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Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-d-Aspartate Receptor Antibody Encephalitis

Anti–N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG wa...

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Autores principales: Blackman, Graham, Kumar, Kieron, Hanrahan, John G., Dalrymple, Anthony, Mullatti, Nandini, Moran, Nick, Valentin, Antonio, Gibson, Lucy, Pollak, Thomas A., David, Anthony S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Journal of Clinical Neurophysiology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886530/
https://www.ncbi.nlm.nih.gov/pubmed/34238869
http://dx.doi.org/10.1097/WNP.0000000000000877
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author Blackman, Graham
Kumar, Kieron
Hanrahan, John G.
Dalrymple, Anthony
Mullatti, Nandini
Moran, Nick
Valentin, Antonio
Gibson, Lucy
Pollak, Thomas A.
David, Anthony S.
author_facet Blackman, Graham
Kumar, Kieron
Hanrahan, John G.
Dalrymple, Anthony
Mullatti, Nandini
Moran, Nick
Valentin, Antonio
Gibson, Lucy
Pollak, Thomas A.
David, Anthony S.
author_sort Blackman, Graham
collection PubMed
description Anti–N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG was able to predict outcomes in patients with suspected anti-NMDAR encephalitis. METHODS: A retrospective, observational study was conducted of patients admitted to a tertiary clinical neuroscience center with suspected anti-NMDAR encephalitis. Peak power and peak frequency within delta (<4 Hz), theta (4–8 Hz), alpha (8 - 13 Hz), and beta (13–30 Hz) frequency bands were calculated for the first clinical EEG recording. Outcome was based on the modified Rankin Scale (mRS) score at 1 year after hospital discharge. Binomial logistic regression using backward elimination was performed with peak frequency and power, anti-NMDAR Encephalitis One-Year Functional Status score, age, and interval from symptom onset to EEG entered as predictors. RESULTS: Twenty patients were included (mean age 48.6 years, 70% female), of which 7 (35%) had a poor clinical outcome (mRS 2–6) at 1 year. There was no association between reported EEG abnormalities and outcome. The final logistic regression model was significant (χ(2)(1) = 6.35, P < 0.012) with peak frequency in the delta range (<4 Hz) the only retained predictor. The model explained 38% of the variance (Nagelkerke R(2)) and correctly classified 85% of cases. Higher peak frequency in the delta range was significantly associated (P = 0.04) with an increased likelihood of poor outcome. CONCLUSIONS: In this exploratory study, it was found that quantitative EEG on routinely collected EEG recordings in patients with suspected anti-NMDAR encephalitis was feasible. A higher peak frequency within the delta range was associated with poorer clinical outcome and may indicate anti-NMDAR-mediated synaptic dysfunction. Quantitative EEG may have clinical utility in predicting outcomes in patients with suspected NMDAR antibody encephalitis, thereby serving as a useful adjunct to qualitative EEG assessment; however, given the small sample size, replication in a larger scale is indicated.
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spelling pubmed-98865302023-02-07 Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-d-Aspartate Receptor Antibody Encephalitis Blackman, Graham Kumar, Kieron Hanrahan, John G. Dalrymple, Anthony Mullatti, Nandini Moran, Nick Valentin, Antonio Gibson, Lucy Pollak, Thomas A. David, Anthony S. J Clin Neurophysiol Original Research Anti–N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG was able to predict outcomes in patients with suspected anti-NMDAR encephalitis. METHODS: A retrospective, observational study was conducted of patients admitted to a tertiary clinical neuroscience center with suspected anti-NMDAR encephalitis. Peak power and peak frequency within delta (<4 Hz), theta (4–8 Hz), alpha (8 - 13 Hz), and beta (13–30 Hz) frequency bands were calculated for the first clinical EEG recording. Outcome was based on the modified Rankin Scale (mRS) score at 1 year after hospital discharge. Binomial logistic regression using backward elimination was performed with peak frequency and power, anti-NMDAR Encephalitis One-Year Functional Status score, age, and interval from symptom onset to EEG entered as predictors. RESULTS: Twenty patients were included (mean age 48.6 years, 70% female), of which 7 (35%) had a poor clinical outcome (mRS 2–6) at 1 year. There was no association between reported EEG abnormalities and outcome. The final logistic regression model was significant (χ(2)(1) = 6.35, P < 0.012) with peak frequency in the delta range (<4 Hz) the only retained predictor. The model explained 38% of the variance (Nagelkerke R(2)) and correctly classified 85% of cases. Higher peak frequency in the delta range was significantly associated (P = 0.04) with an increased likelihood of poor outcome. CONCLUSIONS: In this exploratory study, it was found that quantitative EEG on routinely collected EEG recordings in patients with suspected anti-NMDAR encephalitis was feasible. A higher peak frequency within the delta range was associated with poorer clinical outcome and may indicate anti-NMDAR-mediated synaptic dysfunction. Quantitative EEG may have clinical utility in predicting outcomes in patients with suspected NMDAR antibody encephalitis, thereby serving as a useful adjunct to qualitative EEG assessment; however, given the small sample size, replication in a larger scale is indicated. Journal of Clinical Neurophysiology 2023-02 2021-07-02 /pmc/articles/PMC9886530/ /pubmed/34238869 http://dx.doi.org/10.1097/WNP.0000000000000877 Text en Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Clinical Neurophysiology Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Original Research
Blackman, Graham
Kumar, Kieron
Hanrahan, John G.
Dalrymple, Anthony
Mullatti, Nandini
Moran, Nick
Valentin, Antonio
Gibson, Lucy
Pollak, Thomas A.
David, Anthony S.
Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-d-Aspartate Receptor Antibody Encephalitis
title Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-d-Aspartate Receptor Antibody Encephalitis
title_full Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-d-Aspartate Receptor Antibody Encephalitis
title_fullStr Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-d-Aspartate Receptor Antibody Encephalitis
title_full_unstemmed Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-d-Aspartate Receptor Antibody Encephalitis
title_short Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-d-Aspartate Receptor Antibody Encephalitis
title_sort quantitative eeg as a prognostic tool in suspected anti-n-methyl-d-aspartate receptor antibody encephalitis
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886530/
https://www.ncbi.nlm.nih.gov/pubmed/34238869
http://dx.doi.org/10.1097/WNP.0000000000000877
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