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Ali A, Clarke DF. Digital measures in epilepsy in low-resourced environments. Expert Rev Pharmacoecon Outcomes Res 2024; 24:705-712. [PMID: 37818647 DOI: 10.1080/14737167.2023.2270163] [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: 07/14/2023] [Accepted: 10/09/2023] [Indexed: 10/12/2023]
Abstract
INTRODUCTION Digital measures and digital health-care delivery have been rarely implemented in lower-and-middle-income countries (LMICs), contributing to worsening global disparities and inequities. Sustainable ways to implement and use digital approaches will help to improve time to access, management, and quality of life in persons with epilepsy, goals that remain unreachable in under-resourced communities. As under-resourced environments differ in human and economic resources, no one approach will be appropriate to all LMICs. AREAS COVERED Digital health and tools to monitor and measure digital endpoints and metrics of quality of life will need to be developed or adapted to the specific needs of under-resourced areas. Portable technologies may partially address the urban-rural divide. Careful delineation of stakeholders and their engagement and alignment in all efforts is critically important if these initiatives are to be successfully sustained. Privacy issues, neglected in many regions globally, must be purposefully addressed. EXPERT OPINION Epilepsy care in under-resourced environments has been limited by the lack of relevant technologies for diagnosis and treatment. Digital biomarkers, and investigative technological advances, may finally make it feasible to sustainably improve care delivery and ultimately quality of life including personalized epilepsy care.
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Affiliation(s)
- Amza Ali
- Department of Medicine, Faculty of Medical Sciences, Mona, Kingston, Jamaica
| | - Dave F Clarke
- Dell Medical School, University of Texas at Austin, Austin, TX, USA
- Department of Pediatric Epilepsy, Dell Children's Medical Center of Central Texas, Austin, TX, USA
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2
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Green A, Wegman ME, Ney JP. Economic review of point-of-care EEG. J Med Econ 2024; 27:51-61. [PMID: 38014443 DOI: 10.1080/13696998.2023.2288422] [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: 06/16/2023] [Accepted: 11/23/2023] [Indexed: 11/29/2023]
Abstract
Aims: Point-of-care electroencephalogram (POC-EEG) is an acute care bedside screening tool for the identification of nonconvulsive seizures (NCS) and nonconvulsive status epilepticus (NCSE). The objective of this narrative review is to describe the economic themes related to POC-EEG in the United States (US).Materials and methods: We examined peer-reviewed, published manuscripts on the economic findings of POC-EEG for bedside use in US hospitals, which included those found through targeted searches on PubMed and Google Scholar. Conference abstracts, gray literature offerings, frank advertisements, white papers, and studies conducted outside the US were excluded.Results: Twelve manuscripts were identified and reviewed; results were then grouped into four categories of economic evidence. First, POC-EEG usage was associated with clinical management amendments and antiseizure medication reductions. Second, POC-EEG was correlated with fewer unnecessary transfers to other facilities for monitoring and reduced hospital length of stay (LOS). Third, when identifying NCS or NCSE onsite, POC-EEG was associated with greater reimbursement in Medical Severity-Diagnosis Related Group coding. Fourth, POC-EEG may lower labor costs via decreasing after-hours requests to EEG technologists for conventional EEG (convEEG).Limitations: We conducted a narrative review, not a systematic review. The studies were observational and utilized one rapid circumferential headband system, which limited generalizability of the findings and indicated publication bias. Some sample sizes were small and hospital characteristics may not represent all US hospitals. POC-EEG studies in pediatric populations were also lacking. Ultimately, further research is justified.Conclusions: POC-EEG is a rapid screening tool for NCS and NCSE in critical care and emergency medicine with potential financial benefits through refining clinical management, reducing unnecessary patient transfers and hospital LOS, improving reimbursement, and mitigating burdens on healthcare staff and hospitals. Since POC-EEG has limitations (i.e. no video component and reduced montage), the studies asserted that it did not replace convEEG.
