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Haksteen WE, Nasim GZ, Admiraal MM, Velseboer DC, van Rootselaar AF, Horn J. Indications, results and consequences of electroencephalography in neurocritical care: A retrospective study. J Crit Care 2024; 84:154861. [PMID: 39018590 DOI: 10.1016/j.jcrc.2024.154861] [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: 02/15/2024] [Revised: 06/29/2024] [Accepted: 07/06/2024] [Indexed: 07/19/2024]
Abstract
PURPOSE Electrocencephalography (EEG) is a tool to assess cerebral cortical activity. We investigated the indications and results of routine EEG recordings in neurocritical care patients and corresponding changes in anti-seizure medication (ASM). MATERIALS AND METHODS This was a single-center, retrospective cohort study. We included all adult Intensive Care Unit (ICU) patients with severe acute brain injury who received a routine EEG (30-60 min). Indications, background patterns, presence of rhythmic and periodic patterns, seizures, and adjustments in ASM were documented. RESULTS A total of 109 patients were included. The EEGs were performed primarily to investigate the presence of (non-convulsive) status epilepticus ((NC)SE) and/or seizures. A (slowed) continuous background pattern was present in 94%. Low voltage, burst-suppression and suppressed background patterns were found in six patients (5.5%). Seizures were diagnosed in two patients and (NC)SE was diagnosed in five patients (6.4%). Based on the EEG results, ASM was changed in 47 patients (43%). This encompassed discontinuation of ASM in 27 patients (24.8%) and initiation of ASM in 20 patients (18.3%). CONCLUSIONS All EEGs were performed to investigate the presence of (NC)SE or seizures. A slowed, but continuous background pattern was found in nearly all patients and (NC)SE and seizures were rarely diagnosed. Adjustments in ASM were made in approximately half of the patients.
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Affiliation(s)
- Wolmet E Haksteen
- Amsterdam UMC, University of Amsterdam, Department of Intensive Care, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, Netherlands.
| | - Gulsum Z Nasim
- Amsterdam UMC, University of Amsterdam, Department of Intensive Care, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, Netherlands
| | - Marjolein M Admiraal
- Amsterdam UMC, University of Amsterdam, Department of Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Daan C Velseboer
- Amsterdam UMC, University of Amsterdam, Department of Intensive Care, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, Netherlands
| | - A Fleur van Rootselaar
- Amsterdam UMC, University of Amsterdam, Department of Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Janneke Horn
- Amsterdam UMC, University of Amsterdam, Department of Intensive Care, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, Netherlands
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Nonaka M, Neshige S, Ono N, Yamada H, Takebayashi Y, Ishibashi H, Aoki S, Yamazaki Y, Shishido T, Agari D, Ochi K, Iida K, Maruyama H. Clinical manifestations and outcomes associated with a high 2HELPS2B score in patients with acute impaired consciousness. J Neurol Sci 2024; 465:123174. [PMID: 39241543 DOI: 10.1016/j.jns.2024.123174] [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: 05/23/2024] [Revised: 07/23/2024] [Accepted: 08/08/2024] [Indexed: 09/09/2024]
Abstract
PURPOSE The 2HELPS2B score is an invaluable tool for assessing seizure risk in critically ill patients with unconsciousness. However, this can be challenging for non-epileptologists to use owing to its reliance on electroencephalogram (EEG) analysis. Thus, identifying clinical manifestations associated with high 2HELPS2B scores is crucial. METHODS We examined patients who underwent EEG for acute impaired consciousness in the emergency department between 2020 and 2022. We evaluated the clinical manifestations immediately prior to the EEG tests and identified those associated with a 2HELPS2B score ≥ 2. Additionally, we investigated clinical outcomes in accordance with these manifestations and the 2HELPS2B score. RESULTS A total of 78 patients were included in this study. While the median 2HELPS2B score was 1 (range: 0-6), 13 patients (16.6%) showed electrographic/electroclinical seizures or status epilepticus and 16 patients (20.5%) showed ictal-interictal continuum in their EEGs. Abnormal muscle tonus (p = 0.034) and eye deviation (p = 0.021) were Significantly associated with a 2HELPS2B score ≥ 2. The presence of these manifestations (p < 0.001) and a 2HELPS2B score ≥ 2 (p < 0.001) were both significantly associated with a favorable response to anti-seizure medication. Conversely, patients with a 2HELPS2B score ≥ 2 who exhibited these clinical manifestations were more likely to be non-dischargeable (p = 0.053), have prolonged intensive care unit stays (p = 0.002), or require extended ventilator use (p = 0.082). CONCLUSION Abnormal muscle tonus and eye deviation were significant manifestations compatible with a 2HELPS2B score ≥ 2 and may indicate an increased risk of seizures or the severity of the epileptic condition.
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Affiliation(s)
- Megumi Nonaka
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University, Graduate School of Biomedical and Health Sciences, Japan
| | - Shuichiro Neshige
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University, Graduate School of Biomedical and Health Sciences, Japan; Epilepsy Center, Hiroshima University Hospital, Japan.
| | - Narumi Ono
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University, Graduate School of Biomedical and Health Sciences, Japan
| | - Hidetada Yamada
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University, Graduate School of Biomedical and Health Sciences, Japan
| | - Yoshiko Takebayashi
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University, Graduate School of Biomedical and Health Sciences, Japan
| | - Haruka Ishibashi
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University, Graduate School of Biomedical and Health Sciences, Japan
| | - Shiro Aoki
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University, Graduate School of Biomedical and Health Sciences, Japan
| | - Yu Yamazaki
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University, Graduate School of Biomedical and Health Sciences, Japan
| | - Takeo Shishido
- Department of Neurology, Hiroshima City North Medical Center Asa Citizens Hospital, Japan
| | - Dai Agari
- Department of Neurology, Hiroshima City Hiroshima Citizens Hospital, Japan
| | - Kazuhide Ochi
- Department of Neurology, Hiroshima Prefectural Hospital, Japan
| | - Koji Iida
- Epilepsy Center, Hiroshima University Hospital, Japan
| | - Hirofumi Maruyama
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University, Graduate School of Biomedical and Health Sciences, Japan; Epilepsy Center, Hiroshima University Hospital, Japan
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Albin CSW, Cunha CB, Glaser TP, Schachter M, Snow JW, Oto B. The Approach to Altered Mental Status in the Intensive Care Unit. Semin Neurol 2024. [PMID: 39137901 DOI: 10.1055/s-0044-1788894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Abstract
Altered mental status (AMS) is a syndrome posing substantial burden to patients in the intensive care unit (ICU) in both prevalence and intensity. Unfortunately, ICU patients are often diagnosed merely with syndromic labels, particularly the duo of toxic-metabolic encephalopathy (TME) and delirium. Before applying a nonspecific diagnostic label, every patient with AMS should be evaluated for specific, treatable diseases affecting the central nervous system. This review offers a structured approach to increase the probability of identifying specific causal etiologies of AMS in the critically ill. We provide tips for bedside assessment in the challenging ICU environment and review the role and yield of common neurodiagnostic procedures, including specialized bedside modalities of diagnostic utility in unstable patients. We briefly review two common etiologies of TME (uremic and septic encephalopathies), and then review a selection of high-yield toxicologic, neurologic, and infectious causes of AMS in the ICU, with an emphasis on those that require deliberate consideration as they elude routine screening. The final section lays out an approach to the various etiologies of AMS in the critically ill.
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Affiliation(s)
| | - Cheston B Cunha
- Warren Alpert Medical School of Brown University, Providence, Rhode Island
- Rhode Island Hospital, Providence, Rhode Island
| | - Timlin P Glaser
- University of Arizona College of Medicine, Phoenix, Arizona
- Banner University Medical Center, Phoenix, Arizona
| | | | - Jerry W Snow
- University of Arizona College of Medicine, Phoenix, Arizona
- Banner University Medical Center, Phoenix, Arizona
| | - Brandon Oto
- sBridgeport Hospital, Yale New Haven Health, Bridgeport, Connecticut
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4
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Kalkach-Aparicio M, Fatima S, Selte A, Sheikh IS, Cormier J, Gallagher K, Avagyan G, Cespedes J, Krishnamurthy PV, Elazim AA, Khan N, Hussein OM, Maganti R, Larocque J, Holla S, Desai M, Westover B, Hirsch LJ, Struck AF. Seizure Assessment and Forecasting With Efficient Rapid-EEG: A Retrospective Multicenter Comparative Effectiveness Study. Neurology 2024; 103:e209621. [PMID: 38875512 DOI: 10.1212/wnl.0000000000209621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Approximately 30% of critically ill patients have seizures, and more than half of these seizures do not have an overt clinical correlate. EEG is needed to avoid missing seizures and prevent overtreatment with antiseizure medications. Conventional-EEG (cEEG) resources are logistically constrained and unable to meet their growing demand for seizure detection even in highly developed centers. Brief EEG screening with the validated 2HELPS2B algorithm was proposed as a method to triage cEEG resources, but it is hampered by cEEG requirements, primarily EEG technologists. Seizure risk-stratification using reduced time-to-application rapid response-EEG (rrEEG) systems (∼5 minutes) could be a solution. We assessed the noninferiority of the 2HELPS2B score on a 1-hour rrEEG compared to cEEG. METHODS A multicenter retrospective EEG diagnostic accuracy study was conducted from October 1, 2021, to July 31, 2022. Chart and EEG review performed with consecutive sampling at 4 tertiary care centers, included records of patients ≥18 years old, from January 1, 2018, to June 20, 2022. Monte Carlo simulation power analysis yielded n = 500 rrEEG; for secondary outcomes n = 500 cEEG and propensity-score covariate matching was planned. Primary outcome, noninferiority of rrEEG for seizure risk prediction, was assessed per area under the receiver operator characteristic curve (AUC). Noninferiority margin (0.05) was based on the 2HELPS2B validation study. RESULTS A total of 240 rrEEG with follow-on cEEG were obtained. Median age was 64 (interquartile range 22); 42% were female. 2HELPS2B on a 1-hour rrEEG met noninferiority to cEEG (AUC 0.85, 95% CI 0.78-0.90, p = 0.001). Secondary endpoints of comparison with a matched contemporaneous cEEG showed no significant difference in AUC (0.89, 95% CI 0.83-0.94, p = 0.31); in false negative rate for the 2HELPS2B = 0 group (p = 1.0) rrEEG (0.021, 95% CI 0-0.062), cEEG (0.016, 95% CI 0-0.048); nor in survival analyses. DISCUSSION 2HELPS2B on 1-hour rrEEG is noninferior to cEEG for seizure prediction. Patients with low-risk (2HELPS2B = 0) may be able to forgo prolonged cEEG, allowing for increased monitoring of at-risk patients. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that rrEEG is noninferior to cEEG in calculating the 2HELPS2B score to predict seizure risk.
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Affiliation(s)
- Mariel Kalkach-Aparicio
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Safoora Fatima
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Atakan Selte
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Irfan S Sheikh
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Justine Cormier
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Kaileigh Gallagher
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Gayane Avagyan
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Jorge Cespedes
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Parimala V Krishnamurthy
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Ahmed Abd Elazim
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Natasha Khan
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Omar M Hussein
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Rama Maganti
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Joshua Larocque
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Smitha Holla
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Masoom Desai
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Brandon Westover
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Lawrence J Hirsch
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
| | - Aaron F Struck
- From the Department of Neurology (M.K.-A., R.M., A.F.S.), and Epilepsy Division of the Department of Neurology (S.F., A.S., G.A., P.V.K., J.L., S.H.), University of Wisconsin-Madison; Department of Neurology (S.F.), Southern Illinois University, Carbondale; Department of Neurology (A.S.), UCLA Harbor Medical Center, Torrance, CA; Epilepsy Division of Department of Neurology (I.S.S., K.G.), Massachusetts General Hospital, Boston; Comprehensive Epilepsy Center (J. Cormier, J. Cespedes, L.J.H.), Department of Neurology, Yale University, New Haven, CT; University of Connecticut School of Medicine (J. Cormier), Farmington; Epilepsy Division of Department of Neurology (K.G.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA; UHS Wilson Square Neurology (G.A.), Johnson City, NY; Universidad Autonoma de Centro America (UACA) School of Medicine (J. Cespedes), Granadilla, Cipreses, Costa Rica; Neurology Department (A.A.E., N.K., M.D.), University of New Mexico, Albuquerque; University of South Dakota (A.A.E.), Sanford School of Medicine, Vermillion; Comprehensive Epilepsy Team (O.M.H.), Neurology Department, University of New Mexico, Albuquerque; Center for Neuroengineering and Therapeutics (J.L.), University of Pennsylvania, Philadelphia; Department of Neurology (B.W.), Massachusetts General Hospital; and Beth Israel Deaconess Medical Center (B.W.), Boston, MA
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5
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Porter EM, Franck CT, Adams S. Flexible cost-penalized Bayesian model selection: Developing inclusion paths with an application to diagnosis of heart disease. Stat Med 2024; 43:3073-3091. [PMID: 38800970 DOI: 10.1002/sim.10113] [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] [Received: 04/28/2023] [Revised: 04/17/2024] [Accepted: 05/02/2024] [Indexed: 05/29/2024]
Abstract
We propose a Bayesian model selection approach that allows medical practitioners to select among predictor variables while taking their respective costs into account. Medical procedures almost always incur costs in time and/or money. These costs might exceed their usefulness for modeling the outcome of interest. We develop Bayesian model selection that uses flexible model priors to penalize costly predictors a priori and select a subset of predictors useful relative to their costs. Our approach (i) gives the practitioner control over the magnitude of cost penalization, (ii) enables the prior to scale well with sample size, and (iii) enables the creation of our proposed inclusion path visualization, which can be used to make decisions about individual candidate predictors using both probabilistic and visual tools. We demonstrate the effectiveness of our inclusion path approach and the importance of being able to adjust the magnitude of the prior's cost penalization through a dataset pertaining to heart disease diagnosis in patients at the Cleveland Clinic Foundation, where several candidate predictors with various costs were recorded for patients, and through simulated data.
