Lehnertz Klaus, Mormann Florian, Osterhage Hannes, Müller Andy, Prusseit Jens, Chernihovskyi Anton, Staniek Matthäus, Krug Dieter, Bialonski Stephan, Elger Christian E
Department of Epileptology, University of Bonn, Bonn, Germany.
J Clin Neurophysiol. 2007 Apr;24(2):147-53. doi: 10.1097/WNP.0b013e3180336f16.
Although there are numerous studies exploring basic neuronal mechanisms that are likely to be associated with seizures, to date no definite information is available as to how, when, or why a seizure occurs in humans. The fact that seizures occur without warning in the majority of cases is one of the most disabling aspects of epilepsy. If it were possible to identify preictal precursors from the EEG of epilepsy patients, therapeutic possibilities and quality of life could improve dramatically. The last three decades have witnessed a rapid increase in the development of new EEG analysis techniques that appear to be capable of defining seizure precursors. Since the 1970s, studies on seizure prediction have advanced from preliminary descriptions of preictal phenomena and proof of principle studies via controlled studies to studies on continuous multiday recordings. At present, it is unclear whether prospective algorithms can predict seizures. If prediction algorithms are to be used in invasive seizure intervention techniques in humans, they must be proven to perform considerably better than a random predictor. The authors present an overview of the field of seizure prediction, its history, accomplishments, recent controversies, and potential for future development.
尽管有大量研究探索了可能与癫痫发作相关的基本神经元机制，但迄今为止，关于人类癫痫发作的方式、时间或原因，尚无确切信息。在大多数情况下，癫痫发作毫无征兆，这是癫痫最具致残性的方面之一。如果能够从癫痫患者的脑电图中识别出发作前的先兆，治疗可能性和生活质量将得到显著改善。在过去三十年中，新的脑电图分析技术迅速发展，这些技术似乎能够定义癫痫发作的先兆。自20世纪70年代以来，癫痫发作预测研究已从发作前现象的初步描述和原理验证研究，经过对照研究，发展到连续多日记录的研究。目前，尚不清楚前瞻性算法是否能够预测癫痫发作。如果预测算法要用于人类的侵入性癫痫干预技术，它们必须被证明比随机预测器表现得好得多。作者概述了癫痫发作预测领域，包括其历史、成就、近期争议以及未来发展潜力。