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Affiliation(s)
- Adam Green
- Critical Care Medicine, Cooper University Health Care and Cooper Medical School of Rowan University, Camden, NJ, USA
| | - M Elizabeth Wegman
- Medical Communications, Costello Medical Consulting, Inc, Boston, MA, USA
| | - John P Ney
- Department of Neurology, Boston University Aram V. Chobanian & Edward Avedisian School of Medicine, Boston, MA, USA
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Caffarelli M, Karukonda V, Aghaeeaval M, McQuillen PS, Numis AL, Mackay MT, Press CA, Wintermark M, Fox CK, Amorim E. A quantitative EEG index for the recognition of arterial ischemic stroke in children. Clin Neurophysiol 2023; 156:113-124. [PMID: 37918222 DOI: 10.1016/j.clinph.2023.10.001] [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: 11/08/2022] [Revised: 09/22/2023] [Accepted: 10/02/2023] [Indexed: 11/04/2023]
Abstract
OBJECTIVE To describe and assess performance of the Correlate Of Injury to the Nervous system (COIN) index, a quantitative electroencephalography (EEG) metric designed to identify areas of cerebral dysfunction concerning for stroke. METHODS Case-control study comparing continuous EEG data from children with acute ischemic stroke to children without stroke, with or without encephalopathy. COIN is calculated continuously and compares EEG power between cerebral hemispheres. Stroke relative infarct volume (RIV) was calculated from quantitative neuroimaging analysis. Significance was determined using a two-sample t-test. Sensitivity, specificity, and accuracy were measured using logistic regression. RESULTS Average COIN values were -34.7 in the stroke cohort compared to -9.5 in controls without encephalopathy (p = 0.003) and -10.5 in controls with encephalopathy (p = 0.006). The optimal COIN cutoff to discriminate stroke from controls was -15 in non-encephalopathic and -18 in encephalopathic controls with >92% accuracy in strokes with RIV > 5%. A COIN cutoff of -20 allowed discrimination between strokes with <5% and >5% RIV (p = 0.027). CONCLUSIONS We demonstrate that COIN can identify children with acute ischemic stroke. SIGNIFICANCE COIN may be a valuable tool for stroke identification in children. Additional studies are needed to determine utility as a monitoring technique for children at risk for stroke.
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Affiliation(s)
- Mauro Caffarelli
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
| | - Vishnu Karukonda
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Mahsa Aghaeeaval
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Patrick S McQuillen
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Adam L Numis
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Mark T Mackay
- Royal Children's Hospital, Melbourne, Victoria, Australia; The Murdoch Children's Research Institute Melbourne, Victoria, Australia; The Department of Paediatrics, University of Melbourne, Victoria, Australia
| | - Craig A Press
- Departments of Pediatrics and Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Max Wintermark
- Department of Neuroradiology, University of Texas MD Anderson Center, Houston, TX, USA
| | - Christine K Fox
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Edilberto Amorim
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
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Stephens CM, Mathieson SR, McNamara B, McSweeney N, O'Brien R, O'Mahony O, Boylan GB, Murray DM. Electroencephalography Quality and Application Times in a Pediatric Emergency Department Setting: A Feasibility Study. Pediatr Neurol 2023; 148:82-85. [PMID: 37690268 DOI: 10.1016/j.pediatrneurol.2023.08.016] [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] [Received: 03/27/2023] [Revised: 06/06/2023] [Accepted: 08/14/2023] [Indexed: 09/12/2023]
Abstract
BACKGROUND Status epilepticus is the most common neurological emergency presenting to pediatric emergency departments. Nonconvulsive status epilepticus can be extremely challenging to diagnose, however, requiring electroencephalographic (EEG) confirmation for definitive diagnosis. We aimed to determine the feasibility of achieving a good-quality pediatric EEG recording within 20 minutes of presentation to the emergency department. METHODS Single-center prospective feasibility study in Cork University Hospital, Ireland, between July 2021 and June 2022. Two-channel continuous EEG was recorded from children (1) aged <16 years and (2) with Glasgow Coma Scale <11 or a reduction in baseline Glasgow Coma Scale in the case of a child with a neurodisability. RESULTS Twenty patients were included. The median age at presentation was 65.8 months (interquartile range, 23.2 to 119.0); 50% had a background diagnosis of epilepsy. The most common reason for EEG monitoring was status epilepticus (85%) followed by suspected nonconvulsive status (10%) and reduced consciousness of unknown etiology (5%). The mean length of recording was 93.1 minutes (S.D. 47.4). The mean time to application was 41.3 minutes (S.D. 11.7). The mean percent of artifact in all recordings was 19.3% (S.D. 15.9). Thirteen (65%) EEGs had <25% artifact. Artifact was higher in cases in which active airway management was ongoing. CONCLUSIONS EEG monitoring can be achieved in a pediatric emergency department setting within one hour of presentation. Overall, artifact percentage was low outside of periods of airway manipulation. Future studies are required to determine its use in early seizure detection and its support role in clinical decision-making in these patients.
