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Sansevere AJ, Keenan JS, Pickup E, Conley C, Staso K, Harrar DB. Ictal-Interictal Continuum in the Pediatric Intensive Care Unit. Neurocrit Care 2024:10.1007/s12028-024-01978-4. [PMID: 38671312 DOI: 10.1007/s12028-024-01978-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 03/08/2024] [Indexed: 04/28/2024]
Abstract
BACKGROUND The ictal-interictal continuum (IIC) consists of several electroencephalogram (EEG) patterns that are common in critically ill adults. Studies focused on the IIC are limited in critically ill children and have focused primarily on associations with electrographic seizures (ESs). We report the incidence of the IIC in the pediatric intensive care unit (PICU). We then compare IIC patterns to rhythmic and periodic patterns (RPP) not meeting IIC criteria looking for associations with acute cerebral abnormalities, ES, and in-hospital mortality. METHODS This was a retrospective review of prospectively collected data for patients admitted to the PICU at Children's National Hospital from July 2021 to January 2023 with continuous EEG. We excluded patients with known epilepsy and cerebral injury prior to presentation. All patients were screened for RPP. The American Clinical Neurophysiology Society standardized Critical Care EEG terminology for the IIC was applied to each RPP. Associations between IIC and RPP not meeting IIC criteria, with clinical and EEG variables, were calculated using odds ratios (ORs). RESULTS Of 201 patients, 21% (42/201) had RPP and 12% (24/201) met IIC criteria. Among patients with an IIC pattern, the median age was 3.4 years (interquartile range (IQR) 0.6-12 years). Sixty-seven percent (16/24) of patients met a single IIC criterion, whereas the remainder met two criteria. ESs were identified in 83% (20/24) of patients and cerebral injury was identified in 96% (23/24) of patients with IIC patterns. When comparing patients with IIC patterns with those with RPP not qualifying as an IIC pattern, both patterns were associated with acute cerebral abnormalities (IIC OR 26 [95% confidence interval {CI} 3.4-197], p = 0.0016 vs. RPP OR 3.5 [95% CI 1.1-11], p = 0.03), however, only the IIC was associated with ES (OR 121 [95% CI 33-451], p < 0.0001) versus RPP (OR 1.3 [0.4-5], p = 0.7). CONCLUSIONS Rhythmic and periodic patterns and subsequently the IIC are commonly seen in the PICU and carry a high association with cerebral injury. Additionally, the IIC, seen in more than 10% of critically ill children, is associated with ES. The independent impact of RPP and IIC patterns on secondary brain injury and need for treatment of these patterns independent of ES requires further study.
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Affiliation(s)
- Arnold J Sansevere
- Department of Neurology/Division of Epilepsy and Clinical Neurophysiology, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA.
| | - Julia S Keenan
- Department of Neurology/Division of Epilepsy and Clinical Neurophysiology, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Elizabeth Pickup
- Department of Neurology/Division of Epilepsy and Clinical Neurophysiology, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Caroline Conley
- Department of Neurology/Division of Epilepsy and Clinical Neurophysiology, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
- Department of Critical Care Medicine, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Katelyn Staso
- Department of Neurology/Division of Epilepsy and Clinical Neurophysiology, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
- Department of Critical Care Medicine, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Dana B Harrar
- Department of Neurology/Division of Epilepsy and Clinical Neurophysiology, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
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Sansevere AJ, Janatti A, DiBacco ML, Cavan K, Rotenberg A. Background EEG Suppression Ratio for Early Detection of Cerebral Injury in Pediatric Cardiac Arrest. Neurocrit Care 2024:10.1007/s12028-023-01920-0. [PMID: 38302644 DOI: 10.1007/s12028-023-01920-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 12/05/2023] [Indexed: 02/03/2024]
Abstract
