Quantitative EEG improves prediction of Sturge-Weber syndrome in infants with port-wine birthmark.


Journal

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
ISSN: 1872-8952
Titre abrégé: Clin Neurophysiol
Pays: Netherlands
ID NLM: 100883319

Informations de publication

Date de publication:
10 2021
Historique:
received: 21 03 2021
revised: 05 06 2021
accepted: 19 06 2021
pubmed: 29 8 2021
medline: 23 11 2021
entrez: 28 8 2021
Statut: ppublish

Résumé

Port-wine birthmark (PWB) is a common occurrence in the newborn, and general pediatricians, dermatologists, and ophthalmologists are often called on to make an assessment of risk for Sturge-Weber syndrome (SWS) due to workforce shortages in pediatric neurologists and MRI's low sensitivity for SWS brain involvement in infants. We therefore aimed to develop a quantitative EEG (qEEG) approach to safely screen young infants with PWB for SWS risk and optimal timing of diagnostic MRI. Forty-eight infants (prior to first birthday) underwent EEG recording. Signal processing methods compared voltage between left and right sides using a previously defined pipeline and diagnostic threshold. In this test sample, we compared sensitivity/specificity of the qEEG metric against MRI performed after the first birthday. We also used likelihood ratio testing to determine whether qEEG adds incremental information beyond topographical extent of PWB, another risk marker of brain involvement. qEEG helped predict SWS risk in the first year of life (p = 0.031), with a sensitivity of 50% and a specificity of 81%. It added about 40% incremental information beyond PWB extent alone (p = 0.042). qEEG adds information to risk prediction in infants with facial PWB. qEEG can be used to help determine whether to obtain an MRI in the first year of life. The data collected can assist in developing a predictive model risk calculator that incorporates both PWB extent and qEEG results, which can be validated and then employed in the community.

Identifiants

pubmed: 34454271
pii: S1388-2457(21)00682-9
doi: 10.1016/j.clinph.2021.06.030
pmc: PMC8478826
mid: NIHMS1730819
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2440-2446

Subventions

Organisme : NINDS NIH HHS
ID : K12 NS001696
Pays : United States
Organisme : NINDS NIH HHS
ID : K23 NS073626
Pays : United States
Organisme : NICHD NIH HHS
ID : P50 HD103538
Pays : United States
Organisme : NINDS NIH HHS
ID : U54 NS065705
Pays : United States

Informations de copyright

Copyright © 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Ryan E Gill (RE)

Kennedy Krieger Institute, Baltimore, MD, USA; Johns Hopkins University, Baltimore, MD, USA.

Bohao Tang (B)

Johns Hopkins University, Baltimore, MD, USA.

Lindsay Smegal (L)

Kennedy Krieger Institute, Baltimore, MD, USA.

Jack H Adamek (JH)

Kennedy Krieger Institute, Baltimore, MD, USA.

Danielle McAuliffe (D)

Kennedy Krieger Institute, Baltimore, MD, USA.

Balaji M Lakshmanan (BM)

Kennedy Krieger Institute, Baltimore, MD, USA.

Siddharth Srivastava (S)

Kennedy Krieger Institute, Baltimore, MD, USA; Johns Hopkins University, Baltimore, MD, USA.

Angela M Quain (AM)

Kennedy Krieger Institute, Baltimore, MD, USA.

Alison J Sebold (AJ)

Kennedy Krieger Institute, Baltimore, MD, USA.

Doris D M Lin (DDM)

Johns Hopkins University, Baltimore, MD, USA.

Eric H Kossoff (EH)

Johns Hopkins University, Baltimore, MD, USA.

Brian Caffo (B)

Johns Hopkins University, Baltimore, MD, USA.

Anne M Comi (AM)

Kennedy Krieger Institute, Baltimore, MD, USA; Johns Hopkins University, Baltimore, MD, USA.

Joshua B Ewen (JB)

Kennedy Krieger Institute, Baltimore, MD, USA; Johns Hopkins University, Baltimore, MD, USA. Electronic address: ewen@kennedykrieger.org.

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Classifications MeSH