Document Detail


Validation of a new automated neonatal seizure detection system: A clinician's perspective.
MedLine Citation:
PMID:  21396883     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
OBJECTIVE: To validate an improved automated electroencephalography (EEG)-based neonatal seizure detection algorithm (NeoGuard) in an independent data set. METHODS: EEG background was classified into eight grades based on the evolution of discontinuity and presence of sleep-wake cycles. Patients were further sub-classified into two groups; gpI: mild to moderate (grades 1-5) and gpII: severe (grades 6-8) EEG background abnormalities. Seizures were categorised as definite and dubious. Seizure characteristics were compared between gpI and gpII. The algorithm was tested on 756h of EEG data from 24 consecutive neonates (median 25h per patient) with encephalopathy and recorded seizures during continuous monitoring (cEEG). No selection was made regarding the quality of EEG or presence of artefacts. RESULTS: Seizure amplitudes significantly decreased with worsening EEG background. Seizures were detected with a total sensitivity of 61.9% (1285/2077). The detected seizure burden was 66,244/97,574 s (67.9%). Sensitivity per patient was 65.9%, with a mean positive predictive value (PPV) of 73.7%. After excluding four patients with severely abnormal EEG background, and predominantly having dubious seizures, the algorithm showed a median sensitivity per patient of 86.9%, PPV of 89.5% and false positive rate of 0.28h(-1). Sensitivity tended to be better for patients in gpI. CONCLUSIONS: The algorithm detects neonatal seizures well, has a good PPV and is suited for cEEG monitoring. Changes in electrographic characteristics such as amplitude, duration and rhythmicity in relation to deteriorating EEG background tend to worsen the performance of automated seizure detection. SIGNIFICANCE: cEEG monitoring is important for detecting seizures in the neonatal intensive care unit (NICU). Our automated algorithm reliably detects neonatal seizures that are likely to be clinically most relevant, as reflected by the associated EEG background abnormality.
Authors:
P J Cherian; W Deburchgraeve; R M Swarte; M De Vos; P Govaert; S Van Huffel; G H Visser
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-3-9
Journal Detail:
Title:  Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology     Volume:  -     ISSN:  1872-8952     ISO Abbreviation:  -     Publication Date:  2011 Mar 
Date Detail:
Created Date:  2011-3-14     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100883319     Medline TA:  Clin Neurophysiol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Affiliation:
Section of Clinical Neurophysiology, Department of Neurology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
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