BACKGROUND Our objective was to assess the utility of the 1-h suppression ratio (SR) as a biomarker of cerebral injury and neurologic prognosis after cardiac arrest (CA) in the pediatric hospital setting. METHODS Prospectively, we reviewed data from children presenting after CA and monitored by continuous electroencephalography (cEEG). Patients aged 1 month to 21 years were included. The SR, a quantitative measure of low-voltage cEEG (≤ 3 µV) content, was dichotomized as present or absent if there was > 0% suppression for one continuous hour. A multivariate logistic regression analysis was performed including age, sex, type of CA (i.e., in-hospital or out-of-hospital), and the presence of SR as a predictor of global anoxic cerebral injury as confirmed by magnetic resonance imaging (MRI). RESULTS We included 84 patients with a median age of 4 years (interquartile range 0.9-13), 64% were male, and 49% (41/84) had in-hospital CA. Cerebral injury was seen in 50% of patients, of whom 65% had global injury. One-hour SR presence, independent of amount, predicted cerebral injury with 81% sensitivity (95% confidence interval (CI) (66-91%) and 98% specificity (95% CI 88-100%). Multivariate logistic regression analyses indicated that SR was a significant predictor of both cerebral injury (β = 6.28, p < 0.001) and mortality (β = 3.56, p < 0.001). CONCLUSIONS The SR a sensitive and specific marker of anoxic brain injury and post-CA mortality in the pediatric population. Once detected in the post-CA setting, the 1-h SR may be a useful threshold finding for deployment of early neuroprotective strategies prior or for prompting diagnostic neuroimaging.
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Affiliation(s)
- Arnold J Sansevere
- Division of Epilepsy and Neurophysiology, Boston Children's Hospital, Boston, MA, USA.
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA.
- Division of Epilepsy, Department of Neurology, Children's National Hospital, 111 Michigan Ave NW, Washington, DC, 20001, USA.
| | - Ali Janatti
- Division of Epilepsy and Neurophysiology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - Melissa L DiBacco
- Division of Epilepsy and Neurophysiology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - Kelly Cavan
- Division of Epilepsy and Neurophysiology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - Alexander Rotenberg
- Division of Epilepsy and Neurophysiology, Boston Children's Hospital, Boston, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
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Gupta S, Ritzl EK, Husari KS. Lateralized Rhythmic Delta Activity and Lateralized Periodic Discharges in Critically Ill Pediatric Patients. J Clin Neurophysiol 2024:00004691-990000000-00121. [PMID: 38194635 DOI: 10.1097/wnp.0000000000001064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2024] Open
Abstract
PURPOSE To evaluate the clinical and electrographic characteristics of critically ill pediatric patients with lateralized rhythmic delta activity (LRDA) and compare them with patients with lateralized periodic discharges (LPDs). METHODS This was a retrospective study examining consecutive critically ill pediatric patients (1 month-18 years) with LRDA or LPDs monitored on continuous electroencephalography. Clinical, radiologic, and electrographic characteristics; disease severity; and acute sequelae were compared between the two groups. RESULTS Of 668 pediatric patients monitored on continuous electroencephalography during the study period, 12 (1.79%) patients had LRDA and 15 (2.24%) had LPDs. The underlying etiologies were heterogeneous with no difference in the acuity of brain MRI changes between both groups. Lateralized rhythmic delta activity and LPDs were concordant with the side of MRI abnormality in most patients [85.7% (LRDA) and 83.3% (LPD)]. There was no difference in the measures of disease severity between both groups. Seizures were frequent in both groups (42% in the LRDA group and 73% in the LPD group). Patients in the LPD group had a trend toward requiring a greater number of antiseizure medications for seizure control (median of 4 vs. 2 in the LRDA group, p = 0.09), particularly those patients with LPDs qualifying as ictal-interictal continuum compared with those without ictal-interictal continuum (p = 0.02). CONCLUSIONS Lateralized rhythmic delta activity and LPDs are uncommon EEG findings in the pediatric population. Seizures occur commonly in patients with these patterns. Seizures in patients with LPDs, especially those qualifying as ictal-interictal continuum, showed a trend toward being more refractory. Larger studies are needed in the future to further evaluate these findings.