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Affiliation(s)
- Erica M Porter
- School of Mathematical and Statistical Sciences, Clemson University, Clemson, South Carolina, USA
| | | | - Stephen Adams
- National Security Institute, Virginia Tech, Arlington, Virginia, USA
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6
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Bitar R, Khan UM, Rosenthal ES. Utility and rationale for continuous EEG monitoring: a primer for the general intensivist. Crit Care 2024; 28:244. [PMID: 39014421 PMCID: PMC11251356 DOI: 10.1186/s13054-024-04986-0] [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] [Received: 02/06/2024] [Accepted: 06/09/2024] [Indexed: 07/18/2024] Open
Abstract
This review offers a comprehensive guide for general intensivists on the utility of continuous EEG (cEEG) monitoring for critically ill patients. Beyond the primary role of EEG in detecting seizures, this review explores its utility in neuroprognostication, monitoring neurological deterioration, assessing treatment responses, and aiding rehabilitation in patients with encephalopathy, coma, or other consciousness disorders. Most seizures and status epilepticus (SE) events in the intensive care unit (ICU) setting are nonconvulsive or subtle, making cEEG essential for identifying these otherwise silent events. Imaging and invasive approaches can add to the diagnosis of seizures for specific populations, given that scalp electrodes may fail to identify seizures that may be detected by depth electrodes or electroradiologic findings. When cEEG identifies SE, the risk of secondary neuronal injury related to the time-intensity "burden" often prompts treatment with anti-seizure medications. Similarly, treatment may be administered for seizure-spectrum activity, such as periodic discharges or lateralized rhythmic delta slowing on the ictal-interictal continuum (IIC), even when frank seizures are not evident on the scalp. In this setting, cEEG is utilized empirically to monitor treatment response. Separately, cEEG has other versatile uses for neurotelemetry, including identifying the level of sedation or consciousness. Specific conditions such as sepsis, traumatic brain injury, subarachnoid hemorrhage, and cardiac arrest may each be associated with a unique application of cEEG; for example, predicting impending events of delayed cerebral ischemia, a feared complication in the first two weeks after subarachnoid hemorrhage. After brief training, non-neurophysiologists can learn to interpret quantitative EEG trends that summarize elements of EEG activity, enhancing clinical responsiveness in collaboration with clinical neurophysiologists. Intensivists and other healthcare professionals also play crucial roles in facilitating timely cEEG setup, preventing electrode-related skin injuries, and maintaining patient mobility during monitoring.
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Affiliation(s)
- Ribal Bitar
- Department of Neurology, Massachusetts General Hospital, 55 Fruit St., Lunder 644, Boston, MA, 02114, USA
| | - Usaamah M Khan
- Department of Neurology, Massachusetts General Hospital, 55 Fruit St., Lunder 644, Boston, MA, 02114, USA
| | - Eric S Rosenthal
- Department of Neurology, Massachusetts General Hospital, 55 Fruit St., Lunder 644, Boston, MA, 02114, USA.
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7
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Kerr WT, McFarlane KN, Figueiredo Pucci G. The present and future of seizure detection, prediction, and forecasting with machine learning, including the future impact on clinical trials. Front Neurol 2024; 15:1425490. [PMID: 39055320 PMCID: PMC11269262 DOI: 10.3389/fneur.2024.1425490] [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: 04/29/2024] [Accepted: 06/03/2024] [Indexed: 07/27/2024] Open
Abstract
Seizures have a profound impact on quality of life and mortality, in part because they can be challenging both to detect and forecast. Seizure detection relies upon accurately differentiating transient neurological symptoms caused by abnormal epileptiform activity from similar symptoms with different causes. Seizure forecasting aims to identify when a person has a high or low likelihood of seizure, which is related to seizure prediction. Machine learning and artificial intelligence are data-driven techniques integrated with neurodiagnostic monitoring technologies that attempt to accomplish both of those tasks. In this narrative review, we describe both the existing software and hardware approaches for seizure detection and forecasting, as well as the concepts for how to evaluate the performance of new technologies for future application in clinical practice. These technologies include long-term monitoring both with and without electroencephalography (EEG) that report very high sensitivity as well as reduced false positive detections. In addition, we describe the implications of seizure detection and forecasting upon the evaluation of novel treatments for seizures within clinical trials. Based on these existing data, long-term seizure detection and forecasting with machine learning and artificial intelligence could fundamentally change the clinical care of people with seizures, but there are multiple validation steps necessary to rigorously demonstrate their benefits and costs, relative to the current standard.
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Affiliation(s)
- Wesley T. Kerr
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
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8
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Desai M, Kalkach-Aparicio M, Sheikh IS, Cormier J, Gallagher K, Hussein OM, Cespedes J, Hirsch LJ, Westover B, Struck AF. Evaluating the Impact of Point-of-Care Electroencephalography on Length of Stay in the Intensive Care Unit: Subanalysis of the SAFER-EEG Trial. Neurocrit Care 2024:10.1007/s12028-024-02039-6. [PMID: 38981999 DOI: 10.1007/s12028-024-02039-6] [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: 01/29/2024] [Accepted: 06/05/2024] [Indexed: 07/11/2024]
Abstract
BACKGROUND Electroencephalography (EEG) is needed to diagnose nonconvulsive seizures. Prolonged nonconvulsive seizures are associated with neuronal injuries and deleterious clinical outcomes. However, it is uncertain whether the rapid identification of these seizures using point-of-care EEG (POC-EEG) can have a positive impact on clinical outcomes. METHODS In a retrospective subanalysis of the recently completed multicenter Seizure Assessment and Forecasting with Efficient Rapid-EEG (SAFER-EEG) trial, we compared intensive care unit (ICU) length of stay (LOS), unfavorable functional outcome (modified Rankin Scale score ≥ 4), and time to EEG between adult patients receiving a US Food and Drug Administration-cleared POC-EEG (Ceribell, Inc.) and those receiving conventional EEG (conv-EEG). Patient records from January 2018 to June 2022 at three different academic centers were reviewed, focusing on EEG timing and clinical outcomes. Propensity score matching was applied using key clinical covariates to control for confounders. Medians and interquartile ranges (IQRs) were calculated for descriptive statistics. Nonparametric tests (Mann-Whitney U-test) were used for the continuous variables, and the χ2 test was used for the proportions. RESULTS A total of 283 ICU patients (62 conv-EEG, 221 POC-EEG) were included. The two populations were matched using demographic and clinical characteristics. We found that the ICU LOS was significantly shorter in the POC-EEG cohort compared to the conv-EEG cohort (3.9 [IQR 1.9-8.8] vs. 8.0 [IQR 3.0-16.0] days, p = 0.003). Moreover, modified Rankin Scale functional outcomes were also different between the two EEG cohorts (p = 0.047). CONCLUSIONS This study reveals a significant association between early POC-EEG detection of nonconvulsive seizures and decreased ICU LOS. The POC-EEG differed from conv-EEG, demonstrating better functional outcomes compared with the latter in a matched analysis. These findings corroborate previous research advocating the benefit of early diagnosis of nonconvulsive seizure. The causal relationship between the type of EEG and metrics of interest, such as ICU LOS and functional/clinical outcomes, needs to be confirmed in future prospective randomized studies.
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Affiliation(s)
- Masoom Desai
- Department of Neurology, University of New Mexico, Albuquerque, NM, USA.
| | | | - Irfan S Sheikh
- Epilepsy Division, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Justine Cormier
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, USA
| | - Kaileigh Gallagher
- Epilepsy Division, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Omar M Hussein
- Comprehensive Epilepsy Team, Neurology Department, University of New Mexico, Albuquerque, NM, USA
| | - Jorge Cespedes
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, USA
| | - Lawrence J Hirsch
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, USA
| | - Brandon Westover
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Aaron F Struck
- Department of Neurology, University of Wisconsin, Madison, WI, USA
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9
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Kayal G, Oliveira KN, Haneef Z. Survey of Continuous EEG Monitoring Practices in the United States. J Clin Neurophysiol 2024:00004691-990000000-00142. [PMID: 38916934 DOI: 10.1097/wnp.0000000000001099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2024] Open
Abstract
OBJECTIVE Continuous EEG (cEEG) practice has markedly changed over the last decade given its utility in improving critical care outcomes. However, there are limited data describing the current cEEG infrastructure in US hospitals. METHODS A web-based cEEG practice survey was sent to neurophysiologists at 123 ACGME-accredited epilepsy or clinical neurophysiology programs. RESULTS Neurophysiologists from 100 (81.3%) institutions completed the survey. Most institutions had 3 to 10 EEG faculty (80.0%), 1 to 5 fellows (74.8%), ≥6 technologists (84.9%), and provided coverage to neurology ICUs with >10 patients (71.0%) at a time. Round-the-clock EEG technologist coverage was available at most (90.0%) institutions with technologists mostly being in-house (68.0%). Most institutions without after-hours coverage (8 of 10) attributed this to insufficient technologists. The typical monitoring duration was 24 to 48 hours (23.0 and 40.0%), most commonly for subclinical seizures (68.4%) and spell characterization (11.2%). Larger neurology ICUs had more EEG technologists ( p = 0.02), fellows ( p = 0.001), and quantitative EEG use ( p = 0.001). CONCLUSIONS This survey explores current cEEG practice patterns in the United States. Larger centers had more technologists and fellows. Overall technologist numbers are stable over time, but with a move toward more in-hospital compared with home-based coverage. Reduced availability of EEG technologists was a major factor limiting cEEG availability at some centers.
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Affiliation(s)
- Gina Kayal
- Department of Neurology, Baylor College of Medicine, Houston, Texas, U.S.A.; and
| | - Kristen N Oliveira
- Department of Neurology, Baylor College of Medicine, Houston, Texas, U.S.A.; and
| | - Zulfi Haneef
- Department of Neurology, Baylor College of Medicine, Houston, Texas, U.S.A.; and
- Neurology Care Line, Michael E. DeBakey VA Medical Center, Houston, Texas, U.S.A
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10
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Frontera JA, Gilmore EJ, Johnson EL, Olson D, Rayi A, Tesoro E, Ullman J, Yuan Y, Zafar SF, Rowe S. Guidelines for Seizure Prophylaxis in Adults Hospitalized with Moderate-Severe Traumatic Brain Injury: A Clinical Practice Guideline for Health Care Professionals from the Neurocritical Care Society. Neurocrit Care 2024; 40:819-844. [PMID: 38316735 DOI: 10.1007/s12028-023-01907-x] [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: 11/14/2023] [Accepted: 11/20/2023] [Indexed: 02/07/2024]
Abstract
BACKGROUND There is practice heterogeneity in the use, type, and duration of prophylactic antiseizure medications (ASMs) in patients with moderate-severe traumatic brain injury (TBI). METHODS We conducted a systematic review and meta-analysis of articles assessing ASM prophylaxis in adults with moderate-severe TBI (acute radiographic findings and requiring hospitalization). The population, intervention, comparator, and outcome (PICO) questions were as follows: (1) Should ASM versus no ASM be used in patients with moderate-severe TBI and no history of clinical or electrographic seizures? (2) If an ASM is used, should levetiracetam (LEV) or phenytoin/fosphenytoin (PHT/fPHT) be preferentially used? (3) If an ASM is used, should a long versus short (> 7 vs. ≤ 7 days) duration of prophylaxis be used? The main outcomes were early seizure, late seizure, adverse events, mortality, and functional outcomes. We used Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology to generate recommendations. RESULTS The initial literature search yielded 1998 articles, of which 33 formed the basis of the recommendations: PICO 1: We did not detect any significant positive or negative effect of ASM compared to no ASM on the outcomes of early seizure, late seizure, adverse events, or mortality. PICO 2: We did not detect any significant positive or negative effect of PHT/fPHT compared to LEV for early seizures or mortality, though point estimates suggest fewer late seizures and fewer adverse events with LEV. PICO 3: There were no significant differences in early or late seizures with longer versus shorter ASM use, though cognitive outcomes and adverse events appear worse with protracted use. CONCLUSIONS Based on GRADE criteria, we suggest that ASM or no ASM may be used in patients hospitalized with moderate-severe TBI (weak recommendation, low quality of evidence). If used, we suggest LEV over PHT/fPHT (weak recommendation, very low quality of evidence) for a short duration (≤ 7 days, weak recommendation, low quality of evidence).
