive care unit: A critical review and position statement from an Australian and New Zealand perspective. CRIT CARE RESUSC 2023; 25:9-19. [PMID: 37876987 PMCID: PMC10581281 DOI: 10.1016/j.ccrj.2023.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Objectives This article aims to critically review the literature on continuous electroencephalography (cEEG) monitoring in the intensive care unit (ICU) from an Australian and New Zealand perspective and provide recommendations for clinicians. Design and review methods A taskforce of adult and paediatric neurologists, selected by the Epilepsy Society of Australia, reviewed the literature on cEEG for seizure detection in critically ill neonates, children, and adults in the ICU. The literature on routine EEG and cEEG for other indications was not reviewed. Following an evaluation of the evidence and discussion of controversial issues, consensus was reached, and a document that highlighted important clinical, practical, and economic considerations regarding cEEG in Australia and New Zealand was drafted. Results This review represents a summary of the literature and consensus opinion regarding the use of cEEG in the ICU for detection of seizures, highlighting gaps in evidence, practical problems with implementation, funding shortfalls, and areas for future research. Conclusion While cEEG detects electrographic seizures in a significant proportion of at-risk neonates, children, and adults in the ICU, conferring poorer neurological outcomes and guiding treatment in many settings, the health economic benefits of treating such seizures remain to be proven. Presently, cEEG in Australian and New Zealand ICUs is a largely unfunded clinical resource that is subsequently reserved for the highest-impact patient groups. Wider adoption of cEEG requires further research into impact on functional and health economic outcomes, education and training of the neurology and ICU teams involved, and securement of the necessary resources and funding to support the service.
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Affiliation(s)
- Michaela Waak
- Paediatric Critical Care Research Group, Child Health Research Centre, The University of Queensland, Brisbane, Australia
- Paediatric Intensive Care Unit, Queensland Children's Hospital, South Brisbane, Australia
| | - Joshua Laing
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia
- Comprehensive Epilepsy Program, Alfred Health, Melbourne, Australia
- Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia
| | - Lakshmi Nagarajan
- Department of Neurology, Perth Children's Hospital, Perth, Australia
- Faculty of Health and Medical Sciences, University of Western Australia, Perth, Australia
- Telethon Kids Institute, Perth Children's Hospital, Perth, Australia
| | - Nicholas Lawn
- Western Australian Adult Epilepsy Service, Sir Charles Gardiner Hospital, Perth, Australia
| | - A. Simon Harvey
- Department of Neurology, The Royal Children's Hospital, Melbourne, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, Australia
- Neurosciences Research Group, Murdoch Children's Research Institute, Melbourne, Australia
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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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Waak M, Gibbons K, Sparkes L, Harnischfeger J, Gurr S, Schibler A, Slater A, Malone S. Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol. BMJ Open 2022; 12:e059301. [PMID: 36691237 PMCID: PMC9171209 DOI: 10.1136/bmjopen-2021-059301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 04/19/2022] [Indexed: 01/27/2023] Open
Abstract
INTRODUCTION Approximately 20%-40% of comatose children with risk factors in intensive care have electrographic-only seizures; these go unrecognised due to the absence of continuous electroencephalography (EEG) monitoring (cEEG). Utility of cEEG with high-quality assessment is currently limited due to high-resource requirements. New software analysis tools are available to facilitate bedside cEEG assessment using quantitative EEG (QEEG) trends. The primary aim of this study is to describe accuracy of interpretation of QEEG trends by paediatric intensive care unit (PICU) nurses compared with cEEG assessment by neurologist (standard clinical care) in children at risk of seizures and status epilepticus utilising diagnostic test statistics. The secondary aims are to determine time to seizure detection for QEEG users compared with standard clinical care and describe impact of confounders on accuracy of seizure detection. METHODS AND ANALYSIS This will be a single-centre, prospective observational cohort study evaluating a paediatric QEEG programme utilising the full 19 electrode set. The setting will be a 36-bed quaternary PICU with medical, cardiac and general surgical cases. cEEG studies in PICU patients identified as 'at risk of seizures' will be analysed. Trained bedside clinical nurses will interpret the QEEG. Seizure events will be marked as seizures if >3 QEEG criteria occur. Post-hoc dedicated neurologists, who remain blinded to the QEEG analysis, will interpret the cEEG. Determination of standard test characteristics will assess the primary hypothesis. To calculate 95% (CIs) around the sensitivity and specificity estimates with a CI width of 10%, the sample size needed for sensitivity is 80 patients assuming each EEG will have approximately 9 to 18 1-hour epochs. ETHICS AND DISSEMINATION The study has received approval by the Children's Health Queensland Human Research Ethics Committee (HREC/19/QCHQ/58145). Results will be made available to the funders, critical care survivors and their caregivers, the relevant societies, and other researchers. TRIAL REGISTRATION NUMBER Australian New Zealand Clinical Trials Registry (ANZCTR) 12621001471875.
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Affiliation(s)
- Michaela Waak
- Queensland Children's Hospital Paediatric Intensive Care Unit, South Brisbane, Queensland, Australia
- Centre for Children's Health Research, Brisbane, Queensland, Australia
| | - Kristen Gibbons
- Centre for Children's Health Research, Brisbane, Queensland, Australia
- The University of Queensland, Saint Lucia, Queensland, Australia
| | - Louise Sparkes
- Queensland Children's Hospital Paediatric Intensive Care Unit, South Brisbane, Queensland, Australia
- Centre for Children's Health Research, Brisbane, Queensland, Australia
| | - Jane Harnischfeger
- Queensland Children's Hospital Paediatric Intensive Care Unit, South Brisbane, Queensland, Australia
| | - Sandra Gurr
- Neurosciences, Queensland Children's Hospital, South Brisbane, Queensland, Australia
| | - Andreas Schibler
- St Andrew's War Memorial Hospital, Spring Hill, Queensland, Australia
| | - Anthony Slater
- Queensland Children's Hospital Paediatric Intensive Care Unit, South Brisbane, Queensland, Australia
| | - Stephen Malone
- The University of Queensland, Saint Lucia, Queensland, Australia
- Neurosciences, Queensland Children's Hospital, South Brisbane, Queensland, Australia
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11
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DiBacco ML, Cavan K, Sansevere AJ. Continuous Video Electroencephalography (EEG) for Event Characterization in Critically Ill Children. J Child Neurol 2022; 37:562-567. [PMID: 35635225 DOI: 10.1177/08830738221096014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
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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Affiliation(s)
- Melissa L DiBacco
- Division of Epilepsy and Neurophysiology, 1862Boston Children's Hospital, Boston, MA, USA.,Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - Kelly Cavan
- Division of Epilepsy and Neurophysiology, 1862Boston Children's Hospital, Boston, MA, USA.,Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - Arnold J Sansevere
- Division of Epilepsy and Neurophysiology, 1862Boston Children's Hospital, Boston, MA, USA.,Department of Neurology, Boston Children's Hospital, Boston, MA, USA.,Department of Neurology, Children's National Hospital, Washington, DC, USA
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12
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Lingappa L, Thiruveedi S, Konanki R, Mohanlal S. Nonconvulsive status epilepticus in children with acute encephalopathy: A prospective observational study. J Pediatr Neurosci 2022. [DOI: 10.4103/jpn.jpn_60_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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13
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Brandl U. Rolle des EEG-Neuromonitorings beim Status epilepticus im Kindesalter. KLIN NEUROPHYSIOL 2021. [DOI: 10.1055/a-1536-8756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
ZusammenfasungDas EEG-Neuromonitoring kann bei den verschiedenen klinischen Formen des Status epilepticus im Kindes- und Jugendalter einen erheblichen Beitrag zur diagnostischen Einschätzung und somit der Steuerung der Therapie leisten. Bei einem konvulsiven Status epilepticus ist sein Einsatz kein Bestandteil der Erstversorgung. Sobald die Indikation für eine Narkose (refraktärer Status epilepticus) gestellt wird, bekommt das EEG-Monitoring eine erhebliche Bedeutung sowohl bei der Steuerung der Narkosetiefe als auch bei der Erkennung subklinischer Durchbruchsanfälle. Daneben kann man damit nicht indizierte Maßnahmen bei langdauernden psychogenen Anfällen vermeiden. Beim nonkonvulsiven Status ist das EEG hingegen bereits bei der Diagnosestellung eine wesentliche Maßnahme, ist aber auch hier eine wertvolle Maßnahme zur Therapiekontrolle. Eine Sonderstellung nimmt das EEG-Monitoring in der Intensivmedizin ein, besonders bei encephalopathischen Krankheitsbildern. Subklinische, elektrographische Status als Komplikation sind bei komatösen Patienten anders kaum zu diagnostizieren. Es zeigte sich in mehreren Studien, dass sie einen ungünstigen Einfluss auf das neurologische Behandlungsergebnis haben.