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Affiliation(s)
- Carol M Stephens
- INFANT Research Centre, University College Cork, Cork, Ireland; Department of Paediatrics and Child Health, University College Cork, Cork, Ireland.
| | - Sean R Mathieson
- INFANT Research Centre, University College Cork, Cork, Ireland; Department of Paediatrics and Child Health, University College Cork, Cork, Ireland
| | - Brian McNamara
- Department of Neurophysiology, Cork University Hospital, Cork, Ireland
| | - Niamh McSweeney
- Department of Paediatrics and Child Health, University College Cork, Cork, Ireland; Department of Paediatric Neurology, Cork University Hospital, Cork, Ireland
| | - Rory O'Brien
- Department of Emergency Medicine, Cork University Hospital, Cork, Ireland
| | - Olivia O'Mahony
- Department of Paediatric Neurology, Cork University Hospital, Cork, Ireland
| | - Geraldine B Boylan
- INFANT Research Centre, University College Cork, Cork, Ireland; Department of Paediatrics and Child Health, University College Cork, Cork, Ireland
| | - Deirdre M Murray
- INFANT Research Centre, University College Cork, Cork, Ireland; Department of Paediatrics and Child Health, University College Cork, Cork, Ireland
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Villamar MF, Ayub N, Koenig SJ. Automated Seizure Detection in Patients with Cardiac Arrest: A Retrospective Review of Ceribell™ Rapid-EEG Recordings. Neurocrit Care 2023; 39:505-513. [PMID: 36788179 DOI: 10.1007/s12028-023-01681-w] [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: 08/10/2022] [Accepted: 01/23/2023] [Indexed: 02/16/2023]
Abstract
BACKGROUND In patients with cardiac arrest who remain comatose after return of spontaneous circulation, seizures and other abnormalities on electroencephalogram (EEG) are common. Thus, guidelines recommend urgent initiation of EEG for the evaluation of seizures in this population. Point-of-care EEG systems, such as Ceribell™ Rapid Response EEG (Rapid-EEG), allow for prompt initiation of EEG monitoring, albeit through a reduced-channel montage. Rapid-EEG incorporates an automated seizure detection software (Clarity™) to measure seizure burden in real time and alert clinicians at the bedside when a high seizure burden, consistent with possible status epilepticus, is identified. External validation of Clarity is still needed. Our goal was to evaluate the real-world performance of Clarity for the detection of seizures and status epilepticus in a sample of patients with cardiac arrest. METHODS This study was a retrospective review of Rapid-EEG recordings from all the patients who were admitted to the medical intensive care unit at Kent Hospital (Warwick, RI) between 6/1/2021 and 3/18/2022 for management after cardiac arrest and who underwent Rapid-EEG monitoring as part of their routine clinical care (n = 21). Board-certified epileptologists identified events that met criteria for seizures or status epilepticus, as per the 2021 American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology, and evaluated any seizure burden detections generated by Clarity. RESULTS In this study, 4 of 21 patients with cardiac arrest (19.0%) who underwent Rapid-EEG monitoring had multiple electrographic seizures, and 2 of those patients (9.5%) had electrographic status epilepticus within the first 24 h of the study. None of these ictal abnormalities were detected by the Clarity seizure detection system. Clarity showed 0% seizure burden throughout the entirety of all four Rapid-EEG recordings, including the EEG pages that showed definite seizures or status epilepticus. CONCLUSIONS The presence of frequent electrographic seizures and/or status epilepticus can go undetected by Clarity. Timely and careful review of all raw Rapid-EEG recordings by a qualified human EEG reader is necessary to guide clinical care, regardless of Clarity seizure burden measurements.