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Affiliation(s)
- Jennifer A Frontera
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA.
- Department of Neurology, NYU, 150 55th St., Brooklyn, NY, USA.
| | - Emily J Gilmore
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Emily L Johnson
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - DaiWai Olson
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Appaji Rayi
- Department of Neurology, Charleston Area Medical Center, Charleston, WV, USA
| | - Eljim Tesoro
- Department of Pharmacy Practice, College of Pharmacy, University of Illinois at Chicago, Chicago, IL, USA
| | - Jamie Ullman
- Department of Neurosurgery, Northwell Health, Great Neck, NY, USA
| | - Yuhong Yuan
- Division of Gastroenterology, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Sahar F Zafar
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Shaun Rowe
- Department of Clinical Pharmacology, University of Tennessee Health Science Center College of Pharmacy, Knoxville, TN, USA
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11
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Bencsik C, Josephson C, Soo A, Ainsworth C, Savard M, van Diepen S, Kramer A, Kromm J. The Evolving Role of Electroencephalography in Postarrest Care. Can J Neurol Sci 2024:1-13. [PMID: 38572611 DOI: 10.1017/cjn.2024.55] [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: 04/05/2024]
Abstract
Electroencephalography is an accessible, portable, noninvasive and safe means of evaluating a patient's brain activity. It can aid in diagnosis and management decisions for post-cardiac arrest patients with seizures, myoclonus and other non-epileptic movements. It also plays an important role in a multimodal approach to neuroprognostication predicting both poor and favorable outcomes. Individuals ordering, performing and interpreting these tests, regardless of the indication, should understand the supporting evidence, logistical considerations, limitations and impact the results may have on postarrest patients and their families as outlined herein.
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Affiliation(s)
- Caralyn Bencsik
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
| | - Colin Josephson
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Andrea Soo
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
| | - Craig Ainsworth
- Division of Cardiology, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Martin Savard
- Département de Médecine, Université Laval, Quebec City, QC, Canada
| | - Sean van Diepen
- Department of Critical Care Medicine, University of Alberta, Edmonton, AB, Canada
- Division of Cardiology, Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - Andreas Kramer
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Julie Kromm
- Department of Critical Care Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Health Services, Calgary, AB, Canada
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
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12
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Punia V, Daruvala S, Dhakar MB, Zafar SF, Rubinos C, Ayub N, Hirsch LJ, Sivaraju A. Immediate and long-term management practices of acute symptomatic seizures and epileptiform abnormalities: A cross-sectional international survey. Epilepsia 2024; 65:909-919. [PMID: 38358383 DOI: 10.1111/epi.17915] [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] [Received: 09/19/2023] [Revised: 01/31/2024] [Accepted: 01/31/2024] [Indexed: 02/16/2024]
Abstract
OBJECTIVES Acute symptomatic seizures (ASyS) and epileptiform abnormalities (EAs) on electroencephalography (EEG) are commonly encountered following acute brain injury. Their immediate and long-term management remains poorly investigated. We conducted an international survey to understand their current management. METHODS The cross-sectional web-based survey of 21 fixed-response questions was based on a common clinical encounter: convulsive or suspected ASyS following an acute brain injury. Respondents selected the option that best matched their real-world practice. Respondents completing the survey were compared with those who accessed but did not complete it. RESULTS A total of 783 individuals (44 countries) accessed the survey; 502 completed it. Almost everyone used anti-seizure medications (ASMs) for secondary prophylaxis after convulsive or electrographic ASyS (95.4% and 97.2%, respectively). ASM dose escalation after convulsive ASyS depends on continuous EEG (cEEG) findings: most often increased after electrographic seizures (78% of respondents), followed by lateralized periodic discharges (LPDs; 41%) and sporadic epileptiform discharges (sEDs; 17.5%). If cEEG is unrevealing, one in five respondents discontinue ASMs after a week. In the absence of convulsive and electrographic ASyS, a large proportion of respondents start ASMs due to LPD (66.7%) and sED (44%) on cEEG. At hospital discharge, most respondents (85%) continue ASM without dose change. The recommended duration of outpatient ASM use is as follows: 1-3 months (36%), 3-6 months (30%), 6-12 months (13%), >12 months (11%). Nearly one-third of respondents utilized ancillary testing before outpatient ASM taper, most commonly (79%) a <2 h EEG. Approximately half of respondents had driving restrictions recommended for 6 months after discharge. SIGNIFICANCE ASM use for secondary prophylaxis after convulsive and electrographic ASyS is a universal practice and is continued upon discharge. Outpatient care, particularly the ASM duration, varies significantly. Wide practice heterogeneity in managing acute EAs reflects uncertainty about their significance and management. These results highlight the need for a structured outpatient follow-up and optimized care pathway for patients with ASyS.
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Affiliation(s)
- Vineet Punia
- Epilepsy Center, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Sanaya Daruvala
- Department of Neurology, Warren Alpert School of Medicine, Providence, Rhode Island, USA
| | - Monica B Dhakar
- Department of Neurology, Warren Alpert School of Medicine, Providence, Rhode Island, USA
| | - Sahar F Zafar
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Clio Rubinos
- University of North Carolina, Chapel Hill, North Carolina, USA
| | - Neishay Ayub
- Department of Neurology, Warren Alpert School of Medicine, Providence, Rhode Island, USA
| | - Lawrence J Hirsch
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, Connecticut, USA
| | - Adithya Sivaraju
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, Connecticut, USA
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13
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Frauscher B, Rossetti AO, Beniczky S. Recent advances in clinical electroencephalography. Curr Opin Neurol 2024; 37:134-140. [PMID: 38230652 DOI: 10.1097/wco.0000000000001246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
PURPOSE OF REVIEW Clinical electroencephalography (EEG) is a conservative medical field. This explains likely the significant gap between clinical practice and new research developments. This narrative review discusses possible causes of this discrepancy and how to circumvent them. More specifically, we summarize recent advances in three applications of clinical EEG: source imaging (ESI), high-frequency oscillations (HFOs) and EEG in critically ill patients. RECENT FINDINGS Recently published studies on ESI provide further evidence for the accuracy and clinical utility of this method in the multimodal presurgical evaluation of patients with drug-resistant focal epilepsy, and opened new possibilities for further improvement of the accuracy. HFOs have received much attention as a novel biomarker in epilepsy. However, recent studies questioned their clinical utility at the level of individual patients. We discuss the impediments, show up possible solutions and highlight the perspectives of future research in this field. EEG in the ICU has been one of the major driving forces in the development of clinical EEG. We review the achievements and the limitations in this field. SUMMARY This review will promote clinical implementation of recent advances in EEG, in the fields of ESI, HFOs and EEG in the intensive care.
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Affiliation(s)
- Birgit Frauscher
- Department of Neurology, Duke University Medical Center & Department of Biomedical Engineering, Duke Pratt School of Engineering, Durham, North Carolina, USA
| | - Andrea O Rossetti
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Sándor Beniczky
- Department of Clinical Neurophysiology, Danish Epilepsy Centre, Dianalund
- Aarhus University Hospital, Aarhus, Denmark
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14
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Ney JP, Nuwer MR, Hirsch LJ, Burdelle M, Trice K, Parvizi J. The Cost of After-Hour Electroencephalography. Neurol Clin Pract 2024; 14:e200264. [PMID: 38585440 PMCID: PMC10997216 DOI: 10.1212/cpj.0000000000200264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 11/21/2023] [Indexed: 04/09/2024]
Abstract
Background and Objectives High costs associated with after-hour electroencephalography (EEG) constitute a barrier for financially constrained hospitals to provide this neurodiagnostic procedure outside regular working hours. Our study aims to deepen our understanding of the cost elements involved in delivering EEG services during after-hours. Methods We accessed publicly available data sets and created a cost model depending on 3 most commonly seen staffing scenarios: (1) technologist on-site, (2) technologist on-call from home, and (3) a hybrid of the two. Results Cost of EEG depends on the volume of testing and the staffing plan. Within the various cost elements, labor cost of EEG technologists is the predominant expenditure, which varies across geographic regions and urban areas. Discussion We provide a model to explain why access to EEGs during after-hours has a substantial expense. This model provides a cost calculator tool (made available as part of this publication in eAppendix 1, links.lww.com/CPJ/A513) to estimate the cost of EEG platform based on site-specific staffing scenarios and annual volume.
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Affiliation(s)
- John P Ney
- School of Medicine (JPN), Boston University, MA; Departments of Neurology (MRN), University of California Los Angeles David Geffen School of Medicine; Department of Neurology (LJH), Yale University School of Medicine, New Haven, CT; Department of Neurology and Neurological Sciences (MB, JP), Stanford University School of Medicine, CA; and Neurodiagnostic Technology Programs (KT), Institute of Health Sciences, Hunt Valley, MD
| | - Marc R Nuwer
- School of Medicine (JPN), Boston University, MA; Departments of Neurology (MRN), University of California Los Angeles David Geffen School of Medicine; Department of Neurology (LJH), Yale University School of Medicine, New Haven, CT; Department of Neurology and Neurological Sciences (MB, JP), Stanford University School of Medicine, CA; and Neurodiagnostic Technology Programs (KT), Institute of Health Sciences, Hunt Valley, MD
| | - Lawrence J Hirsch
- School of Medicine (JPN), Boston University, MA; Departments of Neurology (MRN), University of California Los Angeles David Geffen School of Medicine; Department of Neurology (LJH), Yale University School of Medicine, New Haven, CT; Department of Neurology and Neurological Sciences (MB, JP), Stanford University School of Medicine, CA; and Neurodiagnostic Technology Programs (KT), Institute of Health Sciences, Hunt Valley, MD
| | - Mark Burdelle
- School of Medicine (JPN), Boston University, MA; Departments of Neurology (MRN), University of California Los Angeles David Geffen School of Medicine; Department of Neurology (LJH), Yale University School of Medicine, New Haven, CT; Department of Neurology and Neurological Sciences (MB, JP), Stanford University School of Medicine, CA; and Neurodiagnostic Technology Programs (KT), Institute of Health Sciences, Hunt Valley, MD
| | - Kellee Trice
- School of Medicine (JPN), Boston University, MA; Departments of Neurology (MRN), University of California Los Angeles David Geffen School of Medicine; Department of Neurology (LJH), Yale University School of Medicine, New Haven, CT; Department of Neurology and Neurological Sciences (MB, JP), Stanford University School of Medicine, CA; and Neurodiagnostic Technology Programs (KT), Institute of Health Sciences, Hunt Valley, MD
| | - Josef Parvizi
- School of Medicine (JPN), Boston University, MA; Departments of Neurology (MRN), University of California Los Angeles David Geffen School of Medicine; Department of Neurology (LJH), Yale University School of Medicine, New Haven, CT; Department of Neurology and Neurological Sciences (MB, JP), Stanford University School of Medicine, CA; and Neurodiagnostic Technology Programs (KT), Institute of Health Sciences, Hunt Valley, MD
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15
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Xie D, Toutant D, Ng MC. Residual Seizure Rate of Intermittent Inpatient EEG Compared to a Continuous EEG Model. Can J Neurol Sci 2024; 51:246-254. [PMID: 37282558 DOI: 10.1017/cjn.2023.241] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
BACKGROUND Subclinical seizures are common in hospitalized patients and require electroencephalography (EEG) for detection and intervention. At our institution, continuous EEG (cEEG) is not available, but intermittent EEGs are subject to constant live interpretation. As part of quality improvement (QI), we sought to estimate the residual missed seizure rate at a typical quaternary Canadian health care center without cEEG. METHODS We calculated residual risk percentages using the clinically validated 2HELPS2B score to risk-stratify EEGs before deriving a risk percentage using a MATLAB calculator which modeled the risk decay curve for each recording. We generated a range of estimated residual seizure rates depending on whether a pre-cEEG screening EEG was simulated, EEGs showing seizures were included, or repeat EEGs on the same patient were excluded. RESULTS Over a 4-month QI period, 499 inpatient EEGs were scored as low (n = 125), medium (n = 123), and high (n = 251) seizure risk according to 2HELPS2B criteria. Median recording duration was 1:00:06 (interquartile range, IQR 30:40-2:21:10). The model with highest residual seizure rate included recordings with confirmed electrographic seizures (median 20.83%, IQR 20.6-26.6%), while the model with lowest residual seizure rate was in seizure-free recordings (median 10.59%, IQR 4%-20.6%). These rates were significantly higher than the benchmark 5% miss-rate threshold set by 2HELPS2B (p<0.0001). CONCLUSIONS We estimate that intermittent inpatient EEG misses 2-4 times more subclinical seizures than the 2HELPS2B-determined acceptable 5% seizure miss-rate threshold for cEEG. Future research is needed to determine the impact of potentially missed seizures on clinical care.