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Affiliation(s)
- Ulrich Brandl
- Em. Direktor der Klinik für Neuropädiatrie, Universitätsklinikum Jena, Jena
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14
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Yetimakman AF, Kiral E. Quantitative Electroencephalogram in Pediatric Intensive Care Unit in Three Different Clinical Scenarios. JOURNAL OF PEDIATRIC EPILEPSY 2021. [DOI: 10.1055/s-0041-1733858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
AbstractAlthough clinical judgement and sedation scales are primarily used in intensive care units (ICUs) to manage sedation, adjunctive data are needed to direct therapy with sedative and hypnotic agents to prevent side effects and long-term sequelae. In this case report, we described three cases where we used quantitative electroencephalogram (qEEG) data in a pediatric ICU (PICU); to manage these specific clinical situations and to identify the limitations of the qEEG data, two patients were admitted for post–cardiac arrest care and the third was admitted for status epilepticus. In post–cardiac arrest patients, qEEG was mainly used for monitoring depth of sedation and drug titration. Unnecessary use of high-drug doses was prevented, and monitoring also helped to guide clinical intervention for the management of seizure activity. In the patient with status epilepticus, qEEG data on burst suppression and depth of sedation were used. In this report, we describe three different cases where we used qEEG data in a PICU, to give insight on the use of data in specific clinical situations and to describe the limitations of the qEEG data monitoring system.
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Affiliation(s)
- Ayse Filiz Yetimakman
- Department of Pediatric Intensive Care, Kocaeli University Faculty of Medicine, Kocaeli, Turkey
| | - Eylem Kiral
- Department of Pediatric Intensive Care, Faculty of Medicine, Eskisehir Osmangazi University, Eskisehir, Turkey
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Abstract
INTRODUCTION Evidence for continuous EEG monitoring in the pediatric intensive care unit (PICU) is increasing. However, 24/7 access to EEG is not routinely available in most centers, and clinical management is often informed by more limited EEG resources. The experience of EEG was reviewed in a tertiary PICU where 24/7 EEG cover is unavailable. METHODS Retrospective EEG and clinical review of 108 PICU patients. Correlations were carried out between EEG and clinical variables including mortality. The role of EEG in clinical decision making was documented. RESULTS One hundred ninety-six EEGs were carried out in 108 PICU patients over 2.5 years (434 hours of recording). After exclusion of 1 outlying patient with epileptic encephalopathy, 136 EEGs (median duration, 65 minutes; range, 20 minutes to 4 hours 40 minutes) were included. Sixty-two patients (57%) were less than 12 months old. Seizures were detected in 18 of 107 patients (17%); 74% of seizures were subclinical; 72% occurred within the first 30 minutes of recording. Adverse EEG findings were associated with high mortality. Antiepileptic drug use was high in the studied population irrespective of EEG seizure detection. Prevalence of epileptiform discharges and EEG seizures diminished with increasing levels of sedation. CONCLUSIONS EEG provides important diagnostic information in a large proportion of PICU patients. In the absence of 24/7 EEG availability, empirical antiepileptic drug utilization is high.
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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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17
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Fung FW, Parikh DS, Jacobwitz M, Vala L, Donnelly M, Wang Z, Xiao R, Topjian AA, Abend NS. Validation of a model to predict electroencephalographic seizures in critically ill children. Epilepsia 2020; 61:2754-2762. [PMID: 33063870 DOI: 10.1111/epi.16724] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 09/20/2020] [Accepted: 09/21/2020] [Indexed: 01/01/2023]
Abstract
OBJECTIVE Electroencephalographic seizures (ESs) are common in encephalopathic critically ill children, but identification requires extensive resources for continuous electroencephalographic monitoring (CEEG). In a previous study, we developed a clinical prediction rule using three clinical variables (age, acute encephalopathy category, clinically evident seizure[s] prior to CEEG initiation) and two electroencephalographic (EEG) variables (EEG background category and interictal discharges within the first 30 minutes of EEG) to identify patients at high risk for ESs for whom CEEG might be essential. In the current study, we aimed to validate the ES prediction model using an independent cohort. METHODS The prospectively acquired validation cohort consisted of 314 consecutive critically ill children treated in the Pediatric Intensive Care Unit of a quaternary care referral hospital with acute encephalopathy undergoing clinically indicated CEEG. We calculated test characteristics using the previously developed prediction model in the validation cohort. As in the generation cohort study, we selected a 0.10 cutpoint to emphasize sensitivity. RESULTS The incidence of ESs in the validation cohort was 22%. The generation and validation cohorts were alike in most clinical and EEG characteristics. The ES prediction model was well calibrated and well discriminating in the validation cohort. The model had a sensitivity of 90%, specificity of 37%, positive predictive value of 28%, and negative predictive value of 93%. If applied, the model would limit 31% of patients from undergoing CEEG while failing to identify 10% of patients with ESs. The model had similar performance characteristics in the generation and validation cohorts. SIGNIFICANCE A model employing five readily available clinical and EEG variables performed well when validated in a new consecutive cohort. Implementation would substantially reduce CEEG utilization, although some patients with ESs would not be identified. This model may serve a critical role in targeting limited CEEG resources to critically ill children at highest risk for ESs.