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Affiliation(s)
- Siddharth Gupta
- Comprehensive Epilepsy Center, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, U.S.A
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Benedetti GM, Guerriero RM, Press CA. Review of Noninvasive Neuromonitoring Modalities in Children II: EEG, qEEG. Neurocrit Care 2023; 39:618-638. [PMID: 36949358 PMCID: PMC10033183 DOI: 10.1007/s12028-023-01686-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 01/30/2023] [Indexed: 03/24/2023]
Abstract
Critically ill children with acute neurologic dysfunction are at risk for a variety of complications that can be detected by noninvasive bedside neuromonitoring. Continuous electroencephalography (cEEG) is the most widely available and utilized form of neuromonitoring in the pediatric intensive care unit. In this article, we review the role of cEEG and the emerging role of quantitative EEG (qEEG) in this patient population. cEEG has long been established as the gold standard for detecting seizures in critically ill children and assessing treatment response, and its role in background assessment and neuroprognostication after brain injury is also discussed. We explore the emerging utility of both cEEG and qEEG as biomarkers of degree of cerebral dysfunction after specific injuries and their ability to detect both neurologic deterioration and improvement.
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Affiliation(s)
- Giulia M Benedetti
- Division of Pediatric Neurology, Department of Neurology, Seattle Children's Hospital and the University of Washington School of Medicine, Seattle, WA, USA.
- Division of Pediatric Neurology, Department of Pediatrics, C.S. Mott Children's Hospital and the University of Michigan, 1540 E Hospital Drive, Ann Arbor, MI, 48109-4279, USA.
| | - Rejéan M Guerriero
- Division of Pediatric and Developmental Neurology, Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Craig A Press
- Departments of Neurology and Pediatric, Children's Hospital of Philadelphia and Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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Knipe MF, Bush WW, Thomas KE, Williams DC. Periodic discharges in veterinary electroencephalography-A visual review. Front Vet Sci 2023; 10:1037404. [PMID: 36777678 PMCID: PMC9909489 DOI: 10.3389/fvets.2023.1037404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 01/03/2023] [Indexed: 01/27/2023] Open
Abstract
First described in human EEG over 60 years ago, there are very few examples of periodic discharges in the veterinary literature. They are associated with a wide variety of etiologies, both intracranial and systemic, making interpretation challenging. Whether these patterns are indicative of ictal, interictal, or postictal activity is a matter of debate and may vary depending on the clinical features in an individual patient. Periodic discharges have a repeated waveform occurring at nearly regular intervals, with varying morphology of individual discharges from simple sharp waves or slow waves to more complex events. Amplitudes, frequencies, and morphologies of the discharges can fluctuate, occasionally evolving, or resolving over time. This study presents a visual review of several veterinary cases with periodic discharges on EEG similar to those described in human EEG, and discusses the current known pathophysiology of these discharges.
