| pubmed-article:14506067 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:14506067 | lifeskim:mentions | umls-concept:C0014544 | lld:lifeskim |
| pubmed-article:14506067 | lifeskim:mentions | umls-concept:C0025663 | lld:lifeskim |
| pubmed-article:14506067 | lifeskim:mentions | umls-concept:C0220825 | lld:lifeskim |
| pubmed-article:14506067 | lifeskim:mentions | umls-concept:C0681842 | lld:lifeskim |
| pubmed-article:14506067 | pubmed:issue | Pt 12 | lld:pubmed |
| pubmed-article:14506067 | pubmed:dateCreated | 2003-11-10 | lld:pubmed |
| pubmed-article:14506067 | 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. | lld:pubmed |
| pubmed-article:14506067 | pubmed:language | eng | lld:pubmed |
| pubmed-article:14506067 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:14506067 | pubmed:citationSubset | AIM | lld:pubmed |
| pubmed-article:14506067 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:14506067 | pubmed:month | Dec | lld:pubmed |
| pubmed-article:14506067 | pubmed:issn | 0006-8950 | lld:pubmed |
| pubmed-article:14506067 | pubmed:author | pubmed-author:TimmerJJ | lld:pubmed |
| pubmed-article:14506067 | pubmed:author | pubmed-author:Schulze-Bonha... | lld:pubmed |
| pubmed-article:14506067 | pubmed:author | pubmed-author:VossH UHU | lld:pubmed |
| pubmed-article:14506067 | pubmed:author | pubmed-author:WinterhalderM... | lld:pubmed |
| pubmed-article:14506067 | pubmed:author | pubmed-author:MaiwaldTT | lld:pubmed |
| pubmed-article:14506067 | pubmed:author | pubmed-author:Aschenbrenner... | lld:pubmed |
| pubmed-article:14506067 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:14506067 | pubmed:volume | 126 | lld:pubmed |
| pubmed-article:14506067 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:14506067 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:14506067 | pubmed:pagination | 2616-26 | lld:pubmed |
| pubmed-article:14506067 | pubmed:dateRevised | 2004-11-17 | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:meshHeading | pubmed-meshheading:14506067... | lld:pubmed |
| pubmed-article:14506067 | pubmed:year | 2003 | lld:pubmed |
| pubmed-article:14506067 | pubmed:articleTitle | How well can epileptic seizures be predicted? An evaluation of a nonlinear method. | lld:pubmed |
| pubmed-article:14506067 | pubmed:affiliation | Epilepsy Centre, University of Freiburg, Freiburg, Germany. | lld:pubmed |
| pubmed-article:14506067 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:14506067 | pubmed:publicationType | Evaluation Studies | lld:pubmed |
| http://linkedlifedata.com/r... | pubmed:referesTo | pubmed-article:14506067 | lld:pubmed |
| http://linkedlifedata.com/r... | pubmed:referesTo | pubmed-article:14506067 | lld:pubmed |