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Affiliation(s)
- France W Fung
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.,Departments Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.,Division of Neurology, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Darshana S Parikh
- Division of Neurology, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Marin Jacobwitz
- Division of Neurology, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lisa Vala
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Maureen Donnelly
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Zi Wang
- Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Rui Xiao
- Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Alexis A Topjian
- Department of Anesthesia and Critical Care, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.,Department of Anesthesia and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nicholas S Abend
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.,Departments Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.,Division of Neurology, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.,Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.,Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.,Department of Anesthesia and Critical Care, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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18
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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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19
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Griffith JL, Tomko ST, Guerriero RM. Continuous Electroencephalography Monitoring in Critically Ill Infants and Children. Pediatr Neurol 2020; 108:40-46. [PMID: 32446643 DOI: 10.1016/j.pediatrneurol.2020.04.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 04/14/2020] [Accepted: 04/15/2020] [Indexed: 12/15/2022]
Abstract
Continuous video electroencephalography (CEEG) monitoring of critically ill infants and children has expanded rapidly in recent years. Indications for CEEG include evaluation of patients with altered mental status, characterization of paroxysmal events, and detection of electrographic seizures, including monitoring of patients with limited neurological examination or conditions that put them at high risk for electrographic seizures (e.g., cardiac arrest or extracorporeal membrane oxygenation cannulation). Depending on the inclusion criteria and clinical characteristics of the population studied, the percentage of pediatric patients with electrographic seizures varies from 7% to 46% and with electrographic status epilepticus from 1% to 23%. There is also evidence that epileptiform and background CEEG patterns may provide important information about prognosis in certain clinical populations. Quantitative EEG techniques are emerging as a tool to enhance the value of CEEG to provide real-time bedside data for management and prognosis. Continued research is needed to understand the clinical value of seizure detection and identification of other CEEG patterns on the outcomes of critically ill infants and children.
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Affiliation(s)
- Jennifer L Griffith
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri.
| | - Stuart T Tomko
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri
| | - Réjean M Guerriero
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri
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20
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Implementation and Early Evaluation of a Quantitative Electroencephalography Program for Seizure Detection in the PICU. Pediatr Crit Care Med 2020; 21:543-549. [PMID: 32343109 DOI: 10.1097/pcc.0000000000002278] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES To describe implementation and early evaluation of using quantitative electroencephalography for electrographic seizure detection by PICU clinician staff. DESIGN Prospective observational study of electrographic seizure detection by PICU clinicians in patients monitored with quantitative electroencephalography. Quantitative electroencephalography program implementation included a continuous education and training package. Continuous quantitative electroencephalography monitoring consisted of two-channel amplitude-integrated electroencephalography, color density spectral array, and raw-electroencephalography. SETTING PICU. PATIENTS Children less than 18 years old admitted to the PICU during the 14-month study period and deemed at risk of electrographic seizure. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Real time electrographic seizure detection by a PICU team was analyzed for diagnostic accuracy and promptness, against electrographic seizure identification by a trained neurophysiologist, retrospectively reading the same quantitative electroencephalography and blinded to patient details. One-hundred one of 1,510 consecutive admissions (6.7%) during the study period underwent quantitative electroencephalography monitoring. Status epilepticus (35%) and suspected hypoxic-ischemic injury (32%) were the most common indications for quantitative electroencephalography. Electrographic seizure was diagnosed by the neurophysiologist in 12% (n = 12) of the cohort. PICU clinicians correctly diagnosed all 12 patients (100% sensitivity and negative predictive value). An additional eleven patients had a false-positive diagnosis of electrographic seizure (false-positive rate = 52% [31-73%]) leading to a specificity of 88% (79-94%). Median time to detect seizures was 25 minutes (5-218 min). Delayed recognition of electrographic seizure (> 1 hr from onset) occurred in five patients (5/12, 42%). CONCLUSIONS Early evaluation of quantitative electroencephalography program to detect electrographic seizure by PICU clinicians suggested good sensitivity for electrographic seizure detection. However, the high false-positive rate is a challenge. Ongoing work is needed to reduce the false positive diagnoses and avoid electrographic seizure detection delays. A comprehensive training program and regular refresher updates for clinical staff are key components of the program.
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Fung FW, Jacobwitz M, Parikh DS, Vala L, Donnelly M, Fan J, Xiao R, Topjian AA, Abend NS. Development of a model to predict electroencephalographic seizures in critically ill children. Epilepsia 2020; 61:498-508. [PMID: 32077099 DOI: 10.1111/epi.16448] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 01/23/2020] [Accepted: 01/23/2020] [Indexed: 01/10/2023]
Abstract
OBJECTIVE Electroencephalographic seizures (ESs) are common in encephalopathic critically ill children, but ES identification with continuous electroencephalography (EEG) monitoring (CEEG) is resource-intense. We aimed to develop an ES prediction model that would enable clinicians to stratify patients by ES risk and optimally target limited CEEG resources. We aimed to determine whether incorporating data from a screening EEG yielded better performance characteristics than models using clinical variables alone. METHODS We performed a prospective observational study of 719 consecutive critically ill children with acute encephalopathy undergoing CEEG in the pediatric intensive care unit of a quaternary care institution between April 2017 and February 2019. We identified clinical and EEG risk factors for ES. We evaluated model performance with area under the receiver-operating characteristic (ROC) curve (AUC), validated the optimal model with the highest AUC using a fivefold cross-validation, and calculated test characteristics emphasizing high sensitivity. We applied the optimal operating slope strategy to identify the optimal cutoff to define whether a patient should undergo CEEG. RESULTS The incidence of ES was 26%. Variables associated with increased ES risk included age, acute encephalopathy category, clinical seizures prior to CEEG initiation, EEG background, and epileptiform discharges. Combining clinical and EEG variables yielded better model performance (AUC 0.80) than clinical variables alone (AUC 0.69; P < .01). At a 0.10 cutoff selected to emphasize sensitivity, the optimal model had a sensitivity of 92%, specificity of 37%, positive predictive value of 34%, and negative predictive value of 93%. If applied, the model would limit 29% of patients from undergoing CEEG while failing to identify 8% of patients with ES. SIGNIFICANCE A model employing readily available clinical and EEG variables could target limited CEEG resources to critically ill children at highest risk for ES, making CEEG-guided management a more viable neuroprotective strategy.
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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
| | - Darshana S 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
| | - Lisa Vala
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Maureen Donnelly
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jiaxin Fan
- Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, 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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Abstract
PURPOSE We aimed to determine whether clinical EEG reports obtained from children in the intensive care unit with refractory status epilepticus could provide data for comparative effectiveness research studies. METHODS We conducted a retrospective descriptive study to assess the documentation of key variables within clinical continuous EEG monitoring reports based on the American Clinical Neurophysiology Society's standardized EEG terminology for children with refractory status epilepticus from 10 academic centers. Two pediatric electroencephalographers reviewed the EEG reports. We compared reports generated using free text or templates. RESULTS We reviewed 191 EEG reports. Agreement between the electroencephalographers regarding whether a variable was described in the report ranged from fair to very good. The presence of electrographic seizures (ES) was documented in 46% (87/191) of reports, and these reports documented the time of first ES in 64% (56/87), ES duration in 72% (63/85), and ES frequency in 68% (59/87). Reactivity was documented in 16% (31/191) of reports, and it was more often documented in template than in free-text reports (40% vs. 14%, P = 0.006). Other variables were not differentially reported in template versus free-text reports. CONCLUSIONS Many key EEG features are not documented consistently in clinical continuous EEG monitoring reports, including ES characteristics and reactivity assessment. Standardization may be needed for clinical EEG reports to provide informative data for large multicenter observational studies.