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Affiliation(s)
- Marguerite F. Knipe
- Department of Surgical and Radiological Sciences, School of Veterinary Medicine, University of California, Davis, Davis, CA, United States,*Correspondence: Marguerite F. Knipe ✉
| | - William W. Bush
- Bush Veterinary Neurology Service, Leesburg, VA, United States
| | | | - D. Colette Williams
- School of Veterinary Medicine, William R. Pritchard Veterinary Medical Teaching Hospital, University of California, Davis, Davis, CA, United States
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Fung FW, Parikh DS, Massey SL, Fitzgerald MP, Vala L, Donnelly M, Jacobwitz M, Kessler SK, Topjian AA, Abend NS. Periodic and rhythmic patterns in critically ill children: Incidence, interrater agreement, and seizures. Epilepsia 2021; 62:2955-2967. [PMID: 34642942 DOI: 10.1111/epi.17068] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 08/27/2021] [Accepted: 09/01/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVES We aimed to determine the incidence of periodic and rhythmic patterns (PRP), assess the interrater agreement between electroencephalographers scoring PRP using standardized terminology, and analyze associations between PRP and electrographic seizures (ES) in critically ill children. METHODS This was a prospective observational study of consecutive critically ill children undergoing continuous electroencephalographic monitoring (CEEG). PRP were identified by one electroencephalographer, and then two pediatric electroencephalographers independently scored the first 1-h epoch that contained PRP using standardized terminology. We determined the incidence of PRPs, evaluated interrater agreement between electroencephalographers scoring PRP, and evaluated associations between PRP and ES. RESULTS One thousand three hundred ninety-nine patients underwent CEEG. ES occurred in 345 (25%) subjects. PRP, ES + PRP, and ictal-interictal continuum (IIC) patterns occurred in 142 (10%), 81 (6%), and 93 (7%) subjects, respectively. The most common PRP were generalized periodic discharges (GPD; 43, 30%), lateralized periodic discharges (LPD; 34, 24%), generalized rhythmic delta activity (GRDA; 34, 24%), bilateral independent periodic discharges (BIPD; 14, 10%), and lateralized rhythmic delta activity (LRDA; 11, 8%). ES risk varied by PRP type (p < .01). ES occurrence was associated with GPD (odds ratio [OR] = 6.35, p < .01), LPD (OR = 10.45, p < .01), BIPD (OR = 6.77, p < .01), and LRDA (OR = 6.58, p < .01). Some modifying features increased the risk of ES for each of those PRP. GRDA was not significantly associated with ES (OR = 1.34, p = .44). Each of the IIC patterns was associated with ES (OR = 6.83-8.81, p < .01). ES and PRP occurred within 6 h (before or after) in 45 (56%) subjects. SIGNIFICANCE PRP occurred in 10% of critically ill children who underwent CEEG. The most common patterns were GPD, LPD, GRDA, BIPD, and LRDA. The GPD, LPD, BIPD, LRDA, and IIC patterns were associated with ES. GRDA was not associated with ES.
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Affiliation(s)
- France W Fung
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Darshana S Parikh
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Shavonne L Massey
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Mark P Fitzgerald
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Lisa Vala
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Maureen Donnelly
- Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Marin Jacobwitz
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Sudha K Kessler
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Alexis A Topjian
- Department of Anesthesia and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Nicholas S Abend
- Department of Pediatrics (Division of Neurology), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Departments of Neurology and Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.,Department of Neurodiagnostics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Anesthesia & Critical Care, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.,Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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7
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Miyashiro L, Oliveira DE Paulo C, Twardowschy CA. Presence of generalized periodic discharges and hospital mortality. ARQUIVOS DE NEURO-PSIQUIATRIA 2020; 78:356-360. [PMID: 32401832 DOI: 10.1590/0004-282x20200026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 02/19/2020] [Indexed: 11/21/2022]
Abstract
BACKGROUND Generalized periodic discharges (GPDs) are rare patterns that can be found in long-term electroencephalographic monitoring in critical patients. These patterns have been correlated with non-seizure crisis and non-convulsive status epilepticus, associated with poor prognosis. OBJECTIVE To compare the outcome between patients who developed GPDs and patients with other abnormalities in long-term electroencephalographic monitoring. METHODS A retrospective study was performed by analyzing the medical records of 112 patients over 18 years who developed GPDs during long-term electroencephalographic monitoring (12‒16 hours of monitoring) in the intensive care unit of a general hospital, compared with a group that had only nonspecific abnormalities in the monitoring. RESULTS Age and cardiorespiratory arrest (CA) were risk factors for death - OR 1.04 (95% CI 1,02 - 1,07) and p<0.001; OR 3.00 (95% CI 1,01 - 8,92) and p=0.046, respectively. It was not possible to evaluate if GPDs alone were associated with an unfavorable outcome or would be a bias for the development of CA in these patients. However, of the six isolated GPDs cases, 2/3 evolved to death, showing a tendency to worse prognosis. A significant difference (p=0.031) was observed for a worse outcome when comparing the group of 28 patients who presented GPD or CA with the other group which did not present any of these variables; of these 28 patients, 20 (71.4%) died. CONCLUSIONS The presence of post-CA GPDs was associated with worse prognosis, but it was not clear whether these patterns are independent factors of an unfavorable evolution.
