Mormann Florian, Elger Christian E, Lehnertz Klaus
Department of Epileptology, University of Bonn, Sigmund-Freud-Strasse 25, 53105 Bonn, Germany.
Curr Opin Neurol. 2006 Apr;19(2):187-93. doi: 10.1097/01.wco.0000218237.52593.bc.
Our understanding of the mechanisms that lead to the occurrence of epileptic seizures is rather incomplete. If it were possible to identify preictal precursors from the EEG of epilepsy patients, therapeutic possibilities could improve dramatically. Studies on seizure prediction have advanced from preliminary descriptions of preictal phenomena via proof of principle studies and controlled studies to studies on continuous multi-day recordings.
Following mostly promising early reports, recent years have witnessed a debate over the reproducibility of results and suitability of approaches. The current literature is inconclusive as to whether seizures are predictable by prospective algorithms. Prospective out-of-sample studies including a statistical validation are missing. Nevertheless, there are indications of a superior performance for approaches characterizing relations between different brain regions.
Prediction algorithms must be proven to perform better than a random predictor before prospective clinical trials involving seizure intervention techniques in patients can be justified.
我们对导致癫痫发作机制的理解仍相当不完整。如果能够从癫痫患者的脑电图中识别出发作前的先兆，治疗的可能性将大幅提高。关于发作预测的研究已从对发作前现象的初步描述，经过原理验证研究和对照研究，发展到对连续多日记录的研究。
在早期大多颇具前景的报告之后，近年来出现了关于结果可重复性和方法适用性的争论。目前的文献对于前瞻性算法能否预测癫痫发作尚无定论。缺少包括统计验证在内的前瞻性样本外研究。然而，有迹象表明，描述不同脑区之间关系的方法具有更优的性能。
在涉及患者发作干预技术的前瞻性临床试验合理开展之前，必须证明预测算法的表现优于随机预测器。
