Syed T U, Arozullah A M, Loparo K L, Jamasebi R, Suciu G P, Griffin C, Mani R, Syed I, Loddenkemper T, Alexopoulos A V
Epilepsy Center, Neurological Institute, University Hospitals Case Medical Center, Cleveland, OH, USA.
Neurology. 2009 May 12;72(19):1646-52. doi: 10.1212/WNL.0b013e3181a55ef7.
Delay in distinguishing psychogenic nonepileptic seizures (PNES) from epilepsy may result in significant health and economic burdens. Screening tools are needed to facilitate earlier identification of patients with PNES, thereby maximizing cost-effective use of video electroencephalography (VEEG), the expensive gold standard for differentiating PNES from epilepsy. We developed and prospectively validated a self-administered PNES screening questionnaire using variables known to distinguish PNES from epilepsy patients.
Adults referred for inpatient VEEG monitoring at two epilepsy centers were prospectively invited to complete a preliminary 209-item questionnaire assessing demographic, clinical, seizure-related, and psychosocial information that appeared in the literature as potentially useful indicators of PNES. A hybrid neural-bayesian classifier was trained to predict PNES using a sample at one center, and was prospectively validated on a separate set of naive patients from both centers.
Of 211 enrolled subjects from the training center, 181 met the study criteria for either PNES (n = 48, 27%), epilepsy (n = 116, 64%), or coexisting PNES and epilepsy (n = 17, 9%). Variable reduction procedures identified 53 questionnaire items that were necessary to accurately predict PNES diagnosis. The hybrid classifier predicted PNES diagnosis with 94% sensitivity and 83% specificity at the training center, and 85% sensitivity and 85% specificity at the second center (n = 46; 17 PNES, 26 epilepsy, 3 with coexisting PNES and epilepsy).
We developed and prospectively validated a self-administered psychogenic nonepileptic seizure screening questionnaire that could hasten referral for video electroencephalography and reduce the health and economic burdens from delayed diagnosis or misdiagnosis.
区分精神性非癫痫性发作（PNES）和癫痫的延迟可能导致重大的健康和经济负担。需要筛查工具以促进对PNES患者的早期识别，从而最大限度地提高视频脑电图（VEEG）这一区分PNES和癫痫的昂贵金标准的成本效益。我们使用已知可区分PNES和癫痫患者的变量，开发并前瞻性验证了一份自我管理的PNES筛查问卷。
前瞻性邀请到两个癫痫中心接受住院VEEG监测的成年人完成一份初步的209项问卷，该问卷评估人口统计学、临床、发作相关及社会心理信息，这些信息在文献中被视为PNES的潜在有用指标。使用来自一个中心的样本训练了一个混合神经贝叶斯分类器以预测PNES，并在来自两个中心的另一组未接触过该样本的患者中进行前瞻性验证。
在来自训练中心的211名入组受试者中，181名符合PNES（n = 48，27%）、癫痫（n = 116，64%）或PNES与癫痫共存（n = 17，9%）的研究标准。变量约简程序确定了准确预测PNES诊断所需的53项问卷项目。混合分类器在训练中心预测PNES诊断的敏感性为94%，特异性为83%，在第二个中心的敏感性为85%，特异性为85%（n = 46；17例PNES，26例癫痫，3例PNES与癫痫共存）。
我们开发并前瞻性验证了一份自我管理的精神性非癫痫性发作筛查问卷，该问卷可加快视频脑电图检查的转诊，并减轻延迟诊断或误诊带来的健康和经济负担。