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Affiliation(s)
- Larissa Miyashiro
- Pontifícia Universidade Católica do Paraná, Hospital Universitário Cajuru, Curitiba, Paraná, Brazil
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Kamousi B, Karunakaran S, Gururangan K, Markert M, Decker B, Khankhanian P, Mainardi L, Quinn J, Woo R, Parvizi J. Monitoring the Burden of Seizures and Highly Epileptiform Patterns in Critical Care with a Novel Machine Learning Method. Neurocrit Care 2020; 34:908-917. [PMID: 33025543 PMCID: PMC8021593 DOI: 10.1007/s12028-020-01120-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 09/17/2020] [Indexed: 12/18/2022]
Abstract
INTRODUCTION Current electroencephalography (EEG) practice relies on interpretation by expert neurologists, which introduces diagnostic and therapeutic delays that can impact patients' clinical outcomes. As EEG practice expands, these experts are becoming increasingly limited resources. A highly sensitive and specific automated seizure detection system would streamline practice and expedite appropriate management for patients with possible nonconvulsive seizures. We aimed to test the performance of a recently FDA-cleared machine learning method (Claritγ, Ceribell Inc.) that measures the burden of seizure activity in real time and generates bedside alerts for possible status epilepticus (SE). METHODS We retrospectively identified adult patients (n = 353) who underwent evaluation of possible seizures with Rapid Response EEG system (Rapid-EEG, Ceribell Inc.). Automated detection of seizure activity and seizure burden throughout a recording (calculated as the percentage of ten-second epochs with seizure activity in any 5-min EEG segment) was performed with Claritγ, and various thresholds of seizure burden were tested (≥ 10% indicating ≥ 30 s of seizure activity in the last 5 min, ≥ 50% indicating ≥ 2.5 min of seizure activity, and ≥ 90% indicating ≥ 4.5 min of seizure activity and triggering a SE alert). The sensitivity and specificity of Claritγ's real-time seizure burden measurements and SE alerts were compared to the majority consensus of at least two expert neurologists. RESULTS Majority consensus of neurologists labeled the 353 EEGs as normal or slow activity (n = 249), highly epileptiform patterns (HEP, n = 87), or seizures [n = 17, nine longer than 5 min (e.g., SE), and eight shorter than 5 min]. The algorithm generated a SE alert (≥ 90% seizure burden) with 100% sensitivity and 93% specificity. The sensitivity and specificity of various thresholds for seizure burden during EEG recordings for detecting patients with seizures were 100% and 82% for ≥ 50% seizure burden and 88% and 60% for ≥ 10% seizure burden. Of the 179 EEG recordings in which the algorithm detected no seizures, seizures were identified by the expert reviewers in only two cases, indicating a negative predictive value of 99%. DISCUSSION Claritγ detected SE events with high sensitivity and specificity, and it demonstrated a high negative predictive value for distinguishing nonepileptiform activity from seizure and highly epileptiform activity. CONCLUSIONS Ruling out seizures accurately in a large proportion of cases can help prevent unnecessary or aggressive over-treatment in critical care settings, where empiric treatment with antiseizure medications is currently prevalent. Claritγ's high sensitivity for SE and high negative predictive value for cases without epileptiform activity make it a useful tool for triaging treatment and the need for urgent neurological consultation.
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Affiliation(s)
- Baharan Kamousi
- Ceribell Inc., 2483 Old Middlefield Way, Suite 120, Mountain View, CA, USA
| | | | - Kapil Gururangan
- Department of Neurology, The Mount Sinai Hospital, New York, NY, USA
| | - Matthew Markert
- Department of Neurology and Neurological Sciences, Stanford University Medical Center, 300 Pasteur Drive, Stanford, CA, 94305, USA
| | - Barbara Decker
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pouya Khankhanian
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura Mainardi
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - James Quinn
- Department of Emergency Medicine, Stanford University Medical Center, Stanford, CA, USA
| | - Raymond Woo
- Ceribell Inc., 2483 Old Middlefield Way, Suite 120, Mountain View, CA, USA
| | - Josef Parvizi
- Department of Neurology and Neurological Sciences, Stanford University Medical Center, 300 Pasteur Drive, Stanford, CA, 94305, USA.