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Affiliation(s)
- Dave Xie
- Undergraduate Medical Education, University of Manitoba, Winnipeg, MB, Canada
| | - Darion Toutant
- Biomedical Engineering Program, University of Manitoba, Winnipeg, MB, Canada
| | - Marcus C Ng
- Biomedical Engineering Program, University of Manitoba, Winnipeg, MB, Canada
- Section of Neurology, University of Manitoba, Winnipeg, MB, Canada
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16
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Gohara D, Neshige S, Sakahara H, Ohno N, Maruyama H. Therapeutic Time Window With DWI-ADC (Diffusion-Weighted Imaging-Apparent Diffusion Coefficient) Match and Periodic Discharges for Status Epilepticus. Cureus 2024; 16:e53811. [PMID: 38465051 PMCID: PMC10924183 DOI: 10.7759/cureus.53811] [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] [Accepted: 02/07/2024] [Indexed: 03/12/2024] Open
Abstract
A man in his 70s with alcoholic dementia was admitted for acute, prolonged impaired consciousness. Blood and cerebrospinal fluid findings were unremarkable. Brain MRI revealed multiple high-signal cortical regions. Following diazepam and levetiracetam administration, electroencephalography (EEG) revealed <1 Hz lateralized periodic discharges, indicating that the seizures were ceasing. The periodic discharges had disappeared during the gradual recovery process by day 10; however, cortical arterial spin labeling findings persisted only in regions exhibiting cytotoxic edema. Without additional anti-seizure medication, no seizure recurred, but cognitive dysfunction remained. He was transferred to a rehabilitation hospital with the continued oral administration of levetiracetam at 1,000 mg/day. DWI-ADC (diffusion-weighted imaging-apparent diffusion coefficient) match may suggest an indication of a missed suitable treatment window for seizures.
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Affiliation(s)
- Daiki Gohara
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University Hospital, Hiroshima, JPN
| | - Shuichiro Neshige
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University, Hiroshima, JPN
| | - Hideaki Sakahara
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, JPN
| | - Narumi Ohno
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, JPN
| | - Hirofumi Maruyama
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, JPN
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17
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Ammanuel SG, Page PS, Brooks NP, Resnick DK. Development of a Predictive Model for Persistent Instability Following Conservative Management of Type II Odontoid Fractures. World Neurosurg 2024; 181:e422-e426. [PMID: 37863424 DOI: 10.1016/j.wneu.2023.10.073] [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: 09/08/2023] [Revised: 10/12/2023] [Accepted: 10/13/2023] [Indexed: 10/22/2023]
Abstract
BACKGROUND Odontoid fractures are common cervical spine fractures; however, significant controversy exists regarding their treatment. Risk factors for failure of conservative therapy have been identified, although no predictive risk score has been developed to aid in decision-making. METHODS A retrospective review was conducted of all patients evaluated at a level 1 trauma center. Patients identified with type II odontoid fractures as classified by the D'Alonzo Classification system who were treated with external orthosis were included in analysis. Patients were considered to have failed conservative therapy if they were offered surgical intervention. A machine learning method (Risk-SLIM) was then utilized to create a risk stratification score based on risk factors to identify patients at high risk for requiring surgical intervention due to persistent instability. RESULTS A total of 138 patients were identified as presenting with type II odontoid fractures that were treated conservatively; 38 patients were offered surgery for persistent instability. The Odontoid Fracture Predictive Model (OFPM) was created using a machine learning algorithm with a 5-fold cross validation area under the curve of 0.7389 (95% CI: 0.671 to 0.808). Predictive factors were found to include fracture displacement, displacement greater than 5 mm, comminution at the fracture base, and history of smoking. The probability of persistent instability was <5% with a score of 0 and 88% with a score of 5. CONCLUSIONS The OFPM model is a unique, quick, and accurate tool to assist in clinical decision-making in patients with type II odontoid fractures. External validation is necessary to evaluate the validity of these findings.
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Affiliation(s)
- Simon G Ammanuel
- Department of Neurological Surgery, University of Wisconsin Hospitals and Clinics, Madison, Wisconsin, USA.
| | - Paul S Page
- Department of Neurological Surgery, University of Wisconsin Hospitals and Clinics, Madison, Wisconsin, USA
| | - Nathaniel P Brooks
- Department of Neurological Surgery, University of Wisconsin Hospitals and Clinics, Madison, Wisconsin, USA
| | - Daniel K Resnick
- Department of Neurological Surgery, University of Wisconsin Hospitals and Clinics, Madison, Wisconsin, USA
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18
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Rossetti AO, Claassen J, Gaspard N. Status epilepticus in the ICU. Intensive Care Med 2024; 50:1-16. [PMID: 38117319 DOI: 10.1007/s00134-023-07263-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: 07/14/2023] [Accepted: 10/26/2023] [Indexed: 12/21/2023]
Abstract
Status epilepticus (SE) is a common medical emergency associated with significant morbidity and mortality. Management that follows published guidelines is best suited to improve outcomes, with the most severe cases frequently being managed in the intensive care unit (ICU). Diagnosis of convulsive SE can be made without electroencephalography (EEG), but EEG is required to reliably diagnose nonconvulsive SE. Rapidly narrowing down underlying causes for SE is crucial, as this may guide additional management steps. Causes may range from underlying epilepsy to acute brain injuries such as trauma, cardiac arrest, stroke, and infections. Initial management consists of rapid administration of benzodiazepines and one of the following non-sedating intravenous antiseizure medications (ASM): (fos-)phenytoin, levetiracetam, or valproate; other ASM are increasingly used, such as lacosamide or brivaracetam. SE that continues despite these medications is called refractory, and most commonly treated with continuous infusions of midazolam or propofol. Alternatives include further non-sedating ASM and non-pharmacologic approaches. SE that reemerges after weaning or continues despite management with propofol or midazolam is labeled super-refractory SE. At this step, management may include non-sedating or sedating compounds including ketamine and barbiturates. Continuous video EEG is necessary for the management of refractory and super-refractory SE, as these are almost always nonconvulsive. If possible, management of the underlying cause of seizures is crucial particularly for patients with autoimmune encephalitis. Short-term mortality ranges from 10 to 15% after SE and is primarily related to increasing age, underlying etiology, and medical comorbidities. Refractoriness of treatment is clearly related to outcome with mortality rising from 10% in responsive cases, to 25% in refractory, and nearly 40% in super-refractory SE.
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Affiliation(s)
- Andrea O Rossetti
- Department of Neurology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Jan Claassen
- Department of Neurology, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, NY, USA
| | - Nicolas Gaspard
- Service de Neurologie, Hôpital Universitaire de Bruxelles, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, 1070, Brussels, Belgium.
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA.
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19
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Kerr WT, McFarlane KN. Machine Learning and Artificial Intelligence Applications to Epilepsy: a Review for the Practicing Epileptologist. Curr Neurol Neurosci Rep 2023; 23:869-879. [PMID: 38060133 DOI: 10.1007/s11910-023-01318-7] [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] [Accepted: 10/24/2023] [Indexed: 12/08/2023]
Abstract
PURPOSE OF REVIEW Machine Learning (ML) and Artificial Intelligence (AI) are data-driven techniques to translate raw data into applicable and interpretable insights that can assist in clinical decision making. Some of these tools have extremely promising initial results, earning both great excitement and creating hype. This non-technical article reviews recent developments in ML/AI in epilepsy to assist the current practicing epileptologist in understanding both the benefits and limitations of integrating ML/AI tools into their clinical practice. RECENT FINDINGS ML/AI tools have been developed to assist clinicians in almost every clinical decision including (1) predicting future epilepsy in people at risk, (2) detecting and monitoring for seizures, (3) differentiating epilepsy from mimics, (4) using data to improve neuroanatomic localization and lateralization, and (5) tracking and predicting response to medical and surgical treatments. We also discuss practical, ethical, and equity considerations in the development and application of ML/AI tools including chatbots based on Large Language Models (e.g., ChatGPT). ML/AI tools will change how clinical medicine is practiced, but, with rare exceptions, the transferability to other centers, effectiveness, and safety of these approaches have not yet been established rigorously. In the future, ML/AI will not replace epileptologists, but epileptologists with ML/AI will replace epileptologists without ML/AI.
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Affiliation(s)
- Wesley T Kerr
- Department of Neurology, University of Pittsburgh, 3471 Fifth Ave, Kaufmann 811.22, Pittsburgh, PA, 15213, USA.
- Department of Biomedical Informatics, University of Pittsburgh, 3471 Fifth Ave, Kaufmann 811.22, Pittsburgh, PA, 15213, USA.
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA.
| | - Katherine N McFarlane
- Department of Neurology, University of Pittsburgh, 3471 Fifth Ave, Kaufmann 811.22, Pittsburgh, PA, 15213, USA
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20
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Fukuma K, Tojima M, Tanaka T, Kobayashi K, Kajikawa S, Shimotake A, Kamogawa N, Ikeda S, Ishiyama H, Abe S, Morita Y, Nakaoku Y, Ogata S, Nishimura K, Koga M, Toyoda K, Matsumoto R, Takahashi R, Ikeda A, Ihara M. Periodic discharges plus fast activity on electroencephalogram predict worse outcomes in poststroke epilepsy. Epilepsia 2023; 64:3279-3293. [PMID: 37611936 DOI: 10.1111/epi.17760] [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] [Received: 03/11/2023] [Revised: 08/21/2023] [Accepted: 08/21/2023] [Indexed: 08/25/2023]
Abstract
OBJECTIVE Postseizure functional decline is a concern in poststroke epilepsy (PSE). However, data on electroencephalogram (EEG) markers associated with functional decline are scarce. Thus, we investigated whether periodic discharges (PDs) and their specific characteristics are associated with functional decline in patients with PSE. METHODS In this observational study, patients admitted with seizures of PSE and who had scalp EEGs were included. The association between the presence or absence of PDs and postseizure short-term functional decline lasting 7 days after admission was investigated. In patients with PD, EEG markers were explored for risk stratification of short-term functional decline, according to the American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology. The association between EEG markers and imaging findings and long-term functional decline at discharge and 6 months after discharge, defined as an increase in the modified Rankin Scale score compared with the baseline, was evaluated. RESULTS In this study, 307 patients with PSE (median age = 75 years, range = 35-97 years, 64% males; hemorrhagic stroke, 47%) were enrolled. Compared with 247 patients without PDs, 60 patients with PDs were more likely to have short-term functional decline (12 [20%] vs. 8 [3.2%], p < .001), with an adjusted odds ratio (OR) of 4.26 (95% confidence interval [CI] = 1.44-12.6, p = .009). Patients with superimposed fast-activity PDs (PDs+F) had significantly more localized (rather than widespread) lesions (87% vs. 58%, p = .003), prolonged hyperperfusion (100% vs. 62%, p = .023), and a significantly higher risk of short-term functional decline than those with PDs without fast activity (adjusted OR = 22.0, 95% CI = 1.87-259.4, p = .014). Six months after discharge, PDs+F were significantly associated with long-term functional decline (adjusted OR = 4.21, 95% CI = 1.27-13.88, p = .018). SIGNIFICANCE In PSE, PDs+F are associated with sustained neuronal excitation and hyperperfusion, which may be a predictor of postseizure short- and long-term functional decline.
