Department of Neurology, All India Institute of Medical Sciences, New Delhi, India.
Department of Neurology, All India Institute of Medical Sciences, New Delhi, India.
Seizure. 2017 Dec;53:81-85. doi: 10.1016/j.seizure.2017.11.002. Epub 2017 Nov 9.
Investigations such as EEG and brain imaging are often difficult to obtain in primary care settings of resource-limited regions impacting millions of epilepsy patients. We wanted to test the hypothesis that classification of chronic epilepsy into focal and generalized based on clinical history and examination alone would be comparable to making such a classification with additional inputs from EEG and brain imaging.
Two investigators independently classified consecutive chronic epilepsy patients into focal, generalized and unclassified epilepsy. Investigator 1 made this determination using clinical history and examination alone whereas Investigator II additionally used EEG and brain imaging too. We calculated inter observer agreement between the two investigators and also looked at the predictors of focal and generalized epilepsy.
Five hundred and twelve patients were recruited. Inter observer agreement between the two investigators in making the focal versus generalized classification was 96.8%, kappa 0.91 (p<0.0001). When EEG and neuroimaging findings were added to clinical information, there was a change in classification in 3.2% patients. Several predictors of focal and generalized epilepsy were identified.
Classification of chronic epilepsy into focal and generalized can be done reliably in most patients using clinical information alone. Investigating chronic epilepsy patients with EEG and brain imaging may not be necessary in every patient. The results of our study are especially significant for epilepsy patients living in resource-limited regions where such investigations may not always be available.
在资源有限的基层医疗环境中,通常难以进行 EEG 和脑部影像学等检查,这影响了数以百万计的癫痫患者。我们旨在验证一个假设,即仅基于临床病史和检查将慢性癫痫分为局灶性和全面性,与在这些检查的基础上增加 EEG 和脑部影像学检查进行分类的结果相当。
两名调查员独立地将连续的慢性癫痫患者分为局灶性、全面性和未分类性癫痫。调查员 1 仅根据临床病史和检查进行分类,而调查员 2 则同时使用 EEG 和脑部影像学进行分类。我们计算了两名调查员之间的观察者间一致性,并观察了局灶性和全面性癫痫的预测因素。
共招募了 512 名患者。两名调查员在进行局灶性与全面性分类时的观察者间一致性为 96.8%,kappa 值为 0.91(p<0.0001)。当将 EEG 和神经影像学发现与临床信息结合使用时,有 3.2%的患者的分类发生了变化。确定了局灶性和全面性癫痫的几个预测因素。
在大多数患者中,仅使用临床信息即可可靠地对慢性癫痫进行局灶性和全面性分类。并非每个患者都需要对慢性癫痫患者进行 EEG 和脑部影像学检查。我们的研究结果对于生活在资源有限地区的癫痫患者尤为重要,因为这些地区可能无法始终进行这些检查。