Literature DB >> 19782640

Detection of subclinical electroencephalographic seizure patterns with multichannel amplitude-integrated EEG in full-term neonates.

Mireille D Bourez-Swart1, Linda van Rooij2, Cristiano Rizzo3, Linda S de Vries2, Mona C Toet2, Tineke A Gebbink4, Anja G J Ezendam4, Alexander C van Huffelen4.   

Abstract

OBJECTIVE: To compare the seizure pattern detection rate of single-channel and multichannel amplitude-integrated EEG (aEEG), using conventional EEG (cEEG) as a gold standard, in full-term neonates with hypoxic-ischemic encephalopathy. The optimal electrode derivation for seizure detection with single-channel aEEG was also investigated.
METHODS: Twelve infants with cEEG seizure patterns (10s) were investigated. cEEG signals were transformed into aEEG signals. Seizure patterns and the number of patients identified with 1 seizure patterns were calculated for single- and multichannel aEEG.
RESULTS: On cEEG, 121 seizure patterns with a mean duration of 58s were identified, 68% of which occurred over the centrotemporal region. The sensitivity of aEEG for the detection of seizure patterns was 30% (C.I.: 0.22-0.38) for single-channel aEEG and 39% (C.I.: 0.31-0.48) for multichannel aEEG. Multichannel aEEG identified all patients with 1 seizure pattern (C.I.: 0.75-1.00), whereas single-channel aEEG (with C4-C3 as the optimal electrode derivation) identified all but one of the patients (C.I.: 0.66-0.99).
CONCLUSIONS: Seizure pattern detection rate is slightly better with multichannel aEEG compared with single-channel (C4-C3) aEEG. Multichannel aEEG identified correctly all patients with 1 seizure pattern in this small selection of patients. SIGNIFICANCE: Single-channel aEEG may detect most patients (in a selected group) with severe neonatal seizures patterns; patient identification can be improved using multichannel recordings.

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Year:  2009        PMID: 19782640     DOI: 10.1016/j.clinph.2009.08.015

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  12 in total

Review 1.  Continuous electroencephalography monitoring in neonates.

Authors:  Renée A Shellhaas
Journal:  Curr Neurol Neurosci Rep       Date:  2012-08       Impact factor: 5.081

Review 2.  Neurodiagnostic techniques in neonatal critical care.

Authors:  Taeun Chang; Adre du Plessis
Journal:  Curr Neurol Neurosci Rep       Date:  2012-04       Impact factor: 5.081

3.  cEEG electrode-related pressure ulcers in acutely hospitalized patients.

Authors:  Lidia M V R Moura; Thiago S Carneiro; David Kwasnik; Valdery F Moura; Christine S Blodgett; Joseph Cohen; Mary McKenna Guanci; Daniel B Hoch; John Hsu; Andrew J Cole; M Brandon Westover
Journal:  Neurol Clin Pract       Date:  2017-02

Review 4.  Neonatal seizures and status epilepticus.

Authors:  Nicholas S Abend; Courtney J Wusthoff
Journal:  J Clin Neurophysiol       Date:  2012-10       Impact factor: 2.177

5.  Sensitivity of compressed spectral arrays for detecting seizures in acutely ill adults.

Authors:  Craig A Williamson; Sarah Wahlster; Mouhsin M Shafi; M Brandon Westover
Journal:  Neurocrit Care       Date:  2014-02       Impact factor: 3.210

6.  Instantaneous measure of EEG channel importance for improved patient-adaptive neonatal seizure detection.

Authors:  Andriy Temko; Gordon Lightbody; Eoin M Thomas; Geraldine B Boylan; William Marnane
Journal:  IEEE Trans Biomed Eng       Date:  2011-12-07       Impact factor: 4.538

7.  Inclusion of temporal priors for automated neonatal EEG classification.

Authors:  Andriy Temko; Nathan Stevenson; William Marnane; Geraldine Boylan; Gordon Lightbody
Journal:  J Neural Eng       Date:  2012-06-19       Impact factor: 5.379

8.  Sensitivity of quantitative EEG for seizure identification in the intensive care unit.

Authors:  Hiba A Haider; Rosana Esteller; Cecil D Hahn; M Brandon Westover; Jonathan J Halford; Jong W Lee; Mouhsin M Shafi; Nicolas Gaspard; Susan T Herman; Elizabeth E Gerard; Lawrence J Hirsch; Joshua A Ehrenberg; Suzette M LaRoche
Journal:  Neurology       Date:  2016-07-27       Impact factor: 9.910

9.  EEG-based neonatal seizure detection with Support Vector Machines.

Authors:  A Temko; E Thomas; W Marnane; G Lightbody; G Boylan
Journal:  Clin Neurophysiol       Date:  2010-08-14       Impact factor: 3.708

10.  In-depth performance analysis of an EEG based neonatal seizure detection algorithm.

Authors:  S Mathieson; J Rennie; V Livingstone; A Temko; E Low; R M Pressler; G B Boylan
Journal:  Clin Neurophysiol       Date:  2016-02-21       Impact factor: 3.708

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