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Affiliation(s)
- Kazuki Fukuma
- Department of Neurology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Maya Tojima
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Tomotaka Tanaka
- Department of Neurology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Katsuya Kobayashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Shunsuke Kajikawa
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Akihiro Shimotake
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Naruhiko Kamogawa
- Department of Cerebrovascular Medicine, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Shuhei Ikeda
- Department of Neurology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Hiroyuki Ishiyama
- Department of Neurology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Soichiro Abe
- Department of Neurology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Yoshiaki Morita
- Department of Radiology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Yuriko Nakaoku
- Department of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Soshiro Ogata
- Department of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Kunihiro Nishimura
- Department of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Masatoshi Koga
- Department of Cerebrovascular Medicine, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Kazunori Toyoda
- Department of Cerebrovascular Medicine, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Riki Matsumoto
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
- Division of Neurology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Akio Ikeda
- Department of Epilepsy, Movement Disorders, and Physiology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Masafumi Ihara
- Department of Neurology, National Cerebral and Cardiovascular Center, Osaka, Japan
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Neshige S, Toko M, Aoki S, Maruyama H. Density spectrum array and difficult to diagnose seizure activity. QJM 2023; 116:947-948. [PMID: 37338538 DOI: 10.1093/qjmed/hcad138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 06/12/2023] [Indexed: 06/21/2023] Open
Affiliation(s)
- Shuichiro Neshige
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University Graduate School of Biomedical and Health Sciences, Japan
- Epilepsy Center, Hiroshima University Hospital, 1-2-3 Minami-ku Kasumi, Hiroshima 734-8551, Japan
| | - Megumi Toko
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University Graduate School of Biomedical and Health Sciences, Japan
| | - Shiro Aoki
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University Graduate School of Biomedical and Health Sciences, Japan
| | - Hirofumi Maruyama
- Department of Clinical Neuroscience and Therapeutics, Hiroshima University Graduate School of Biomedical and Health Sciences, Japan
- Epilepsy Center, Hiroshima University Hospital, 1-2-3 Minami-ku Kasumi, Hiroshima 734-8551, Japan
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22
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Fenter H, Rossetti AO, Beuchat I. Continuous versus Routine Electroencephalography in the Intensive Care Unit: A Review of Current Evidence. Eur Neurol 2023; 87:17-25. [PMID: 37952533 PMCID: PMC11003555 DOI: 10.1159/000535085] [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: 07/17/2023] [Accepted: 11/05/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND Electroencephalography (EEG) has long been used to detect seizures in patients with disorders of consciousness. In recent years, there has been a drastically increased adoption of continuous EEG (cEEG) in the intensive care units (ICUs). Given the resources necessary to record and interpret cEEG, this is still not available in every center and widespread recommendations to use continuous instead of routine EEG (typically lasting 20 min) are still a matter of some debate. Considering recent literature and personal experience, this review offers a rationale and practical advice to address this question. SUMMARY Despite the development of increasingly performant imaging techniques and several validated biomarkers, EEG remains central to clinicians in the intensive care unit and has been experiencing expanding popularity for at least 2 decades. Not only does EEG allow seizure or status epilepticus detection, which in the ICU often present without clinical movements, but it is also paramount for the prognostic evaluation of comatose patients, especially after cardiac arrest, and for detecting delayed ischemia after subarachnoid hemorrhage. At the end of the last Century, improvements of technical and digital aspects regarding recording and storage of EEG tracings have progressively led to the era of cEEG and automated quantitative analysis. KEY MESSAGES As compared to repeated rEEG, cEEG in comatose patients does not seem to improve clinical prognosis to a relevant extent, despite allowing a more performant of detection ictal events and consequent therapeutic modifications. The choice between cEEG and rEEG must therefore always be patient-tailored.
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Affiliation(s)
- Helene Fenter
- Department of Neurology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Andrea O Rossetti
- Department of Neurology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Isabelle Beuchat
- Department of Neurology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, Lausanne, Switzerland
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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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Haider HA, Perucca P. Targeted continuous EEG monitoring in critically ill patients: The long and the short of a scalability problem. Epilepsia Open 2023; 8:721-723. [PMID: 37343151 PMCID: PMC10472376 DOI: 10.1002/epi4.12777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 06/16/2023] [Indexed: 06/23/2023] Open
Affiliation(s)
- Hiba A. Haider
- Department of Neurology, Comprehensive Epilepsy CenterUniversity of ChicagoChicagoIllinoisUSA
| | - Piero Perucca
- Department of Medicine (Austin Health), Epilepsy Research CentreThe University of MelbourneMelbourneVictoriaAustralia
- Bladin‐Berkovic Comprehensive Epilepsy Program, Department of NeurologyAustin HealthMelbourneVictoriaAustralia
- Department of Neuroscience, Central Clinical SchoolMonash UniversityMelbourneVictoriaAustralia
- Department of NeurologyAlfred HealthMelbourneVictoriaAustralia
- Department of NeurologyThe Royal Melbourne HospitalMelbourneVictoriaAustralia
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25
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Morris NA, Sarwal A. Neurologic Complications of Critical Medical Illness. Continuum (Minneap Minn) 2023; 29:848-886. [PMID: 37341333 DOI: 10.1212/con.0000000000001278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/22/2023]
Abstract
OBJECTIVE This article reviews the neurologic complications encountered in patients admitted to non-neurologic intensive care units, outlines various scenarios in which a neurologic consultation can add to the diagnosis or management of a critically ill patient, and provides advice on the best diagnostic approach in the evaluation of these patients. LATEST DEVELOPMENTS Increasing recognition of neurologic complications and their adverse impact on long-term outcomes has led to increased neurology involvement in non-neurologic intensive care units. The COVID-19 pandemic has highlighted the importance of having a structured clinical approach to neurologic complications of critical illness as well as the critical care management of patients with chronic neurologic disabilities. ESSENTIAL POINTS Critical illness is often accompanied by neurologic complications. Neurologists need to be aware of the unique needs of critically ill patients, especially the nuances of the neurologic examination, challenges in diagnostic testing, and neuropharmacologic aspects of commonly used medications.
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26
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Lee DA, Park KM, Kim HC, Khoo CS, Lee BI, Kim SE. Spectrum of Ictal-Interictal Continuum: The Significance of 2HELPS2B Score and Background Suppression. J Clin Neurophysiol 2023; 40:364-370. [PMID: 34510091 DOI: 10.1097/wnp.0000000000000894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
PURPOSE The aims of this study were to identify (1) the spectrum of ictal-interictal continuum (IIC) using the two dimensions of 2HELPS2B score and background suppression and (2) the response to subsequent anti-seizure drugs depends on the spectrum of IIC. METHODS The study prospectively enrolled 62 patients with IIC on EEG. The diagnosis of nonconvulsive status epilepticus was attempted with Salzburg criteria as well as clinical and neuroimaging data. IICs were dichotomized into patients with nonconvulsive status epilepticus and coma-IIC. The 2HELPS2B score was evaluated as the original proposal. The suppression ratio was analyzed with Persyst software. RESULTS Forty-seven cases (75.8%) were nonconvulsive status epilepticus-IIC and 15 cases (24.2%) were coma-IIC. Multivariate analysis revealed that the 2HELPS2B score was the only significant variable dichotomizing the spectrum of IIC (odds ratio, 3.0; 95% confidence interval, 1.06-8.6; P = 0.03 for nonconvulsive status epilepticus-IIC). In addition, the suppression ratio was significantly negatively correlated with 2HELPS2B scores (Spearman coefficient = -0.37, P = 0.004 for left hemisphere and Spearman coefficient = -0.3, P = 0.02 for right hemisphere). Furthermore, patients with higher 2HELPS2B score (74% [14/19] in ≥2 points vs. 44% [14/32] in <2 points, P = 0.03 by χ 2 test) and lower suppression ratio (62% [23/37] in ≤2.18 vs. 35% [6/17] in >2.18, P = 0.06 by χ 2 test) seemed to be more responsive to subsequent anti-seizure drug. CONCLUSIONS The 2HELPS2B score and background suppression can be used to distinguish the spectrum of IIC and thereby predict the response to subsequent anti-seizure drug.
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Affiliation(s)
- Dong Ah Lee
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
| | - Kang Min Park
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
| | - Hyung Chan Kim
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
| | - Ching Soong Khoo
- Neurology Unit, Department of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia ; and
| | - Byung In Lee
- Department of Neurology, CHA Ilsan Medical Center, Ilsan, Republic of Korea
| | - Sung Eun Kim
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea
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27
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Fong MWK. Critical care EEG monitoring: improving access and unravelling potentially epileptic patterns. Curr Opin Neurol 2023; 36:61-68. [PMID: 36762643 DOI: 10.1097/wco.0000000000001147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
PURPOSE OF REVIEW The major advances in critical care EEG have been the development of rapid response EEG, major revision of the American Clinical Neurophysiology Society's (ACNS) standardized critical care EEG terminology, and the commencement of treatment trials on rhythmic and periodic patterns (RPPs) that do not qualify as seizures. RECENT FINDINGS Rapid response EEG (rEEG) has proven an important supplement to full montage continuous EEG monitoring (cEEG). This EEG can be applied in a few minutes and provides excellent ability to exclude seizures, selecting those where conversion to cEEG would have the greatest diagnostic yield. Once cEEG has been commenced, the durations required to adequately exclude seizures have been refined. The ACNS provided major revision and expansion to the standardized critical care EEG terminology, which paved the way for determining with great accuracy the RPPs that are associated with seizures and that are capable of causing neurologic symptoms and/or secondary neuronal injury. The current limitations to multicenter treatment trials of these patterns have been highlighted. SUMMARY Novel methods of EEG in critical care have been expanding access to all patients where clinically indicated. Standardized EEG terminology has provided the framework to determine what patterns in which presenting causes warrant treatment vs. those that do not.
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Affiliation(s)
- Michael W K Fong
- Westmead Comprehensive Epilepsy Unit, Westmead Hospital, University of Sydney, Sydney, Australia
- Comprehensive Epilepsy Center, Department of Neurology, Yale University School of Medicine, New Haven, Connecticut, USA
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Gavaret M, Iftimovici A, Pruvost-Robieux E. EEG: Current relevance and promising quantitative analyses. Rev Neurol (Paris) 2023; 179:352-360. [PMID: 36907708 DOI: 10.1016/j.neurol.2022.12.008] [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: 09/09/2022] [Revised: 12/02/2022] [Accepted: 12/06/2022] [Indexed: 03/12/2023]
Abstract
Electroencephalography (EEG) remains an essential tool, characterized by an excellent temporal resolution and offering a real window on cerebral functions. Surface EEG signals are mainly generated by the postsynaptic activities of synchronously activated neural assemblies. EEG is also a low-cost tool, easy to use at bed-side, allowing to record brain electrical activities with a low number or up to 256 surface electrodes. For clinical purpose, EEG remains a critical investigation for epilepsies, sleep disorders, disorders of consciousness. Its temporal resolution and practicability also make EEG a necessary tool for cognitive neurosciences and brain-computer interfaces. EEG visual analysis is essential in clinical practice and the subject of recent progresses. Several EEG-based quantitative analyses may complete the visual analysis, such as event-related potentials, source localizations, brain connectivity and microstates analyses. Some developments in surface EEG electrodes appear also, potentially promising for long term continuous EEGs. We overview in this article some recent progresses in visual EEG analysis and promising quantitative analyses.
