Linked Life Data

14506067

Source:http://linkedlifedata.com/resource/pubmed/id/14506067

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
Pt 12
pubmed:dateCreated
2003-11-10
pubmed:abstractText
The unpredictability of the occurrence of epileptic seizures contributes to the burden of the disease to a major degree. Thus, various methods have been proposed to predict the onset of seizures based on EEG recordings. A nonlinear feature motivated by the correlation dimension is a seemingly promising approach. In a previous study this method was reported to identify 'preictal dimension drops' up to 19 min before seizure onset, exceeding the variability of interictal data sets of 30-50 min duration. Here we have investigated the sensitivity and specificity of this method based on invasive long-term recordings from 21 patients with medically intractable partial epilepsies, who underwent invasive pre-surgical monitoring. The evaluation of interictal 24-h recordings comprising the sleep-wake cycle showed that only one out of 88 seizures was preceded by a significant preictal dimension drop. In a second analysis, the relation between dimension drops within time windows of up to 50 min before seizure onset and interictal periods was investigated. For false-prediction rates below 0.1/h, the sensitivity ranged from 8.3 to 38.3% depending on the prediction window length. Overall, the mean length and amplitude of dimension drops showed no significant differences between interictal and preictal data sets.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0006-8950
pubmed:author
pubmed:issnType
Print
pubmed:volume
126
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2616-26
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
How well can epileptic seizures be predicted? An evaluation of a nonlinear method.
pubmed:affiliation
Epilepsy Centre, University of Freiburg, Freiburg, Germany.
pubmed:publicationType
Journal Article, Evaluation Studies