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Current Status of Continuous Electroencephalographic Monitoring in Critically Ill Children. Pediatr Neurol 2019; 101:11-17. [PMID: 31493974 DOI: 10.1016/j.pediatrneurol.2019.07.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Revised: 06/13/2019] [Accepted: 07/26/2019] [Indexed: 11/21/2022]
Abstract
The utilization of continuous electroencephalographic monitoring in critical care units has increased significantly, and several consensus statements and guidelines have been published. The use of critical care electroencephalographic monitoring has become a standard of care in many centers in the United States and other countries. The most common indication is to detect electrographic seizures and status epilepticus. Other indications include monitoring treatment efficacy in patients with electrographic seizures and status epilepticus, evaluating the degree of disturbance of function in patients with encephalopathy, monitoring brain function in patients treated with sedation and neuromuscular blocking agents, and event characterization. The urgent initiation of critical care electroencephalographic monitoring is recommended in certain clinical populations, but varies among institutions. The consensus among neurologists is to start treatment after identifying electrographic seizures or electrographic status epilepticus with or without clinical signs. However, the optimal treatment of nonconvulsive and electrographic-only seizures remains controversial. Critical care electroencephalographic monitoring has significant impact on clinical management, but there is lack of clear evidence that treatment guided by critical care electroencephalographic monitoring leads to improvement of clinical and neurodevelopmental outcome. There are substantial discrepancies among institutions on personnel and technical support used for critical care electroencephalographic monitoring. The optimal critical care electroencephalographic monitoring team should include electroencephalographers with experience in critical care electroencephalographic monitoring interpretation and appropriately trained technologists certified in electroencephalography by the American Board of Registration of Electroencephalographic and Evoked Potential Technologists specializing in critical care electroencephalographic monitoring or long-term monitoring.
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24
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Electrographic seizure burden and outcomes following pediatric status epilepticus. Epilepsy Behav 2019; 101:106409. [PMID: 31420288 DOI: 10.1016/j.yebeh.2019.07.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 07/04/2019] [Indexed: 12/11/2022]
Abstract
Pediatric status epilepticus carries a substantial risk for morbidity and mortality, but the relationship between seizure burden, treatment, and outcome remains incompletely understood. This review summarizes the evidence linking seizure burden and outcomes among critically ill children in the intensive care unit (ICU), a population in whom accurate quantification of seizure burden is possible using continuous electroencephalographic monitoring. Several high-quality observational studies among critically ill children have reported an association between higher seizure burden and worse outcome, even after adjusting for potential confounders such as age, etiology, and illness severity. Although these studies support the hypothesis that seizures contribute to brain injury and worsen outcome, a causal link between seizures and outcome remains to be proven. The relationship between seizures and outcome is likely complex, and dependent on factors such as etiology, preexisting neurological disability, medication exposure, and possibly individual genetic factors. Studies attempting to define this complex relationship will need to measure and account for these factors in their analyses. This article is part of the Special Issue "Proceedings of the 7th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures".
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Topjian AA, de Caen A, Wainwright MS, Abella BS, Abend NS, Atkins DL, Bembea MM, Fink EL, Guerguerian AM, Haskell SE, Kilgannon JH, Lasa JJ, Hazinski MF. Pediatric Post–Cardiac Arrest Care: A Scientific Statement From the American Heart Association. Circulation 2019; 140:e194-e233. [DOI: 10.1161/cir.0000000000000697] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Successful resuscitation from cardiac arrest results in a post–cardiac arrest syndrome, which can evolve in the days to weeks after return of sustained circulation. The components of post–cardiac arrest syndrome are brain injury, myocardial dysfunction, systemic ischemia/reperfusion response, and persistent precipitating pathophysiology. Pediatric post–cardiac arrest care focuses on anticipating, identifying, and treating this complex physiology to improve survival and neurological outcomes. This scientific statement on post–cardiac arrest care is the result of a consensus process that included pediatric and adult emergency medicine, critical care, cardiac critical care, cardiology, neurology, and nursing specialists who analyzed the past 20 years of pediatric cardiac arrest, adult cardiac arrest, and pediatric critical illness peer-reviewed published literature. The statement summarizes the epidemiology, pathophysiology, management, and prognostication after return of sustained circulation after cardiac arrest, and it provides consensus on the current evidence supporting elements of pediatric post–cardiac arrest care.
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26
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Conventional and quantitative EEG in status epilepticus. Seizure 2018; 68:38-45. [PMID: 30528098 DOI: 10.1016/j.seizure.2018.09.011] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Revised: 09/11/2018] [Accepted: 09/14/2018] [Indexed: 01/10/2023] Open
Abstract
PURPOSE To summarize the use of continuous electroencephalographic monitoring (cEEG) in the diagnosis and management of pediatric convulsive status epilepticus (CSE) and subsequent non-convulsive seizures (NCS) with a focus on available guidelines and infrastructure. In addition, we provide an overview of quantitative EEG (QEEG) for the identification of NCS in critically ill children. METHODS We performed a review of the medical literature on the use of cEEG and QEEG in pediatric CSE. This included published guideline, consensus statements, and literature focused on the use of cEEG and QEEG to detect NCS. RESULTS cEEG monitoring is recommended for prompt recognition of ongoing seizures that may be subtle, masked by pharmacologic paralysis, and or converted from convulsive seizures to NCS after administration of anti-seizure medications. Evidence indicating that high seizure burden is associated with worse outcome has motivated prompt recognition and management of NCS. The American Clinical Neurophysiology Society's consensus statement recommends a minimum of 24 h to exclude electrographic seizures, while the Neurocritical Care Society's guideline suggests 48 h in patients that are comatose. The use of QEEG amongst electroencephalographers and critical care medicine providers is increasing for NCS detection in critically ill children. The sensitivity and specificity of QEEG to detect NCS ranges from 65 to 83% and 65-92%, respectively. CONCLUSION The use of cEEG is important to the diagnosis and treatment of NCS or subtle clinical seizures after pediatric CSE. QEEG allows cEEG data to be reviewed and interpreted quickly and is a useful tool for detection of NCS after CSE.
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Benedetti GM, Silverstein FS, Rau SM, Lester SG, Benedetti MH, Shellhaas RA. Sedation and Analgesia Influence Electroencephalography Monitoring in Pediatric Neurocritical Care. Pediatr Neurol 2018; 87:57-64. [PMID: 30049426 DOI: 10.1016/j.pediatrneurol.2018.05.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Accepted: 05/01/2018] [Indexed: 12/11/2022]
Abstract
OBJECTIVES We assessed neuroactive medication use in critically ill children who require neurological consultation and evaluated the associations between administration of these medications and continuous electroencephalography (cEEG) utilization and seizure frequency. METHODS We evaluated exposure to sedatives, analgesics, anesthetics, and paralytics in consecutive patients (0 days to 18 years) for whom neurological consultation was requested in three intensive care units (ICUs) [neonatal (NICU), pediatric (PICU), and cardiothoracic (PCTU)]) at one children's hospital. We assessed cEEG usage and seizure incidence in relation to drug exposure. RESULTS From November 2015 to November 2016, 300 consecutive patients were evaluated (93 NICU, 139 PICU, and 68 PCTU). Ninety-seven (32%) were receiving ≥1 sedative infusion at the time of consultation [NICU 7 (8%), PICU 50(36%), PCTU 40 (58%%]; 91 (30%) received ≥1 paralytic agent within the preceding 24 hours. Continuous electroencephalography was performed more often for patients treated with sedative infusions (81 of 97 versus 133 of 203, P = 0.001) and paralytic medications (80 of 91 versus 134 of 209, P < 0.001) within 24 hours preceding consultation than those who were not. Sixty-eight of 214 (32%) had electrographic seizures (65 of 68 within initial 24 hours of monitoring); seizures were less common among patients who had received sedative infusions (18 of 81 versus 51 of 133, P = 0.014). In multivariable analysis of seizure likelihood, only younger age was associated with increased risk (P = 0.037). CONCLUSIONS Critically ill infants and children are frequently treated with sedatives, anesthetics, analgesics, and paralytics. Neuroactive medications limit bedside neurological assessments and, in this cohort, were associated with increased cEEG usage. Our data underscore the need to study the effect of these medications on clinical care and long-term outcomes.