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Affiliation(s)
- M Gavaret
- Université Paris Cité, INSERM UMR 1266, IPNP (Institute of Psychiatry and Neuroscience of Paris), France; Service de Neurophysiologie Clinique et Epileptologie, GHU Paris Psychiatrie et Neurosciences, Paris, France; FHU NeuroVasc, Paris, France.
| | - A Iftimovici
- Université Paris Cité, INSERM UMR 1266, IPNP (Institute of Psychiatry and Neuroscience of Paris), France; NeuroSpin, Atomic Energy Commission, Gif-sur-Yvette, France; Pôle PEPIT, GHU Paris Psychiatrie et Neurosciences, Paris, France
| | - E Pruvost-Robieux
- Université Paris Cité, INSERM UMR 1266, IPNP (Institute of Psychiatry and Neuroscience of Paris), France; Service de Neurophysiologie Clinique et Epileptologie, GHU Paris Psychiatrie et Neurosciences, Paris, France; FHU NeuroVasc, Paris, France
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29
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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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30
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Pavel AM, O'Toole JM, Proietti J, Livingstone V, Mitra S, Marnane WP, Finder M, Dempsey EM, Murray DM, Boylan GB. Machine learning for the early prediction of infants with electrographic seizures in neonatal hypoxic-ischemic encephalopathy. Epilepsia 2023; 64:456-468. [PMID: 36398397 PMCID: PMC10107538 DOI: 10.1111/epi.17468] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 10/26/2022] [Accepted: 11/15/2022] [Indexed: 11/20/2022]
Abstract
OBJECTIVE To assess if early clinical and electroencephalography (EEG) features predict later seizure development in infants with hypoxic-ischemic encephalopathy (HIE). METHODS Clinical and EEG parameters <12 h of birth from infants with HIE across eight European Neonatal Units were used to develop seizure-prediction models. Clinical parameters included intrapartum complications, fetal distress, gestational age, delivery mode, gender, birth weight, Apgar scores, assisted ventilation, cord pH, and blood gases. The earliest EEG hour provided a qualitative analysis (discontinuity, amplitude, asymmetry/asynchrony, sleep-wake cycle [SWC]) and a quantitative analysis (power, discontinuity, spectral distribution, inter-hemispheric connectivity) from full montage and two-channel amplitude-integrated EEG (aEEG). Subgroup analysis, only including infants without anti-seizure medication (ASM) prior to EEG was also performed. Machine-learning (ML) models (random forest and gradient boosting algorithms) were developed to predict infants who would later develop seizures and assessed using Matthews correlation coefficient (MCC) and area under the receiver-operating characteristic curve (AUC). RESULTS The study included 162 infants with HIE (53 had seizures). Low Apgar, need for ventilation, high lactate, low base excess, absent SWC, low EEG power, and increased EEG discontinuity were associated with seizures. The following predictive models were developed: clinical (MCC 0.368, AUC 0.681), qualitative EEG (MCC 0.467, AUC 0.729), quantitative EEG (MCC 0.473, AUC 0.730), clinical and qualitative EEG (MCC 0.470, AUC 0.721), and clinical and quantitative EEG (MCC 0.513, AUC 0.746). The clinical and qualitative-EEG model significantly outperformed the clinical model alone (MCC 0.470 vs 0.368, p-value .037). The clinical and quantitative-EEG model significantly outperformed the clinical model (MCC 0.513 vs 0.368, p-value .012). The clinical and quantitative-EEG model for infants without ASM (n = 131) had MCC 0.588, AUC 0.832. Performance for quantitative aEEG (n = 159) was MCC 0.381, AUC 0.696 and clinical and quantitative aEEG was MCC 0.384, AUC 0.720. SIGNIFICANCE Early EEG background analysis combined with readily available clinical data helped predict infants who were at highest risk of seizures, hours before they occur. Automated quantitative-EEG analysis was as good as expert analysis for predicting seizures, supporting the use of automated assessment tools for early evaluation of HIE.
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Affiliation(s)
- Andreea M. Pavel
- INFANT Research CentreUniversity College CorkCorkIreland
- Department of Paediatrics and Child HealthUniversity College CorkCorkIreland
| | - John M. O'Toole
- INFANT Research CentreUniversity College CorkCorkIreland
- Department of Paediatrics and Child HealthUniversity College CorkCorkIreland
| | | | - Vicki Livingstone
- INFANT Research CentreUniversity College CorkCorkIreland
- Department of Paediatrics and Child HealthUniversity College CorkCorkIreland
| | | | - William P. Marnane
- INFANT Research CentreUniversity College CorkCorkIreland
- Electrical & Electronic EngineeringSchool of EngineeringUniversity College CorkCorkIreland
| | - Mikael Finder
- Department of Neonatal MedicineKarolinska University HospitalStockholmSweden
- Division of Paediatrics, Department CLINTECKarolinska InstitutetStockholmSweden
| | - Eugene M. Dempsey
- INFANT Research CentreUniversity College CorkCorkIreland
- Department of Paediatrics and Child HealthUniversity College CorkCorkIreland
| | - Deirdre M. Murray
- INFANT Research CentreUniversity College CorkCorkIreland
- Department of Paediatrics and Child HealthUniversity College CorkCorkIreland
| | - Geraldine B. Boylan
- INFANT Research CentreUniversity College CorkCorkIreland
- Department of Paediatrics and Child HealthUniversity College CorkCorkIreland
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Zawar I, Ghosal S, Hantus S, Punia V. Indications for continuous electroencephalographic (cEEG) monitoring: What do they tell us? Epilepsy Res 2023; 190:107088. [PMID: 36731271 DOI: 10.1016/j.eplepsyres.2023.107088] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 12/27/2022] [Accepted: 01/12/2023] [Indexed: 01/21/2023]
Abstract
OBJECTIVE While studies have explored clinical and EEG predictors of seizures on continuous EEG (cEEG), the role of cEEG indications as predictors of seizures has not been studied. Our study aims to fill this knowledge gap. METHODS We used the prospective cEEG database at Cleveland Clinic for the 2016 calendar year. Patients ≥ 18 years who underwent cEEG for the indication of altered mental status (AMS) and seizure-like events (SLE: motor or patient-reported events) were included. Baseline characteristics and EEG findings were compared between the two groups. Multivariable regression was used to compare the two groups and identify seizure detection risk factors. RESULTS Of 2227 patients (mean age 59.4 years) who met the inclusion criteria, 882 (50% females) underwent cEEG for AMS and 1345(51% females) for SLE. SLE patients were younger(OR: 0.988, CI: 0.98-0.99, p < 0.001), had longer monitoring(OR:1.04, CI:1.00-1.07, p = 0.033), were more likely to have epilepsy-related-breakthrough seizures(OR:25.9, CI:0.5.89-115, p < 0.001), psychogenic non-epileptic spells (OR:6.85, CI:1.60-29.3, p = 0.008), were more awake (p < 0.001) and more likely to be on anti-seizure medications(OR:1.60, CI:1.29-1.98, p < 0.001). On multivariable analysis, SLE was an independent predictor of seizure detection (OR: 2.60, CI: 1.77-3.88, p < 0.001). SIGNIFICANCE Our findings highlight the differences in patients undergoing cEEG for AMS vs. SLE. SLE as a cEEG indication represents an independent predictor of seizures on cEEG and, therefore, deserves special attention. Future multicenter studies are needed to validate our findings.
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Affiliation(s)
- Ifrah Zawar
- Department of Neurology, Epilepsy Division, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.
| | - Soutik Ghosal
- Department of Public Health Sciences, Division of Biostatistics, University of Virginia School of Medicine, Charlottesville, VA 22908, USA.
| | - Stephen Hantus
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
| | - Vineet Punia
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
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32
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Freund BE, Brigham T, Salman S, Kaplan PW, Tatum WO. From Alpha to Zeta: A Systematic Review of Zeta Waves. J Clin Neurophysiol 2023; 40:2-8. [PMID: 36604788 DOI: 10.1097/wnp.0000000000000972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
PURPOSE Electroencephalogram is used for prognostication and diagnosis in critically ill patients and is vital in developing clinical management algorithms. Unique waveforms on EEG may distinguish neurological disorders and define a potential for seizures. To better characterize zeta waves, we sought to define their electroclinical spectrum. METHODS We performed a systematic review using MEDLINE, Embase, Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Review [through Ovid], Scopus, Science Citation Index Expanded and Emerging Sources Citation Index [through the Web of Science], and Epistemonikos. Grey literature resources were searched. RESULTS Five hundred thirty-seven articles were identified. After excluding duplicates and reviewing titles, abstracts, and bodies and bibliographies of articles, four studies reported 64 cases describing data from patients with zeta waves, with a prevalence of 3 to 4%. Various and often incomplete clinical, neuroimaging, and EEG data were available. 57 patients (89.1%) had a focal cerebral lesion concordant with the location of zeta waves on EEG. 26 patients (40.6%) had clinical seizures, all but one being focal onset. Thirteen patients (20%) had epileptiform activity on EEG. Typically, zeta waves were located in the frontal head regions, often with generalized, frontal, predominant, rhythmic delta activity and associated with focal EEG suppression. CONCLUSIONS Zeta waves frequently represent an underlying focal structural lesion. Their presence suggests a heightened risk for seizures. The small number of retrospective cases series in the literature reporting zeta waves might be an underrepresentation. We suggest a need for prospective studies of cEEG in critically ill patients to determine their clinical significance.
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Affiliation(s)
- Brin E Freund
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, U.S.A
| | - Tara Brigham
- Mayo Clinic Libraries, Mayo Clinic, Jacksonville, Florida, U.S.A.; and
| | - Saif Salman
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, U.S.A
| | - Peter W Kaplan
- Department of Neurology, Johns Hopkins Bayview Medical Center, Baltimore, Maryland, U.S.A
| | - William O Tatum
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, U.S.A
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Abou Khaled KJ, Bou Nasif M, Freiji C, Hirsch LJ, Fong MW. Rapid response EEG with needle electrodes in an intensive care unit with limited resources. Clin Neurophysiol Pract 2023; 8:44-48. [PMID: 36949936 PMCID: PMC10025002 DOI: 10.1016/j.cnp.2023.02.002] [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: 09/12/2022] [Revised: 01/17/2023] [Accepted: 02/14/2023] [Indexed: 02/24/2023] Open
Abstract
Objective Continuous EEG (cEEG) is the gold standard for detecting seizures and rhythmic and periodic patterns (RPPs) in critically ill patients but is often not available in health systems with limited resources. The current study aims to determine the feasibility and utility of low-cost, practical, limited montage, sub-dermal needle electrode EEG in a setting where otherwise no EEG would be available. Methods The study included all adult patients admitted to the intensive care unit of a single center over a 24-month period. Members of the existing ICU care team, mostly nurses, were trained to place 8 sub-dermal needle EEG electrodes to achieve rapid, limited montage-EEG recording. Clinical outcomes were recorded, including any reported major complications; and the EEG findings documented, including background characterization, RPPs, and seizures. Results One hundred twenty-three patients, mean age 68 years, underwent an average of 15.6 min of EEG recording. There were no complications of electrode placement. Overall, 13.0% had seizures (8.1% qualifying as status epilepticus [SE]), 18.7 % had generalized periodic discharges (GPDs), 4.9% had lateralized periodic discharges (LPDs), and 11.4 % sporadic epileptiform discharges (sEDs). Greater mortality was observed in patients with worse background EEGs, seizures, LPDs, or sEDs. Conclusions Rapid, limited montage EEG could be achieved safely and inexpensively in a broad population of critically ill patients following minimal training of existing care teams. Significance For resource poor centers or centers outside of major metropolitan areas who otherwise have no access to EEG, this may prove a useful method for screening for non-convulsive seizures and status epilepticus.
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Affiliation(s)
- Karine J. Abou Khaled
- Department of Neurology, Hotel-Dieu de France Hospital, Saint-Joseph University, Beirut, Lebanon
- Corresponding author.
| | - Mei Bou Nasif
- Department of Medicine, Hotel-Dieu de France Hospital, Saint-Joseph University, Beirut, Lebanon
| | - Claudia Freiji
- Illinois Risk Lab, Department of Mathematics, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - Lawrence J. Hirsch
- Comprehensive Epilepsy Center, Yale School of Medicine, New Haven, CT, USA
| | - Michael W.K. Fong
- Comprehensive Epilepsy Center, Yale School of Medicine, New Haven, CT, USA
- Westmead Comprehensive Epilepsy Unit, Westmead Hospital, University of Sydney, Sydney, Australia
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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: 3] [Impact Index Per Article: 1.5] [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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Page PS, Greeneway GP, Ammanuel SG, Resnick DK. Creation and validation of a predictive model for lumbar synovial cyst recurrence following decompression without fusion. J Neurosurg Spine 2022; 37:851-854. [PMID: 35907198 DOI: 10.3171/2022.5.spine22504] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 05/27/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Lumbar synovial cysts (LSCs) represent a relatively rare clinical pathology that may result in radiculopathy or neurogenic claudication. Because of the potential for recurrence of these cysts, some authors advocate for segmental fusion, as opposed to decompression alone, as a way to eliminate the risk for recurrence. The objective of this study was to create a predictive score for synovial cyst recurrence following decompression without fusion. METHODS A retrospective chart review was completed of all patients evaluated at a single center over 20 years who were found to have symptomatic LSCs requiring intervention. Only patients undergoing decompression without fusion were included in the analysis. Following this review, baseline characteristics were obtained as well as radiological information. A machine learning method (risk-calibrated supersparse linear integer model) was then used to create a risk stratification score to identify patients at high risk for symptomatic cyst recurrence requiring repeat surgical intervention. Following the creation of this model, a fivefold cross-validation was completed. RESULTS In total, 89 patients were identified who had complete radiological information. Of these 89 patients, 11 developed cyst recurrence requiring reoperation. The Lumbar Synovial Cyst Score was then created with an area under the curve of 0.83 and calibration error of 11.0%. Factors predictive of recurrence were found to include facet inclination angle > 45°, canal stenosis > 50%, T2 joint space hyperintensity, and presence of grade I spondylolisthesis. The probability of cyst recurrence ranged from < 5% for a score of 2 or less to > 88% for a score of 7. CONCLUSIONS The Lumbar Synovial Cyst Score model is a quick and accurate tool to assist in clinical decision-making in the treatment of LSCs.