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Prato G, De Grandis E, Mancardi MM, Cordani R, Giacomini T, Pisciotta L, Uccella S, Severino M, Tortora D, Pavanello M, Bertamino M, Verrina E, Caridi G, Di Rocco M, Nobili L. Schimke immuno-osseous dysplasia, two new cases with peculiar EEG pattern. Brain Dev 2020; 42:408-413. [PMID: 32115305 DOI: 10.1016/j.braindev.2020.01.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 01/09/2020] [Accepted: 01/29/2020] [Indexed: 10/24/2022]
Abstract
Schimke Immuno-Osseous Dysplasia (SIOD) is an autosomal recessive multisystem disorder caused by pathogenic variants in the gene SMARCAL1. The clinical picture is characterized by spondyloepiphyseal dysplasia resulting in growth failure, nephropathy and T-cell deficiency. Neurologic manifestations include microcephaly, cognitive impairment, migraine-like headaches and cerebrovascular manifestations such as cerebral atherosclerotic vascular disease and reversible cerebral vasoconstriction. The role of SMARCAL1 deficiency in non-vascular neurological complications is still under debate. Epilepsy has been reported in a few patients, even in the absence of brain abnormalities. Data regarding electroencephalographic (EEG) patterns in SIOD are scarce METHODS: We describe the clinical, neuroradiological and EEG findings in two unrelated patients with SIOD showing a peculiar pseudo-periodic EEG pattern apparently not related to the cerebrovascular complications, since it was recognized both before and after cerebrovascular events CONCLUSION: Our observations support the hypothesis that SMARCAL1plays an important role in neurodevelopment and brain function and expand the spectrum of neurological abnormalities related to SIOD.
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Affiliation(s)
- Giulia Prato
- Unit of Child Neuropsychiatry, Epilepsy Centre, Department of Medical and Surgical Neuroscience and Rehabilitation, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
| | - Elisa De Grandis
- Unit of Child Neuropsychiatry, Epilepsy Centre, Department of Medical and Surgical Neuroscience and Rehabilitation, IRCCS Istituto Giannina Gaslini, Genoa, Italy; Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy.
| | - Maria Margherita Mancardi
- Unit of Child Neuropsychiatry, Epilepsy Centre, Department of Medical and Surgical Neuroscience and Rehabilitation, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
| | - Ramona Cordani
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy.
| | - Thea Giacomini
- Unit of Child Neuropsychiatry, Epilepsy Centre, Department of Medical and Surgical Neuroscience and Rehabilitation, IRCCS Istituto Giannina Gaslini, Genoa, Italy; Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy.
| | - Livia Pisciotta
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy.
| | - Sara Uccella
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy
| | | | - Domenico Tortora
- Neuroradiology Unit, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
| | - Marco Pavanello
- Neurosurgery Unit, Department of Clinical and Surgical Neurosciences and Rehabilitation, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
| | - Marta Bertamino
- Physical Medicine and Rehabilitation Unit, Department of Clinical and Surgical Neurosciences and Rehabilitation, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
| | - Enrico Verrina
- Dialysis Unit, Department of Paediatrics, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
| | - Gianluca Caridi
- Laboratory of Molecular Nephrology, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
| | - Maja Di Rocco
- Unit of Rare Diseases, Department of Pediatrics, IRCCS Istituto Giannina Gaslini, Genoa, Italy.
| | - Lino Nobili
- Unit of Child Neuropsychiatry, Epilepsy Centre, Department of Medical and Surgical Neuroscience and Rehabilitation, IRCCS Istituto Giannina Gaslini, Genoa, Italy; Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy.
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