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Affiliation(s)
- Mauricio F Villamar
- Department of Neurology, The Warren Alpert Medical School of Brown University, Providence, RI, USA.
- Department of Medicine, Kent Hospital, Warwick, RI, USA.
| | - Neishay Ayub
- Department of Neurology, The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Seth J Koenig
- Department of Medicine, Kent Hospital, Warwick, RI, USA
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Eberhard E, Beckerman SR. Rapid-Response Electroencephalography in Seizure Diagnosis and Patient Care: Lessons From a Community Hospital. J Neurosci Nurs 2023; 55:157-163. [PMID: 37556461 DOI: 10.1097/jnn.0000000000000715] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
ABSTRACT BACKGROUND: Nonconvulsive seizures are a major source of in-hospital morbidity and a cause of unexplained encephalopathy in critically ill patients. Electroencephalography (EEG) is essential to confirm nonconvulsive seizures and can guide patient-specific workup, treatment, and prognostication. In a 208-bed community hospital, EEG services were limited to 1 part-time EEG technician and 1 EEG machine shared between inpatient and outpatient settings. Its use was restricted to typical business hours. A nursing-led quality improvement (QI) project endeavored to enhance access to EEG by introducing a point-of-care rapid-response EEG program. METHODS: For this project, a multidisciplinary protocol was developed to deploy a Food and Drug Administration-cleared, point-of-care rapid-response EEG platform (Ceribell Inc) in a community hospital's emergency department and inpatient units to streamline neurodiagnostic workups. This QI project compared EEG volume, study location, time-to-EEG, number of cases with seizures captured on EEG, and hospital-level financial metrics of diagnosis-related group reimbursements and length of stay for the 6 months before (pre-QI, using conventional EEG) and 6 months after implementing the rapid-response protocol (post-QI). RESULTS: Electroencephalography volume increased from 35 studies pre-QI to 115 post-QI (3.29-fold increase), whereas the median time from EEG order to EEG start decreased 7.6-fold (74 [34-187] minutes post-QI vs 562 [321-1034] minutes pre-QI). Point-of-care EEG was also associated with more confirmed seizure diagnoses compared with conventional EEG (27/115 post-QI vs 0/35 pre-QI). This resulted in additional diagnosis-related group reimbursements and hospital revenue. Availability of point-of-care EEG was also associated with a shorter median length of stay. CONCLUSION: A nurse-led, rapid-response EEG protocol at a community hospital resulted in significant improvements in EEG accessibility and seizure diagnosis with hospital-level financial benefits. By expanding access to EEG, confirming nonconvulsive seizures, and increasing care efficiency, rapid-response EEG protocols can enhance patient care.