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Affiliation(s)
- Giulia M Benedetti
- Department of Pediatrics, Division of Pediatric Neurology, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, Michigan
| | - Faye S Silverstein
- Department of Pediatrics, Division of Pediatric Neurology, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, Michigan
| | - Stephanie M Rau
- Department of Pediatrics, Division of Pediatric Neurology, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, Michigan
| | - Shannon G Lester
- Department of Pediatrics, Division of Pediatric Neurology, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, Michigan
| | - Marco H Benedetti
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Renée A Shellhaas
- Department of Pediatrics, Division of Pediatric Neurology, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, Michigan.
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Outcomes following electrographic seizures and electrographic status epilepticus in the pediatric and neonatal ICUs. Curr Opin Neurol 2018; 30:156-164. [PMID: 28118303 DOI: 10.1097/wco.0000000000000425] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW Increasing recognition of electrographic seizures and electrographic status epilepticus in critically ill neonates and children has highlighted the importance of identifying their potential contributions to neurological outcomes to guide optimal management. RECENT FINDINGS Recent studies in children and neonates have found an independent association between increasing seizure burden and worse short-term and long-term outcomes, even after adjusting for other important contributors to outcome such as seizure cause and illness severity. The risk of worse neurological outcome has been shown to increase above a seizure burden threshold of 12-13 min/h, which is considerably lower than the conventional definition of status epilepticus of 30 min/h. Randomized controlled trials in neonates have demonstrated that electroencephalography-targeted therapy can successfully reduce seizure burden, but due to their small size these trials have not been able to demonstrate that more aggressive electroencephalography-targeted treatment of both subclinical and clinical seizures results in improved outcome. SUMMARY Despite mounting evidence for an independent association between increasing seizure burden and worse outcome, further study is needed to determine whether early seizure identification and aggressive antiseizure treatment can improve neurodevelopmental outcomes.
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Vasquez A, Farias-Moeller R, Tatum W. Pediatric refractory and super-refractory status epilepticus. Seizure 2018; 68:62-71. [PMID: 29941225 DOI: 10.1016/j.seizure.2018.05.012] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 05/17/2018] [Accepted: 05/19/2018] [Indexed: 01/01/2023] Open
Abstract
PURPOSE To summarize the available evidence related to pediatric refractory status epilepticus (RSE) and super-refractory status epilepticus (SRSE), with emphasis on epidemiology, etiologies, therapeutic approaches, and clinical outcomes. METHODS Narrative review of the medical literature using MEDLINE database. RESULTS RSE is defined as status epilepticus (SE) that fails to respond to adequately used first- and second-line antiepileptic drugs. SRSE occurs when SE persist for 24 h or more after administration of anesthesia, or recurs after its withdrawal. RSE and SRSE represent complex neurological emergencies associated with long-term neurological dysfunction and high mortality. Challenges in management arise as the underlying etiology is not always promptly recognized and therapeutic options become limited with prolonged seizures. Treatment decisions mainly rely on case series or experts' opinions. The comparative effectiveness of different treatment strategies has not been evaluated in large prospective series or randomized clinical trials. Continuous infusion of anesthetic agents is the most common treatment for RSE and SRSE, although many questions on optimal dosing and rate of administration remain unanswered. The use of non-pharmacological therapies is documented in case series or reports with low level of evidence. In addition to neurological complications resulting from prolonged seizures, children with RSE/SRSE often develop systemic complications associated with polypharmacy and prolonged hospital stay. CONCLUSION RSE and SRSE are neurological emergencies with limited therapeutic options. Multi-national collaborative efforts are desirable to evaluate the safety and efficacy of current RSE/SRSE therapies, and potentially impact patients' outcomes.
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Affiliation(s)
- Alejandra Vasquez
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.
| | - Raquel Farias-Moeller
- Department of Neurology, Division of Pediatric Neurology, Children's Hospital of Wisconsin, Medical College of Wisconsin, Milwaukee, WI, United States.
| | - William Tatum
- Department of Neurology, Mayo Clinic Florida, 4500 San Pablo Rd, Jacksonville, FL, 32224, United States.
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Gaínza-Lein M, Sánchez Fernández I, Loddenkemper T. Use of EEG in critically ill children and neonates in the United States of America. J Neurol 2017; 264:1165-1173. [PMID: 28503704 DOI: 10.1007/s00415-017-8510-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Revised: 05/04/2017] [Accepted: 05/06/2017] [Indexed: 01/06/2023]
Abstract
The objective of the study was to estimate the proportion of patients who receive an electroencephalogram (EEG) among five common indications for EEG monitoring in the intensive care unit: traumatic brain injury (TBI), extracorporeal membrane oxygenation (ECMO), cardiac arrest, cardiac surgery and hypoxic-ischemic encephalopathy (HIE). We performed a retrospective cross-sectional descriptive study utilizing the Kids' Inpatient Database (KID) for the years 2010-2012. The KID is the largest pediatric inpatient database in the USA and it is based on discharge reports created by hospitals for billing purposes. We evaluated the use of electroencephalogram (EEG) or video-electroencephalogram in critically ill children who were mechanically ventilated. The KID database had a population of approximately 6,000,000 pediatric admissions. Among 22,127 admissions of critically ill children who had mechanical ventilation, 1504 (6.8%) admissions had ECMO, 9201 (41.6%) TBI, 4068 (18.4%) HIE, 2774 (12.5%) cardiac arrest, and 4580 (20.7%) cardiac surgery. All five conditions had a higher proportion of males, with the highest (69.8%) in the TBI group. The mortality rates ranged from 7.02 to 39.9% (lowest in cardiac surgery and highest in ECMO). The estimated use of EEG was 1.6% in cardiac surgery, 4.1% in TBI, 7.2% in ECMO, 8.2% in cardiac arrest, and 12.1% in HIE, with an overall use of 5.8%. Among common indications for EEG monitoring in critically ill children and neonates, the estimated proportion of patients actually having an EEG is low.
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Affiliation(s)
- Marina Gaínza-Lein
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Facultad de Medicina, Universidad Austral de Chile, Valdivia, Chile
| | - Iván Sánchez Fernández
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Child Neurology, Hospital Sant Joan de Déu, Universidad de Barcelona, Barcelona, Spain
| | - Tobias Loddenkemper
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
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Abstract
PURPOSE OF REVIEW Approximately one in five children admitted to a pediatric ICU have a new central nervous system injury or a neurological complication of their critical illness. The spectrum of neurologic insults in children is diverse and clinical practice is largely empirical, as few randomized, controlled trials have been reported. This lack of data poses a substantial challenge to the practice of pediatric neurocritical care (PNCC). PNCC has emerged as a novel subspecialty, and its presence is expanding within tertiary care centers. This review highlights the recent advances in the field, with a focus on traumatic brain injury (TBI), cardiac arrest, and stroke as disease models. RECENT FINDINGS Variable approaches to the structure of a PNCC service have been reported, comprising multidisciplinary teams from neurology, critical care, neurosurgery, neuroradiology, and anesthesia. Neurologic morbidity is substantial in critically ill children and the increased use of continuous electroencephalography monitoring has highlighted this burden. Therapeutic hypothermia has not proven effective for treatment of children with severe TBI or out-of-hospital cardiac arrest. However, results of studies of severe TBI suggest that multidisciplinary care in the ICU and adherence to guidelines for care can reduce mortality and improve outcome. SUMMARY There is an unmet need for clinicians with expertise in the practice of brain-directed critical care for children. Although much of the practice of PNCC may remain empiric, a focus on the regionalization of care, creating defined training paths, practice within multidisciplinary teams, protocol-directed care, and improved measures of long-term outcome to quantify the impact of such care can provide evidence to direct the maturation of this field.
