Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, New York, NY 10467, USA.
Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, New York, NY 10467, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, NY 10461, USA.
Neurol Clin. 2009 Nov;27(4):925-940. doi: 10.1016/j.ncl.2009.06.002.
This article reviews the epilepsy cycle, distinguishing the interictal, preictal, ictal, and postictal phases. Evidence suggesting that the preictal phase can sometimes be identified based on neurophysiologic signals, premonitory features, the presence of trigger factors, or self-report is also reviewed. Diary studies have shown that seizures are not randomly distributed in time and that a subgroup of persons with epilepsy can predict an impending seizure. Paper diary data and preliminary analysis of electronic diary data suggest that seizure prediction is feasible. Whereas all of this evidence sets the stage for seizure prediction and preemptive therapy, several questions remain unanswered. First, what proportion of persons with epilepsy can predict their seizures? Second, within and among individuals, how accurate is prediction? Third, can prediction be improved through education about group level or individual predictors? And finally, in a group that can make robust predictions what are the most effective interventions for reducing seizure probability at times of high risk? The answers to these questions could reduce the burden of epilepsy by making seizures predictable and setting the stage for preemptive therapy. This work could improve the understanding of epilepsy by providing a context for studying the transitions from the interictal to preictal and ictal states. More prospective studies are needed; challenges certainly exist, but as the studies discussed here demonstrate, the field is rich with promise for improving the lives of patients with epilepsy.
本文回顾了癫痫周期，区分了发作间期、发作前期、发作期和发作后期。还回顾了一些证据表明，根据神经生理信号、前驱特征、触发因素的存在或自我报告，有时可以识别发作前期。日记研究表明，癫痫发作并不是随机分布的，一些癫痫患者可以预测即将发生的癫痫发作。纸质日记数据和电子日记数据的初步分析表明，癫痫发作预测是可行的。尽管所有这些证据都为癫痫发作预测和预防性治疗奠定了基础，但仍有几个问题尚未得到解答。首先，有多少癫痫患者可以预测他们的癫痫发作？其次，在个体内部和之间，预测的准确性如何？第三，通过关于群体或个体预测因素的教育，是否可以提高预测能力？最后，在一个能够做出可靠预测的群体中，在高风险时期降低癫痫发作概率的最有效干预措施是什么？这些问题的答案可以通过使癫痫发作可预测并为预防性治疗奠定基础，来减轻癫痫的负担。这项工作可以通过为研究从发作间期到发作前期和发作期的转变提供背景，从而加深对癫痫的理解。需要更多的前瞻性研究；当然存在挑战，但正如本文所讨论的那样，该领域充满了改善癫痫患者生活的希望。