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Affiliation(s)
- Eleanor Eberhard
- Eleanor Eberhard, DNP MBA RN, is VP, CNO, and COO, Dignity Health Sequoia Hospital
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Ward J, Green A, Cole R, Zarbiv S, Dumond S, Clough J, Rincon F. Implementation and impact of a point of care electroencephalography platform in a community hospital: a cohort study. Front Digit Health 2023; 5:1035442. [PMID: 37609070 PMCID: PMC10441220 DOI: 10.3389/fdgth.2023.1035442] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 07/17/2023] [Indexed: 08/24/2023] Open
Abstract
Objective To determine the clinical and financial feasibility of implementing a poc-EEG system in a community hospital. Design Data from a prospective cohort displaying abnormal mentation concerning for NCSE or rhythmic movements due to potential underlying seizure necessitating EEG was collected and compared to a control group containing patient data from 2020. Setting A teaching community hospital with limited EEG support. Patients The study group consisted of patients requiring emergent EEG during hours when conventional EEG was unavailable. Control group is made up of patients who were emergently transferred for EEG during the historical period. Interventions Application and interpretation of Ceribell®, a poc-EEG system. Measurement and main results 88 patients were eligible with indications for poc-EEG including hyperkinetic movements post-cardiac arrest (19%), abnormal mentation after possible seizure (46%), and unresponsive patients with concern for NCSE (35%). 21% had seizure burden on poc-EEG and 4.5% had seizure activity on follow-up EEG. A mean of 1.1 patients per month required transfer to a tertiary care center for continuous EEG. For the control period, a total of 22 patients or a mean of 2 patients per month were transferred for emergent EEG. Annually, we observed a decrease in the number of transferred patients in the post-implementation period by 10.8 (95% CI: -2.17-23.64, p = 0.1). Financial analysis of the control found the hospital system incurred a loss of $3,463.11 per patient transferred for an annual loss of $83,114.64. In the study group, this would compute to an annual loss of $45,713.05 for an overall decrease in amount lost of $37,401.59. We compared amount lost per patient between historical controls and study patients. Implementation of poc-EEG resulted in an overall decrease in annual amount lost of $37,401.59 by avoidance of transfer fees. We calculated the amount gained per patient in the study group to be $13,936.44. To cover the cost of the poc-EEG system, 8.59 patients would need to avoid transfer annually. Conclusion A poc-EEG system can be safely implemented in a community hospital leading to an absolute decrease in transfers to tertiary hospital. This decrease in patient transfers can cover the cost of implementing the poc-EEG system. The additional benefits from transfer avoidance include clinical benefits such as rapid appropriate treatment of seizures and avoidance of unnecessary treatment as well as negating transfer risk and keeping the patient at their local hospital.
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Affiliation(s)
- Jared Ward
- Department of Medicine, Division of Critical Care Medicine, Cooper University Hospital, Cooper University Medical School of Rowan University, Camden, NJ, United States
| | - Adam Green
- Department of Medicine, Division of Critical Care Medicine, Cooper University Hospital, Cooper University Medical School of Rowan University, Camden, NJ, United States
| | - Robert Cole
- Department of Medicine, Division of Critical Care Medicine, Cooper University Hospital, Cooper University Medical School of Rowan University, Camden, NJ, United States
| | - Samson Zarbiv
- Department of Medicine, Division of Critical Care Medicine, Cooper University Hospital, Cooper University Medical School of Rowan University, Camden, NJ, United States
| | - Stanley Dumond
- Department of Medicine, Critical Care Medicine Fellowship, Inspira Medical Center, Vineland, NJ, United States
| | - Jessica Clough
- Cardiopulmonary Department, Inspira Health, Vineland, NJ, United States
| | - Fred Rincon
- Department of Neurology, Cooper University Hospital, Cooper University Medical School of Rowan University, Camden, NJ, United States
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Freund BE, Feyissa AM. EEG as an indispensable tool during and after the COVID-19 pandemic: A review of tribulations and successes. Front Neurol 2022; 13:1087969. [PMID: 36530612 PMCID: PMC9755176 DOI: 10.3389/fneur.2022.1087969] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 11/17/2022] [Indexed: 10/03/2023] Open
Abstract
During the coronavirus disease 2019 (COVID-19) pandemic, elective and non-emergent tests and procedures were delayed or suspended in lieu of diverting resources to more emergent treatment of critically ill patients and to avoid the spread and contraction of COVID-19. Further, the workforce was stretched thin, and healthcare facilities saw high turnover rates for full-time and contract employees, which strained the system and reduced the ability to provide clinical services. One of the casualties of these changes was electroencephalography (EEG) procedures, which have been performed less frequently throughout the world since the pandemic. Whether considered routine or emergent, the deferral of EEG studies can cause downstream effects, including a delay in diagnosis and initiation of treatment for epilepsy and non-epileptic seizures resulting in a higher risk of morbidity and mortality. Despite these limitations, the importance and utility of EEG and EEG technologists have been reinforced with the development of COVID-related neurological complications, including encephalopathy and seizures, which require EEG for diagnosis and treatment. Since the pandemic, reliance on remote telemonitoring has further highlighted the value and ease of using EEG. There has also been a heightened interest in rapid EEG devices that non-technologist professionals can attach quickly, allowing minimum patient contact to avoid exposure to COVID-19 and taking advantage of remote EEG monitoring. This review discusses the acute and potential long-term effects of the COVID-19 pandemic on the use and performance of EEG.