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Treatment Trials for Neonatal Seizures: The Effect of Design on Sample Size. PLoS One 2016; 11:e0165693. [PMID: 27824913 PMCID: PMC5100925 DOI: 10.1371/journal.pone.0165693] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 10/17/2016] [Indexed: 12/12/2022] Open
Abstract
Neonatal seizures are common in the neonatal intensive care unit. Clinicians treat these seizures with several anti-epileptic drugs (AEDs) to reduce seizures in a neonate. Current AEDs exhibit sub-optimal efficacy and several randomized control trials (RCT) of novel AEDs are planned. The aim of this study was to measure the influence of trial design on the required sample size of a RCT. We used seizure time courses from 41 term neonates with hypoxic ischaemic encephalopathy to build seizure treatment trial simulations. We used five outcome measures, three AED protocols, eight treatment delays from seizure onset (Td) and four levels of trial AED efficacy to simulate different RCTs. We performed power calculations for each RCT design and analysed the resultant sample size. We also assessed the rate of false positives, or placebo effect, in typical uncontrolled studies. We found that the false positive rate ranged from 5 to 85% of patients depending on RCT design. For controlled trials, the choice of outcome measure had the largest effect on sample size with median differences of 30.7 fold (IQR: 13.7–40.0) across a range of AED protocols, Td and trial AED efficacy (p<0.001). RCTs that compared the trial AED with positive controls required sample sizes with a median fold increase of 3.2 (IQR: 1.9–11.9; p<0.001). Delays in AED administration from seizure onset also increased the required sample size 2.1 fold (IQR: 1.7–2.9; p<0.001). Subgroup analysis showed that RCTs in neonates treated with hypothermia required a median fold increase in sample size of 2.6 (IQR: 2.4–3.0) compared to trials in normothermic neonates (p<0.001). These results show that RCT design has a profound influence on the required sample size. Trials that use a control group, appropriate outcome measure, and control for differences in Td between groups in analysis will be valid and minimise sample size.
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Lamblin MD, Szurhaj W, Chochoi M, Delval A, Derambure P. Monitorage EEG continu en réanimation. Neurophysiol Clin 2016. [DOI: 10.1016/j.neucli.2016.06.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Smith DM, McGinnis EL, Walleigh DJ, Abend NS. Management of Status Epilepticus in Children. J Clin Med 2016; 5:jcm5040047. [PMID: 27089373 PMCID: PMC4850470 DOI: 10.3390/jcm5040047] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Revised: 04/02/2016] [Accepted: 04/07/2016] [Indexed: 01/04/2023] Open
Abstract
Status epilepticus is a common pediatric neurological emergency. Management includes prompt administration of appropriately selected anti-seizure medications, identification and treatment of seizure precipitant(s), as well as identification and management of associated systemic complications. This review discusses the definitions, classification, epidemiology and management of status epilepticus and refractory status epilepticus in children.
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Affiliation(s)
- Douglas M Smith
- Departments of Neurology and Pediatrics, The Perelman School of Medicine at the University of Pennsylvania, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
| | - Emily L McGinnis
- Departments of Neurology and Pediatrics, The Perelman School of Medicine at the University of Pennsylvania, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
| | - Diana J Walleigh
- Departments of Neurology and Pediatrics, The Perelman School of Medicine at the University of Pennsylvania, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
| | - Nicholas S Abend
- Departments of Neurology and Pediatrics, The Perelman School of Medicine at the University of Pennsylvania, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
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Consensus statement on continuous EEG in critically ill adults and children, part I: indications. J Clin Neurophysiol 2016; 32:87-95. [PMID: 25626778 DOI: 10.1097/wnp.0000000000000166] [Citation(s) in RCA: 382] [Impact Index Per Article: 47.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
INTRODUCTION Critical Care Continuous EEG (CCEEG) is a common procedure to monitor brain function in patients with altered mental status in intensive care units. There is significant variability in patient populations undergoing CCEEG and in technical specifications for CCEEG performance. METHODS The Critical Care Continuous EEG Task Force of the American Clinical Neurophysiology Society developed expert consensus recommendations on the use of CCEEG in critically ill adults and children. RECOMMENDATIONS The consensus panel recommends CCEEG for diagnosis of nonconvulsive seizures, nonconvulsive status epilepticus, and other paroxysmal events, and for assessment of the efficacy of therapy for seizures and status epilepticus. The consensus panel suggests CCEEG for identification of ischemia in patients at high risk for cerebral ischemia; for assessment of level of consciousness in patients receiving intravenous sedation or pharmacologically induced coma; and for prognostication in patients after cardiac arrest. For each indication, the consensus panel describes the patient populations for which CCEEG is indicated, evidence supporting use of CCEEG, utility of video and quantitative EEG trends, suggested timing and duration of CCEEG, and suggested frequency of review and interpretation. CONCLUSION CCEEG has an important role in detection of secondary injuries such as seizures and ischemia in critically ill adults and children with altered mental status.
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Consensus statement on continuous EEG in critically ill adults and children, part II: personnel, technical specifications, and clinical practice. J Clin Neurophysiol 2016; 32:96-108. [PMID: 25626777 DOI: 10.1097/wnp.0000000000000165] [Citation(s) in RCA: 161] [Impact Index Per Article: 20.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
INTRODUCTION Critical Care Continuous EEG (CCEEG) is a common procedure to monitor brain function in patients with altered mental status in intensive care units. There is significant variability in patient populations undergoing CCEEG and in technical specifications for CCEEG performance. METHODS The Critical Care Continuous EEG Task Force of the American Clinical Neurophysiology Society developed expert consensus recommendations on the use of CCEEG in critically ill adults and children. RECOMMENDATIONS The consensus panel describes the qualifications and responsibilities of CCEEG personnel including neurodiagnostic technologists and interpreting physicians. The panel outlines required equipment for CCEEG, including electrodes, EEG machine and amplifier specifications, equipment for polygraphic data acquisition, EEG and video review machines, central monitoring equipment, and network, remote access, and data storage equipment. The consensus panel also describes how CCEEG should be acquired, reviewed and interpreted. The panel suggests methods for patient selection and triage; initiation of CCEEG; daily maintenance of CCEEG; electrode removal and infection control; quantitative EEG techniques; EEG and behavioral monitoring by non-physician personnel; review, interpretation, and reports; and data storage protocols. CONCLUSION Recommended qualifications for CCEEG personnel and CCEEG technical specifications will facilitate standardization of this emerging technology.