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Wang X, Yang F, Chen B, Jiang W. Non‐convulsive seizures and non‐convulsive status epilepticus in neuro‐intensive care unit. Acta Neurol Scand 2022; 146:752-760. [DOI: 10.1111/ane.13718] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 10/07/2022] [Accepted: 10/11/2022] [Indexed: 11/28/2022]
Affiliation(s)
- Xuan Wang
- Department of Neurology, Xijing Hospital Fourth Military Medical University Xi'an China
| | - Fang Yang
- Department of Neurology, Xijing Hospital Fourth Military Medical University Xi'an China
| | - Beibei Chen
- Department of Neurology, Xijing Hospital Fourth Military Medical University Xi'an China
| | - Wen Jiang
- Department of Neurology, Xijing Hospital Fourth Military Medical University Xi'an China
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Gélisse P, Kaplan PW. How to evaluate and assess the epileptogenic/seizure potential of periodic discharges along the ictal-interictal continuum? ZEITSCHRIFT FÜR EPILEPTOLOGIE 2022. [DOI: 10.1007/s10309-022-00526-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
AbstractThe ictal–interictal continuum (IIC) is a concept used for those particular EEG patterns that do not meet the strict criteria for status epilepticus but may be associated with neuronal injury. The aim of this article is to review equivocal periodic patterns and to discuss their clinical significance along the IIC. The risk of seizures increases when the frequency of periodic discharges exceeds 2 Hz and when the pattern has features of superimposed rhythmic, sharp, or fast activity (plus modifier). Lateralized periodic discharges (LPDs) are one of the best examples of the IIC. Criteria have been proposed for identifying patterns along the IIC that we called “peri-ictal” LPDs. There is ongoing debate about when to treat patients with these EEG patterns along this spectrum. The term IIC is only an EEG description, and does not in itself reflect a clinical diagnosis, hence management is based on EEG alone. The decision to intensify treatment is based on the combination of EEG, the underlying etiology, the level of consciousness, comorbidities, imaging, and other surrogates of “damage.”
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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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Muhlestein WE, Koduri S, Park P. Commentary: Development and Validation of a Predictive Model for Failure of Medical Management in Spinal Epidural Abscesses. Neurosurgery 2022; 91:e81-e82. [PMID: 35876675 DOI: 10.1227/neu.0000000000002066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 05/10/2022] [Indexed: 11/19/2022] Open
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Page PS, Greeneway GP, Ammanuel SG, Brooks NP. Development and Validation of a Predictive Model for Failure of Medical Management in Spinal Epidural Abscesses. Neurosurgery 2022; 91:422-426. [PMID: 35584275 DOI: 10.1227/neu.0000000000002043] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 04/03/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The optimal management of spinal epidural abscesses (SEA) secondary to primary spinal infections has demonstrated large variability in the literature. Although some literature suggests a high rate of neurological deterioration, others suggest failure of medical management is uncommon. OBJECTIVE To develop a predictive model to evaluate the likelihood of failure of medical therapy in the setting of SEA. METHODS A retrospective review was conducted of all patients presenting with SEA from primary spinal infections. Patients presenting with MRI evidence of SEA without neurological deficits were included. Failure of medical management was defined as requiring surgical intervention over 72 hours after the initiation of antibiotics. A machine learning method (Risk-Calibrated Supersparse Linear Integer Model) was used to create a risk stratification score to identify patients at high risk for requiring surgical intervention. RESULTS In total, 159 patients were identified as presenting with MRI findings of SEA without evidence of neurological deficit. Of these patients, 50 required delayed surgery compared with 109 whose infection were successfully treated with surgical intervention. The Spinal Epidural Abscess Predictive Score was created using a machine learning model with an area under the curve of 0.8043 with calibration error of 14.7%. Factors included active malignancy, spondylodiscitis, organism identification, blood cultures, and sex. The probability of failure of medical management ranged from <5% for a score of 2 or less and >95% for a score of 7 or more. CONCLUSION The Spinal Epidural Abscess Predictive Score model is a quick and accurate tool to assist in clinical decision-making in SEA.
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Affiliation(s)
- Paul S Page
- Department of Neurological Surgery, University of Wisconsin Hospitals and Clinics, Madison, Wisconsin, USA
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Pinto LF, Oliveira JPSD, Midon AM. Status epilepticus: review on diagnosis, monitoring and treatment. ARQUIVOS DE NEURO-PSIQUIATRIA 2022; 80:193-203. [PMID: 35976303 PMCID: PMC9491413 DOI: 10.1590/0004-282x-anp-2022-s113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 04/29/2022] [Indexed: 06/15/2023]
Abstract
Status epilepticus (SE) is a frequent neurological emergency associated with high morbidity and mortality. According to the new ILAE 2015 definition, SE results either from the failure of the mechanisms responsible for seizure termination or initiation, leading to abnormally prolonged seizures. The definition has different time points for convulsive, focal and absence SE. Time is brain. There are changes in synaptic receptors leading to a more proconvulsant state and increased risk of brain lesion and sequelae with long duration. Management of SE must include three pillars: stop seizures, stabilize patients to avoid secondary lesions and treat underlying causes. Convulsive SE is defined after 5 minutes and is a major emergency. Benzodiazepines are the initial treatment, and should be given fast and an adequate dose. Phenytoin/fosphenytoin, levetiracetam and valproic acid are evidence choices for second line treatment. If SE persists, anesthetic drugs are probably the best option for third line treatment, despite lack of evidence. Midazolam is usually the best initial choice and barbiturates should be considered for refractory cases. Nonconvulsive status epilepticus has a similar initial approach, with benzodiazepines and second line intravenous (IV) agents, but after that, aggressiveness should be balanced considering risk of lesion due to seizures and medical complications caused by aggressive treatment. Usually, the best approach is the use of sequential IV antiepileptic drugs (oral/tube are options if IV options are not available). EEG monitoring is crucial for diagnosis of nonconvulsive SE, after initial control of convulsive SE and treatment control. Institutional protocols are advised to improve care.
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Affiliation(s)
- Lecio Figueira Pinto
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, Grupo de Epilepsia, São Paulo SP, Brazil
| | | | - Aston Marques Midon
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Departamento de Neurologia, São Paulo SP, Brazil
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EEG recording latency in critically ill patients: impact on outcome. An analysis of a randomized controlled trial (CERTA). Clin Neurophysiol 2022; 139:23-27. [DOI: 10.1016/j.clinph.2022.04.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/29/2022] [Accepted: 04/04/2022] [Indexed: 12/14/2022]
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Fatima S, Sun M, Gjini K, Struck AF. Association Between Lateralized Periodic Discharge Amplitude and Seizure on Continuous EEG Monitoring in Patients With Structural Brain Abnormality in Critical Illness. Front Neurol 2022; 13:840247. [PMID: 35370885 PMCID: PMC8966838 DOI: 10.3389/fneur.2022.840247] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 02/07/2022] [Indexed: 12/15/2022] Open
Abstract
Objective To investigate the association between lateralized periodic discharge (LPD) amplitude and seizure risk on an individual level in patients with structural brain abnormality. Methods Retrospective case-control study of patients with structural brain abnormality undergoing continuous EEG monitoring was performed. We included 10 patients with LPDs and seizures as cases and 10 controls, patients with LPDs without seizure. Analysis was performed with a mixed-effects model with primary outcome measure of number of seizures per 8-h EEG epoch with fixed effects being variables of interest and random effect being subject ID. Results Epochs with seizures showed a higher absolute amplitude (corrected p = 0.04) and a higher relative amplitude (corrected p = 0.04) of LPDs. Additionally, the number of seizures was higher in epochs that had LPDs with plus features (uncorrected p = 0.002) and LPDs with higher relative amplitude (uncorrected p = 0.005). Conclusion Higher LPD amplitude is associated with increased risk of seizures on an individual patient level. A decreasing amplitude is suggestive of decreasing seizure risk, and may in fact be suggestive of decreasing ictal character of LPDs.
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Affiliation(s)
- Safoora Fatima
- Department of Neurology, Wisconsin Hospital and Clinics, University of Wisconsin, Madison, WI, United States,*Correspondence: Safoora Fatima
| | - Mengzhen Sun
- Department of Neurology, Wisconsin Hospital and Clinics, University of Wisconsin, Madison, WI, United States
| | - Klevest Gjini
- Department of Neurology, Wisconsin Hospital and Clinics, University of Wisconsin, Madison, WI, United States
| | - Aaron F. Struck
- Department of Neurology, Wisconsin Hospital and Clinics, University of Wisconsin, Madison, WI, United States,William S. Middleton Memorial Veterans Hospital, University of Wisconsin, Madison, WI, United States
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Foreman B, Lee H, Okonkwo DO, Strong AJ, Pahl C, Shutter LA, Dreier JP, Ngwenya LB, Hartings JA. The Relationship Between Seizures and Spreading Depolarizations in Patients with Severe Traumatic Brain Injury. Neurocrit Care 2022; 37:31-48. [PMID: 35174446 DOI: 10.1007/s12028-022-01441-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 01/04/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND Both seizures and spreading depolarizations (SDs) are commonly detected using electrocorticography (ECoG) after severe traumatic brain injury (TBI). A close relationship between seizures and SDs has been described, but the implications of detecting either or both remain unclear. We sought to characterize the relationship between these two phenomena and their clinical significance. METHODS We performed a post hoc analysis of a prospective observational clinical study of patients with severe TBI requiring neurosurgery at five academic neurotrauma centers. A subdural electrode array was placed intraoperatively and ECoG was recorded during intensive care. SDs, seizures, and high-frequency background characteristics were quantified offline using published standards and terminology. The primary outcome was the Glasgow Outcome Scale-Extended score at 6 months post injury. RESULTS There were 138 patients with valid ECoG recordings; the mean age was 47 ± 19 years, and 104 (75%) were men. Overall, 2,219 ECoG-detected seizures occurred in 38 of 138 (28%) patients in a bimodal pattern, with peak incidences at 1.7-1.8 days and 3.8-4.0 days post injury. Seizures detected on scalp electroencephalography (EEG) were diagnosed by standard clinical care in only 18 of 138 (13%). Of 15 patients with ECoG-detected seizures and contemporaneous scalp EEG, seven (47%) had no definite scalp EEG correlate. ECoG-detected seizures were significantly associated with the severity and number of SDs, which occurred in 83 of 138 (60%) of patients. Temporal interactions were observed in 17 of 24 (70.8%) patients with both ECoG-detected seizures and SDs. After controlling for known prognostic covariates and the presence of SDs, seizures detected on either ECoG or scalp EEG did not have an independent association with 6-month functional outcome but portended worse outcome among those with clustered or isoelectric SDs. CONCLUSIONS In patients with severe TBI requiring neurosurgery, seizures were half as common as SDs. Seizures would have gone undetected without ECoG monitoring in 20% of patients. Although seizures alone did not influence 6-month functional outcomes in this cohort, they were independently associated with electrographic worsening and a lack of motor improvement following surgery. Temporal interactions between ECoG-detected seizures and SDs were common and held prognostic implications. Together, seizures and SDs may occur along a dynamic continuum of factors critical to the development of secondary brain injury. ECoG provides information integral to the clinical management of patients with TBI.