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Affiliation(s)
| | - Anteneh M. Feyissa
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL, United States
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Sharma S, Nunes M, Alkhachroum A. Adult Critical Care Electroencephalography Monitoring for Seizures: A Narrative Review. Front Neurol 2022; 13:951286. [PMID: 35911927 PMCID: PMC9334872 DOI: 10.3389/fneur.2022.951286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 06/22/2022] [Indexed: 11/13/2022] Open
Abstract
Electroencephalography (EEG) is an important and relatively inexpensive tool that allows intensivists to monitor cerebral activity of critically ill patients in real time. Seizure detection in patients with and without acute brain injury is the primary reason to obtain an EEG in the Intensive Care Unit (ICU). In response to the increased demand of EEG, advances in quantitative EEG (qEEG) created an approach to review large amounts of data instantly. Finally, rapid response EEG is now available to reduce the time to detect electrographic seizures in limited-resource settings. This review article provides a concise overview of the technical aspects of EEG monitoring for seizures, clinical indications for EEG, the various available modalities of EEG, common and challenging EEG patterns, and barriers to EEG monitoring in the ICU.
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Affiliation(s)
- Sonali Sharma
- Department of Neurology, University of Miami, Miami, FL, United States
- Department of Neurology, Jackson Memorial Hospital, Miami, FL, United States
| | - Michelle Nunes
- Department of Neurology, University of Miami, Miami, FL, United States
- Department of Neurology, Jackson Memorial Hospital, Miami, FL, United States
| | - Ayham Alkhachroum
- Department of Neurology, University of Miami, Miami, FL, United States
- Department of Neurology, Jackson Memorial Hospital, Miami, FL, United States
- *Correspondence: Ayham Alkhachroum
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Villamar MF, Albuja AC. "Water in the Tube" Artifact Mimicking Epileptiform Abnormalities on Point-of-Care EEG. Neurohospitalist 2022; 12:581-582. [PMID: 35755223 PMCID: PMC9214931 DOI: 10.1177/19418744221088162] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/01/2023] Open
Affiliation(s)
- Mauricio F. Villamar
- Department of Neurology, The Warren Alpert Medical School of Brown University, Providence, RI, USA
- Department of Medicine, Kent Hospital, Warwick, RI, USA
| | - Ana C. Albuja
- Department of Neurology, The Warren Alpert Medical School of Brown University, Providence, RI, USA
- Department of Pediatrics, The Warren Alpert Medical School of Brown University, Providence, RI, USA
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Murphey DK, Anderson ER. The Past, Present, and Future of Tele-EEG. Semin Neurol 2022; 42:31-38. [PMID: 35576928 DOI: 10.1055/s-0041-1742242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Tele-electroencephalogram (EEG) has become more pervasive over the last 20 years due to advances in technology, both independent of and driven by personnel shortages. The professionalization of EEG services has both limited growth and controlled the quality of tele-EEG. Growing data on the conditions that benefit from brain monitoring have informed increased critical care EEG and ambulatory EEG utilization. Guidelines that marshal responsible use of still-limited resources and changes in broadband and billing practices have also shaped the tele-EEG landscape. It is helpful to characterize the drivers of tele-EEG to navigate barriers to sustainable growth and to build dynamic systems that anticipate challenges in any of the domains that expand access and enhance quality of these diagnostic services. We explore the historical factors and current trends in tele-EEG in the United States in this review.