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Abstract
Recognition of nonconvulsive status epilepticus (NCSE) is gaining increasing attention in the assessment and evaluation of critically ill pediatric patients. The underlying cause of NCSE is often the most important factor in determining outcome. However, there is a growing body of literature suggesting that electrical seizure burden in NCSE also contributes to unfavorable outcomes. Determination of impact of NCSE on outcome based on current evidence involves consideration of heterogeneous study settings, study populations, and process of care and outcome measures. In addition, the lack of data on neurocognitive function prior to episodes of NCSE as well as limited long-term neurocognitive assessment data confines precise conclusions about neurocognitive changes. This article is part of a Special Issue entitled "Status Epilepticus".
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Affiliation(s)
- Saba Jafarpour
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Tobias Loddenkemper
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
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Detection of electrographic seizures by critical care providers using color density spectral array after cardiac arrest is feasible. Pediatr Crit Care Med 2015; 16:461-7. [PMID: 25651050 PMCID: PMC4456208 DOI: 10.1097/pcc.0000000000000352] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
OBJECTIVE To determine the accuracy and reliability of electroencephalographic seizure detection by critical care providers using color density spectral array electroencephalography. DESIGN Tutorial and questionnaire. SUBJECTS Critical care providers (attending physicians, fellow trainees, and nurses). INTERVENTIONS A standardized powerpoint color density spectral array tutorial followed by classification of 200 color density spectral array images as displaying seizures or not displaying seizures. MEASUREMENTS AND MAIN RESULTS Using conventional electroencephalography recordings obtained from patients who underwent electroencephalography monitoring after cardiac arrest, we created 100 color density spectral array images, 30% of which displayed seizures. The gold standard for seizure category was electroencephalographer determination from the full montage conventional electroencephalography. Participants did not have access to the conventional electroencephalography tracings. After completing a standardized color density spectral array tutorial, images were presented to participants in duplicate and in random order. Twenty critical care physicians (12 attendings and eight fellows) and 19 critical care nurses classified the color density spectral array images as having any seizure(s) or no seizures. The 39 critical care providers had a color density spectral array seizure detection sensitivity of 70% (95% CI, 67-73%), specificity of 68% (95% CI, 67-70%), positive predictive value of 46%, and negative predictive value of 86%. The sensitivity of color density spectral array detection of status epilepticus was 72% (95% CI, 69-74%). CONCLUSION Determining which post-cardiac arrest patients experience electrographic seizures by critical care providers is feasible after a brief training. There is moderate sensitivity for seizure and status epilepticus detection and a high negative predictive value.
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Hansen G, Joffe AR, Bowman SM, Richer L. Nonconvulsive seizures and status epilepticus in pediatric head trauma: A national survey. SAGE Open Med 2015; 3:2050312115573817. [PMID: 26770768 PMCID: PMC4679225 DOI: 10.1177/2050312115573817] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2014] [Accepted: 01/22/2015] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVES It remains uncertain whether nonconvulsive seizures and nonconvulsive status epilepticus in pediatric traumatic brain injury are deleterious to the brain and/or impact the recovery from injury. Consequently, optimal electroencephalographic surveillance and management is unknown. We aimed to determine specialists' opinion regarding the detection and treatment of nonconvulsive seizures or nonconvulsive status epilepticus in pediatric traumatic brain injury, regardless of their practice. METHODS In 2012, 183 surveys were sent to all 93 neurologists, 27 neurosurgeons, and 63 intensivists in the14 tertiary pediatric hospitals across Canada. The survey included an initial scenario of pediatric TBI that evolved into three further scenarios. Each scenario had required responses and an embedded branching logic algorithm ascertaining clinical management. The survey instrument assimilated data about the importance of nonconvulsive status epilepticus and nonconvulsive seizures detection and treatment, and whether they are a cause of brain injury that adversely affects neurologic outcomes. RESULTS Of the 79 specialists who replied (43% response rate), 68%-78% elected to order an electroencephalographic across all four scenarios, and one-third (31%-36%; scenario dependent) would request an urgent electroencephalographic (within the hour) in the comatose pediatric traumatic brain injury patient. In the absence of pharmacologic paralysis or intracranial pressure spikes, half-hour electroencephalographic (41%-55%) was preferred over ⩾24-h continuous electroencephalographic monitoring (29%-40%). Finally, nonconvulsive status epilepticus (81%-87%) and nonconvulsive seizures (61%-73%) were considered to be a cause of poor neurologic outcomes warranting aggressive pharmacologic management. CONCLUSION The Canadian specialists' opinion is that nonconvulsive seizures and nonconvulsive status epilepticus are biomarkers of brain injury and contribute to worsened outcomes. This suggests the urgency of future outcome-oriented research in the identification and management of nonconvulsive seizures or nonconvulsive status epilepticus.
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Affiliation(s)
| | - Ari R Joffe
- Department of Pediatrics, University of Alberta, Edmonton, AB, Canada
| | - Stephen M Bowman
- Johns Hopkins University, Baltimore, MD, USA
- University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Lawrence Richer
- Department of Pediatrics, University of Alberta, Edmonton, AB, Canada
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Nguyen The Tich S, Cheliout-Heraut F. Continuous EEG monitoring in children in the intensive care unit (ICU). Neurophysiol Clin 2015; 45:75-80. [PMID: 25660126 DOI: 10.1016/j.neucli.2014.11.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2014] [Accepted: 11/16/2014] [Indexed: 11/30/2022] Open
Abstract
Pediatric EEG in the intensive care unit (ICU) requires specific technical requirements in order to yield relevant data depending upon clinical scenario: diagnosis of electroclinical or subclinical seizures, their quantification before and after therapeutic changes and sometimes evaluation of severity of cortical dysfunction. The urgent nature of these indications implies the rapid set-up of the EEG system by qualified staff and possibility of maintaining the electrodes in place during long periods of time. Various techniques are available today for EEG monitoring, the interpretation of which depends on the contribution of an experienced physician. Among recent techniques, those most commonly used are trend curves obtained via signal analysis such as amplitude EEG (a-EEG) and density spectral array (DSA) or compressed spectral array (CSA). Trend curves enable the digital creation of a display graph containing several hours of transformed and compressed EEG recorded data. Visualized on one sole display graph, these trend curves can facilitate the identification of very slow changes in EEG background activity and their variation (alertness cycles, changes linked to treatment administrations) as well as seizure patterns and their quantification. In this chapter, we propose a brief overview of monitoring techniques, followed by a review of the various data yielded by EEG monitoring as well as the relevance of this type of management; finally, detailed clinical indications will be discussed after thorough analysis of the literature.
