Anticipating the unobserved: Prediction of subclinical seizures
Anticipating the unobserved: Prediction of subclinical seizures
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DOI：
10.1016/j.yebeh.2011.08.023
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发表时间：
2011-12-01
影响因子：
2.6
通讯作者：
Schelter, Bjoern
中科院分区：
文献类型：
--
作者：
Feldwisch-Drentrup, Hinnerk;Ihle, Matthias;Schelter, Bjoern
亚临床发作（SCS）在癫痫的诊断和治疗中很少被考虑，在癫痫发作预测的研究中也没有系统的分析。在这里，我们调查是否亚临床癫痫发作的预测是可行的，以及它们的发生可能会影响预测算法的性能。使用欧洲数据库的长期记录的表面和侵入性脑电图数据，我们分析了21例SCS患者的数据，包括413临床表现癫痫发作（CS）和3341 SCS。基于平均相位相干性，我们研究了CS和SCS的预测性能。两种类型的癫痫发作具有相似的预测敏感性。SCS的显著性能远高于CS，尤其是对于有创记录的患者。当分析由预测CS触发的假警报时，21名患者中有9名患者的这些假预测中有相当数量是由SCS引起的。尽管目前观察到的预测性能可能不足以用于大多数患者的临床应用，但可以得出结论，SCS的预测在与CS相似的水平上是可行的，并且允许预测更多的癫痫损害患者，这也可能减少实际上正确预测CS的假警报的数量。自动癫痫检测和预测的未来。(C)2011 Elsevier Inc. All rights reserved.
Subclinical seizures (SCS) have rarely been considered in the diagnosis and therapy of epilepsy and have not been systematically analyzed in studies on seizure prediction. Here, we investigate whether predictions of subclinical seizures are feasible and how their occurrence may affect the performance of prediction algorithms. Using the European database of long-term recordings of surface and invasive electroencephalography data, we analyzed the data from 21 patients with SCS, including in total 413 clinically manifest seizures (CS) and 3341 SCS. Based on the mean phase coherence we investigated the predictive performance of CS and SCS. The two types of seizures had similar prediction sensitivities. Significant performance was found considerably more often for SCS than for CS, especially for patients with invasive recordings. When analyzing false alarms triggered by predicting CS, a significant number of these false predictions were followed by SCS for 9 of 21 patients. Although currently observed prediction performance may not be deemed sufficient for clinical applications for the majority of the patients, it can be concluded that the prediction of SCS is feasible on a similar level as for CS and allows a prediction of more of the seizures impairing patients, possibly also reducing the number of false alarms that were in fact correct predictions of CS.This article is part of a Supplemental Special Issue entitled The Future of Automated Seizure Detection and Prediction. (C) 2011 Elsevier Inc. All rights reserved.