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Davey Z, Gupta PB, Li DR, Nayak RU, Govindarajan P. Rapid Response EEG: Current State and Future Directions. Curr Neurol Neurosci Rep 2022; 22:839-846. [PMID: 36434488 PMCID: PMC9702853 DOI: 10.1007/s11910-022-01243-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/10/2022] [Indexed: 11/27/2022]
Abstract
PURPOSE OF REVIEW To critically appraise the literature on the application, methods, and advances in emergency electroencephalography (EEG). RECENT FINDINGS The development of rapid EEG (rEEG) technologies and other reduced montage approaches, along with advances in machine learning over the past decade, has increased the rate and access to EEG acquisition. These achievements have made EEG in the emergency setting a practical diagnostic technique for detecting seizures, suspected nonconvulsive status epilepticus (NCSE), altered mental status, stroke, and in the setting of sedation. Growing evidence supports using EEG to expedite medical decision-making in the setting of suspected acute neurological injury. This review covers approaches to acquiring EEG in the emergency setting in the adult and pediatric populations. We also cover the clinical impact of this data, the time associated with emergency EEG, and the costs of acquiring EEG in these settings. Finally, we discuss the advances in artificial intelligence for rapid electrophysiological interpretation.
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Affiliation(s)
- Zachary Davey
- grid.414467.40000 0001 0560 6544Department of Neurology, Walter Reed National Military Medical Center, Bethesda, MD USA
| | - Pranjal Bodh Gupta
- grid.240952.80000000087342732Department of Emergency Medicine, Stanford Medicine, Palo Alto, CA USA
| | - David R. Li
- grid.240952.80000000087342732Department of Emergency Medicine, Stanford Medicine, Palo Alto, CA USA
| | - Rahul Uday Nayak
- grid.240952.80000000087342732Department of Emergency Medicine, Stanford Medicine, Palo Alto, CA USA
| | - Prasanthi Govindarajan
- grid.240952.80000000087342732Department of Emergency Medicine, Stanford Medicine, Palo Alto, CA USA
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Murphy BB, Scheid BH, Hendricks Q, Apollo NV, Litt B, Vitale F. Time Evolution of the Skin-Electrode Interface Impedance under Different Skin Treatments. SENSORS (BASEL, SWITZERLAND) 2021; 21:5210. [PMID: 34372446 PMCID: PMC8348734 DOI: 10.3390/s21155210] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 07/22/2021] [Accepted: 07/29/2021] [Indexed: 01/04/2023]
Abstract
A low and stable impedance at the skin-electrode interface is key to high-fidelity acquisition of biosignals, both acutely and in the long term. However, recording quality is highly variable due to the complex nature of human skin. Here, we present an experimental and modeling framework to investigate the interfacial impedance behavior, and describe how skin interventions affect its stability over time. To illustrate this approach, we report experimental measurements on the skin-electrode impedance using pre-gelled, clinical-grade electrodes in healthy human subjects recorded over 24 h following four skin treatments: (i) mechanical abrasion, (ii) chemical exfoliation, (iii) microporation, and (iv) no treatment. In the immediate post-treatment period, mechanical abrasion yields the lowest initial impedance, whereas the other treatments provide modest improvement compared to untreated skin. After 24 h, however, the impedance becomes more uniform across all groups (<20 kΩ at 10 Hz). The impedance data are fitted with an equivalent circuit model of the complete skin-electrode interface, clearly identifying skin-level versus electrode-level contributions to the overall impedance. Using this model, we systematically investigate how time and treatment affect the impedance response, and show that removal of the superficial epidermal layers is essential to achieving a low, long-term stable interface impedance.
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Affiliation(s)
- Brendan B. Murphy
- Department of Bioengineering, 240 Skirkanich Hall, University of Pennsylvania, 210 S. 33rd Street, Philadelphia, PA 19104, USA; (B.B.M.); (B.H.S.); (Q.H.); (B.L.)
- Center for Neuroengineering & Therapeutics, 301 Hayden Hall, University of Pennsylvania, 240 S. 33rd Street, Philadelphia, PA 19104, USA;
- Center for Neurotrauma, Neurodegeneration, and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, 3900 Woodlawn Ave., Philadelphia, PA 19104, USA
| | - Brittany H. Scheid
- Department of Bioengineering, 240 Skirkanich Hall, University of Pennsylvania, 210 S. 33rd Street, Philadelphia, PA 19104, USA; (B.B.M.); (B.H.S.); (Q.H.); (B.L.)