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Affiliation(s)
- Brandon Foreman
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, 231 Albert Sabin Way, Cincinnati, OH, USA. .,Collaborative for Research on Acute Neurological Injuries, University of Cincinnati, Cincinnati, OH, USA.
| | - Hyunjo Lee
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, 231 Albert Sabin Way, Cincinnati, OH, USA.,Collaborative for Research on Acute Neurological Injuries, University of Cincinnati, Cincinnati, OH, USA
| | - David O Okonkwo
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Anthony J Strong
- Department of Basic and Clinical Neuroscience, King's College London, London, UK
| | - Clemens Pahl
- Department of Intensive Care Medicine, King's College Hospital, London, UK
| | - Lori A Shutter
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Critical Care Medicine and Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jens P Dreier
- Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Experimental Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany.,Einstein Center for Neurosciences Berlin, Berlin, Germany
| | - Laura B Ngwenya
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, 231 Albert Sabin Way, Cincinnati, OH, USA.,Collaborative for Research on Acute Neurological Injuries, University of Cincinnati, Cincinnati, OH, USA.,Department of Neurosurgery, University of Cincinnati, Cincinnati, OH, USA
| | - Jed A Hartings
- Collaborative for Research on Acute Neurological Injuries, University of Cincinnati, Cincinnati, OH, USA.,Department of Neurosurgery, University of Cincinnati, Cincinnati, OH, USA
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Fan JM, Singhal NS, Guterman EL. Management of Status Epilepticus and Indications for Inpatient Electroencephalography Monitoring. Neurol Clin 2022; 40:1-16. [PMID: 34798964 DOI: 10.1016/j.ncl.2021.08.001] [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: 11/22/2022]
Abstract
Status epilepticus (SE) is a neurologic emergency requiring immediate time-sensitive treatment to minimize neuronal injury and systemic complications. Minimizing time to administration of first- and second-line therapy is necessary to optimize the chances of successful seizure termination in generalized convulsive SE (GCSE). The approach to refractory and superrefractory GCSE is less well defined. Multiple agents with differing complementary actions that facilitate seizure termination are recommended. Nonconvulsive SE (NCSE) has a wide range of presentations and approaches to treatment. Continuous electroencephalography is critical to the management of both GCSE and NCSE, while its use for patients without seizure continues to expand.
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Affiliation(s)
- Joline M Fan
- Department of Neurology, University of California, San Francisco, 505 Parnassus Avenue, M798 Box 0114, San Francisco, CA 94143, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA.
| | - Neel S Singhal
- Department of Neurology, University of California, San Francisco, 505 Parnassus Avenue, M798 Box 0114, San Francisco, CA 94143, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Elan L Guterman
- Department of Neurology, University of California, San Francisco, 505 Parnassus Avenue, M798 Box 0114, San Francisco, CA 94143, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
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Peedicail J, Mehdiratta N, Zhu S, Nedjadrasul P, Ng MC. Quantitative burst suppression on serial intermittent EEG in refractory status epilepticus. Clin Neurophysiol Pract 2021; 6:275-280. [PMID: 34825115 PMCID: PMC8604990 DOI: 10.1016/j.cnp.2021.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 10/03/2021] [Accepted: 10/23/2021] [Indexed: 11/24/2022] Open
Abstract
Quantitative burst suppression ratios (QBSR) represent depth of EEG suppression. Deeper QBSR on serial intermittent EEG did not affect survival in RSE. Non-suppressive continuous EEG effects on RSE mortality merits further research.
Objectives In refractory status epilepticus (RSE), the optimal degree of suppression (EEG burst suppression or merely suppressing seizures) remains unknown. Many centers lacking continuous EEG must default to serial intermittent recordings where uncertainty from lack of data may prompt more aggressive suppression. In this study, we sought to determine whether the quantitative burst suppression ratio (QBSR) from serial intermittent EEG recording is associated with RSE patient outcome. Methods We screened the EEG database to identify non-anoxic adult RSE patients for EEG and chart review. QBSR was calculated per 10-second EEG epoch as the percentage of time during which EEG amplitude was <3 µV. Patients who survived 1–3 months after discharge from ICU and hospital comprised the favorable group. Further to initial unadjusted univariate analysis of all pooled QBSR, we conducted multivariate analyses to account for individual patient confounders (“per-capita analysis”), uneven number of EEG recordings (“per-session analysis”), and uneven number of epochs (“per-epoch analysis”). We analyzed gender, anesthetic number, and adjusted status epilepticus severity score (aSTESS) as confounders. Results In 135,765 QBSR values over 160 EEG recordings (median 2.17 h every ≥24 h) from 17 patients on Propofol, Midazolam, and/or Ketamine, QBSR was deeper in the favorable group (p < 0.001) on initial unadjusted analysis. However, on adjusted multivariate analysis, there was consistently no association between QBSR and outcome. Higher aSTESS consistently associated with unfavorable outcome on per-capita (p = 0.033), per-session (p = 0.048) and per-epoch (p < 0.001) analyses. Greater maximal number of non-barbiturate anesthetic associated with favorable outcome on per-epoch analysis (p < 0.001). Conclusions There was no association between depth of EEG suppression using non-barbiturate anesthetic and RSE patient outcome based on QBSR from serial intermittent EEG. A per-epoch association between non-barbiturate anesthetic and favorable outcome suggests an effect from non-suppressive time-varying EEG content. Significance Targeting and following deeper burst suppression through non-barbiturate anesthetics on serial intermittent EEG monitoring of RSE is of limited utility.
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Affiliation(s)
- Joseph Peedicail
- Section of Neurology, University of Manitoba, Winnipeg, MB, Canada
| | - Neil Mehdiratta
- Section of Neurology, University of Manitoba, Winnipeg, MB, Canada
| | - Shenghua Zhu
- Department of Radiology, University of Ottawa, Ottawa, ON, Canada
| | | | - Marcus C Ng
- Section of Neurology, University of Manitoba, Winnipeg, MB, Canada
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Abstract
Purpose of this review This review presents current therapy for seizures in the intensive care unit. The reader is provided with recent evidence regarding the use of EEG in determining treatment for acute seizures. Proposed treatment approaches for seizures and status epilepticus are provided. Controversies and complexity of selecting treatments are discussed. Recent findings Critical Care EEG Monitoring Research Consortium analyzed the association of periodic and rhythmic electroencephalographic patterns with seizures and found that lateralized and generalized periodic discharges and lateralized rhythmic delta were associated with increased seizure risk. Applications using modified EEG techniques have demonstrated more rapid feedback to the ICU than was previously possible. Summary Accurate diagnosis and efficient treatment of seizures in the ICU is challenging due to patient factors, complexities of antiepileptic drug therapy, and the required expertise for EEG interpretation. Selection of optimally effective therapy for seizures or status epilepticus depends on multiple factors, making collaboration between neurophysiologists and the ICU team of paramount importance.
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Affiliation(s)
- Jane G Boggs
- Comprehensive Epilepsy Center, Wake Forest University, Winston-Salem, NC USA
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Rosenthal ES. Seizures, Status Epilepticus, and Continuous EEG in the Intensive Care Unit. Continuum (Minneap Minn) 2021; 27:1321-1343. [PMID: 34618762 DOI: 10.1212/con.0000000000001012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
PURPOSE OF REVIEW This article discusses the evolving definitions of seizures and status epilepticus in the critical care environment and the role of critical care EEG in both diagnosing seizure activity and serving as a predictive biomarker of clinical trajectory. RECENT FINDINGS Initial screening EEG has been validated as a tool to predict which patients are at risk of future seizures. However, accepted definitions of seizures and nonconvulsive status epilepticus encourage a treatment trial when the diagnosis on EEG is indeterminate because of periodic or rhythmic patterns or uncertain clinical correlation. Similarly, recent data have demonstrated the diagnostic utility of intracranial EEG in increasing the yield of seizure detection. EEG has additionally been validated as a diagnostic biomarker of covert consciousness, a predictive biomarker of cerebral ischemia and impending neurologic deterioration, and a prognostic biomarker of coma recovery and status epilepticus resolution. A recent randomized trial concluded that patients allocated to continuous EEG had no difference in mortality than those undergoing intermittent EEG but could not demonstrate whether this lack of difference was because of studying heterogeneous conditions, examining a monitoring tool rather than a therapeutic approach, or examining an outcome measure (mortality) perhaps more strongly associated with early withdrawal of life-sustaining therapy than to a sustained response to pharmacotherapy. SUMMARY Seizures and status epilepticus are events of synchronous hypermetabolic activity that are either discrete and intermittent or, alternatively, continuous. Seizures and status epilepticus represent the far end of a continuum of ictal-interictal patterns that include lateralized rhythmic delta activity and periodic discharges, which not only predict future seizures but may be further classified as status epilepticus on the basis of intracranial EEG monitoring or a diagnostic trial of antiseizure medication therapy. In particularly challenging cases, neuroimaging or multimodality neuromonitoring may be a useful adjunct documenting metabolic crisis. Specialized uses of EEG as a prognostic biomarker have emerged in traumatic brain injury for predicting language function and covert consciousness, cardiac arrest for predicting coma recovery, and subarachnoid hemorrhage for predicting neurologic deterioration due to delayed cerebral ischemia.
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Jacq G, Legriel S. Nurses: The Missing Link in Continuous EEG Monitoring? Neurol Clin Pract 2021; 11:363-364. [PMID: 34840861 PMCID: PMC8610515 DOI: 10.1212/cpj.0000000000001108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Gwenaëlle Jacq
- Intensive Care Unit (GJ, SL), Centre Hospitalier de Versailles; IctalGroup (GJ, SL), Le Chesnay; and Paris-Saclay University (SL), UVSQ, INSERM, CESP, Villejuif, France
| | - Stephane Legriel
- Intensive Care Unit (GJ, SL), Centre Hospitalier de Versailles; IctalGroup (GJ, SL), Le Chesnay; and Paris-Saclay University (SL), UVSQ, INSERM, CESP, Villejuif, France
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Jones FJ, Sanches PR, Smith JR, Zafar SF, Hernandez-Diaz S, Blacker D, Hsu J, Schwamm LH, Westover MB, Moura LM. Anticonvulsant Primary and Secondary Prophylaxis for Acute Ischemic Stroke Patients: A Decision Analysis. Stroke 2021; 52:2782-2791. [PMID: 34126758 PMCID: PMC8384723 DOI: 10.1161/strokeaha.120.033299] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background and Purpose We examined the impact of 3 anticonvulsant prophylaxis strategies on quality-adjusted life-years (QALYs) among patients with an incident acute ischemic stroke. Methods We created a decision tree to evaluate 3 strategies: (1) long-term primary prophylaxis; (2) short-term secondary prophylaxis after an early seizure with lifetime prophylaxis if persistent or late seizures (LSs) developed; and (3) long-term secondary prophylaxis if either early, late, or persistent seizures developed. The outcome was quality-adjusted life expectancy (QALY). We created 4 base cases to simulate common clinical scenarios: (1) female patient aged 40 years with a 2% or 11% lifetime risk of an LS and a 33% lifetime risk of an adverse drug reaction (ADR); (2) male patient aged 65 years with a 6% or 29% LS risk and 60% ADR risk; (3) male patient aged 50 years with an 18% or 65% LS risk and 33% ADR risk; and (4) female patient aged 80 years with a 29% or 83% LS risk and 80% ADR risk. In sensitivity analyses, we altered the parameters and assumptions. Results Across all 4 base cases, primary prophylaxis yielded the fewest QALYs when compared with secondary prophylaxis. For example, under scenario 1, strategies 2 and 3 resulted in 7.17 QALYs each, but strategy 1 yielded only 6.91 QALYs. Under scenario 4, strategies 2 and 3 yielded 2.85 QALYs compared with 1.40 QALYs for strategy 1. Under scenarios in which patients had higher ADR risks, strategy 2 led to the most QALYs. Conclusions Short-term therapy with continued anticonvulsant prophylaxis only after postischemic stroke seizures arise dominates lifetime primary prophylaxis in all scenarios examined. Our findings reinforce the necessity of close follow-up and discontinuation of anticonvulsant seizure prophylaxis started during acute ischemic stroke hospitalization.
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Affiliation(s)
- Felipe J.S. Jones
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Paula R. Sanches
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
- Department of Critical Care Medicine, Hospital Israelita Albert Einstein, Sao Paulo, Brazil
| | - Jason R. Smith
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Sahar F. Zafar
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
- Department of Neurology, Harvard Medical School, Boston, Massachusetts
| | - Sonia Hernandez-Diaz
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Deborah Blacker
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - John Hsu
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts. Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Mongan Institute for Health Policy, Massachusetts General Hospital, Boston, Massachusetts
| | - Lee H. Schwamm
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
- Department of Neurology, Harvard Medical School, Boston, Massachusetts
| | - Michael B. Westover
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
- Department of Neurology, Harvard Medical School, Boston, Massachusetts
| | - Lidia M.V.R. Moura
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
- Department of Neurology, Harvard Medical School, Boston, Massachusetts
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