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Affiliation(s)
- S Nguyen The Tich
- Unité de Neurologie pédiatrique, CHU d'Angers, LARIS EA 7315, LUNAM, Angers, France.
| | - F Cheliout-Heraut
- Service de physiologie-explorations fonctionnelles, CHU de Garches, UVSQ, Garches, France
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Yang A, Arndt DH, Berg RA, Carpenter JL, Chapman KE, Dlugos DJ, Gallentine WB, Giza CC, Goldstein JL, Hahn CD, Lerner JT, Loddenkemper T, Matsumoto JH, Nash KB, Payne ET, Sánchez Fernández I, Shults J, Topjian AA, Williams K, Wusthoff CJ, Abend NS. Development and validation of a seizure prediction model in critically ill children. Seizure 2015; 25:104-11. [PMID: 25458097 PMCID: PMC4315714 DOI: 10.1016/j.seizure.2014.09.013] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2014] [Revised: 09/25/2014] [Accepted: 09/29/2014] [Indexed: 11/15/2022] Open
Abstract
PURPOSE Electrographic seizures are common in encephalopathic critically ill children, but identification requires continuous EEG monitoring (CEEG). Development of a seizure prediction model would enable more efficient use of limited CEEG resources. We aimed to develop and validate a seizure prediction model for use among encephalopathic critically ill children. METHOD We developed a seizure prediction model using a retrospectively acquired multi-center database of children with acute encephalopathy without an epilepsy diagnosis, who underwent clinically indicated CEEG. We performed model validation using a separate prospectively acquired single center database. Predictor variables were chosen to be readily available to clinicians prior to the onset of CEEG and included: age, etiology category, clinical seizures prior to CEEG, initial EEG background category, and inter-ictal discharge category. RESULTS The model has fair to good discrimination ability and overall performance. At the optimal cut-off point in the validation dataset, the model has a sensitivity of 59% and a specificity of 81%. Varied cut-off points could be chosen to optimize sensitivity or specificity depending on available CEEG resources. CONCLUSION Despite inherent variability between centers, a model developed using multi-center CEEG data and few readily available variables could guide the use of limited CEEG resources when applied at a single center. Depending on CEEG resources, centers could choose lower cut-off points to maximize identification of all patients with seizures (but with more patients monitored) or higher cut-off points to reduce resource utilization by reducing monitoring of lower risk patients (but with failure to identify some patients with seizures).
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Affiliation(s)
- Amy Yang
- Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at The University of Pennsylvania, United States
| | - Daniel H Arndt
- Departments of Pediatrics and Neurology, Beaumont Children's Hospital and Oakland University William Beaumont School of Medicine, Royal Oak, MI, United States
| | - Robert A Berg
- Department of Anesthesia and Critical Care Medicine, The Children's Hospital of Philadelphia and The Perelman School of Medicine at The University of Pennsylvania, Philadelphia, PA, United States
| | - Jessica L Carpenter
- Department of Neurology, Children's National Medical Center, Washington, DC, United States
| | - Kevin E Chapman
- Department of Pediatrics and Neurology, Children's Hospital Colorado and University of Colorado School of Medicine, Aurora, CO, United States
| | - 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, United States
| | - William B Gallentine
- Division of Neurology, Duke Children's Hospital and Duke University School of Medicine, Durham, NC, United States
| | - 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, United States
| | - Joshua L Goldstein
- Division of Neurology, Children's Memorial Hospital and Northwestern University Feinberg School of Medicine, Chicago, IL, United States
| | - Cecil D Hahn
- Division of Neurology, The Hospital for Sick Children and University of Toronto, Toronto, ON, United States
| | - 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, United States
| | - Tobias Loddenkemper
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - 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, United States
| | - Kendall B Nash
- Department of Neurology, University of California San Francisco, San Francisco, CA, United States
| | - Eric T Payne
- Division of Neurology, The Hospital for Sick Children and University of Toronto, Toronto, ON, United States
| | - Iván Sánchez Fernández
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Justine Shults
- Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at The University of Pennsylvania, United States
| | - Alexis A Topjian
- Department of Anesthesia and Critical Care Medicine, The Children's Hospital of Philadelphia and The Perelman School of Medicine at The University of Pennsylvania, Philadelphia, PA, United States
| | - Korwyn Williams
- Department of Pediatrics, University of Arizona College of Medicine and Barrow's Neurological Institute at Phoenix Children's Hospital, Phoenix, AZ, United States
| | - Courtney J Wusthoff
- Division of Child Neurology, Stanford University, Palo Alto, CA, United States
| | - 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, United States.
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42
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Grinspan ZM, Pon S, Greenfield JP, Malhotra S, Kosofsky BE. Multimodal monitoring in the pediatric intensive care unit: new modalities and informatics challenges. Semin Pediatr Neurol 2014; 21:291-8. [PMID: 25727511 DOI: 10.1016/j.spen.2014.10.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
We review several newer modalities to monitor the brain in children with acute neurologic disease in the pediatric intensive care unit, such as partial brain tissue oxygen tension (PbtO2), jugular venous oxygen saturation (SjvO2), near infrared spectroscopy (NIRS), thermal diffusion measurement of cerebral blood flow, cerebral microdialysis, and EEG. We then discuss the informatics challenges to acquire, consolidate, analyze, and display the data. Acquisition includes multiple data types: discrete, waveform, and continuous. Consolidation requires device interoperability and time synchronization. Analysis could include pressure reactivity index and quantitative EEG. Displays should communicate the patient's current status, longitudinal and trend information, and critical alarms.
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Affiliation(s)
- Zachary M Grinspan
- Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY; Department of Pediatrics, Weill Cornell Medical College, New York, NY; Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, NY; New York Presbyterian Hospital, New York, NY.
| | - Steven Pon
- Department of Pediatrics, Weill Cornell Medical College, New York, NY; New York Presbyterian Hospital, New York, NY
| | - Jeffrey P Greenfield
- New York Presbyterian Hospital, New York, NY; Department of Neurologic Surgery, Weill Cornell Medical College, New York, NY
| | - Sameer Malhotra
- Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, NY; New York Presbyterian Hospital, New York, NY; Physician Organization, Weill Cornell Medical College, New York, NY
| | - Barry E Kosofsky
- Department of Pediatrics, Weill Cornell Medical College, New York, NY; New York Presbyterian Hospital, New York, NY
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Abstract
PURPOSE OF REVIEW To discuss the use of continuous video-electroencephalographic (cEEG) monitoring among critically ill children at risk for electrographic seizures and status epilepticus. RECENT FINDINGS Recent reports have demonstrated the growing, but heterogeneous, use of cEEG monitoring among North American pediatric institutions, and provided evidence for the high prevalence of subclinical seizures, particularly among encephalopathic patients with acute brain injury. Increasing seizure burden and status epilepticus have been shown to be independently associated with worse short-term and long-term outcomes. SUMMARY Certain high-risk children frequently experience electrographic seizures and status epilepticus, often without clinical signs, necessitating the use of cEEG monitoring for their diagnosis and management. Although an increasing electrographic seizure burden and status epilepticus are independently associated with worse outcome, further studies are needed to determine whether aggressive use of antiepileptic drugs to reduce seizure burden can improve outcome.
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44
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[French guidelines on electroencephalogram]. Neurophysiol Clin 2014; 44:515-612. [PMID: 25435392 DOI: 10.1016/j.neucli.2014.10.001] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2014] [Accepted: 10/07/2014] [Indexed: 12/11/2022] Open
Abstract
Electroencephalography allows the functional analysis of electrical brain cortical activity and is the gold standard for analyzing electrophysiological processes involved in epilepsy but also in several other dysfunctions of the central nervous system. Morphological imaging yields complementary data, yet it cannot replace the essential functional analysis tool that is EEG. Furthermore, EEG has the great advantage of being non-invasive, easy to perform and allows control tests when follow-up is necessary, even at the patient's bedside. Faced with the advances in knowledge, techniques and indications, the Société de Neurophysiologie Clinique de Langue Française (SNCLF) and the Ligue Française Contre l'Épilepsie (LFCE) found it necessary to provide an update on EEG recommendations. This article will review the methodology applied to this work, refine the various topics detailed in the following chapters. It will go over the summary of recommendations for each of these chapters and underline proposals for writing an EEG report. Some questions could not be answered by the review of the literature; in those cases, an expert advice was given by the working and reading groups in addition to the guidelines.
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45
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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: 41] [Impact Index Per Article: 4.1] [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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