- Center for Neuroengineering & Therapeutics, 301 Hayden Hall, University of Pennsylvania, 240 S. 33rd Street, Philadelphia, PA 19104, USA;
| | - Quincy Hendricks
- Department of Bioengineering, 240 Skirkanich Hall, University of Pennsylvania, 210 S. 33rd Street, Philadelphia, PA 19104, USA; (B.B.M.); (B.H.S.); (Q.H.); (B.L.)
- Center for Neuroengineering & Therapeutics, 301 Hayden Hall, University of Pennsylvania, 240 S. 33rd Street, Philadelphia, PA 19104, USA;
- Center for Neurotrauma, Neurodegeneration, and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, 3900 Woodlawn Ave., Philadelphia, PA 19104, USA
| | - Nicholas V. Apollo
- Center for Neuroengineering & Therapeutics, 301 Hayden Hall, University of Pennsylvania, 240 S. 33rd Street, Philadelphia, PA 19104, USA;
- Center for Neurotrauma, Neurodegeneration, and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, 3900 Woodlawn Ave., Philadelphia, PA 19104, USA
| | - Brian Litt
- Department of Bioengineering, 240 Skirkanich Hall, University of Pennsylvania, 210 S. 33rd Street, Philadelphia, PA 19104, USA; (B.B.M.); (B.H.S.); (Q.H.); (B.L.)
- Center for Neuroengineering & Therapeutics, 301 Hayden Hall, University of Pennsylvania, 240 S. 33rd Street, Philadelphia, PA 19104, USA;
- Department of Neurology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Flavia Vitale
- Department of Bioengineering, 240 Skirkanich Hall, University of Pennsylvania, 210 S. 33rd Street, Philadelphia, PA 19104, USA; (B.B.M.); (B.H.S.); (Q.H.); (B.L.)
- Center for Neuroengineering & Therapeutics, 301 Hayden Hall, University of Pennsylvania, 240 S. 33rd Street, Philadelphia, PA 19104, USA;
- Center for Neurotrauma, Neurodegeneration, and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, 3900 Woodlawn Ave., Philadelphia, PA 19104, USA
- Department of Neurology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
- Department of Physical Medicine & Rehabilitation, University of Pennsylvania, 1800 Lombard Street, Philadelphia, PA 19147, USA
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LaMonte MP. Ceribell EEG shortens seizure diagnosis and workforce time and is useful for COVID isolation. Epilepsia Open 2021; 6:331-338. [PMID: 34033243 PMCID: PMC8013275 DOI: 10.1002/epi4.12474] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 01/22/2021] [Accepted: 01/31/2021] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE To determine whether the portable Ceribell® electroencephalograph (EEG) (Mountain View, CA) used for suspected status epilepticus (SE) can reduce time to diagnosis and on-call workforce demands and whether it can be applied to patients in respiratory isolation. METHODS A multidisciplinary team developed a protocol for the use of the Ceribell EEG. The staff deploying the device, the attending physician, and the interpreting neurologist completed evaluation tools for each patient. Data maintained for quality and resource planning of 18-channel electroencephalography ordered for suspected SE were used as controls. Times to diagnosis were compared by application of Welch-Satterthwaite tests and workforce call-in demands by Fisher's exact t test. We evaluated qualitative data related to the use of the EEG in COVID-19 isolation rooms and on its technical aspects and acceptance by staff members. RESULTS The Ceribell EEG reduced diagnosis time (P = .0000006) and on-call workforce demand (P = .02). The device can be used at any time of day in any hospital care area and has advantages in respiratory isolation rooms. SIGNIFICANCE Compared with a standard 18-channel EEG, the Ceribell device allowed earlier diagnosis of SE and non-SE conditions and reduced workforce demands. Due to the ease of its use and its simple components, which can be readily disinfected, it is advantageous for COVID-19 patients in isolation.
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Affiliation(s)
- Marian P LaMonte
- Ascension St. Agnes Hospital, University of Maryland School of Medicine, Baltimore, MD, USA
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